Podcasts about cpg

Caulipower's sale to Urban Farmer in November 2025 marked the latest chapter in one of the most remarkable founder stories in modern CPG.  Before the acquisition, the company was generating more than $120 million in annual sales and had established a dominant position in better-for-you frozen food. But for founder Gail Becker, building a successful company was never just about creating enterprise value — and that makes this conversation worth revisiting. When Gail joined Taste Radio in March 2025, she spoke candidly about the motivations behind Caulipower, the company she built after seeing an opportunity to make the foods people loved more accessible and better for them.    With the benefit of hindsight — and knowing where the Caulipower journey ultimately led — Gail's perspective on success feels especially resonant. She opens up about the emotional rewards of entrepreneurship, the relationships she developed with consumers and the leadership lessons she learned while scaling Caulipower into a market leader with a national retail footprint of more than 25,000 stores. Whether you're hearing it for the first time or revisiting it with the outcome of Caulipower's sale in mind, Gail's message is clear: building a valuable company is one thing. Building something that genuinely matters is something else entirely. Show notes: 0:25: Interview: Gail Becker, Founder, Caulipower – Recorded at the lively Caulipower booth at Expo West 2025, Gail Becker takes us behind the development of the brand's new dill pickle pizza, a product that spent two years in development before reaching shelves. She outlines the three must-have criteria for every new Caulipower product and explains why expanding access to better-for-you food remains central to the company's mission. Gail also discusses the brand's willingness to challenge conventions and reflects on the intensity and optimism that defined Caulipower's early days. Despite being naturally private, she became the public face of the brand and shares what she's learned about navigating that role — including the importance of knowing when to say no. Brands in this episode: Caulipower

What if the moment where the buying decision actually gets made is still the part of the journey we understand the least?Agility depends on seeing what customers actually do — not just what they clicked — and being able to act on it while the promotion is still running.Today we're talking about the gap between where brands are putting their media money and where they can actually see it working. Retail media budgets are climbing, stores are getting reinvested in, and yet the shelf itself remains one of the least instrumented parts of the customer journey. We'll be covering:- Why the surge in retail media spend hasn't automatically produced better measurement.- What it takes to connect a digital impression to what a shopper actually does in the aisle.- How marketing, merchandising, and store operations have to work differently to act on any of it.To help me discuss this topic, I'd like to welcome, Angie Westbrock, CEO at Standard AI.About Angie WestbrockAngie Westbrock brings 20+ years of experience in retail, CPG and tech to her role as the CEO at Standard AI, the retail analytics startup valued at $1B that's helping retailers and brands understand shopper behavior so they can improve the customer experience and their bottom lines. Angie specializes in scaling teams, culture, and business operations to support massive growth. She's bucked the mold of what's expected of women since the start of her career; she was one of the first brewing managers at Anheuser-Busch, one of the youngest women to run a plant at CPG giant Sara-Lee, and helped lead Lyft's global Covid-task force with a young family at home.Angie Westbrock on LinkedIn: https://www.linkedin.com/in/angie-westbrock-a2581111/---------- Resources ---------- Standard AI: standard.aiThe Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fChaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1Start building your own apps with Replit and get $20 off. Learn more: https://aglbrnd.co/r/93531742a7625a20Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716baCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.comThe Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

We're creating space for the brains behind the brands we love, and asking good questions along the way. The result is a deep dive into the how and why of brand-building, from blueprints to launch day, customers as community and the detours in between. big lessons, easy listening. In this episode of Read Receipt, Sean sits down with Stephanie Farsht, CEO and co-founder of Small Wonder, the luxury waterless hair care brand built on a powder-to-lather format that activates fresh in the shower. Stephanie's path to founder wasn't conventional. She spent 16 years at Target in innovation and strategy, then eight years teaching entrepreneurship at Northwestern's Kellogg School of Management, before teaming up with two co-founders to reinvent hair care around a simple idea: potent ingredients work best freshly activated, not sitting in water for months. She gets honest about the messy middle, the pre-dosed pod experiment that flopped with 100 testers, the bottle that clogged after two weeks, and why she still emails customers herself when they cancel. Along the way she shares hard-won lessons on product obsession, failing fast, raising on your own timeline, and building a mission-driven brand in a category most investors are walking away from. Tune in for an inside look at building a category-defining brand through relentless iteration, customer intimacy, and a refusal to ship anything less than the best product possible! Chapters: 00:00 - Cold open 01:38 - Target, then teaching at Kellogg 08:40 - The powder-to-lather idea 11:01 - Becoming a CEO she never planned to be 13:00 - Two years of R&D through COVID 16:43 - Self-funding, no fixed timeline 18:01 - The pod experiment that flopped 23:09 - Designing the patented Wonder Bottle 25:24 - Doubt, failure, and identity 31:57 - Why the founder still does customer service 39:46 - Revenue, raising, and the road to retail 46:45 - Time is what kills companies 48:05 - All or nothing: a billion-dollar mission

As inflation, margin pressure and shifting consumer behavior reshape the CPG landscape, private label is having a major moment — and brands need to decide how they'll respond. The hosts unpack why more retailers are embracing private label, how brands can leverage it to strengthen cash flow without undermining their own business, and why saying no to an opportunity could simply hand it to a competitor. Show notes: 0:20: Meetups & Mingling. Honey Mama's Mashups. Private Label, Big Moment. Networking Pays. CPG Wins & Woes. Weird Snacks. – The hosts kick off the episode with some playful banter about Ray's absence before reflecting on Taste Radio's recent Chicago Meetup and previewing upcoming events in San Diego, San Francisco and London. They sample a variety of new Honey Mama's products and discuss how the brand has evolved its product line without losing its core identity. The conversation then turns to the resurgence of private label amid inflation and a K-shaped economy, with Melissa highlighting a recent Nombase podcast focused on how brands can use private label to generate cash flow without diluting their core business. The hosts also make the case for attending industry events, emphasizing that networking can lead to unexpected opportunities and that founders should consistently invest in their networks rather than scrambling to build one when they need it. They spotlight several entrepreneurs and brands, including Goldie Lemonade founder Sean Rosenberg, Plainspeak Water from Sara Brooks, and Bake Me Healthy founder Kimberly Lau, whose decision to wind down her business underscores just how difficult building a successful CPG company can be. Finally, they sample a uniquely Canadian snack called Long Chips, debate whether the bacon flavor is actually bacon, and marvel at the product's unusual format. Brands in this episode: Honey Mama's, Stumptown Coffee, Prana, Goldie Lemonade, GNGR Labs, Plainspeak, Bake Me Healthy, Kodiak Cakes, Long Chips, Pringles

Kendall Kransdorf is the founder of Cotto, a line of whipped cottage cheese dips bringing real protein and big flavor to the refrigerated dip aisle. On this episode of In the Sauce, Ali and Kendall discuss turning a personal food habit into a product, the test and learn approach, and the particular challenges of building a refrigerated dairy brand.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Paul Altman is a Partner and Managing Director and joined The Sage Group at its inception in 2000. He focuses on consumer M&A transactions, advising high-growth lifestyle brands on transactions across multiple subsectors, including e-commerce, specialty retail, apparel & accessories, home, CPG, wellness, and beauty & personal care companies. He attended University of Michigan Ross for a joint BBA and law degree, and went to Wharton for his MBA. www.sagellc.com

In this episode of Veteran on the Move, guest Nate Amidon joins host Joe Crane to discuss his transition from serving as an Air Force C-17 pilot with over 20 years of military experience to founding Form100 Consulting. Choosing corporate tech consulting over the traditional airline route, Nate highlights veterans as an untapped talent pool capable of filling the severe lack of leadership training in the corporate software world. Through consulting and staffing, his team embeds veteran leaders into companies to translate mission-driven focus into software development, teaching teams how to lead through influence rather than rank and prepare for unexpected transition challenges. Episode Resources: Form100 Consulting   About Our Guest   Nate Amidon is the founder and CEO of Form100 Consulting, a veteran-owned tech consulting firm that applies military leadership principles to modern software organizations. His team has improved technology practices for Fortune 500 companies across manufacturing, aviation, CPG, and defense sectors. Nate served over 20 years in the Air Force as a C-17 pilot, accumulating 4,000 flight hours, 800 combat hours, and earning 5 Air Medals. His experience leading aircrews and planning large-scale missions shapes Form100s approach to alignment, clarity, and execution in technology programs.   About Our Sponsors Navy Federal Credit Union   If you're looking for a positive sign toward homeownership, this is it. That's because Navy Federal Credit Union's Homebuyers Choice loan has downpayment options as low as zero percent with no required private mortgage insurance. These benefits make homeownership more achievable for their members. Learn more here.  Terms and conditions apply. Loans subject to approval and eligibility requirements.  At Navy Federal, our members are the mission.    Join the conversation on Facebook! Check out Veteran on the Move on Facebook to connect with our guests and other listeners. A place where you can network with other like-minded veterans who are transitioning to entrepreneurship and get updates on people, programs and resources to help you in YOUR transition to entrepreneurship.   Want to be our next guest? Send us an email at interview@veteranonthemove.com.  Did you love this episode? Leave us a 5-star rating and review!  Download Joe Crane's Top 7 Paths to Freedom or get it on your mobile device. Text VETERAN to 38470. Veteran On the Move podcast has published 600 episodes. Our listeners have the opportunity to hear in-depth interviews conducted by host Joe Crane. The podcast features people, programs, and resources to assist veterans in their transition to entrepreneurship.  As a result, Veteran On the Move has over 7,000,000 verified downloads through Stitcher Radio, SoundCloud, iTunes and RSS Feed Syndication making it one of the most popular Military Entrepreneur Shows on the Internet Today. Disclosure: Some of the links above are affiliate links. This means that, at zer  

What does it take for an emerging CPG brand to go from promising to investable? Brian Folmer, founder of FirstLook and FirstLook Ventures, offers a behind-the-scenes look at how he evaluates the next generation of consumer brands. FirstLook is a "Shark Tank in a box" platform that vets hundreds of brands before putting a select group of products in the hands of nearly 100 investors, while FirstLook Ventures takes that deal flow a step further by funding emerging companies alongside its investor community.  Brian reveals what catches his attention—from traction and valuation to market potential, founder quality and the elusive "X factor"—and shares why some brands make the cut while others don't. He also explains why overpricing a company can stall a fundraise, how potent consumer pain points can create breakout opportunities, and why today's shift toward cleaner, less-processed products is creating new opportunities for CPG founders. Show notes: 0:20: Brian Folmer, Founder, FirstLook & FirstLook Ventures – Brian chats about his background and foray into CPG investment before explaining First Look's model and the criteria the company uses to vet hundreds of brands and select a group of products to present monthly to its investor members. The First Look Ventures founder also breaks down the factors that influence investment decisions, including valuation, sales traction, retail interest, market size, pricing, category potential and founder quality. Using Laurel's Coffee, Miils, Boost Cous, SUUS, Awesome Aminos, Zoli Gummy Pops and Magna as examples, he discusses what makes brands stand out and the importance of solving a clear consumer need. He also addresses regulatory and legal risk, the shift toward cleaner and less-processed products, the growing use of AI to build more efficient companies and the "X factor" he looks for in founders. Folmer explains why an inflated valuation can slow a fundraise, why a large market matters and what founders can do to get investors' attention, including keeping outreach concise and making pitch decks mobile-friendly. Brands in this episode: Laurel's Coffee, Miils, Boost Cous, SUUS, Awesome Aminos, Gruns, Zoli Gummy Pops, Poppi, Vita Coco, Siete, Vaquero Bandito, Primal Queen, Magna, Ugly Drinks

