Podcasts about segmenting

In this episode, Sasha Orloff talks with Jean-Denis Greze, Co-founder and CEO of Town, about building an AI-powered tax solution for SMBs, exploring the startup's origin, the balance between automation and human expertise, strategic market targeting, funding insights, and the transformative potential of AI in tax preparation. -- SPONSORS: Notion Boost your startup with Notion—the ultimate connected workspace trusted by thousands worldwide! From engineering specs to onboarding and fundraising, Notion keeps your team organized and efficient. For a limited time, get 6 months of Notion AI FREE to supercharge your workflow. Claim your offer now at ⁠⁠https://notion.com/startups/puzzle⁠⁠ Puzzle

Send us a textYou spent thousands on influencer marketing… and barely got a sale.The problem isn't the creator. It's your system.In this video, I break down why most brands fail with influencers—and how the top-performing brands are building performance-based creator funnels that actually move revenue.This is for you if:You've run influencer campaigns and saw little-to-no returnYou're still paying flat fees with no tracking or affiliate backendYou want to build a repeatable influencer model that scales with your brandWhat you'll learn:The 3 biggest reasons influencer campaigns flopHow to structure hybrid affiliate deals with upside for both sidesWhy Spark Ads should come after performance proof—not beforeHow to stop treating creators like props—and start treating them like partners

Are you looking to create a steady stream of income for your nonprofit? Monthly giving programs might be the answer you've been searching for. In this episode, I'm joined by Katherine Lacefield, a seasoned philanthropic consultant with over 20 years of experience, to explore the power of recurring donations. Building a Successful Monthly Giving Program - Creating a compelling narrative around your program - Crafting an exclusive experience for monthly donors - Implementing effective stewardship strategies Strategies for Growing Your Monthly Donor Base - Targeting existing donors for conversion - Segmenting your audience for personalized outreach - Leveraging year-end campaigns to boost monthly giving Retaining and Engaging Monthly Donors - Tracking key metrics for program health - Conducting exit surveys to improve retention - Making the giving experience fun and memorable One of Katherine's standout tips? Don't wait for perfection. Launch your program and refine it as you go. Remember, if you don't believe in the value of monthly donations to your organization, how can you expect others to? Whether you're considering starting a monthly giving program or looking to revamp an existing one, this episode is packed with actionable advice to help you create a sustainable source of funding for your nonprofit. Ready to take your fundraising to the next level? Tune in now and discover how to build a thriving community of monthly supporters for your cause. Want to Skip Ahead? Here are Some Key Takeaways:  03:28 Exploring the Benefits of Monthly Giving The advantages of monthly giving programs for nonprofit are consistent finances, operational stability, and sustainability. Its cost-effective and a great long-term value for organizations. 08:18 Crafting an Effective Monthly Giving Campaign Create a separate donation page, name the program, and develop stewardship strategies. It's also so important to build relationships with donors and suggests personalizing communication to increase retention and engagement.  15:49 Strategies for Growing Monthly Donor Programs To start building your program start with existing donors. Segment your database and craft a compelling story. Get an example of a client that converted on-time donors into monthly donors and how clear communication and goal-setting is impactful.  24:47 Tracking and Improving Monthly Donor Retention Monitoring monthly donor retention and gathering feedback is critical to the health of the program. Track donor longevity, reasons for leaving, and overall satisfaction. Even if someone stops being a monthly donor, maintaining relationships is important to encourage future support. 28:25 Final Tips for Successful Monthly Giving Programs Build confidence in your organization's mission, don't waiting for perfection before launching, and making the donor experience fun and engaging. Build personal connections with donors and think creatively about fundraising approaches. Katherine Lacefield Katherine Lacefield is a trusted partner in the philanthropic space, leveraging over 20 years of experience empowering organizations and individuals to bring about positive impact in their communities. Her knowledge and expertise span many areas, from overall fundraising strategy, monthly donations, major donation campaigns, and peer-to-peer, to a nuanced understanding of the global grantmaking landscape, animal welfare and rights, and sustainable development. She is the founder of Just Be Cause Consulting and the host of the Just Be Cause Podcast. Learn more at www.justbecause.consulting Threads: https://www.threads.net/@just.because.consulting?xmt=AQGzrTxxXpSOESIRL4Q6G-lzM-EGknSAHAJ7m51p3yMirJw Podcast: http://www.justbecause.consulting/podcast https://www.linkedin.com/in/katherine-mac-donald/ https://www.facebook.com/JustBeCauseConsulting https://www.instagram.com/just.because.consulting/ Connect with us on LinkedIn: https://www.linkedin.com/company/the-first-click Learn more about The First Click: https://thefirstclick.net Schedule a Digital Marketing Therapy Session: https://thefirstclick.net/officehours