When we first dicsussed the Summer of Simulative AI in 2024 we knew it would be a brief summer, but it has recently come back with a vengeance with SimGym in April and now Simile AI's $2B Series B, backed by GreenOaks and Index Ventures with prominent backers like Fei-Fei Li and Andrej Karpathy, running tens of millions of simulations for Fortune 100 clients like CVS and 85–99% accuracy vs human focus groups. Time to catch up on why this Second Summer of simulation is working!From creating Smallville, the landmark 2023 paper on Generative Agents that showed AI characters could remember, plan, socialize, and develop emergent behaviors, to now building foundation models of human behavior, Joon Sung Park is trying to answer a much bigger question: what if we could simulate the world before making decisions in it? In this episode, the Simile co-founder and CEO joins us to unpack the path from generative agents to digital twins, why today's frontier models still fail to capture how humans actually behave, and what it would take to eventually simulate all 8 billion people on Earth.We go deep on Simile's approach to modeling human behavior: long-form interviews, observational and transaction data, randomized controlled trials, population-level and individual-level models, and post-training on the causal mechanisms behind why people make decisions. Joon explains how his research created digital twins that reproduced human behavior and attitudes 85% as accurately as people reproduced their own responses, why models optimized to be rational can be bad simulations of irrational humans, and why understanding “social physics” may require changing model weights rather than simply prompting frontier LLMs.We also explore the much larger ambition behind simulation: testing products and policies before deploying them, finding counterintuitive paths toward desired outcomes, modeling emergent behavior across entire societies, and potentially tackling problems like climate change, democratic instability, and UBI. Joon reflects on scaling laws for simulation, the economics of data-center-scale simulated worlds, the connection to Thomas Schelling and psychohistory, why simulation is surprisingly similar to painting, and whether we might already be living in one.We discuss:* How Smallville and Generative Agents led to Simile* Why Joon's team asked: “What if we can just recreate the world that we live in?”* Why useful personal agents require deep models of their users* Memory architectures, Markdown files, and the limits of prompting* “Social physics” and behavioral foundation models* Why web data captures what people say more than what they actually do* Interviews, transactions, observational data, and randomized controlled trials* Why predicting the future matters less than understanding how to shape it* How Simile creates representative simulated populations* Simulation versus prediction and the connection to Foundation's psychohistory* How to evaluate simulations instead of simply stacking LLM hallucinations* Creating digital twins of 1,000 real people and reaching 85% behavioral accuracy* Why frontier models can struggle to reproduce real human behavior* Why good simulations need to reproduce human biases and mistakes* Post-training models on randomized controlled trials* Population-level versus individual-level simulation* Scaling laws for human simulation* The long-term ambition to simulate all 8 billion people on Earth* Whether simulations could help solve climate change or detect collapsing democracy* Thomas Schelling and the history of agent-based modeling* Why future simulations could require an entire data center* Multi-agent simulations and what happens when simulated people interact* Replacing expensive human panels with synthetic populations* Why market research is only the starting point for simulation* Why Joon sees simulation as surprisingly similar to painting* Using simulation to study questions like UBI* Whether we are already living in a simulation* Why AGI and simulation may be the twin technologies of advanced civilizationsJoon Sung Park* LinkedIn: https://www.linkedin.com/in/joonspark* X: https://x.com/joon_s_pk* Website: https://www.joonsungpark.com* Simile: https://www.simile.comTimestamps00:00:00 Introduction and Joon's Path from Art to AI00:01:46 Smallville, Generative Agents, and the Origins of Simulation00:05:03 “Let's Just Create a World” and the Future of Personal Agents00:09:53 Social Physics and Behavioral Foundation Models00:14:08 Prediction vs. Simulation: How Do You Shape the Future?00:16:59 How Simile Models Real People and Populations00:25:35 Evaluating Simulations, Digital Twins, and 85% Accuracy00:30:23 Post-Training Models to Reproduce Human Behavior00:40:04 Scaling Laws and Simulating 8 Billion People00:43:10 From Schelling to Society-Scale Agent Simulations00:46:13 The Cost and Economics of Simulating the World00:52:05 Real-World Use Cases, Synthetic Populations, and the Market00:57:27 The Future of Simulation, Painting, and UBI01:04:23 Are We Already Living in a Simulation?01:06:08 Building Simile and HiringTranscriptIntroduction: Joon Sung Park, Simile, and the Story So FarVibhu [00:00:00]: Today, we have Joon in the podcast. Excited to kick this one off. Very exciting company. I wanna kick off and ask you the question, talk us through the story of your life. How have you gotten here?Joon [00:00:13]: Yeah, for sure. I'm really excited to be here. A story of my life. So I was born in Korea, and I lived there for a good 11 years or so of my life, and then my family moved to Boston. So we moved when I was 11, and my parents were doctors, so they were going through their postdoctoral studies. My dad was a surgeon, so he was doing his sabbatical years at the Boston Children's Hospital. So I grew up there, not too close to tech. I was very much a music and artsy, painting kind of guy.Vibhu [00:00:49]: Painting.Joon [00:00:49]: Exactly. I got into painting a little bit later, in high school, but that's what I used to do. And then I grew up mostly in the East Coast after Korea. So I lived a good number of years in New Hampshire, and then I went to college in Pennsylvania. And I got into more of this tech scene, in college. So I was originally trained to be an artist. I thought that would be my professional career. So it wasn't a hobby. It was like, “Hey, let's make a living out of this.” And then gradually, I got really interested in this idea of, hey, the greatest artist often creates their own medium, and the best medium that we had available today was in computation. So I decided to go deeper into that, and one thing led to another, and we can go deeper into this, but I decided that research was something that I gradually got interested in, and here I am.Smallville, Generative Agents, and the 2023 Breakout PaperSwyx [00:01:46]: So there's a lot that you packed into the research components. You had one of the best papers of 2023, which was the generative agents paper, commonly known as the Smallville paper.Swyx [00:01:58]: Feel free to call back to anything else that you mentioned, but most people would have heard of you from this. Do you have any statistics on how many people have, like, read it? arXiv gives you something, right? Some stats.Joon [00:02:10]: Yeah, it's a good question. How many people have read it, I'm not sure.Joon [00:02:14]: I know we do keep track of citations, and they are going up quite fast.Swyx [00:02:23]: Yeah, Google Scholar has 7,200 citations.Vibhu [00:02:25]: I feel like it made a bigger hit than that, and it was a pretty instrumental paper. It got cited so many times.Swyx [00:02:34]: It is frequently the answer when people ask, “What is the best paper you've read recently?” It's this one.Vibhu [00:02:39]: I thought the memory component was pretty underrated. It was a very good early memory system, and one of the biggest papers.Foundation Models and the Search for Killer ApplicationsJoon [00:02:47]: Yeah, so maybe I can talk a little bit about how this particular paper came together. So when I got into research, it was back in 2020 when I started my PhD program at Stanford, and that was the year, when we were about to get GPT-3 to be available. So we already had GPT-2, and you could sense that there was this new class of models that was just becoming available in the market, and the team got very intrigued. And the general consensus was, “Well, is this model going to be useful for anything?” “It's really strange that these models are not trained to do any particular task.” But we decided to take a bet. So a large group of scholars at Stanford, and it was led by one of my co-founders, Percy Liang, and we came togetherSwyx [00:03:35]: Who coined foundation models.Joon [00:03:36]: Who coined the term foundation models. We wrote this paper, where that term came from called Opportunities and Risks of Foundation Models. And during that process, really the thing that I started to think deeply about was, here is a model that is fundamentally new in our ecosystem. The reason why this was new was it wasn't, again, trained to do anything in particular, but its premise was it could do anything and everything. It was like a stem cell, if you were to take a biology analogy. And I got really interested in this idea that, well, if we were to really think about what are the killer applications that this particular technology would enable, what would that be? Many of my colleagues were using this for simple classification, simple generations. Interesting that these models can do that, but from an interaction perspective, not that interesting. We've known how to do that for many decades. And what we came down to was these models are trained on this very broad data from the web, right? So these are human behavioral data. It's social media, Wikipedia, all these data. So if you poke at the right angle, then you could see human behavior that would just pop out that's quite realistic, and we've never seen that before.The Time Machine Game and Recreating the WorldJoon [00:04:45]: So that got us really interested. The exercise that we decided to do, with this particular group of colleagues, Michael Bernstein, Percy Liang, and myself, who ended up becoming my co-founder at Simile, we sat down and we played this game that we call the time machine game.Joon [00:05:03]: Imagine we were to get on a time machine and fast-forward 10 years and look back. What would have been the single application that will have mattered that would be the most interesting and inspiring? And when we thought, “Well, what if we can just recreate the world that we live in?” it's really hard to get more ambitious than that. Like, let's just create a world.Joon [00:05:24]: And that's where we started. And initially, we had this paper that was a precursor to the generative agents paper called Social Simulacra.Swyx [00:05:32]: Before you go further, were there other candidates for the most ambitious thing in the time machine exercise? What was number two or number three?Personal Agents, User Models, and Why Simulation Came FirstJoon [00:05:44]: There is a close second that we were considering, which ended up becoming more of these automation tools, especially the vision around really personalized agents that would do things for you.Swyx [00:05:59]: That's also happening.Joon [00:06:00]: It's also happening. But it was interesting for us, right, in that the reason why, we decided to go with the idea of simulation, one, I was a huge science fiction nerd, and this idea of creating simulation, I was personally really just fascinated. I loved the idea. It's really cool to see, like, a game town like this and just see these agents live in it. But at the same time, my bet was if you were to create a really amazing personal assistant out of this technology, what you need first is an amazing model of your users. So I told a model, “Hey, can you go buy late dinner for me?” And it orders Hawaiian pizza, and I do not like pineapples on my pizza. Then it totally failed. The way for it to not make that mistake is only by having a deep understanding of who I am. And I gave a very simple and dumb example here, but you can imagine how this core understanding of people is instrumental. This is how, if we have our family and closest friends, they have a good mental model of who we are. That's the basis of our social connection. So our bet also was this technology around simulation, creating accurate representation of people ought to precede the more complex agents that would automate the world that we live in. So that was the bet. But that was a very close second, and I'm still very much fascinated by it. I think there's a lot of interesting work that's going around. My hot take here, though, is I don't think we've seen a true personal assistant that's useful, in ways that meet the ambition of that particular line of work. I think there are early applications that are interesting, and if you talk to even ChatGPT nowadays or Claude, they know a lot about us. So a lot of the generation it's doing, I do think it's much more tailored, but I think the ambition is quite large in that field, and I don't think we quite have all the right ingredients just yet.Swyx [00:08:01]: So OpenClaw and these personal agents, what do you want to see from them that they don't currently have?Memory, Markdown, and the Limits of PromptingJoon [00:08:09]: I do think it's slowly getting there, but I do generally want them to have much deeper understanding of the person. Right now, you look at the models. OpenClaw, what it's leveraging is a Markdown file, and I think it's quite clever, right? So if you look at the generative agents paper, this was the same intuition that we had, where initially when we were creating the memory architecture for the generative agents, and, like, this is, like, back in 2022, so we didn't really quite have the idea of even agentive architecture or the term agent. But the intuition that we shared with some of the work that's coming out today was we initially thought, “Well, do we want to make the memory into, let's say, knowledge graph? Do we want to train a bespoke model?” All of these things. And what we decided to do was, “No. Just forget about all this.” These language models are quite good at modeling text and understanding and reasoning about text. So just put everything in a Markdown file or a text file. You're done. I thought that was quite interesting that we could do that, and there's a lot of strength in doing that. But also, there are limitations. It's the way you retrieve and make sense of data that's extremely large, it takes a lot of work. So I think that technology is getting better. I also do, however, think, there are certain things you just cannot shape just by prompting the model. So to some degree, you do need to touch the parameters of the model itself. So there is this work that I do think does need to happen, and it is happening. The question is, how far can we take it? How do we source data, and how do you also create an ecosystem where people are continuously feeding data to this model so it's learning about you?Vibhu [00:09:50]: What's the intuition between why you need to do it in the model?Social Physics and Behavior Foundation ModelsJoon [00:09:53]: My intuition behind the actual when do you train or even post-train a model versus just prompt a model is if the model has to learn the underlying physics of the world that it's operating in. So it has to learn new social physics. The places where it doesn't have to train are the places where it already has the physics. We trust the physics. It already has the base statistics, but it's just trying to react to an environment. Then I think you can just prompt your way into getting the actions out of it. I don't think the models that are out in the open have yet learned the complete mapping of social physics of humanity. This is one of the core theses of Simile, right? And one of the core reasons why that is the case is if you look at the data that the model was trained on, these models were trained on the web data, like, whatever was available on the web. And these are really interesting data sets, but they are fundamentally the self-exposed attitudinal data with some behavior data that's sprinkled around here and there. And it has yet to learn the really deep behavioral nature of people, not just what people say they do online, but what they do in real life. And this is one of what I would consider to be the dark knowledge of humanity that we haven't quite captured. And it's these data that would also need to get factored into the model creation.Vibhu [00:11:21]: You call it behavior foundation model.Vibhu [00:11:23]: There's a good one-liner here, but outside of that, what type of data do you need? What are you changing on the model level? How do you go about modeling, doing a behavior foundation model?The Three Data Buckets: Interviews, Behavior, and CausalityJoon [00:11:35]: We think about data in three buckets. So one bucket is interview data. It's quite interesting. Rich qualitative data is interesting. It's not behavioral, but we would literally ask people, “Hey, tell me the story of your life.”Vibhu [00:11:53]: It's just what we're doing here exactly.Joon [00:11:54]: The question that you all asked at the beginning of this interview literally is the question we also ask. And we ask our participants to go a little bit deeper, than how far I went. Maybe I can give more of my life story in lieu of this. But the reason why that data is interesting is by learning about this very long-tail information about people, you get a lot of texture around this model, like, this person as a model. So even understanding their childhood memory or even their trauma, their first love, these things, quite informative in ways that's really hard to predict. So that's one. Then there are two tranches of what I would consider to be the behavioral data. One kind of behavioral data is observational. So these might be like transaction data, or these might be data that you can get by scraping the web, right? So you can imagine why these data sets would be interesting, right, because they give you the base statistics of people's behavior.Joon [00:12:55]: But then there is the last category of data, that I personally think is perhaps the most important, which is the data that describes the causal mechanism, the whys of people. Some of this is covered by the interview data, the qualitative, because people talk about why they made certain decisions. But really, where you get to see the most behavioral aspect of this is in randomized controlled trials, like RCTs. Imagine you have the same setup, but you have a few different variables that you are trying to tweak. Can you get realistic human behavior out of it in ways where, imagine you had this particular option. Imagine you're even trying to choose whether you're going to drink coffee or not. The day you drink coffee versus the day you didn't drink coffee, does your behavior change? That's a data set that describes a causal mechanism. This is quite important in modeling people. The reason why this is important is oftentimes when people come to us, or not just to us, but the reason why people are interested in simulation isn't because they want to predict the future. If you're trying to win against the stock market, predicting the future is interesting.Prediction vs. Simulation: Shaping the FutureJoon [00:14:08]: But most people, most decision-makers, what they want to know is, how can we shape the future? It doesn't really help you to hear that your sales are going to tank in two quarters. They're just gonna say, “Wow, that sucks.” What they want to know is, well, what do we need to do now to avoid that future? That's the causal mechanism. And this is also very hard data to come by, right, because the world is our ground truth, but it happens once. So in a very controlled setup where everything is equal except for one variable, this kind of data set rarely happens. So this is a reason why this data set is both hard to come by and quite important if you're trying to model human behavior.Swyx [00:14:50]: So behavior, I think, is the hardest data set to acquire. What is out there? What is even possible? You're not going to know a lot of details about my life. I don't even have data for myself on my own health or habits, and I just don't log everything. So how can you have that data?Joon [00:15:14]: So we run a lot of randomized controlled trials.Swyx [00:15:17]: But you put people in the lab, they watch them sleep, or what?Joon [00:15:20]: We do care a lot about the consent process. People know that we invite them to be a member of this community to both share data and have themselves represented in different forms. But we bring a lot of people to the lab, or virtual lab, where we design experiments that would pose them real behavioral decisions. And often in these experimental setups, what makes the difference between what is attitudinal versus behavioral is whether the stake in your decision is real. That's ultimately what makes it behavioral. So in these setups, we are inspired by our colleagues in social sciences, psychology, and so forth. So when they run studies, the techniques they utilize is imagine there's an online store that you're inviting people to come by. Then whatever they purchase in this experiment, they actually get that item delivered. Like, these are the things that make the stakes real. So we run a lot of these experiments, and we also do partner with firms. Right now, we also have customers who are quite excited to at least give us a glimpse of the behaviors that their users exhibit so that we can get a little bit deeper understanding of how people behave in these different platforms.How Customers Use Simile: Populations, Queries, and ExperimentsVibhu [00:16:39]: I think on the customer side, they have a lot of data about their users, who has bought. They have the action data.Vibhu [00:16:47]: Can you walk us through an example of what someone comes to you for? What questions would they want solved? Do you customize a model for them? Do you have something off the shelf? What does that look like?Joon [00:16:59]: Today, when people leverage our models, it's often to better understand the population of their interest. So usually, the start of the relationship, we come together and hear about what population they want us to model, right? So it might be that if you're a CPG company that's selling to all of the US, then maybe it's fairly straightforward. You want to model the gen pop of the US. But at the same time, if there is a vertical or if there's a market that they're trying to go into, imagine, they want to better understand, let's say, people in their 20s and 30s living in California. That's a much more specific population. So we hear about this population, and we go recruit these people, with consent, and with incentives, and we collect some of their data and create a model of these people. Then what our product allows you to do is query them. So it can take as input a filter that is a description of the population that you want to talk to, just like the one I just mentioned, and an environment. The environment can literally be survey questions, behavioral experiments, It can be A/B testing. Oftentimes, the core use cases are things like concept testing, to start with. But also, people sometimes want to do focus groups or one of the fun use cases that we also serve is even modeling things like earnings calls for public companies.Joon [00:18:21]: So these are the use cases that we often start with.Swyx [00:18:23]: Concept testing, is that an established term? I've never heard of concept testing.Concept Testing, Gallup, and PoliticsJoon [00:18:27]: Yeah. So it has to do with they have, let's say, different messaging, different products, different ideas.Swyx [00:18:32]: It's like a marketing exercise.Swyx [00:18:33]: Okay, got it. Got it. Politics?Joon [00:18:36]: We do, have a strategic partnership with Gallup, and of course, Gallup is deep into policy space and so forth. Right now, we have not worked deeply with politics, like that area just yet, however.Swyx [00:18:49]: I'm curious if there is demand or if they really would have different needs that somehow fundamentally don't mix with your existing, users or people.Joon [00:19:00]: I think there's certainly demand.Joon [00:19:02]: But we are very much mindful of how this technology gets adopted and the societal impact that we'll end up having with this technology. And I do see politics as an area where a company has to be particularly thoughtful about the way they operate and make impact. So this is where we also want to make sure that we form enough of guardrail and perspective on how to leverage this technology before we go on to serve markets like the politics.Swyx [00:19:29]: I'll give people an example. one of my favorite shows is The West Wing. I don't know if people have watched.Swyx [00:19:34]: One of the key storylines is, like, the president has, multiple sclerosis, but they haven't. they need to figure out how to disclose it. So they run a poll with a fake governor and ask people to respond on the poll,Counterfactuals, Polling, and When Simulation Is UsefulSwyx [00:19:47]: They try to make decisions based on the results of that poll on, like, how well they'll be received, like where, how should we play this?Swyx [00:19:54]: And I'm like, well, I think those counterfactual things, I would use a simulation for this if I could trust it.Joon [00:20:01]: For sure.Joon [00:20:02]: In that show, how'd it go?Swyx [00:20:04]: In that show, it was, like a foregone conclusion. They were like, “We know it's bad. We just don't know how bad.” And then the poll came back. It was like, “It's really bad.” And then they just did it anyway.Joon [00:20:14]: Part of it is to show, right? So you're, you're looking at the ideaSwyx [00:20:17]: Maximizing drama.Joon [00:20:18]: How bad could it be? Oh, it's horrible.Swyx [00:20:20]: And to some extent, I think that is part of the trick of the, or the challenge or with being a customer of yours, which is that if I know it's. if I roughly know and can intuitSwyx [00:20:35]: What the effect is going to be, do I need you? What sensitivity of it, of effect do I need in order to make a decision, right? So for example, if I, my approval rating is 50%Swyx [00:20:48]: And I, they have this negative piece, news item comes out, and it drops to 30.Swyx [00:20:52]: If it drops to 20, if it drops to 40, do I care? No. It, I know it drops. It's negative. So when do I care about simulations?Joon [00:21:01]: You do something that's clearly bad, that's not popular, and people don't like you, like, yeah, it's likeSwyx [00:21:05]: You don't need a simulation.Joon [00:21:07]: Yeah. Well, so there are a couple of things. one is, there are use cases where, like every day, developers, designers, policymakers, marketers, every single day, they create assets. They create new products. And turns out, it's many of the decisions in hindsight is obvious. Yes, of course this is bad, but we still run those studies because understanding the magnitude and understanding how acute something is quite difficult, even if, we feel like, of course, like this makes sense. this is the reason why we make so many mistakes. Like, every time somebody goes online and say something that has huge backlash, you look at that and like, “What an idiot.” However, it's tough. That's one. There's also another aspect here, which is, again, this is the reason why simulation is different from prediction. In simulation, in the ideal case scenario. So what simulation is trying to show is it's trying to show each step of the way or each step that we need to take to get to a certain outcome, right? So in the most advanced simulations, sometimes the next step that we're suggesting might be quite counterintuitive. The analogy that I sometimes give, and I ground it in a more realistic example, but, I, as I mentioned, I'm a huge fan of science fiction, and I don't know how, many of the audience members have read, like, things like the Foundation series by Asimov.Simulation as a Path, Not Just a PredictionSwyx [00:22:37]: Oh, yeah. We've mentioned psychohistory a number of times.Joon [00:22:39]: Okay, fantastic. So I might be, talking to the right crew. If you read Foundation series, literally the first act is there's a group of scientists who have found out that, “Oh, our galactic empire is going to collapse, and we're going to have 30,000 years of unrest.” And they run psychohistory, the simulator that tries to teach them, “Okay, how can we keep this unrest to a 1,000 years?” And they plan this out, and the first step of that plan is to get the scientists who say, “Okay, this is coming,” exiled into this random place in this, galax- galaxy.Swyx [00:23:18]: Terminus.Joon [00:23:19]: Exactly. And that's so counterintuitive. Like, what a strange move that you literally sent the group of scientists who was raising voice around this potential collapse of galactic empire into nowhere. How is that the right first move? Well, it turns out in this particular simulation, that was the move.Joon [00:23:40]: It's these things, right? And the reason why these reasoning is possible is because you're showing the step function or each step that results in a particular outcome. So really what simulation allows you to do in its highest form is you give it not a problem or question, like what would people answer to the survey? That's not what we do. What we tell it is, “Here is a goal that we have. In the context of foundation, we want to keep the unrest to a 1,000 years. What is the path that we need to take now to get to that particular future?” And that's what simulation allows you to do. Now, translating that into real market, imagine you're a automobile company and you're about to release a, EV, and you're trying to understand, well, how do we market EV, to make sure that our stock price goes up? But what if the answer comes down that, well, you can market your EV in XYZ way, but that might change people's perception around the cars that's not EV and make your overall sales to go down. Not very intuitive, especially all you're trying to optimize is EV salesss, and that's the only thing that you're tracking, then that might result in a completely wrong solution, or at least different solution than what you would have expected, whether it's right or wrong.Joon [00:24:57]: That's the power of simulation.Swyx [00:24:58]: For listeners, we covered a similar topic with Mikhail Parakhin from Shopify, where they are working on SimGym. I don't know if he ever talked to you about it. it's very similar.Joon [00:25:07]: ISwyx [00:25:07]: The goal is increased conversion, but then the journey is very unusual.Joon [00:25:12]: Journey is unusual.Swyx [00:25:12]: Yeah. The-- He's trying to look for interventions on a shopping trajectory, which is similar to what you're saying. Like, it's not about the attitudinal, is your word for it.Swyx [00:25:24]: It's about behavior.Joon [00:25:25]: It's about behavior.Swyx [00:25:25]: And that's exactly the difference, right? It's, like, not about the near-term direction about-- but it's more about, like, how do you affect multiple turns of interactions.Vibhu [00:25:35]: You had a good quote at the start about this as well. It's not about people wanting to know the outcome. It's about how they can change it, change the way to get there, something like that. But I wanna take it back to how do we know this is grounded? LikeGrounding and Evaluating Digital TwinsVibhu [00:25:47]: How do you run evals? How do you test that simulations come through? if I was to do the same thing that you described with, say, your favorite LLM, Opus, GPT-5.6, have some agent to map out these thingsVibhu [00:26:02]: How different are the answers we would get if I give it the same goal, the same objective, make a decent system? You're saying that you need to change the model weight. You have your own solution to this. But how far off are we, and how do you check if it's grounded? you have some interesting stuff on your site that points to how you run real evals, but if you could take us through that side. I think that's one of the big concerns that people have. They're like, “LLMs hallucinate.”Vibhu [00:26:27]: “You're just hallucinating layer after layer,” right?Joon [00:26:30]: The way we do this, and this is the paper that we worked on after the generative agents paper that really became the, at least for Simile and also the field of simulation and synthetic panels, really became the foundation. Yeah, this is the paper. the paper is called Generative Agent Simulations of 1000 People. Here's what we've done. For this paper, we brought 1,000 people that's representatively sampled from the US to a virtual lab. And what we have done was we spent two hours collecting fairly wide-ranging data. In this particular study, we focused a lot on this interview data, that was, whose script was taken from this project called American Voices Project. And then we would also pair that with a lot of behavior data and so forth, whatever we can collect within two hours. And then we would send these people away for a couple of weeks. And during that time, I would use this data to create their digital twins. And I would bring the humans, participants back after 2 weeks and have them complete a battery of surveys, experiments, behavior studies. So we have the list here, which included things like behavioral economics games. We would run literally, like, Big Five personality test, General Social Survey. We would also go ahead and run the randomized controlled trials that were published on PNAS. And we would have their digital twins predict how the source individuals would have acted in these studies and surveys. And this is where we could replicate people's behaviors and attitudes 85 percent as accurately as people would replicate their own. So that was the first really paper that gave this validated results that we can model individuals in an accurate way. And what we ended up finding now, of course, in AI space, so this paper came out at the end of 2024. AI space, a year and a half, 2 years, that's a lifetime.85% Accuracy and Why Frontier Models Miss Human BehaviorSwyx [00:28:24]: Yeah. Just, for listeners who are not seeing the YouTube, I just wanna say, like, the headline figure is 85 percent accuracy, like, which is a big improvement over all the otherSwyx [00:28:34]: Methods that you showed.Joon [00:28:36]: But the part that was particularly striking to us, especially as we improved this technology even further, was the generative AI models like ChatGPT, Claude that's coming out, it does give you the right foundation. However, what they do not consider is the true attitudinal and behavioral aspect of people, especially in the population that you care about. So what these models are really good at today is they're trying to become the super rational, objective machines, right? So you go get their data from places like Mercor, Scale. You talk to professional programmers, scientists to create model that's amazing at reasoning. That's what they do. Simile doesn't care about any of this. The models that we're talking about here, what we're trying to create are models that are as dumb as I am, right? So if I make some mistakes, the model has to make the same mistake.Swyx [00:29:34]: Oh, that's very hard.Joon [00:29:35]: That's very hard.Swyx [00:29:36]: You're solving Murphy's paradox.Joon [00:29:37]: That's exactly. And this is a completely different data and training objective. This is also where we see quite a bit of discrepancy in the performance in human behavior prediction between the frontier models, Simile's model, and the models being created in this space, where in some cases, the model performance of frontier models go all the way down to 20, 30 percent, especially if you go into that more niche population on topics that our customers would care about. On more gen pop, it might be around 50 to 60 percent. So it's not very robust. Like, you wouldn't want to make your decision off of these and these findings. If you can bring that up to 85 percent, that is ultimately what people end up getting very excited about.Swyx [00:30:20]: Yeah. Do we wanna keep going on the paper, routes?Joon [00:30:23]: Yeah, for sure. So the last one, was an interesting one. So this, paper was the follow-up paper that we had, to the 1000 agents paper, where the idea was now can we augment the models even further and post-train a model based on a lot of randomized controlled trials? So this was an interesting one. The data is always the most interesting part of modeling in many ways. The data that we got here was there's this, there's this platform called Open Science Framework. So some, the audience might be familiar with this. And there has been, especially in the social sciences over the past 5 years or so, there has been this concern around replicability of studies. And so it was a bit of a crisis, the scientists acknowledged, where we rerun the study and we don't see the same finding.Post-Training on RCTs and Replication StudiesVibhu [00:31:12]: Oof.Joon [00:31:12]: It's tough. And the reason why it's there-- that was often the case was there's this survival bias where the papers that get published often need to maintain what we call the value of less than 0.05 in the experiments that we ran. That suggests that only-- there's only 5% chance that the results that we saw is false positive. But the tricky part was all the papers that were not published, and there's still a 5% chance that whatever we publish is totally just randomly generated. Like, there's a 5% chance that, hey, this effect is not real, but it just happened to be real because of the sampling bias. So because of that, what scientists started to do was they started to register their studies. So before running an experiment, they would go to this platform and say, “Here is the data. Here is the population that we're collecting, and here's the hypotheses.” And they would just say, “Here is our hypothesis.” Like, “This is what we believe.” And you cannot retroactively change those hypotheses. This is what gives us more scientific statistical confidence that whatever effect that you ended up seeing is true. So that ended up creating this really interesting platform where there's one platform that has now contains tens of thousands of real-world experiments and hypotheses. And a lot of these are really high-quality, like, professionally designed behavior studies and random- randomized controlled trials. So we got the data and the studies from this platform and used that to make a point. And this particular, model is not, something that we're serving commercially because this was a part of the open science. But this particular data set, helped us make a point that by collecting a lot of these randomized controlled trials, that are really well-designed, we can make significant improvement in model's capability to predict human behaviors. So that's what this paper was about.Vibhu [00:33:10]: Is this stuff done on a individual level? Like, do I need to tune the model per individual, per company? Is there foundation model changes and then some slight post-training? Anything you can share there?Population-Level vs. Individual-Level ModelsJoon [00:33:21]: So this particular model was trained. the data we had at the level of individuals, but this particular model was trained. We experimented with both. And this is what we end up doing at Simile too. We always train 2, distinct model. One is what we call the population-level model. The other is what we call the individual-level model. And both take very similar input, which is the description of a subpopulation or individual and a stimuli. In this particular work, we've done the same. Here, the results that we are reporting are much more geared towards individuals because we do think that is a harder task in many ways, but that's what we have done.Vibhu [00:34:02]: You seen anything on the questions that humans can solve that models can't solve? So likeHuman Biases, Mundane Choices, and What Models MissVibhu [00:34:09]: Currently, it's, I live 5 minutes walk away from a car wash. It's a 10-minute drive. Should I walk or drive?Joon [00:34:16]: Huh.Vibhu [00:34:16]: The model will say, “Oh, walk to the car wash.” And, you don't have your car.Vibhu [00:34:20]: Is anything like this a problem in simulation? You would assume, like, very simple for human to think about, but if the model is saying you should walk to the car wash, anything here?Joon [00:34:32]: It's less, what can we solve, but I think it's more about what biases or mistakes do people make that models miss. Like, imagine that you are, like the. When I was still at Stanford, I lived in Palo Alto. So it's about, I would say, 40-minute walk from the campus. You ask the model, “Okay, let's go home. What can I, what can I do?” It would likely call an Uber or, give me, the bus time. But for the longest time, I really liked walking back. And the reason why I wanted to do that was not for efficiency. It really helped me think. And I like to walk for, half an hour or 40 minutes or so a day, where I just get to, just think about ideas, research, just get lost in my thoughts. That's very human activity. Unless the model has seen that and understands the importance of that activity, it would miss these kinds of features. So that I think, is fundamentally what we're trying to model. Like, what is fundamentally human might not be the most efficient thing to do, might not be the right thing to do, but things that make us who we are.Swyx [00:35:43]: I'm curious if, there are some data sets that you really want that would materially help you. One version of this may be interesting, which is more valuable to you to acquire as a data set, all of LinkedIn, all of Twitter, all of Facebook?What Data Matters: Social Media, Transactions, and FacebookJoon [00:35:57]: It's a little bit hard to rank, in part because, there's, there's this product saying where no feedback is wrong because it teaches you something about your users. Doesn't matter what feedback.Joon [00:36:11]: I think it's a little bit like that.Swyx [00:36:12]: So just whatever is bigger.Vibhu [00:36:13]: What about a different domain? Say it was. What about all of Amazon data?Joon [00:36:17]: Oh, yeah.Vibhu [00:36:18]: Shopping data, right?Joon [00:36:18]: Shopping data. So Amazon data is interesting in that it's very much behavioral, although, like, what people do on social media, you could squint and say that is also behavioral. But the transaction data is always interesting. It is also most commonly available, however.Joon [00:36:33]: If we were to look at purely social media, like if you really, if I were, if I had to really pick, Facebook likely is interesting because I do think it is most a default version of people. Because you go to LinkedIn, it's very much professional environment. So people put up their, they have their guards up, right? And that still is interesting because that is true human attitude and behavior, but it is not your base state. you go to Twitter- Twitter, people have their own crazy personas, or depending on who you are. Like, my Twitter profile and, persona is very much, initially was I was very much an academic. “Hey, I'm here to share my studies.” Now, I share, things that's related to Simile. But Facebook is one of those more private space where people just connect with their friends. In that way, I do think it shows you a little bit more about who that person is. So if I had to pick, I'd likely pick, Facebook.Swyx [00:37:30]: Yeah. And you're interested in, like, the whole person and their background and philosophy. I, is it too clinical or too machine learning-oriented to just say this is just ways to inject variance and biases? The broad question, is, like, is this any better than a randomized, like, combinatorial explosion version? So we have a link to the TencentBillion Personas, Synthetic Demographics, and Bespoke DataSwyx [00:37:54]: Billion persona paper, where they did not do any of the groundwork that you are doing.Swyx [00:37:59]: They just did like a cross matrix of here's all the professions in the world, here's all the people, possible backgrounds in the world, do a dot product across all of them, and that's it. That's your prompt for a billion people.Swyx [00:38:12]: This will do something. I don't know if it'll do what you do, but it gets you some way, some percent of the way there.Joon [00:38:18]: So this was an interesting paper. Like, what I admired about this paper when it came out was the scale. And you do gradually want to be able to simulate really large societies and interactions. So the scale is definitely admirable. it is relying heavily on the known statistics that went into training the model. So to the extent that you believe that statistics is correct, this is not a bad way to go about this. But the thesis here, and this is something that we also have seen in the market, like if this works, then we have solved simulation.Joon [00:38:54]: It,Swyx [00:38:55]: Because I survey, like, okay, 5% of the US population is in construction.Swyx [00:39:01]: The other 5% is in medicine, whatever, right? And then you just keep going down the list, and then you do the other side. 5% has, like, the big 5 personalitySwyx [00:39:08]: Of, like, neurotic or whatever. That's it.Joon [00:39:11]: That's it. So if you believe that the underlying data set and the platform that we're leveraging has all the right statistics, then this will have solved it. you're at that point merely retrieving the knowledge that is already embedded in the model, in the model parameters. That's not, unfortunately, what we see, where there is such detailed and also niche knowledge about people that if you just take one example, it might feel very mundane, but it's quite rich when you put together, that you do need to do a lot of bespoke data collection to better understand people. And this is also, I think what makes this particular, job fun, which you want to deeply understand people, and the process of deeply understanding them requires a lot of attention to the details. And you do need to pay attention to and pay respect to the daily lives that people lead.Scaling Simulation: From Thousands to SocietiesVibhu [00:40:04]: I wanna talk about scaling simulation.Vibhu [00:40:07]: So what can't we simulate, what can we simulate, and how does scaling affect this? So how big are the models? What if we go from, 8B, like, couple 100 billionVibhu [00:40:18]: Like billion000 parameters, billion000? Do we get scaling? Any interesting emergence? Like, at a certain scale, at a certain amount of training, you uncover anything unusual and any learnings from that?Joon [00:40:31]: What we are seeing is at Simile, so we do post-train our own model. The thing that we're seeing is the early glimpse of scaling law in simulations. The more data about humans and more compute you ingest, you start to get predictive and predictable gains of the model performance in simulating it, simulating people.Vibhu [00:40:51]: Ooh. We need a scaling law curve.Joon [00:40:52]: It's scaling law. Whenever you find it's a beautiful thing. And we're starting to see the glimpse of it, which is quite exciting. But if you talk about the ambition of simulation as a whole, it's not merely about building a model. It's about building a model, then creating the agents that become the individuals in a much larger ecosystem. So they're creating this multi-agent simulation. Down the line, you want these multi-agent simulation to also live in a very rich environment, right? What we are really trying to get to at that point is, hey, can we create. All right, let's do a time machine game again, and 5 years, 10 years into the future, can we create a simulation of 8 billion people living on Earth? I think that's quite interesting. And that really is the vision. And once you get to that state, the questions that you can help answer for the society also start to change from my perspective. The answers are fundamentally about emergence of the emergent behavior of society and large groups of people.Joon [00:41:53]: So the questions that I get excited by, and maybe this is a stodgy- a bit. I have my, academic side of me.Joon [00:42:01]: And for me, it's questions like, can we help solve climate change? If you look at climate change as a problem space, this is what we, like social scientists would often call it the wicked problems, problem where you have many actors with competing incentives for trying to make a very complex decision and coordinating that coordination decision. Very difficult to really solve in real life, which is also the reason why we couldn't solve it. Can simulation help us solve that? Another one is, can we understand the signals for collapsing democracy, or can we understand or can we uncover the origin story of the monetary system? These are societal questions that we never really had a good way of answering. If we can create simulations of our society, you have to believe that these are the problems that we can solve. So that's really the ambition of this field. And, I also think, yes, I think there's a Nobel Prize to be won there, which wouldn't be surprising. And I think there's some amazing societal impact that we can have to help people make better decisions.Climate Change, Democracy, and Societal SimulationSwyx [00:43:04]: Nobel Prize in economics?Joon [00:43:06]: In economics.Swyx [00:43:06]: Oh, I see. I see. Rooting for you to write that paper.Joon [00:43:10]: One of these days. But, one of the scholars that I was deeply inspired by, When I was coming into the space of simulation, is this scholar, named Thomas Schelling.Schelling, Agent-Based Models, and the Nobel PrizeSwyx [00:43:23]: Schelling point?Joon [00:43:24]: So the canonical example of the work that he's done was he was one of the creators of agent-based modeling. So this was, like, in the 1970s and 80s. It's very early days, but this was truly one of the first exemplars of simulations. And one of the canonical model from that time, and of course many of these simulations are trying to tackle the societal problems that's most relevant for their era, it was called the model of segregation. So racial segregation was a big topic, that, we cared about. And what they've done was they created this grid world where they had red dots and blue dots. And these dots were, back in the day, like, they were the agents, and they had a simple rule that governed their behavior. If certain percentage of your neighbors are of different color and if that goes above certain threshold, then you move to a new location at random.Joon [00:44:21]: One of the striking finding of this paper or this agent-based model was for the longest time, people thought the segregation within society was caused by explicit and overt racism.Joon [00:44:34]: But if you look at this model, people's preference towards living with people of the same color, that preference can be very minute.Joon [00:44:42]: But the very small difference causes the society to segregate completely over time. This was very counterintuitive for a lot of people. And this particular work ended up informing housing policies. Mixed income housing, got really inspired by this work. And Thomas Schelling ends up winning the Nobel Prize for having laid the groundwork for very early versions of simulations. The opportunity that I do see here in the more scientific terms, is agent-based models for the longest, had impact in the 1980s, 90s, to some extent, early 2000s, but it has now gotten forgotten by the community a little bit. Because as you can imagine, red dots and blue dots is not really a rich description of people.Joon [00:45:31]: But with the emergence of things like generative AI and, in particular, generative agents, we do have an opportunity to create these agent-based models that are high fidelity enough to help us make really complex decisions. And that's the opportunity that I see. If that truly works, then yes, that is the work that will result in a Nobel Prize.Swyx [00:45:53]: Yeah. For what it's worth, and I grew up in Singapore. 80% of Singapore is in public housing, and public housing has, enforced racial quotas for exactly that reason, which is very interesting. okay, so we talk about scaling, we talk about all these, the agent possible applications.Cost, Reuse, and the Economics of SimulationSwyx [00:46:13]: I'm scared about the cost. if you even-- let's just keep it to the US, about 8 billion people.Swyx [00:46:21]: But, how much does it cost to model so many hundreds of millions of people?Joon [00:46:26]: Oftentimes today, we don't start at that scale, this stage of the, of industry and simulation as technology. But we can get our users extremely rich and meaningful insights even by modeling thousands, tens of thousands of people. And today what we do is every week we are collecting data on the scale of tens of thousands people's data, and we have panel partnerships that gets us to tens of millions of people globally. So that's what we do today.Swyx [00:46:55]: And just as a side note once you've collected one person for one studySwyx [00:46:59]: Can you reuse that same person for all the subsequent studies?Joon [00:47:03]: That's exactly right.Swyx [00:47:03]: Okay.Joon [00:47:04]: The beauty of this model and these agents is the fact that they are domain-agnostic.Joon [00:47:08]: That what you're really trying to understand is what is the fundamental nature of these people? What's their social physics? And there are a lot of, a lot of, people that does change over time. Like, even, like, even things like, how many times have you gone have you been to, like, CVS the past week? that will change. But there's so many traits about people that are also known to never change. Like, your risk tolerance doesn't really change over time. It's very consistent. So it's these things that we're trying to learn. But the scale we are operating is right now hundreds or, tens of thousands to hundreds of thousands. And in many of the core use cases that we are deployed in, and this is more than enough population, to cover those. Really, at that point, what you care about is less the number of people, but more do you have the right subpopulation of interest covered? And this is also the reason why people want a larger sample. It's not because they want, stronger statistical guarantees. It's more that can they filter down to any population of their interest. However, you can also imagine in 10 years, if we truly believe that the compute is going to scale, that we'll have much more availability for compute, and our ambition for simulation is also going to scale accordingly, there's definitely a reason for us to create an entire data center worth of simulations.Joon [00:48:35]: Or in my hunch here is I do think in the next some number of years, we will start creating simulations that will cost as much as training a foundation model. But perhaps it's going to be so valuable to the society that it would be a no-brainer. Right now, even today, like, we are training bunch of new foundation model just so we can say we trained one and we spent tens of millions. But if we can create a simulation at the level of society that would solve climate change, I would run that today. I would raise the money right now just to run that.Multi-Agent Simulation and Social InfluenceSwyx [00:49:10]: Amazing. the follow-up question is, does it also compound if you let the simulations talk to each other?Swyx [00:49:18]: Or do they already do that today? They don't, right, as far as I understand?Joon [00:49:22]: It depends on what simulation you're trying to run.Joon [00:49:24]: In the multi-agent simulation setup, the agents do talk to each other.Swyx [00:49:28]: Right, which is exactly Smallville, right?Joon [00:49:29]: That's right.Swyx [00:49:30]: But a lot of times, for example, in commerce, you're just by yourself, so there's no point talking. which is way cheaper.Vibhu [00:49:37]: But they use all these levels, right? Like, you decide what you will buy based on what other people around you buy and talk about, right?Swyx [00:49:43]: It depends.Vibhu [00:49:44]: It depends.Swyx [00:49:45]: Again, I'm, I'm coming at this from a cost point of view. I'm like, “Oh my God.” LikeVibhu [00:49:48]: I thinkSwyx [00:49:49]: If there is, like, some combinatorial thing of, like, thousands of people talking to thousands of people, then that one million X's might cost.Vibhu [00:49:56]: I have a very different view as the cost point aside. Like, running these studies in reality is a lot more expensive, right? Running any study like this is you gotta have people do it, you gotta sign people up. It's very expensive and sometimes, like, not feasible to run the study.Vibhu [00:50:14]: But the outcome or the decisions you make are very expensive on them, right? So spend X million on something that, the overall process costs 100 million might as well, right? There's, there's a lot of value to be had there. It's a small cost, but I'm excited on the cost side.Joon [00:50:33]: To some extent, and when you deploy technology, you often want to deploy in a way where you can replace existing budget or you can make things more efficient, and that is the best way to deploy. However, the way you capture the long-term value of the technology is making the argument that, no, it's the upside, that by making this better decision using simulation, you have saved yourself or made yourself hundreds of millions or even billions of dollars, and that's a case to be made.Vibhu [00:51:06]: Random tangent question. So if you're doing a lot of inference, a lot of model multi-agent stuff, are you at the point where it makes sense to, train a model that' very sparse? You're expecting to do multi-million dollar runs. Are you thinking about this in model architecture standpoint or inference efficiency, or, you're still at the research phase of it works, we're not super there yet?Joon [00:51:34]: Efficiency, we do think quite a bit about. this is technology that is deployed now in some of the largest enterprise companies in the world, and we do process significant number of queries, that are trying to, simulate the populations in the world. So efficiency is a consistent thing. we don't want to over-optimize too early, so I wouldn't say, like, this is the higher bid Right now, but this is definitely something that we think pretty carefully about.Swyx [00:52:05]: Yeah. Are there other case studies? So we, you talked about CVS, talked about Gallup, Deloitte, Wealthfront.Efficiency, Enterprise Use, and Real-World Case StudiesJoon [00:52:12]: Wealthfront is an interesting one, because one of the things they were trying to do, they were one of the first customers that wanted to do product testing that goes beyond just asking people what they think about, let's say, behavior experiments and so forth. So there, really what we had to do was reason about multimodal input, so images, but also you can also imagine, like, these agents traversing through Figma mockups or websites. So some of the things that our agents can also do is it can be given a domain, like, or, like, a website URL and go use it for a while. It's these things. And Wealthfront was one of the first, customers, that was very excited about this possibility.Vibhu [00:52:53]: What have people been asking? Like, is there any demand that we have not covered? Like, UI testing, right?Vibhu [00:52:59]: I wanna try a new. I wanna ship a new feature, test the UI, simulate how people will do it. Any interesting things that you're seeing demand for?Product Testing, Websites, and Synthetic PanelsJoon [00:53:08]: Today, a lot of the demand does come from like, the places where people have historically used human panels, we can now replace with agents, and these synthetic populations. And this is not replacing human panel. in many ways, the simulation that Simile is building is grounded. So the way that I think about this is we are trying to represent humanity at scale. And in that way, the use cases are what we would expect, but it's the scale of deployment that surprises me.Joon [00:53:44]: Turns out there are so many decisions that people make every day in these organizations, groups, and we want to be able to say, “We listen to people. We have consulted our users.” But in reality, that is rarely the case because getting to people and asking them many questions, it's difficult. It's both costly, time-consuming, but most importantly, people are just not available. If I had to answer 1000 survey questions for this one particular, vendor, even if I wanted to do that, like, I would never do it. And that's very much the case. What simulation can do is ensure that the voices of people are always represented in rooms where the decisions for them is made, right? So all the stakeholders of this particular product launch, ideally they're consulted. That's what this technology really is trying to enable.Market Size, TAM, and Human Decision-MakingSwyx [00:54:39]: In my mind, that means it skews towards more consumer focus, right? Like, anything with a wide enough customer base where you do benefit from the diversity that you represent. What are some rough statistics, just for people who are not familiar with this market in general, what's the market size that. I'm sure you have some, like, rough numbers. market size is, like, a vague questionSwyx [00:55:01]: But, like, how much do people spend?Joon [00:55:03]: So market research is a $100 billion industry.Joon [00:55:06]: But the thing about simulation is not a tool for market research. Simulation is a tool for human decision-making. So the question around what is a TAM here is quite tricky, right? Because it's easy to say, “Well, market research TAM is roughly 100 million or 100 billion.” so is it a TAM? And not really, right? Because in many ways, you're trying to inform all human decision-making. You're trying to inform every decision that are made about humans for humans. What is a TAM for that? It's really unclear. And I'll be honest. Like, I have a scientific background, I have a research background, so I didn't come into the field calculating, oh, what is the TAM for human decision-making? But I just had to assume, well, if we can inform every decision that is made about human for human, that has to be big.Swyx [00:55:58]: Some- something valuable.Joon [00:55:59]: Exactly.Swyx [00:55:59]: To some extent, you are a unicorn founder now, and you have to care as a CEO. But, like, I do think, like, yeah, when you go into these boardrooms with people that you're quoting millions of dollars of contracts for, like, you have to say, “Well, here's what you spend on humans-”Swyx [00:56:15]: “. And here's what we save you, and it's 85% similar.”Joon [00:56:19]: And certainly, the value case, is something that we care deeply about. Like, what is the value that we provide to the users and the decision-makers? But this is also where, like, as a founder, I think valuation only tells one very superficial aspect of the story, and I try not to think too much about valuation, in general, because that's not what also motivates a team or certainly doesn't. I'm, I-- Again, the interesting thing about researchers is we are happy living in academia, getting paid next to. we get paid okay. we don't get paid that much, as a researcher here in academia, but it's the impact and it's the, it's the value that we can provide to the individuals and the society that really drives us. And in that way, ultimately what drives us is the impact. Does the simulation we provide have a real impact in people's decision-making in ways that progresses our society forward? If the answer is yes, then yes. that has to be great business, and we see that in numbers, and we do care deeply about that upside story, but that's the heart of it.Where Simulation Goes NextVibhu [00:57:27]: Do you have any timeline predictions? So we talked about scaling laws of simulations.Vibhu [00:57:33]: You brought up, okay, maybe one day we can simulate how to solve climate change.Vibhu [00:57:38]: Where are we now?Vibhu [00:57:40]: If that's not the end state, what is an end state, and what does progress look like?Joon [00:57:45]: So what I sometimes tell people is simulation as industry, it feels a lot like where GPT-3.5, GPT-4 was, for the AGI saga, which is we have now technology that is powerful enough to do real damage on the verticals that we are tackling. At the same time, there's a lot of progress that is yet to come. And that's, I think, where this is. So the way I see it, I do think there will continue to be breakthroughs both in data, in algorithms, and there will be much more aggressive scaling that will also happen over the next few years. But I think that's roughly where we are.Swyx [00:58:27]: I think that was about the ro

The CPG Guys are joined in this episode by Anita Watkins, CEO of the Insights Association which empowers more than 30,000 data and insights professionals. Its collective voice fuels growth, strengthens advocacy, and advances careers. Guided by ethics and truth, we bring understanding to an uncertain world.Follow Anita on LinkedIn at: https://www.linkedin.com/in/anita-watkins-8b33224Follow the Insights Association online at: https://www.insightsassociation.org/Anita answers these questions:You spent two decades at Kantar, most recently as Chief Solutions Leader for Creative, Innovation, and Qualitative — and now you're leading a trade association. What drew you to the Insights Association at this particular moment in the industry's evolution?The IA represents over 30,000 data and insights professionals. In your first months as CEO, what surprised you most about stepping into an advocacy and membership role versus a commercial one?CPG companies are under enormous pressure — tariffs, private label competition, shrinking research budgets. How is the insights function holding up, and where do you see it either gaining or losing strategic influence in the C-suite? The IA just held its Ignite: CPG event in Cincinnati. What were the dominant themes that emerged, and what does that tell us about what CPG insights leaders are most anxious about right now?You have a webinar series literally titled “Simulating Humans” — that's a provocative framing. How should CPG brands think about AI-generated synthetic respondents vs. real consumer research, and where does the IA draw the line on standards?AI is both a threat and an opportunity for the insights profession. In your view, what's the single biggest risk AI poses to the integrity of consumer data — and what is the IA doing about it?The IA has been driving the Global Data Quality Excellence Pledge and launching new resources around procurement and incentive guidelines. For CPG brands buying research, what should they actually be demanding from their vendors right now that most of them aren't?Survey fraud and data integrity issues have become a serious industry problem. How bad is it, and what levers does the IA have to enforce quality standards across the ecosystem?The IA is actively tracking state-by-state privacy legislation, GDPR, and now the proposed SECURE Data Act. How does a fragmented U.S. privacy landscape create operational headaches for CPG brands doing consumer research at scale?The IA recently raised concerns about how the Department of Labor classifies research respondents. That's a sleeper issue with real cost implications — can you walk our listeners through what's at stake?Anita, you've been recognized for developing the next generation of insights leaders throughout your career. With burnout high among market researchers and AI changing the job description rapidly, what would you tell a young person today about why this profession is still worth pursuing?You said upon your appointment: “I've spent my career believing in the power of insights to drive better decisions and better outcomes.” For CPG brands that are deprioritizing primary research in favor of data lakes and retail media signals — what's the cost of that trade-off that they might not be seeing?CPG Guys Website: http://CPGguys.comFMCG Guys Website: http://FMCGguys.comSheCOMMERCE Website: https://shecommercepodcast.com/Rhea Raj's Website: http://rhearaj.comLara Raj in Katseye: https://www.katseye.world/DISCLAIMER: The content in this podcast episode is provided for general informational purposes only. By listening to our episode, you understand that no information contained in this episode should be construed as advice from CPGGUYS, LLC or the individual author, hosts, or guests, nor is it intended to be a substitute for research on any subject matter. Reference to any specific product or entity does not constitute an endorsement or recommendation by CPGGUYS, LLC. The views expressed by guests are their own and their appearance on the program does not imply an endorsement of them or any entity they represent.CPGGUYS LLC expressly disclaims any and all liability or responsibility for any direct, indirect, incidental, special, consequential or other damages arising out of any individual's use of, reference to, or inability to use this podcast or the information we presented in this podcast.

Elisabeth and Gina Galvin are the mother-daughter founders of Stellar Snacks. On this episode of ITS, Elisabeth, Gina, and Ali discuss how lessons from Elisabeth's first food business shaped Stellar, what it takes to own and operate your own manufacturing, and how they've built a distinctive snack brand while navigating growth, retail, and working together as a family.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of STRAT, retired Marine intelligence officer LtCol. Hal Kempfer examines consequence management and warns of the risks he associates with a potential Super El Niño. Drawing on decades of work with military commands, FEMA, DHS, intelligence organizations, and state and local agencies, Kempfer traces the evolution of all-hazards consequence management and argues that critical gaps remain in disaster intelligence and decision support. He revisits lessons from Hurricane Katrina, the development and abandonment of CPG-502, and the intended role of state and local fusion centers in helping leaders understand threats, damage, and cascading consequences. Kempfer also explores California's historic flood vulnerability, including the catastrophic storms of 1861–62, and considers what extreme precipitation could mean for infrastructure, supply chains, businesses, governments, and communities today. His central message: preparedness must go beyond assurances. Leaders need realistic assessments, integrated intelligence, mitigation planning, and action before a major disaster actually arrives unexpectedly.Takeaways:Consequence management prepares organizations for natural and manmade disasters.Disaster intelligence provides leaders critical information for timely decisions.Hurricane Katrina exposed major gaps in federal disaster preparedness.CPG-502 sought stronger state and local disaster intelligence capabilities.Kempfer argues CPG-502 was never adequately implemented nationwide.California's historic floods demonstrate the catastrophic potential of extreme rainfall.Super El Niño could severely challenge existing emergency preparedness systems.Businesses must prepare for workforce, infrastructure, and supply disruptions.#STRATPodcast #HalKempfer #MutualBroadcastingSystem #StrategicRiskAnalysis #ConsequenceManagement #SuperElNino #DisasterPreparedness #EmergencyManagement #DisasterIntelligence #NationalSecurity #RiskAssessment #CrisisManagement #EmergencyPreparedness #CaliforniaFlooding #ExtremeWeather #HomelandSecurity #FEMA #DisasterResponse #CriticalInfrastructure #StrategicIntelligence

What happens when a founder decides to pull a product off 400 store shelves not because it failed, but because scaling the wrong economics is a fast track to killing a company. In this masterclass on CPG entrepreneurship, Omar Atia, Co-Founder & CEO of ZeroCarb LYFE, joins host Rose Hamilton, CEO of Compass Rose Ventures, to break down the mechanics of building a resilient, high-value enterprise.  Omar traces his evolution from corporate R&D to startup leadership, delivering a candid blueprint for navigating the hidden traps of rapid expansion, commercializing novel manufacturing processes, and making disciplined financial trade-offs. Key Takeaways & Business Frameworks: * Unit Economics Over Top-Line Growth: Why exiting 400 Sprouts locations was the smartest move for long-term enterprise value, proving that revenue without margin is just noise. * Bridging R&D and Commercial Scale: The operational reality of transforming a four-ingredient, kitchen-table innovation into a scalable, patented manufacturing system. * Positioning for Market Realities: How tracking customer behavior led ZeroCarb LYFE to pivot its core value proposition from "low-carb" to "highest protein-to-calorie ratio," proving why messaging must evolve alongside the market. * Omnichannel Strategy Demystified: A tactical breakdown of how to use direct-to-consumer for immediate feedback loops, food service for margin stability, and selective retail for broader reach. * Capitalizing on Structural Consumer Shifts: How to build product strategies around macro health shifts, including the rise of GLP-1 medications, by prioritizing high-protein, calorie-efficient nutrition. Whether you are scaling a CPG brand, refining your go-to-market strategy, or evaluating channel profitability, this interview serves as a practical guide to operational discipline and sustainable growth. For more on ZeroCarb LYFE visit: https://zerocarblyfe.com/ If you enjoyed this episode, please leave The Story of a Brand Show a rating and review.  Plus, don't forget to follow us on Apple and Spotify.  Your support helps us bring you more content like this!

Chicago's CPG scene is thriving, and we got a taste of it firsthand. Fresh off our latest Taste Radio meetup, we spotlight the city's vibrant brand community and sample a fascinating lineup of products discovered at the highly touted, unceremoniously shuttered and ultimately resurrected Foxtrot Market. The haul includes a wildly complex salted lemonade, a Mexican-inspired sparkling tonic, a soda-meets-sparkling-water brand, a caffeine-plus-protein bar and a "chai baby." Along the way, we unpack what these products reveal about flavor, functionality, packaging and the increasingly unconventional ways brands are competing for consumers' attention. Show notes: 0:20: A First For Us. Chi Fourth. Pilots, Battlers, Angels. A Trot For A Haul. Eye-Popping Innovation. – Ray's hotel room becomes a temporary studio as the hosts recap Taste Radio's Chicago Meetup at Pilot Project Brewing in Logan Square, which drew about 120 founders, operators and CPG professionals. They reflect on Chicago's vibrant and increasingly influential CPG scene, including a visit to the revamped Foxtrot Market, rebuilt after its collapse in 2024. The hosts sample and discuss emerging beverage brands including Five Corners Beverage Company, Aire, Ruby and Barbet, highlighting a growing appetite for complex, distinctive flavors and unconventional combinations, particularly among brands positioned as non-alcoholic cocktails. They also explore Beanies' coated soybeans, Freeman House's microbrew chai made with Oatly and Jilly's Jerky. The conversation then turns to Hall Pass, the new better-for-you chocolate brand from RXBAR founder Peter Rahal, which is launching exclusively at Walmart and reflects his broader strategy of creating lower-calorie, lower-sugar versions of familiar foods. The episode closes with a look ahead to upcoming Taste Radio meetups in San Diego, San Francisco and London. Brands in this episode: Five Corners Beverage Company, Aire, Ruby, Barbet, Beanies, Unhinged, Honey Mama's, Stumptown Coffee Roasters, Freeman House, Oatly, Jilly's Jerky, Hall Pass, RXBAR, David Protein, Pilot Project Brewing, Battle Bars, Ghia, Spindrift, Biena Snacks, TalkBack

Want to get your product into retail stores but don't know how to find buyers, pitch them, or prove your brand is retail-ready?In this episode of Small Business PR, Gloria Chou sits down with Alli Ball, founder of Food Biz Wiz, who has helped more than 3,500 CPG brands get onto retail shelves and generate over $1 billion in revenue.Alli breaks down exactly what retail buyers are looking for—and why getting the first purchase order is only the beginning.You'll learn:The 5 Ps retail buyers evaluate: product, pricing, placement, purchasing, and promotionHow to find retail buyers without paying for outdated buyer listsHow to use AI tools like Perplexity and Claude to research potential retailers and buyer contactsWhat to include in a retail buyer pitch (and what makes buyers ignore you)Why small brands should start with local and regional retailers before trying to land national chainsThe pricing mistake that can prevent your brand from scalingHow to drive sales once your product actually hits retail shelvesWhy every buyer pitch needs a specific call to actionHow often to follow up—and why Alli recommends following up until you get a yes or noWhether you're a CPG founder, product-based business, or small brand trying to get into retail stores, this episode gives you a practical roadmap for finding buyers, pitching your product, getting onto shelves, and turning that first retail placement into repeat orders.Connect with Alli Ball:Instagram: @foodbizwizDM her “rebuttal” for her 100 Buyer No's guide.Want your business to become the one AI recommends?In my free AI Visibility Masterclass, I'll show you how small business owners are using PR, media features, and credibility signals to increase their AI visibility, earn press without hiring a PR agency, and get discovered by customers at the exact moment they're ready to buy.

This interview is disseminated on behalf of Spartan Metals Corp.Spartan Metals (TSXV: W | OTCQB: SPRMF | FSE: J03) President and CEO Brett R. Marsh, M.Sc., MBA, CPG, joins Stocks to Watch to discuss the company's strategy to advance domestic tungsten projects amid a growing U.S. focus on critical mineral supply chains.Brett provides an overview of Spartan's Eagle Project in Nevada and Victorio Project in New Mexico, two tungsten assets at different stages of development. The conversation also covers upcoming catalysts, including maiden drilling at Eagle and an updated mineral resource estimate supporting a preliminary economic assessment for Victorio, with the PEA expected in early Q4 2026.Visit: https://spartanmetals.comWatch the full YouTube interview here: https://www.youtube.com/watch?v=Ow-cFHNTZuYAnd follow us to stay updated: https://www.youtube.com/@stockstowatchofficial 

In this special mashup episode of the RETHINK Retail Podcast, host Jeremy Goldman sits down with leaders from New York & Company, Elizée, Ross-Simons, and Paradise Naturals USA live from eTail Boston We dig into the exact tactics driving retail performance today: turning product returns into upsells, replacing point systems with paid VIP perks, and adapting product lines for GLP-1 users. INSIDE THE EPISODE: AI That Makes Money vs. AI That Replaces People Guests: Laura Cantor (VP of Marketing & Ecommerce, New York & Company) & Avani Oswal (Head of Digital, Elizée) - How New York & Company uses AI to read natural-language return reasons and automatically prompt customers with tailored exchange options. - How luxury footwear brand Elizée uses AI for lifestyle image background extensions and stock prediction without losing brand aesthetics. - Why small brands are running fast A/B tests with AI tools while legacy competitors get stuck in legal and corporate red tape. Ditching Point Systems for a $95 Paid VIP Club Guest: Diana Stuparu (VP of Ecommerce & Marketing, Ross-Simons) - Why 74-year-old jeweler Ross-Simons abandoned traditional discount points in favor of immediate, tangible value. - The breakdown of Ross-Simons' paid loyalty program (including three $50 order coupons, free 2-day shipping, and free returns). - How dedicated, real-person shopping assistants based in Rhode Island guide high-intent customers through complex gemstone and estate collections. - Using simple inputs like birth months to deploy automated, story-driven campaigns around monthly birthstones. Amazon Launchpads, CPG Mergers, & GLP-1 Demand Guest: Katya Vass (Founder, Paradise Naturals USA) - Why Paradise Naturals built an "Amazon-first" strategy to capture high-intent buyers searching for gut health tools without spending heavily on DTC ad acquisition. - How agile founders innovate faster than newly consolidated CPG mega-brands (like P&G acquiring Thorne). - Building advocate networks out of real customers who saw visceral health improvements rather than paying traditional influencers. - How appetite-suppressing GLP-1 medications are driving customers toward easy, nutrient-dense protein sources like bone broth powders to meet daily nutritional baselines. Listen above for an inside look at the strategies and operational playbooks shaping the future of retail execution.

This episode we're continuing our Category Review series! We have rising star in the retail industry, John Lane, from Raley's and Matt Williams, CEO and Founder of The CPG Collective. JJohn has led and leads several new product innovation strategies for Raley's and now oversees Frozen as Sr. Category Manager & Product Innovation. We'll get insight into how he and buyers look at category reviews - what they want to see from brokers and brands and what not to do. Matt has extensive knowledge in the CPG industry working his way up as a sales rep to being in high level c-suite positions with Odwalla, Dean Foods, Beecher's Handmade Cheese and Tattooed Chef before starting his hybrid CPG brokerage that focuses on California. The knowledge we will gain from this conversation will be priceless!

Send us Fan MailNate Littlewood, founder of Future Ready CFO, joins Noah Wickham on the MAG Growth Podcast to explain why profitable Amazon and e-commerce brands can still run short on cash. They cover the difference between profit and cash flow, how inventory can drain working capital, and why fast growth can create financial pressure. Nate also shares how founders can use ROI math, bottleneck analysis, and team skills to choose better growth projects. The conversation also looks at the 80/20 rule, underperforming SKUs, product catalog growth, and why adding more Amazon products does not always lead to more sales. Amazon sellers, CPG brands, and e-commerce founders can use these ideas to make better financial decisions and focus on profitable growth.If cash flow, inventory costs, or profit margins are holding the brand back, book a call with us to figure out what needs fixing first. https://bit.ly/4jMZtxu #AmazonSeller #Ecommerce #CashFlow #AmazonFBA #Entrepreneurship Want free resources? Dowload our Free Amazon guides here:Download the 2026 Amazon AI Operating Manual: https://bit.ly/3SLmusPAmazon Receiving Delay Guide: https://hubs.ly/Q04cdD4c0Amazon Catalog Spring Cleaning: https://hubs.ly/Q046BVfp0Amazon Proft Margin Defense 2026: https://hubs.ly/Q042trRH0Amazon SEO Toolkit 2026: https://bit.ly/4oC2ClTAmazon Seller Strategy Report 2026: https://bit.ly/3YN1RME2026 Ecommerce Website & SEO Readiness Checklist: https://hubs.ly/Q04btghf0Amazon 2026 PPC guide: https://bit.ly/4lF0OYX Timestamps00:00 - Pricing, Margin, and Ecommerce Growth01:50 - Nate Littlewood and Future Ready CFO03:54 - Why Founders Are Data Rich but Decision Poor06:51 - Knowing When a Business Is Ready to Grow08:37 - Using ROI to Pick Growth Projects09:45 - Finding Bottlenecks in an Ecommerce Business11:14 - Matching Growth Plans to Team Skills13:53 - Why Profitable Brands Can Have No Cash15:34 - How Fast-Growing Brands Grow Broke17:14 - The 80/20 Rule for Amazon Products18:05 - Calculating the Real Cost of Each SKU20:12 - The Jam Study and Too Much Product Choice21:24 - When More Amazon SKUs Hurt the Business23:43 - New Products vs Product Variations-----------------------------------------------------------------------------------------Follow us:LinkedIn: https://www.linkedin.com/company/28605816/Instagram: https://www.instagram.com/stevenpopemag/Pinterest: https://www.pinterest.com/myamazonguys/Twitter: https://twitter.com/myamazonguySubscribe to the My Amazon Guy podcast: https://podcast.myamazonguy.comApple Podcast: https://podcasts.apple.com/us/podcast/my-amazon-guy/id1501974229Spotify: https://open.spotify.com/show/4A5ASHGGfr6s4wWNQIqyVwSupport the show

The real scoop on getting into distribution — straight from the person who reviews the applications. Amanda Coish of Purity Life breaks down what actually earns a "yes." We've had the big-picture conversation about distribution before. This time we wanted the unfiltered version, so we sat down with Amanda Coish, who leads brand selection and onboarding at Purity Life — one of Canada's major natural-channel distributors. She reviews hundreds of brands a year while managing a portfolio of 400-plus, and she tells us exactly what separates the brands that get picked up from the ones that never hear back. If you're a founder eyeing distribution, this is the conversation to listen to twice. Amanda walks through the review process, the compliance and readiness gaps that get an application quietly declined, why "I'll do Instagram and Facebook" isn't the promotional support retailers are asking for, and the realistic timeline from application to product actually shipping out of the warehouse. Phil and Kenny pull on their buyer and CPG experience to translate what she's really signalling — including the two-word tells that make a buyer think "no." It's a candid look at the mechanics of Canadian retail: finite warehouse space, the fight for shelf, hip-pocket deals, brokers, national vs. regional compliance, and why that first year of a partnership demands real work from the brand, not autopilot. Want the big-picture view first? Catch our earlier conversation with Matthew from Purity Life: https://open.spotify.com/episode/1JHvuuWIQNhnMPqRTm1o7b?si=0d057c5cc302413c In this episode: How Purity reviews new brands — and the first things they check The readiness and compliance gaps that get you a quiet "no" Why promotional support (not social media spend) is what retailers want The real application-to-launch timeline and why it takes months What a healthy distributor relationship looks like after you're in A big thank you to CHFA for sponsoring the podcast. If you're a brand thinking about the natural channel, this is where you need to be — learn more and register: https://www.chfanow.ca/toronto/

Caitlin Skae is Director of Consumer Marketing at Carbone Fine Food. On this episode of ITS, Caitlin and Ali discuss how Carbone is building a grocery brand that stands on its own while drawing strength from its restaurant roots, why cultural relevance can't rely on celebrity alone, and how events, creators, and retail have become one connected marketing engine.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Advanced R&D Architecture: Eliminating Bioavailability Bottlenecks and Scaling Product Formulation with Vardan Ter-AntonyanIn a recent episode of The Thoughtful Entrepreneur Podcast, host Josh Elledge sat down with Vardan Ter-Antonyan, Founder and Managing Principal of Ter-Antonyan Consulting LLC, to examine the complex technical hurdles and scaling friction that routinely derail product development across the pharmaceutical, nutraceutical, dietary supplement, and functional food sectors. Vardan, an international R&D consultant, formulation scientist, and operational strategist, details how life sciences and consumer packaged goods enterprises can overcome low ingredient solubility and commercial manufacturing bottlenecks. This conversation provides a comprehensive, technical guide for R&D directors, technical founders, and operations leaders looking to deploy advanced drug delivery systems, improve product bioavailability, and leverage Lean Six Sigma methodologies to accelerate time-to-market.The Advanced Delivery Architecture: Deploying Nanotechnology and Streamlining Scale-Up ManufacturingThe primary technical bottleneck stalling the commercial viability of modern pharmaceutical and nutraceutical formulations is poor water solubility among active lipophilic compounds, which frequently results in minimal gastrointestinal absorption and wasted active ingredients. Vardan Ter-Antonyan explains that when a technical team relies on conventional formulation methods for oil-based actives, bioavailability can drop to single-digit percentages, eroding consumer efficacy and inflating raw material expenses. To overcome these absorption limits, forward-thinking R&D teams must deploy advanced nanotechnology platforms—such as self-nanoemulsifying drug delivery systems (SNEDDS), liposomal encapsulation, and cyclodextrin inclusion complexes—to dramatically increase active surface area. Incorporating controlled-release technologies like hydrogels or multi-layer tablet matrices further optimizes therapeutic delivery, giving brands a distinct, scientifically validated edge in competitive consumer markets.Translating complex laboratory formulations into predictable, large-scale commercial manufacturing requires a disciplined bridge between technical R&D and operational execution. Many emerging startups and mid-market product brands encounter severe scale-up failures because early-stage formulation choices fail to account for commercial equipment tolerances, raw material variations, or regulatory compliance standards. Applying Lean Six Sigma principles and root-cause analysis allows technical leaders to map every step of the manufacturing pipeline, systematically eliminate operational waste, and standardize production variables before committing capital to full-scale runs. This data-driven, engineering-first approach prevents costly batch rejections, shortens regulatory review timelines, and ensures that innovative formulations maintain their integrity during high-volume production.Furthermore, sustaining long-term innovation in highly regulated CPG and health sectors demands an agile executive mindset that balances rigorous scientific discipline with operational flexibility. Technical founders must avoid spreading critical R&D resources across unproven initiatives, choosing instead to prioritize high-yield projects like functional beverages, dissolvable powders, or oral pouches that solve clear consumer pain points. Drawing parallels to high-altitude mountaineering, technical leadership requires endurance, clear risk assessment, and the strategic agility to adjust formulation roadmaps when real-world production data demands a pivot. When cutting-edge delivery science, Lean Six Sigma operational controls, and clear portfolio prioritization are synthesized into a single R&D architecture, an enterprise eliminates technical bottlenecks, safeguards its margins, and predictably expands its market equity.About Vardan Ter-AntonyanVardan Ter-Antonyan is the Founder and Managing Principal of Ter-Antonyan Consulting LLC, a prominent formulation scientist, and a global operations strategist with over two decades of cross-industry experience. Specializing in pharmaceuticals, dietary supplements, functional foods, cosmetics, medical devices, and cannabis, Vardan helps technical teams solve complex bioavailability challenges and scale manufacturing processes. He is the author of The C-Suite Bible, host of his own industry podcast, and an expert consultant dedicated to eliminating technical bottlenecks for emerging and established product brands.About Ter-Antonyan Consulting LLCTer-Antonyan Consulting LLC is an elite technical advisory firm and operational consultancy engineered to help life sciences, CPG, and supplement companies accelerate product development and scale manufacturing. The firm specializes in delivering custom bioavailability enhancement playbooks, nanotechnology delivery integration, Lean Six Sigma process optimization, and lab-to-commercial scale-up support. Through rigorous root-cause audits and tailored R&D roadmaps, Ter-Antonyan Consulting LLC enables organizations to remove technical debt, improve product performance, and maximize enterprise valuation.Links Mentioned in This EpisodeTer-Antonyan Consulting LLC Official Website: vardanterantonyan.comVardan Ter-Antonyan on LinkedIn: linkedin.com/in/vardanterantonyanKey Episode HighlightsImproving Bioavailability via Nanotechnology: Deploying nanoemulsions, liposomes, and SNEDDS to overcome lipophilic compound solubility limitations and maximize active ingredient absorption.Engineering Controlled-Release Systems: Utilizing multi-layer matrices and micro-encapsulation to deliver sustained-release profiles for functional foods and pharmaceuticals.The Lab-to-Commercial Scale-Up Framework: Applying Lean Six Sigma methodologies to eliminate manufacturing waste and prevent batch rejections during commercial scale-up.Root-Cause Bottleneck Identification: Auditing R&D workflows and production data to resolve technical obstacles stalling product launch timelines.Agile R&D Portfolio Prioritization: Concentrating technical capital on high-ROI delivery formats like oral pouches, dissolvable powders, and functional beverages.ConclusionThe conversation with Vardan Ter-Antonyan underscores that accelerating product innovation in regulated markets requires an intentional balance of advanced formulation science and rigorous operational discipline. By standardizing internal R&D governance, embracing modern nanotechnology delivery platforms, and systematically eliminating scale-up friction, business leaders can transform complex technical concepts into highly structured, self-sustaining commercial assets.More from The Thoughtful Entrepreneur

Getting a massive retail PO can feel like the breakthrough your CPG brand has been waiting for. But what if saying “yes” actually puts you out of business?In this episode of CPG Insiders, Dr. Mark Young and Justin are joined by CPA and fractional CFO Scotty Palmer to break down one of the biggest challenges facing growing consumer brands: managing cash while scaling.Scotty shares real-world examples of brands that looked profitable on paper but were nearly out of cash, companies trapped by expensive receivables factoring, and founders who landed major retail opportunities only to discover they couldn't afford to fulfill them.They also unpack why your best-selling SKU isn't necessarily your most profitable, how rapid retail expansion can create a cash-flow crisis, and why looking backward at financial statements isn't enough when your business is growing forward.In this episode:The difference between profitability and cash flowWhy a big retail PO can actually hurt your businessThe hidden cost of receivables factoringHow to model cash needs before entering more storesWhy more SKUs don't always mean more profitHow to identify your most profitable products and channelsThe difference between a bookkeeper, controller, and CFOWhy growing brands need a forward-looking financial strategyIf you're building a CPG brand and preparing to scale into brick-and-mortar retail, this episode will help you understand the numbers behind sustainable growth.Learn more about CPG Insiders: https://cpginsiders.com/Connect with Scotty Palmer / Take the financial quiz: https://palmersadvisers.com/Get your copy of The 27 Unbreakable Rules: https://a.co/d/0bUR3OHeSubscribe for more conversations about building, scaling, and growing successful consumer brands.#CPG #CPGBrands #CashFlow #RetailStrategy #businessgrowth #CPGInsiders

What makes a brand worth betting on? Ken Sadowsky, affectionately known as "The Beverage Whisperer," returns to Taste Radio with a sharp look at where the biggest opportunities — and potential pitfalls — are emerging across the beverage category.  A senior advisor at Verlinvest, board director at Vita Coco and Icelandic Glacial, and early-stage investor in several emerging beverage brands, Ken explains why coconut water still has plenty of runway, what founders can learn from playing the long game, and why he believes colostrum could represent the next big functional beverage opportunity. Ken also shares his perspective on the rise of caffeine-free energy, hydration, matcha, protein and functional beverages. He also offers candid takes on celebrity-backed brands, flavor versus function, packaging, category positioning and the question he asks when evaluating any new beverage. Show notes: 0:20: Ken Sadowsky, Sr. Advisor, Verlinvest – Ken kicks things off by praising his beloved Red Sox before sharing his perspective on why coconut water has quietly become one of beverage's fastest-growing categories. He explains how strategic decisions by major beverage companies can temporarily shape retailer perceptions of an entire category, and why occasion- and benefit-based shopping may increasingly blur traditional category lines, particularly in smaller-format stores. Ken also discusses several emerging brands in his investment portfolio, including Rite, a caffeine-free energy drink powered by ketones and paraxanthine, and Leisure Hydration, which he sees as a function-first product with a more relaxed approach to hydration. He and Ray also evaluate products from Stillers, Yass, Gimber, Fizzin Protein and Grind. At the heart of Ken's philosophy is a simple question: Why will a consumer buy the product again? While functional benefits can drive trial, he argues that taste remains critical to repeat purchase in most categories. For founders, he emphasizes the importance of spending time in stores, studying the competitive set and allowing consumers to determine where a product belongs rather than relying too heavily on conventional category definitions. Ken also weighs in on celebrity-backed brands, arguing that celebrity involvement can drive discovery but is far more powerful when the celebrity genuinely invests in and believes in the business. He reflects on the extraordinary velocity of beverages compared with other CPG categories and explains why he often asks if a brand has the potential to sell a billion cans. Brands in this episode: Vita Coco, Harmless Harvest, Zico, Gatorade, Red Bull, Monster Energy, Celsius, Rite Energy, Parch, Subourbon Life, Ponyboy Slings, MOTH Cocktails, Spikedade, Super Lyte, Yass, Orange Toucan, Leisure Hydration, Spindrift, Coca-Cola, Neau Water, Eatyx, Oshee, Stiller's, Gimber, Vitaminwater, Pirate's Booty, AriZona Beverages, Ancient Nutrition, Fair Life, Fizzen Protein, Protein Pop, Grind, Onyx Coffee, Donpon Energy  

Join the Millionaire University AI Mastermind at ⁠⁠⁠⁠⁠⁠MillionaireUniversity.com/AI #1031 What if the future of content creation depends less on algorithms and more on real human connection? In this episode, host Brien Gearin talks with Susie Bulloch — founder of Hey Grill, Hey — about how she grew a $35 WordPress site into a thriving barbecue brand with viral recipes, national retail products, and a deeply loyal community. Susie breaks down how AI is reshaping the creator economy and why she's pivoting toward products, community, and more “analog” experiences that algorithms can't replace. This episode is a must-listen for anyone building a brand in the new era of content creation! (Original Air Date - 12/4/25) What we discuss with Susie: + Origin of Hey Grill, Hey + Breaking into a male-dominated BBQ space + Growing a content business organically + Launching a successful CPG product line + Impact of AI on creators + Shifts in the creator economy + Importance of audience relationship building + Pivoting toward analog and in-person experiences + Building paid communities and memberships + Preparing for the future of content businesses Thank you, Susie! Check out Hey Grill, Hey at ⁠HeyGrillHey.com⁠⁠⁠⁠. Follow Susie on all social platforms @heygrillhey. Watch the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠video podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ of this episode! Get your FREE 5 Minute Business Plan at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠MillionaireUniversity.com/Plan⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ To get exclusive offers mentioned in this episode and to support the show, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠MillionaireUniversity.com/Sponsors Learn more about your ad choices. Visit megaphone.fm/adchoices

Liquid Death is all jokes and dark humor on the surface, but the canned water brand's chief media and digital commerce officer, Benoit Vatere, takes measurement deadly seriously. He's tackling one of the gnarliest problems in CPG: proving that media actually moves product off the shelves.

In this in-depth interview, Aaron Henderson, CEO of Sweetleaf Stevia, shares his extensive experience in the grocery and CPG industry, focusing on natural sweeteners, supply chain intricacies, and evolving consumer trends like GLP-1. Discover insights on sourcing, product innovation, industry challenges, and the future of natural sweeteners in a rapidly changing market. Aaron Henderson is the current CEO of Wisdom Natural Brands, makers of SweetLeaf Stevia, with 25+ years of leadership experience driving growth across marketing, sales and brand strategy. As former CEO of The Touch Agency, Aaron worked on 200+ brands and saw 38 acquisitions. Co-founder of Midnight Venture Partners, a leading early stage venture capital fund focused on better-for-you brands.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

As part of the Retail Sound Bites summer replay series, Barry Thomas revisits one of the podcast's most impactful conversations, highlighting the evolving role of category management and its growing importance across the retail landscape. Featuring insights from Ferrero's Bala, this episode explores how retailers and CPG manufacturers can use category thinking to drive growth, strengthen shopper engagement, and prepare for the future of commerce. A must-listen for retail leaders, category managers, and FMCG professionals looking to stay ahead of industry change.   Have a topic you'd like us to cover? Contact us at Kantar's Retail Sound Bites Podcast.   Contact Barry: Email | LinkedIn   Contact Rachel: Email | LinkedIn

Kristyn Carriere went from running taste panels at Cadbury and formulating for Godiva to founding her own Canadian chocolate brand. This is what happens when a real food scientist decides to build a CPG company. On this episode, Kristyn Carriere of Seven Summit Snacks joins Phil and Kenny to talk about turning deep R&D experience into a grab-and-go energy chocolate — and why a big-company background changes how you launch. We get into the science of chocolate (conching, flavour optimization, why the same bar tastes different in five countries), the consumer-led product development that got the recipe right in three tries instead of hundreds, and the packaging and branding choices that help the bar stand out in two of the most saturated aisles in the store. Kristyn also shares the deeply personal story that gave the brand its name and brought her back home to Canada. There's a real lesson in here for founders: making something in your kitchen is one thing — knowing the industry, the iterations, and the science behind market fit is what actually moves a brand forward. Find Seven Summit Snacks at https://sevensummitssnacks.com/, on Amazon, and in retailers like Running Room, MEC, and Community Natural Foods. In this episode: From Disney on Ice to food science to global chocolate R&D Inside Cadbury and Godiva: how big chocolate really formulates The origin of Seven Summit Snacks and the story behind the name Consumer-led development: nailing the recipe in three tries Building for two customer types — online buyers vs. in-store shoppers Winning the aisle with packaging, iconography, and clean ingredients A big thank you to CHFA for sponsoring This Commerce Life. CHFA is the voice of Canada's natural health and organic products industry, and their trade shows are where the best emerging brands and buyers connect. Heading to Toronto? Sign up for CHFA East and be part of it: https://www.chfanow.ca/toronto

This week on Two Parents & A Podcast, happy Monday!! We're kicking things off with the MOST RANDOM comeback story: Nerds Gummy Clusters took a declining $50M brand to $850M in five years?! (Alex wants a whole documentary about whoever greenlit the cluster.) You might be asking why we start with this (lol) and it's simple.. Alex's leggings smelled like mildew, and Jules apparently has a condition (called dysgeusia) that makes water taste like mildew after she eats gummy clusters. Mind you, this was all supposed to be an off camera conversation LOL. But it leads us to a bigger convo: is CPG entering its fast fashion era? Cinnabon Oreos, bacon flavored Cinnamon Toast Crunch.. Harrison explains how these collabs actually work behind the scenes (including who pays who!) Then some travel talk: our flight home from Vancouver got switched to an 11:30 PM red eye?! Landing at 5:30 AM.. with a toddler. We've decided to switch flights, but survival tips for red eyes with toddlers are always welcome for the future. And speaking of taking your advice: a swim coach DMed us about the Puddle Jumper (they teach kids to float upright, which is NOT what you want) so we're officially returning ours and trying swim belts instead. This is why we love you guys!! Then the internet section: a full deep dive into Acquired Style's wedding and the NYC influencer universe (Harrison had SO many questions), and college dorm rooms being fully out of control.. we're WALLPAPERING dorm rooms now?! Whatever happened to picking out your bedding and calling it a day hahaha Then the meat & bones: activity play vs. imagination play with toddlers. Alex got 4.5 hours deep into imaginary farm stories this weekend (brain: fried, heart: full

Nestlé just dropped $523 million dollars to fully acquire the German complete nutrition brand Yfood. But don't totally overlook this as just another simple brand acquisition. And that's because it could become an important part of Nestle's (mostly still disguised) global strategy to conquer the “Age of Ozempic” marketplace. Obviously, increasing household penetration of weight-loss drugs mean less food overall is being eaten, which has driven demand for hyper-concentrated, nutrient-dense meals, snacks, and liquids instead. But let's see if Nestle begins to utilize Yfood as a gateway to drive GLP-1 patients into their new companion frozen food line…and eventually into personalized health platforms. Nevertheless, this isn't a one-off, as Danone and Lactalis are buying up competitors too…further strengthening my long-held thesis that in the modern CPG business landscape, true power belongs to those not just feeding consumers (but fueling them).

Procter & Gamble just dropped a staggering $3.8 billion to acquire Thorne, leaving mainstream financial commentators and health enthusiasts completely shocked. Why would a consumer packaged goods (CPG) titan known for Pampers, Tide, and Crest buy a premium dietary supplement brand? In this video, I'll pull back the curtain on the financial architecture and the radical corporate strategy driving this massive M&A transaction. This is far from just selling vitamins...creating a massive strategic paradigm shift into AI-powered predictive health, longevity, and data-rich consumer ecosystems. I'm breaking down the private equity wins for L Catterton, Thorne's massive manufacturing and testing moats, and how P&G completely outmaneuvered rivals like Unilever and Haleon to dominate the healthcare practitioner market. Plus, we address the biggest question on every consumer's mind: Will P&G dilute Thorne's ingredients and destroy its scientific integrity? If you want to understand the future of proactive, personalized, and integrative consumer healthcare, this deep dive is for you.

Getting your product on the shelf is only the first step. The real challenge is getting shoppers to notice it, try it, and buy it.In this episode, I sit down with Matthew Kubick of Local Demo Service to break down how CPG brands can use in-store demos to drive sales, learn from customers, and build stronger retail velocity.We talk about Matthew's simple four-step framework for turning samples into purchases, why founders should do their own demos early on, and how your strategy should change across retailers like Sprouts and Costco.If you're trying to improve sell-through, make the most of your retail launch, or turn sampling into actual sales, this episode is packed with practical strategies you can use.Startup to Scale is a podcast by Foodbevy, an online community to connect emerging food, beverage, and CPG founders to great resources and partners to grow their business. Visit us at Foodbevy.com to learn about becoming a member or an industry partner today.

Even in a tough fundraising market, investors are still writing checks. The question is: to whom? This week, we break down the latest CPG investment data and examine why protein-packed, dye-free, and ingredient-conscious startups continue to stand out with investors. We also take a closer look at the emerging products generating buzz – including protein candy, mushroom lemonade, snacking croutons, and tinned protein bars – and what they say about the future of food and beverage. Show notes: 0:20: A Timely Story. Which Direction? Head North. Algae Oil Is Hot. Jacked Up. Crunch, Sip, Snack. – The hosts open the episode by discussing the rapid rise of better-for-you candy, prompted by a recent New York Times article highlighting the category's momentum. While debating the role of alternative sweeteners and whether consumers ultimately prefer lower-sugar formulations or products made with real sugar, they also discuss how the success of brands like Poppi has inspired entrepreneurs to apply similar better-for-you playbooks to adjacent categories. The conversation then shifts to investment trends, drawing on Northhall's Q2 2026 Food, Beverage & CPG Financing Report to examine which early-stage concepts are attracting the most investor interest. They highlight recent funding rounds for companies such as Buffs and Algae Cooking Club, along with large-scale M&A activity driven by major corporations repositioning their portfolios around evolving consumer preferences. The hosts also turn their attention to a range of new products, including protein bars packaged in sardine-style tins, snacking croutons, Korean-style bone broth, and mushroom-infused sparkling lemonade. They discuss merchandising strategies, consumer appeal, and whether these unconventional formats and flavors have the potential to break into the mainstream. Brands in this episode: Rotten, Original Tiniez, Chewerz, Happy Candy, Better Sour, SmartSweets, Joyride, Good Greed, Poppi, Olipop, Buffs, Algae Cooking Club, Jacked Granny, RXBAR, David, Croots, Kushi,  Pepperidge Farm, Reclamation, Brodo, Brio Drinks, Goldie

This week we continue our series on Category Reviews - prying knowledge out of industry veterans from all angles. Last week we touched on how soon a broker/brand should reach out, what buyers like to see and what they do or do not want to hear + much more! If you missed that episode - it's worthy of a Spotify or Apple Podcasts listen! This week we will capitalize on buying experience from Darren Viscount who has nearly 30 years of retail buying under his belt in various roles from Category Manager to Director of Purchasing of Center Store/Vitamins. Darren has been very involved in all aspects of CPG the last 6+ years on LinkedIn and we look foward to hearing his perspective! We will also get the sales POV from Kate Cash. Kate has nearly 20 years in the CPG space starting her roots in a natural foods co-op, working as a broker and various sales roles - working her way up from a sales rep to a VP of Sales and now runs her own sales agency helping brands scale and providing them with customized sales leadership.

Hank Watt shares the inspiring story of how he discovered the miracle berry and turned it into a successful business that was featured on Shark Tank and promoted by Jennifer Garner. Learn how the berry makes sour taste sweeter than sugar, how it helped Hank control his emotional eating, how he and his partner built the business, and future potential of this revolutionary product that can transform taste and improve health. Key TopicsHow Hank learned about the miracle berry and its effectsWhat drove Hank & Juliano to launch the businessChallenges in preserving the berry to scale operationsInnovative freeze-drying process to preserve potencyMarket strategy and word-of-mouth growthFuture applications for the berrySound Bites"I swear, I heard the angels and the chorus singing. I felt the whoosh of the gates. I felt like the sunshine come down on me. Like I I had this transformative experience immediately where I became a believer instantly.”“LA is a type of place where if you're keeping weight off for any period of time, especially a significant amount, people want to know like what's your secret?”“He was like, I've got a couple conditions. We have to keep the berry pure. It has to stay raw. Like we don't need to add anything to it. We need to also figure out how to preserve it because we cannot deal with a cold chain.““The sharks have been phenomenal. The best business decision Juliano and I have ever made.”“Jennifer Garner put a video up on her Instagram… that put us on the map and it made us legit.”“These need to be on every table, kind of like butter, salt, and pepper. You know, it's there if you need it and you want it.”Chapters00:00 Introduction to Nature's Wildberry02:57 The Discovery of the Miracle Berry05:45 Transformative Experiences with the Berry09:02 The Locus of Control and Personal Empowerment11:53 Impact on Health and Diet14:57 Business Journey and Challenges17:52 The Berry's Unique Properties and Taste Testing20:55 Community and Word of Mouth Marketing24:01 The Decision to Start a Business26:52 Lessons from Personal Experiences30:10 The Future of Nature's Wildberry32:53 The Journey Begins: Overcoming Doubts35:14 Cracking the Code: Innovation in Preservation40:27 From Concept to Consumer: The Direct-to-Consumer Shift48:01 Shark Tank: A Game Changer for Growth55:02 Future Aspirations: Expanding Horizons01:00:44 Advice for Aspiring Entrepreneurs: Patience and Partnership01:08:12 A Better World: Quality of Life and CompassionLinksHank Watt on LinkedIn - https://www.linkedin.com/in/hankwattNature's Wild Berry - https://natureswildberry.com/Nature's Wild Berry on Instagram - https://www.instagram.com/natureswildberryNature's Wild Berry on Facebook - https://www.facebook.com/natureswildberryNature's Wild Berry on TikTok - https://www.tiktok.com/@natureswildberryNature's Wild Berry on YouTube - https://www.youtube.com/natureswildberryNature's Wild Berry on X - https://x.com/natureswildbrryNature's Wild Berry on Pinterest - https://www.pinterest.com/natureswildberry/…Brands for a Better World Episode Archive - http://brandsforabetterworld.com/Brands for a Better World on LinkedIn - https://www.linkedin.com/company/brand-for-a-better-world/Modern Species - https://modernspecies.com/Modern Species on LinkedIn - https://www.linkedin.com/company/modern-species/Gage Mitchell on LinkedIn - https://www.linkedin.com/in/gagemitchell/…Print Magazine Design Podcasts - https://www.printmag.com/categories/printcast/…Heritage Radio Network - https://heritageradionetwork.org/Heritage Radio Network on LinkedIn - https://www.linkedin.com/company/heritage-radio-network/posts/Heritage Radio Network on Facebook - https://www.facebook.com/HeritageRadioNetworkHeritage Radio Network on X - https://x.com/Heritage_RadioHeritage Radio Network on Instagram - https://www.instagram.com/heritage_radio/Heritage Radio Network on Youtube - https://www.youtube.com/@heritage_radio…The Food Institute - https://foodinstitute.com/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Narelle Plapp started Food for Health twenty years ago making recipes for patients who couldn't find allergy-friendly food on any shelf. She loaded her first Woolworths order by hand - 14 pallets that showed up via fax and had to be paid on delivery, funded by $13,000 from her parents. One SKU eventually did over $2 million in a single retailer. Then she did something most brand founders never attempt: she borrowed $8 million, bought a paddock, and built her own factory. Nine years later, Grain and Bake is a $35 million business - targeting $45 million this year - manufacturing for some of Australia's biggest food brands, running 24 hours a day, five days a week. In this interview, Narelle breaks down what it actually costs to manufacture an allergy-friendly bar, the brutal reality of retailer margins most founders don't see until it's too late, and how she convinced the bank to back a factory before she had a single confirmed customer. What you'll learn in this interview: • How she got her first Woolworths ranging by making sure friends and family bought out every trial store • Why she borrowed $8M to build a factory on a paddock - and the soft commitments from brands that got the bank across the line • What it actually costs to manufacture an allergy-friendly bar - the hidden 10-hour cleans, swabs, and 8-person cleaning crews most founders never budget for • The $0.40 per bar reality - and how to work backwards from RRP to know if your margins will survive retail • Why retailer category margins have jumped from 35% to 55% minimum over 20 years - and what that means for your P&L before you pitch Coles or Woolies • The 13-week clock: how long you have to prove velocity on shelf before you get cut • How a $4M investment in automated cartoning increased her line output by 30% - and why she passed the savings to her brand clients • Why she trawled Europe to find the right oven - and what it takes to commission a factory when you've never built one before • The Grain and Bake client model: why manufacturing for other brands makes her a partner in their success, not just a supplier • What she'd tell every CPG founder before they pitch a retailer - the whiteboard session that changed one AFL footballer's entire business plan If you're building a CPG brand, trying to understand the real cost of manufacturing and retail at scale, or just want an unfiltered view of what Australian food manufacturing actually looks like from the inside, this conversation will fundamentally change how you think about supply chain, margins, and what it takes to build something that lasts 20 years. SAVE 50% ON OMNISEND FOR 3 MONTHS Get 50% off your first 3 months of email and SMS marketing with Omnisend with the code FOUNDR50. Just head to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://your.omnisend.com/foundr⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to get started. WANT TO GROW YOUR BRAND WITH META ADS? Join the Foundr Operators Waitlist → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://foundr.com/operators⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ HOW WE CAN HELP YOU SCALE YOUR BUSINESS FASTER Learn directly from 7, 8 & 9-figure founders inside Foundr+ Start your $1 trial → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com/startdollartrial⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ PREFER A CUSTOM ROADMAP AND 1-ON-1 COACHING? → Starting from scratch? Apply here → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://foundr.com/pages/coaching-start-application⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ → Already have a store? Apply here → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://foundr.com/pages/coaching-growth-application⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CONNECT WITH NATHAN CHAN Instagram → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/nathanchan⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/nathanhchan/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CONNECT WITH NARELLE PLAP Instagram → ⁠https://www.instagram.com/narelleplapp/ LinkedIn → ⁠https://www.linkedin.com/in/narelle-plapp-27b3771a/ Website → https://grainandbakeco.com.au/ FOLLOW FOUNDR FOR MORE BUSINESS GROWTH STRATEGIES YouTube → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/2uyvzdt⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Website → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/foundr/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.facebook.com/foundr⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Twitter → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.twitter.com/foundr⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/foundr/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Podcast → ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com/podcast⁠

Are your hormones really the problem, or is your body missing the nutrients it needs to function properly? If you've accepted painful periods, PMS, mood swings, or low energy as "normal," this conversation may completely change the way you think about hormone health.  Joining me is Izzy Fischer, founder of DailyBasis, who shares the science behind cycle syncing nutrition and why women have different nutritional needs throughout the menstrual cycle. We cover the roles of estrogen and progesterone and why iron and B vitamins matter for women of all ages. You'll understand why foundational nutrition matters long before PMS symptoms become severe and how building healthy habits today can support hormonal resilience for years to come, especially in menopause.   "PMS is not normal. We should not all be in pain; we should be feeling relatively good most of the time." ~ Izzy Fischer   In This Episode: - Izzy's nutrition and entrepreneurship background - Nutrients that women need to optimize hormones - Estrogen and progesterone cycle explained - Core nutrients for women: Iron and vitamins - Why foundational nutrition matters from a young age - How DailyBasis supplements work for women - Testimonials and where to buy DailyBasis supplements   Products & Resources Mentioned: DailyBasis Supplements for Women: Get 30% off your first month of Cycle Routine at https://dailybasislife.superfiliate.com/MYERS or use code MYERS at checkout Fresh-Pressed Olive Oil: Try a full-size $39 bottle for just $1 to cover shipping at https://getfreshwendy.com   Bon Charge Red Light Face Mask: Get 15% off sitewide, plus free shipping and a 12-month warranty, with code WENDY at https://boncharge.com/  Heavy Metals Quiz: Check your toxicity score and receive a free video series on how to detox your body. Take the quiz at https://heavymetalsquiz.com    About Izzy Fischer: Izzy Fischer is a second-time founder, CPG marketer, and health-focused innovator building DailyBasis, a women's health company designed to help women feel genuinely good in their bodies with a daily supplement built around the menstrual cycle.  She built and exited her first company at 23 and worked in nutrition, brand, and product leadership at Tufts Human Nutrition Center, Eclipse Foods, and Clif Bar. You can learn more about her supplement line at https://www.dailybasislife.com/    Disclaimer The Myers Detox Podcast was created and hosted by Dr. Wendy Myers. This podcast is for information purposes only. Statements and views expressed on this podcast are not medical advice. This podcast, including Wendy Myers and the producers, disclaims responsibility for any possible adverse effects from using the information contained herein. The opinions of guests are their own, and this podcast does not endorse or accept responsibility for statements made by guests. This podcast does not make any representations or warranties about guests' qualifications or credibility. Individuals on this podcast may have a direct or indirect financial interest in products or services referred to herein. If you think you have a medical problem, consult a licensed physician.

Esther Levy is a food scientist, consultant, and founder of Evolve Food Consultants. On this episode of ITS, Esther and Ali discuss why food science is at the center of every successful food business, how founders can better navigate product development, manufacturing, and supply chains, and why today's conversations around GLP-1, clean labels, MAHA, and ingredient transparency are changing the way brands think about innovation and growth.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

How should founders value an early-stage consumer brand, negotiate with investors and raise capital without giving away more of the company than they intended? In this second part of my conversation with Phil Hails-Smith, Managing Partner at Joelson, we move from founder equity into investment, valuation and the legal foundations required to scale a CPG brand.Phil explains why private-company valuation is an art rather than a science, how SEIS and EIS can support early fundraising, and why an ambitious valuation can create painful dilution if the business later misses its plan. We also discuss responsible AI policies, investor due diligence, change-of-control clauses and why owning every element of your intellectual property can determine whether an eventual sale completes.What You'll LearnHow SEIS and EIS can help early-stage founders attract investment.What investors consider when valuing a pre-revenue or early-revenue consumer brand.Why raising at too high a valuation can cost founders more equity later.What a scaling company should include in its AI policy.How contracts and intellectual-property ownership affect an eventual exit.Key Topics DiscussedMoving from founder equity into external investmentSEIS and EIS tax incentivesRaising an initial seed roundValuing pre-revenue and early-revenue consumer businessesRevenue multiples and future growth potentialWhy valuation is an art rather than a scienceBalancing company valuation against founder dilutionThe dangers of raising at an unsustainable valuationDown rounds and the effect on founder ownershipChanges in investor appetite for consumer and CPG brandsWhy defensible physical products may appeal to investorsResponsible company use of AIProtecting confidential and personal informationControlling which AI tools employees can usePreparing for private equity or strategic acquisitionReviewing customer and supplier contractsChange-of-control provisionsMaking sure the company owns its brand assetsThe Innocent logo dispute and the importance of intellectual propertyWhy unresolved legal issues can delay or jeopardise a saleUseful linkshttps://joelsonlaw.com/Like this episode?PLEASE share the love by sharing this episode with another founder building a challenger brand, a colleague or a mate who loves brilliant non-alcoholic drinks, or anyone trying to work out how to build a sharper, more focused growth model.Don't forget to FOLLOW or SUBSCRIBE to Brand Growth Heroes on your favourite podcast app, and even LEAVE A REVIEW - both of these actions make a MASSIVE difference to our mission to help more founders just like you.Join our communityInstagram (https://www.instagram.com/brandgrowthheroes)LinkedIn (https://www.linkedin.com/company/brand-growth-heroes/?viewAsMember=true)Youtube (https://www.youtube.com/@brandgrowthheroes)Find out more about the programmes and courses Fiona runs here (https://www.brandgrowthheroes.com/mini-mba-2026)Join the NextGen CPG WhatsApp group for founders leaning in to the value that a leadership approach to engaging with AI can unlock for businesses like yours.*** Thanks to Brand Growth Heroes' podcast sponsor — Joelson, the commercial law firm ***If you're a founder, you already know how much energy goes into building the perfect product, creating standout branding and connecting with consumers.But scaling a CPG business also brings legal complexities that can make or break your growth journey - from contracts and regulatory compliance to protecting your intellectual property.That's why we're proud to partner with Joelson, the leading commercial law firm specialising in helping founders of scaling consumer brands.Joelson works with brands like Little Moons, Trip, Eat Natural, Bear Graze and Pulsin, and advised the innocent founders on their landmark sale to Coca-Cola - and still work with them at JamJar Investments today!Joelson is offering a FREE LEGAL CONSULTATION to all BGH listeners (https://joelsonlaw.com/contact/) - we highly recommend you take them up on it!CreditsThanks to our Sound Engineer Gyp Buggane at Ballagroove.com and the entire Brand Growth Heroes team.

Ace Hardware's RedVest Media is rewriting the retail advertising playbook by turning a late market entry into a strategic advantage across its 5,200 store footprint. Head of Retail Media Molly Hjelm joins Mike Shields to explain why friction-free Pacvue integration, closed-loop endemic attribution, and re-embracing physical stores outperform legacy off-platform tactics. Key Highlights ⏰ The Late-Mover Edge: Launching a network today means skipping years of clunky tech builds and plugging straight into mature e-commerce and delivery setups.

Points of discussion: 1. Drink Small Beer - Learn more at: www.craftbeerrebranded.com / http://www.beyondbeerbook.com - Have a topic or question you'd like us to field on the show? Shoot it our way: hello@cododesign.com - Join 9,500+ food and bev industry pros who are subscribed to the Beer Branding Trends Newsletter (and access all past issues) at: www.beerbrandingtrends.com  

Josh Blyskal, Special Projects at Profound, returns to the show for a data-rich, in-person conversation with Ross Hudgens about what's actually true in AI search right now, and what's just noise.  Josh makes the case that the industry's obsession with tracking frequency is mostly a distraction (running a prompt 10x a day vs. once barely moves your visibility score) and that the real hard problem is still attribution. He walks through a new model some advanced teams are using, treating agent attention as a proxy for human attention and heavily discounting citations into "clicks,” and shares why ChatGPT referral traffic is up 60% since mid-March, especially for CPG.  From there they get into why GEO is fundamentally a relationship business (the Reddit–Google negotiations, why Claude cites Reddit almost never, and the walled-garden problem), what actually separates slop from signal, and why listicles still do the "caloric work" of teaching a model an industry.  Show Notes 0:00 How often should you track Prompts? 08:14 The new attribution model 14:05 GEO as a relationship business 20:05 What separates slop from signal 26:43 Product pages, versus queries and battle cards 30:21 ChatGPT vs. Claude 34:12 Future-proofing your stack 40:55 Video, social and the language arbitrage 49:18 Imitation vs. creation & where GEO is headed Show Links Josh's website Josh on LinkedIn Preorder "Generative Engine Optimization: The Definitive Guide to AI SEO" by Ross Hudgens Subscribe for weekly episodes Listen on Apple Listen on Spotify Follow Ross on X Follow Siege Media on X Email Ross   Subscribe today for weekly tips: https://bit.ly/3dBM61f Listen on iTunes: https://podcasts.apple.com/us/podcast/content-and-conversation-seo-tips-from-siege-media/id1289467174 Listen on Spotify: https://open.spotify.com/show/1kiaFGXO5UcT2qXVRuXjsM Listen on Google: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zaW1wbGVjYXN0LmNvbS9jT3NjUkdLeA Follow Siege on Twitter: http://twitter.com/siegemedia Follow Ross on Twitter: http://twitter.com/rosshudgens Directed by Cara Brown: https://twitter.com/cararbrown Email Ross: ross@siegemedia.com #seo | #contentmarketing

With “protein mania” pushing the macronutrient into top-of-mind status (arguably creating more purchasing impulsivity), is it finally time for Premier Protein to embrace the “single life”? BellRing Brands (NYSE: BRBR) is a portfolio that owns a collection of convenient nutrition brands like Premier Protein and Dymatize Nutrition, which was previously wholly-owned by Post Holdings. A fast-paced and busy lifestyle is pushing consumers to switch to quick and healthy meal options. This has resulted in above average categorical growth rates and increased household penetration of RTD protein shakes that promote active lifestyles. Additionally, powders are becoming more mainstream, and category proliferation has created an environment where more consumers are purchasing both every day and performance nutrition positioned protein products at grocery stores and mass retailers. Bellring Brands reported 2026 Q3 net sales of $570.4 million, which was up 4.2% YoY. Premier Protein (~85% of BellRing Brands total revenue) increased by 0.7% YoY, driven by volume growth but partially offset by a decrease in price/product mix. Dymatize Nutrition was up 26.7% YoY, driven by higher average net selling prices. Moreover, I provide deep dives into Premier Protein RTD protein shakes business activity, along with examining similar metrics surrounding the protein powders from Premier Protein and Dymatize Nutrition. But then, Michael Axelrod officially took over as the new CEO of BellRing Brands. And you might be asking yourself, who is Michael Axelrod…and can he help improve performance and better translate category leadership into more consistent, profitable growth over time. In all honesty, since he only started a handful of days ago…and hasn't laid out his strategic initiatives yet, I'm not totally sure. But here's what I'll say, Michael Axelrod has extensive up- and downstream CPG industry experience…and trust he'll strengthen execution and improve operational discipline (most notably involving Premier Protein's regionally diverse contract manufacturing network). However, here's my biggest concern…can he effectively transition Premier Protein into this “full-fledged beverage company,” a much-needed strategic reality that previous leadership seemed hellbent on not embracing. And in a market where “singles” are quickly becoming a larger share of the total RTD protein shakes market, Premier Protein must think more deeply about not only its DSD distribution strategy but organizational structure. Right now, the RTD protein shakes category is more dynamic and competitive than ever, thus for Premier Protein to remain the market leader it will require not only greater operational discipline but new capabilities.

Running the global digital and insights organization at one of the world's largest and most storied CPG companies takes a combination of data chops, marketing savvy, and collaborative leadership skills. Keith Lehman, Global Director, Digital Commerce Marketing at Colgate-Palmolive has all of that, but in addition he credits his intense curiosity for being the additional element that helps drive the processes to help his internal customers uncover the next best action for growth. Keith joins the podcast to explain how they are building the machine to power Colgate's next era of growth.

What does it look like to build a CPG brand when you've already seen both success and failure?Kristoffer Quiaoit, founder of Good Journey Foods, shares how he's approaching this company with a new mindset grounded in self-awareness, mental health, and long-term sustainability.We start with how Good Journey is being built today, from decision making to daily practices, and why staying even keel has become a core part of his leadership style.Then we go back to Nui Foods, the company that came before, and unpack what happened, what he learned, and how that experience forced him to confront parts of himself that ultimately made him a better founder.We also get into the role of nutrition, parenting, and personal development, and why building a business often becomes the catalyst for deeper personal growth.Startup to Scale is a podcast by Foodbevy, an online community to connect emerging food, beverage, and CPG founders to great resources and partners to grow their business. Visit us at Foodbevy.com to learn about becoming a member or an industry partner today.

Consumer expectations are changing fast, and brands of every size are being forced to adapt.  In this episode, we discuss what PepsiCo's response to GLP-1s and inflation signals for CPG. We also dive into Vita Coco's acquisition of a super-premium rival, and sample everything from cereal-inspired protein shakes and date-sweetened cola to birch water and caffeinated banana milk. Show notes: 0:20: Chi, Summer. Is Ce Real? Pep Rally. Coco + Copra. Date Drink. The Two a Yous. It's French. — Ray and Melissa lament how quickly summer is slipping away, but they're looking ahead to Taste Radio's upcoming meetup in Chicago. Meanwhile, Mike is mixing up an unconventional concoction he swears will improve his physique. Melissa then leads a conversation about PepsiCo's response to GLP-1 adoption and persistent inflation, prompting a discussion about how major CPG companies are balancing lower prices on core products with innovation in premium and functional offerings—a dynamic that's creating both headwinds and opportunities for emerging brands. The hosts also examine Vita Coco's acquisition of premium coconut water brand Copra, viewing it as a strategic move to expand across multiple price tiers and compete more directly with Harmless Harvest. Ray samples Unpop's date-sweetened cola and highlights Tuyyo agua fresca hydration sticks, NYMBL high-protein ice cream, and OOZ birch water, while Melissa gives high marks to Halfday iced tea and Matcha DNA's powdered matcha lattes. Brands in this episode: Spylt, Miils, Doritos, Carbone, Copra, Vita Coco, Harmless Harvest, Jolt Cola, Olipop, Poppi, Nixie, Stiller's, Coca-Cola, Pepsi, Halfday, Nymbl, Protein Pints, David, Tuyyo, Unpop, OOZ, Matcha DNA, Minor Figures

Noah Hopton, CEO and Founder of Finvisor, helps startups and growing businesses simplify operations by building integrated back-office teams that combine accounting, finance, payroll, HR, insurance, and technology. By combining experienced financial professionals with modern technology, Noah enables businesses to streamline operations, stay compliant, and focus on sustainable growth.  In this conversation, Noah introduces The Adjacent Extension Framework—Earn the Trust, Build the Relationship, Listen for Other Problems, Connect Other Specialists, and Empower the Team with Tech. He explains why proactive service creates lasting client relationships, how solving adjacent business challenges leads to sustainable growth, and why integrated back-office teams outperform disconnected vendors. Noah also shares how AI is reshaping finance operations by automating repetitive work, empowering finance professionals to focus on strategic decision-making, and helping businesses leverage technology to enhance—not replace—human expertise. — How to Outsource Your Back Office with Noah Hopton  Good day, listeners. Steve Preda here with the Management Blueprint Podcast, and my guest today is Noah Hopton, the CEO and Founder of Finvisor, helping seed and Series A companies that have outgrown spreadsheets and part-time bookkeepers but aren’t ready for a full-time finance team yet. Their job is to give you the financial clarity to make good decisions at every stage of growth. Noah, welcome to the show.  Yeah. Pleasure to be here, Steve.  Well, great to have you here, and I’m very curious about your career and your business and what you built here. I’m particularly curious about your personal ‘Why’ and how you manifest it in your business.  Personal ‘Why.’ That’s great. Well, I’ll be honest, I didn’t go in thinking I was going to be an accountant or run an accounting firm. You know, I studied accounting in school. Eventually, I thought I was going to probably be more in a kind of front-of-house sales relationship because I enjoyed the people part—making relationships and meeting people.  But I was very fortunate that I found the consulting, fractional CFO world, where I got to discover a love of problem-solving, creating relationships, and creating value for clients. For me, it was kind of this love of helping clients understand their business, helping clients understand what to think about around the corner, where it's not just being in-house with one set of books that you're closing.Share on X  When you’re at Finvisor, my day-to-day, at least when I started, was probably working with 10 to 12 clients a month and helping them understand, “Okay, how did they perform last month? Can they hire a certain number of people? And what’s the plan going forward?”  Yeah, I mean, that’s super helpful. I started life in accounting as well with KPMG, and what attracted me was to essentially have that language of business so that I would be able to understand how a business works and have this confidence of not flying blind, right? That’s really, really cool. So how did you evolve from a CFO into a founder? What was the trigger point for you?  So I was very fortunate. I actually was at a prior firm at one point when I started my career, and they were a little bit like the cobbler with bad shoes, where eventually they decided they had to close shop, and clients were going to be given notice. I, myself, was given notice saying, “Hey, in a week, you’re not going to have a job, Noah.” And so I was really given this moment in life, saying, “Hey, if I enjoy what I’ve been doing, do I think I could do it better than the firm I’d been at?  And do I want to make this leap into being a founder and starting a business?” And so my co-founder and I both talked to each other and said, “Look, we love our clients. We love what we’ve been trying to build. I think we just need to do a little bit of a refresh and restructuring of how this operates.” And so we started our own company. I was very lucky that I started with about, I had about 30 clients and a team of four on day one, which I think is unusual.  Most people in the accounting space start off as a one-person shop, trying to grow from one to two, and having to double their clients or double their size to get there. We were fortunate to have five team members and 30 clients on day one. Originally, our vision was just, “Hey, let’s help with the fractional CFO and the bookkeeping,” but that really evolved over time as we added additional services and really understood where our clients were having problems in their back office.  What are the areas where maybe the insurance brokers they’d been working with weren’t very hands-on and kind of came in once a year? Our clients were asking us, as their CFO, “Hey, can you help us select our health insurance?” And we’re like, “Well, we’re kind of doing the broker’s job. Why don’t we build out our own team?” So that was one of the first verticals we moved into and added by building an insurance brokerage. From there, we kept building, where now not only do you have your CFO and accountant helping you, but you also have them with the ability to go out to market, help you compare quotes, and help get your insurance in place. So you’re essentially expanding the array of virtual services that you’re providing, or fractional services that you’re providing, to your clients?  Correct. Yeah. We really try to own the full back office end to end because I think a lot of people deal with, “Okay, great, I have a bookkeeper, I have a tax accountant, I have an R&D tax provider,” and they’re dealing with four or five different vendors that don’t really communicate. The client is the person playing telephone between the two, and we’re like, “Wait, stop. Why is this the solution?” We should just build a different business where it’s all under the Finvisor umbrella.  It’s all full-time team members who are actually working together on behalf of the client, even if fractionally. Some of our clients only need five hours of a payroll specialist, but they need someone to own that role, and they need that person to be able to talk to their sales tax team because it’s like, “Oh, we hired someone in a new state. Is sales tax applicable there?” And connect those dots because, when you have these disconnected providers, you have a lot of things that can drop because they’re not in people’s field of view.  Yeah, I mean, it’s a great service. If you can get a competent team that will take care of your back office, then you can focus on figuring out message-market fit and then essentially scaling revenue. You don’t have to worry about it, and you don’t have to babysit inexperienced people that maybe you can afford to hire, but who would not be able to own the job.  Yeah, exactly. I mean, it’s kind of the, “Do you want to…” You know, I think at least when we started in 2014, there was more of a generalist bookkeeper. That’s kind of the typical solution people went with. Nothing against that, but it’s kind of nice to have dedicated specialists in the different back-office areas that you need. I mean, bookkeepers are great.  They’re usually not your best payroll and HR people. They’re not thinking about California final-paycheck laws, or whether you need to offer a 401(k) if you hire someone in California. Whereas, if you have someone whose entire job is payroll and HR, and you need Finvisor to help run your payroll, they’re going to be thinking about those edge cases and helping you along so that you can just build your business, get to the next milestone, and not worry about tripping yourself up because of compliance, taxes, or a lack of visibility in your reporting. Yeah, that’s great peace of mind. So this podcast is about frameworks, and I wonder, what is your framework? How do you help your clients, or how do you figure things out? What have you developed? We’re about 400 frameworks in, so I’m looking for something unique that helps you and is easy to explain—three to five steps maximum.  Yeah. I mean, one of the ones that comes to mind for us is what we’ve really called the Adjacent Extension Framework. So, first, do really good work and earn your client's trust in one area. Makes it easy for them to approach you.Share on X For us, it’s historically been accounting. People think, “Great, get my books put together.” But for us, it’s really about creating a relationship and earning the client’s trust.  Then, as step two, listen for the other problems they’re having. What are the adjacent problems they’re asking you to solve? And then for us, what we’ve really done is double down in those other areas by building specialists in those verticals. Once you’ve earned the client’s trust, if you’re doing their accounting and all of a sudden they’re struggling with invoicing or collections, you can say, “Hey, we can also help you with accounts receivable and collection efforts because we see your AR balance increasing on your financial statements.” At that point, they’re already thinking, “Great, I like working with this person.  Let’s give their team a try and help us solve another problem.” So, for us, it’s really been about finding those adjacent problems, building a team that specializes in them, and then connecting the client with the right expert. The last piece that’s really coming to market now is using technology to empower the team. Historically, a lot of our value came from having experts who could handle the edge cases or the gray areas between payroll, accounting, taxes, and sales tax. Now, with technology, you can also build the data infrastructure to highlight what’s happening for the client while helping guide the team as they manage those clients.  Love it. So what I’m hearing is, number one—or maybe even number zero—is do a great job, right?  The trust.  Okay. So that’s maybe another way of saying it: earn the trust. But is doing a good job enough to earn that trust, or is there more to it?  I mean, I think in any service business, you want to be proactive. A lot of bookkeepers, accountants, and even legal professionals are usually waiting for the client to ask a question before providing an answer. I think the goal should be to think ahead for the client and proactively provide guidance. That came naturally for us because we sit in the fractional CFO seat.Share on X  But even if you’re just doing bookkeeping, you can still catch these things for clients and help them out. Or if you’re selling P&C insurance and helping clients with their general liability coverage, you can think about what other types of coverage they may need. So I’d say the more proactive you can be, the better. The other thing is meeting clients where they already are.  For us, a lot of our clients are on Slack, so we connect with them on Slack. We chat with them as if we were full-time employees because we don’t want the experience to feel different. We don’t want you to feel like you’re emailing a generic support inbox and not knowing when someone is going to get back to you. If you only need fractional-level support, it shouldn’t feel like you’re getting fractional value or a fractional level of communication.  I love it. So you actually own the function inside the organization, so it feels like you’re part of the team, or your people are part of their team. So that builds the trust. So, do a great job, or earn the trust, number one. Number two, build the relationship. Number three, listen to other problems that they might have. Number four, connect them to other specialists. And number five, empower the team with technology.  Yeah. That’s a lot of it. I mean, as an advisor, we’ve grown… I mean, 60% of our growth comes from client referrals. So I think you know you’re doing something right if clients are recommending you to their friends and network. And so hopefully, if someone’s listening to this and you’re not getting referrals, you should be thinking about, “How do we either create more trust for our clients to be referring us, or how do we become more top of mind when clients are having these conversations?”  That’s great. So 60% of your growth comes from referrals. What’s the other 40%? How do you drive growth? What drives growth for you? What’s the other way to drive growth besides referrals?  Yeah. I mean, I think it’s also being connected with the ecosystem that you’re in. In our space, there are a lot of technology partners. Think about Xero, which is an accounting software, QuickBooks Online, NetSuite, payroll software like Rippling, Bill.com. They all have accounting partnerships, and the more you can build with them and grow your team alongside them, clients will reach out to them and say, “Hey, do you have someone who can help us set up Bill.com or help us set up Rippling?  We don’t have a payroll team to do our state tax registrations.” So we’ve seen a lot of good momentum as our software partners start sending us clients to help us grow. I think the other area is trying to figure out where you can have partnerships that will do introductions. We’ve been very fortunate in partnering with a number of VCs. Obviously, the VCs have worked with us because we’re on the board, or we had a mutual client. A lot of them will start to build partnership channels, and it’s a great opportunity.  They’ll say, “We just invested in this company, and you should go talk to Noah’s team to help with your accounting or your fractional CFO.” So it’s really about finding those tangential operators or entities that complement whatever you’re doing.  So are these primarily personal relationships that need to scale, or do you have a way to scale this across other people in your organization—this ability to develop partners? Or is it mainly you?  It depends on the role. A lot of our fractional CFOs on the team continue to build relationships. I would say probably 40% of our new clients come through a channel that’s not through me. There’ll be other people on our team who have built relationships with another VC or another software company. I think one of the key things we’ve always focused on is hiring people who are very, I would say “doers” might be the wrong word, but people who can self-manage and be project managers.  If you find the right people who can take a step back and look at the bigger picture, I mean, sometimes people come to Finvisor and they don’t realize that we ourselves are a business. Yes, you’re doing accounting like you were in-house and getting the books closed, but if you do good work and you realize clients are having problems, you have to think, “Hey, how can I help clients more and also help Finvisor create a win-win?” A lot of times, when we’re hiring, we’re trying to find people who have that type of drive to continue building and helping us internally, and not just do one part of the puzzle they’re responsible for. That might not be the most direct answer, but I would say a lot of it is hiring—making sure it's not just me leading the growth, but me building a team that can help lead the growth outside of just me.Share on X  Yeah. So how do you share the context so that your team members can connect the dots as well as you can? What’s your approach to that?  There’s a couple of ways we’ve done it. One way is we use a note-taker that then feeds into our CRM. For all client communication, whether they meet with us on Zoom or Google Meet, the transcripts are put into a centralized hub for us. It also connects to our CRM in terms of what we’re doing for the clients. At any point in time, someone can ask, “Hey, what’s going on with this client?” They can understand, “Great, this is what the payroll team talked to them about this week.  This is what the CFO team talked to them about last month. These are the problems they’ve been bringing up.” So we can capture that information without it having to be provided orally every single time, and without having to rely on a chat or an email to the team. There are some moments when it’s useful to give the team a larger update, but in general, it’s good to figure out a way to capture the essence of what you’re doing for your clients so that the team can then, in an AI chat-specific way, talk through, “Hey, great, what’s going on with this client? What are their needs? What has changed in the last six months? Who’s working on the client?”  I’ll have a VC that we’re talking to say, “Oh, we’re looking to invest in the CPG space and this type of vertical. Do you have any clients?” We’re at a point now where I don’t know every client. I usually have an idea about most clients, but there are definitely clients where I don’t know everything that’s happened in the last six months because I don’t talk to all 200 clients.  But I can go to our central hub to gain that information and understand, “Okay, great, which client is looking to fundraise and might want to be connected to this VC?” It’s a nice way to connect the dots. They’re looking to invest. The client is looking to raise. We also do brown-bag sessions. We’re a distributed team, so I think you have to be a little more intentional about how you educate the team. We’ll have weekly meetings where we walk through new technology, new changes in what we’re offering, new positioning, and continue educating the team in a more structured format.  The other thing we’ve done to help the team understand what’s going on is to make information as accessible as possible, similar to how we communicate with clients. So the team doesn’t have to log in to a pretty outdated CRM to pull information on a client. It’s either available directly in the Slack conversation or in a more modern tool like Notion, where you can easily search and find the information you want. So basically, you’re managing and harvesting your data and using that to feed people information about how they can develop partnerships. Is that what I’m hearing?  Yeah. And I think a lot of it is also figuring out which playbooks and processes are repeatable, documenting them better, and then educating the team around them. For example, with our fractional CFOs, we want to be in the board meeting. If we can be in the board meeting, A, we can help clients answer questions about their finances more easily, and B, it’s good to have visibility into what the board is saying about the business and where they want to go.  Then, obviously, the VCs are going to say, “Oh, great, this is Ian at Finvisor.” If he reaches out to me about a partnership, they’re going to have a better understanding of what we do because they’ve been in the room with us—or they’ve been in a virtual or in-person boardroom with us.  So you’re basically sharing the playbook so that they have a better understanding of what they can refer you for. Correct. Yeah.  So, switching gears here, Noah, what’s one thing that you’re trying to actively figure out in your business right now?  I mean, the question everyone is trying to figure out, at least in my space, is how they’re going to use AI in some fashion. That’s the kind of million-dollar question everyone keeps talking about—AI in accounting, AI in finance. Right now, we’re really structured in how we’re trying to use it and apply it. But the question I have is, what’s the next year going to look like? What’s five years going to look like as this technology gets more legs and more trust behind it? We’re pretty intentional about what we’re building and how we’re using some of the newer technology with AI. But I think there’s a lot that, at least for me, you have to continue to iterate. The world today feels different than it did three months ago. I’d say for most of Finvisor’s history—and this has been 12 years—it hasn’t felt like that, where a year later things might feel marginally different because we’re maybe 20% bigger or whatever might have happened.  Now, I think there’s a lot more excitement and unknown around technology and how it can either make people more efficient or help highlight and surface better issues that clients need to talk through. But I also feel like we’re in a moment where everyone’s trying to throw AI into every technology. So we're also trying to stay true to who we are, which is people first, relationships first—technology powering us, not being the solution.Share on X  So as you’re scaling AI to improve the information that your people have, your CFOs have, that presumably is going to lead to people doing less of the mechanical, repeatable tasks and more of the judgment tasks. So how do you scale judgment as you’re scaling the impact with AI?  On our side, I think it’s A, trying to organize and structure the data coming in. B, trying to create tooling that isn’t unique to one client but is built in a way that can be customized for each customer. A lot of the firms I talk to that are in the Finvisor space just take a blanket approach—turn Claude on for every fractional CFO, let them connect it to QuickBooks, and try to figure out their own playbooks.  That’s not how we’ve ever run the business. We don’t just hire accountants and let them run the accounting and see how the output turns out. We’re more focused on figuring out what is actually useful for review. Right now, I think AI has been most helpful around quality. It can definitely check that things are consistent and make sure edge cases are being caught.  I think we’re going to get to a future state where it’s not only making sure quality is at the 95th percentile of confidence, but also giving visibility into metrics like CAC, LTV, and churn—things that would normally take longer to pull together. Your fractional CFO might currently spend hours reviewing Stripe data or Shopify data to come to a conclusion. AI can cut out maybe 40% of that data-cleanup layer, where it’s like, “Okay, now they have the tools to dig in and understand what the underlying problem is,” instead of spending so much time cleaning up the data and getting everything organized.  So currently, at least my thesis is that it’s going to allow us to manage more clients because some of the day-to-day—I don’t want to call it busy work—but the work you have to do before you get to the exciting parts of the job will become more automated and less manual, like pulling data out of Stripe, Shopify, your CRM, or NetSuite.  So does that mean you’ll have a different type of people, maybe higher-level thinkers? Or do you think you can elevate your current team to that level?  Yeah. I think you’re… Sorry, I know I was originally answering this through the fractional CFO lens. Most of our fractional CFOs are already at the top of that organizational pyramid. For them, it’s really about helping them have cleaner data, better visibility into the actions they need to take, and better insight into what they should be reviewing and discussing with the client.  If I think more broadly about the back-office finance team, I do think a lot of the more generalist staff accountant and AP specialist roles won’t be spending as much time on the day-to-day blocking and tackling. If a client has 1,000 transactions a month flowing through their bank and credit cards, historically that accountant would sit in QuickBooks Online clicking “Okay, okay, okay,” reviewing every transaction and coding it. Eighty percent of those transactions will simply be coded automatically in real time as they come in. That leaves them to focus on the 20% that actually requires human judgment.  For me, the question is, can we continue to empower those people to be more impactful with that 20%? Are they the right people for that 20%? We’ve always tried to hire people who are proactive and broader thinkers, so I think we have the right team to step into that. If we’d built a traditional BPO model with an outsourced accounting team made up of people who were really just coding transactions at a basic level, I’d be more worried because getting those people to step up and handle edge cases is difficult.  But that’s not how we’ve historically built Finvisor. We’ve always tried to find people who are a little more… I’d rather hire an A-plus player than a B-player just because there’s some savings in the cost structure. I’d rather have the right people who can perform 80% of the time when they’re at bat than just hire someone because they’re cheaper.  Yeah.  Wrong baseball analogy there, but yeah.  Yeah, I understand. So you have A-plus people. Maybe the people who are doing more bookkeeping-type services—their jobs may become automated—but your A-players are going to have best-in-class information, and they can serve more clients that way.  Yeah. I still think that if you think about the typical accounting structure—if you’re working in-house and you have a bookkeeper and a controller—it’s still helpful. Depending on the size of the company, if you’re a small company, you probably won’t need that bookkeeper.  The controller can handle the edge cases and close the books. But at a certain scale, you’ll still want that junior resource supporting the controller so the controller can focus on the higher-level, more strategic work. I think people will simply be able to do more with less if they’re the right person. There will be people who, if they aren’t good at staying on their toes and figuring out edge cases, won’t be the right fit.  AI will probably replace some of those roles. But I think there’s a great opportunity for people who can think more strategically. They don’t have to be a CFO. They can just be a really smart bookkeeper who’s good at handling edge cases. They’ll simply be able to manage three times as many clients as they could when they had to code every single transaction.  Okay. If you had a magic wand and you could fix one thing in your business over the next 12 months, what would it be?  One area that we probably haven’t prioritized enough because of growth is SEO, AEO, and our overall sales build-out. Our paid advertising hasn’t been the strongest part of our business because it hasn’t been the top priority. If I had a magic wand, I’d have someone clean up our SEO and AEO visibility because I know clients love us and we do great work, but I don’t think we’re showing up the way I’d like from an SEO and AEO perspective. So that would be it. Yeah.  Yeah. Yeah. Love it. So, who are your ideal customers? Who do you want knocking on your door? Is it venture-backed companies primarily, or do you also work with private company founders? Who are your sweet-spot customers?  A lot of our clients are going to be in that 5-to-50-employee range, where they don’t need a full-time back office, a full-time accountant, a full-time CFO, or a full-time payroll specialist, but they need someone to own those roles. That way, we can put together the right Finvisor team to support them. We’ve intentionally made ourselves pretty modular, so while the largest group of our clients is in the tech VC world, we also have a lot of SMBs—law firms, beauty businesses, and other professional services businesses.  I would say that, if you looked at the Finvisor client base as a whole, you’d probably see a lot of startups. But we’re also starting to see more SMBs and more traditional businesses that don’t have VC funding but still need help with their accounting, bookkeeping, and modernizing their back office. So it’s a bit of both. Most of our clients are going to be in that 10-to-50- or 100-employee range, where they’re complex enough that they care about their financials and want to understand what they spent last month, where they’re going, and how they’re going to get there.  Earlier-stage companies are sometimes just a little too early. If you’re a one- or two-person company with just an idea, there’s a reason people think about their financials on more of a cash basis. They can think about the five clients they’re working with. Their bank balance ties pretty closely to their financials. There’s not a huge difference between the two when you’re a sole proprietor.  But as you start to evolve, that’s where Finvisor can provide more value. For all of our clients, we do accrual accounting, so we’re recognizing your revenue and your costs over the life of the service. As you start to grow and build, that’s really helpful. Obviously, if you’re at day one, it’s less impactful because you’re living more day to day, week to week, and month to month.  Steve Preda: Okay. So if we have those kinds of companies—which we do among our listeners—and they hear about this and want to fix their back office and outsource it to a reliable partner who can help them own those functions and give them good advice, what’s the best entry point? Where should they go, and how can they connect with you personally as well?  Yeah. hello@finvisor.com comes to me and the sales team. There’s probably a 95% chance you’ll talk to me if you reach out because I still love connecting with most new businesses that come through the door. The other area I wanted to call out that could be helpful for businesses is PEOs. PEOs are great, but I think at some point clients need to graduate from the PEO, and Finvisor is uniquely positioned to be both your insurance broker—helping you quote large-group plans—and your payroll and HR team to help you leave the PEO.  For a lot of our clients, once they pass that 100-employee mark, it’s like, “Great, we now qualify for a large-group plan,” which might have better rates than what they’re getting through the PEO. They just don’t have the team or bandwidth to get off the PEO. We’ll come alongside those larger companies and say, “Great, let’s quote a large-group plan for you. We’ll also put together a transition plan to register you in the 20 states where your employees are currently located.  We’ll make sure you get your workers’ compensation and employment practices liability insurance in place so there’s really no difference—apples to apples—from being in the PEO to running your own payroll.” We help with that transition because I’m always surprised to see companies with hundreds of employees still on a PEO, where the savings could be in the hundreds of thousands of dollars if they left. They just don’t have the internal team because they’ve always been on a PEO. They’ve never had to do state registrations, so they don’t know how to do them. Because of that, they’re usually not looking for an alternative path to get off that structure. We can at least review it with them and help them out if it’s a good fit. And just to remind our listeners what a PEO is, in case they don’t know.  Oh, sorry. Yeah. A PEO is a Professional Employer Organization. If you’ve heard of companies like TriNet or Justworks, they’re PEOs. In the health insurance space, there are four primary ways you can get health insurance. Most companies start with small-group plans in the early days because they’re state-mandated. For example, in California, if you’re under 100 employees, the rates my company gets would be the same rates Steve’s company gets if we’re both under 100 employees and we’re asking Blue Shield for a quote from the same ZIP code. That’s small-group insurance.  Then there’s level-funded, where carriers quote specifically based on your employee group. There’s large-group, which is somewhat similar but designed for larger organizations. Then there’s the PEO. Let’s say you’re a 10-person company. You don’t have enough employees to qualify for large-group health insurance, which is usually discounted because the risk is spread across hundreds of employees. The PEO says, “We’ll employ your team. Instead of you directly employing 10 people and buying health insurance for only those 10 people, we’ll employ your team and give you rates based on the 10,000 employees we already have.” PEOs are really popular in places like California and New York, where health insurance is very expensive.  But once you get above about 100 employees, you can usually qualify for your own large-group rates, which are similar to what the PEO is getting. The difference is that the PEO is generally marking up those rates because they need to make a margin on the plan. You can often get those rates directly yourself.  Yeah. That makes perfect sense. Okay. So if you’re listening to this and you’re building a venture-backed startup, or you’re the founder of a professional services firm, a law firm, or another small business with 10 to 100 employees, and you don’t yet have the budget—or maybe you simply don’t need—a full-time CFO, insurance advisor, HR leader, and other functional specialists, then reach out to Noah and Finvisor.  Check out what they have to offer and see what services might be a good fit for your business. Thanks, Noah, for coming on the show and sharing your expertise. It’s fascinating to see how this field is evolving, how you’re tapping into technology, and how you’re focusing on the highest-quality CFOs to help your clients. If you enjoyed this conversation, stay tuned.  Follow us on YouTube, Apple Podcasts, or wherever you get your podcasts. Make sure you don’t miss an episode. Every week, we bring you exciting entrepreneurs and their best management frameworks. Thanks for coming, Noah, and thanks for listening.  Thanks, Steve. Appreciate it. Important Links: Noah's LinkedIn Noah's  website Noah's email: hello@finvisor.com

Jennifer Barney is the founder of Barney Butter, author of the newsletter The Business of Food, and an advisor on food manufacturing and agricultural innovation. On this episode of ITS, Jennifer and Ali talk about the CPG system. what she's optimistic about, and how founders need to understand the economics of what they're building. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On today's episode, we welcome Katie Lee, Founder of Katie's Pizza & Pasta — a chef-driven Italian restaurant and fast-growing CPG brand based in St. Louis. Katie's journey from high school dropout, recovering addict and single mom to James Beard-recognized restaurateur and one of the fastest-growing food entrepreneurs in America is a powerful story of resilience, grit and building something from scratch. In this episode, Katie shares how she launched her first restaurant in 2008 and helped ignite the artisan Italian pizza movement in the Midwest. She talks about taking Katie's from a beloved neighborhood restaurant to the national frozen food aisle, why handmade quality and rigorously sourced ingredients remain core to the brand, and what it took to produce 400,000 pizzas for Target in just 96 days — all by hand. We also discuss clean comfort food, building a brand with real identity, staying true to your roots while scaling, and what founders should do when the idea they believe in still isn't working. A must-listen for founders, operators, food lovers and anyone interested in resilience, restaurant growth, CPG, brand building and what it really takes to scale without losing the soul of the product.   Are you interested in sponsoring and advertising on The Kara Goldin Show, which is now in the Top 1% of Entrepreneur podcasts in the world? Let me know by contacting me at karagoldin@gmail.com. You can also find me @‌KaraGoldin on all networks.   To learn more about Katie Lee and Katie's Pizza & Pasta:https://www.katies.com/https://www.instagram.com/katiespizzaandpasta/https://www.instagram.com/katiepizzalee/https://www.linkedin.com/in/leekatie/   Sponsored By: AT&T Business - Switch to AT&T Business at business.att.com Chime - Join the millions who are already banking fee-free today. Head to Chime.com/KARAGOLDIN. Superhuman Go - Helps the whole team move faster. Find out more at Superhuman.com   Check out our website to view this episode's show notes: https://karagoldin.com/podcast/871