Cold to Connected: Making Your Email Marketing MeaningfulB2B Marketing Excellence & AI Podcast with Donna PetersonAre your emails building real relationships—or just filling inboxes?In this episode, I share how to create meaningful connections through email marketing that actually resonate with your audience. I'll walk you through why industry-specific lists from trusted publishers make all the difference, and how segmenting those lists can lead to better engagement.You'll hear how I use AI tools like ChatGPT to craft personalized, value-focused messages that speak directly to the recipient's needs—not just their job titles. Plus, we'll talk about list maintenance, branding consistency, and simple nurturing strategies that build trust and make life easier for your sales team.Whether you're just getting started or looking to refine your current efforts, this episode is full of practical tips to help you create emails people actually want to read.Timestamps:• 00:00 – Welcome: The Real Purpose Behind Your Emails• 00:52 – Why Industry-Specific Lists Matter So Much• 02:45 – Segmenting for Relevance and Respect• 05:04 – How AI Can Help Personalize (Without Sounding Robotic)• 06:47 – Messaging That Builds Trust and Adds Value• 08:26 – Using Industry Knowledge to Cut Through the Noise• 10:43 – Quick Recap: What You Can Start Doing Today• 15:10 – Final Thoughts & A Gentle Challenge

Join host David Pisarek and email fundraising expert Vanessa Chase Lockshin in this value-packed episode of the Non-Profit Digital Success Podcast, where they uncover what really makes fundraising emails successful for non-profits.Vanessa, founder of The Storytelling Non-Profit, shares her proven strategies for crafting emails that not only get opened but also inspire action. From subject lines that stop the scroll to segmentation tips that increase engagement, this episode is a must-listen for any non-profit looking to level up their email game.Discover the keys to:✔️ Writing subject lines that get clicks✔️ Using storytelling to create emotional connections✔️ Segmenting your email list to increase donations✔️ Finding the best times and days to send✔️ Measuring and improving your campaign performanceWhether you're just starting to build your email list or looking to turn your next campaign into a fundraising powerhouse, Vanessa offers expert advice you can put into practice right away.Tune in to The Top Fundraising Email Secrets with Vanessa Chase Lockshin and take your email fundraising to the next level.

Welcome back to the Alt Goes Mainstream podcast.Today's episode is with a private markets veteran who has been working in the wealth channel before it was considered "the wealth channel."We sat down in the studio with Peter Aliprantis. Peter joined EQT in October 2024 as a Partner and Head of Private Wealth Americas. He's hit the ground running to build out a wealth team in the Americas and help continue to grow the EQT brand in the US.Peter brings a wealth of knowledge to the private wealth solutions world, garnering over 25 years of experience in the space. Prior to joining EQT, Peter spent 12 years at TPG Angelo Gordon as a Managing Director, where he focused on new business development and intermediary distribution.Peter and I had a fascinating conversation about everything from the early days of the wealth channel to the evolution of product innovation in private markets. We discussed:What working in the wealth channel was like before it was called “the wealth channel.”How to build a new brand in a different geography.How not being the loudest voice in the room can be effective when working with the wealth channel.How education helps to serve distribution efforts and how an innovative and unique approach to education with EQT's ThinQ platform has helped build brand, trust, and credibility.Why institutions are also beneficiaries of the innovation with evergreen structures that were initially designed for the wealth channel.How product innovation will continue in the wealth channel.How model portfolios will evolve.Thanks Peter for coming on the show to share your wisdom and expertise.Subscribe to Alt Goes Mainstream to receive the weekly newsletter every Sunday and all of AGM's podcasts.A word from AGM podcast sponsor, Ultimus Fund SolutionsThis episode of Alt Goes Mainstream is brought to you by Ultimus Fund Solutions, a leading full-service fund administrator for asset managers in private and public markets. As private markets continue to move into the mainstream, the industry requires infrastructure solutions that help funds and investors keep pace. In an increasingly sophisticated financial marketplace, investment managers must navigate a growing array of challenges: elaborate fund structures, specialized strategies, evolving compliance requirements, a growing need for sophisticated reporting, and intensifying demands for transparency.To assist with these challenging opportunities, more and more fund sponsors and asset managers are turning to Ultimus, a leading service provider that blends high tech and high touch in unique and customized fund administration and middle office solutions for a diverse and growing universe of over 450 clients and 1,800 funds, representing $500 billion assets under administration, all handled by a team of over 1,000 professionals. Ultimus offers a wide range of capabilities across registered funds, private funds and public plans, as well as outsourced middle office services. Delivering operational excellence, Ultimus helps firms manage the ever-changing regulatory environment while meeting the needs of their institutional and retail investors. Ultimus provides comprehensive operational support and fund governance services to help managers successfully launch retail alternative products.Visit www.ultimusfundsolutions.com to learn more about Ultimus' technology enhanced services and solutions or contact Ultimus Executive Vice President of Business Development Gary Harris on email at gharris@ultimusfundsolutions.com.We thank Ultimus for their support of alts going mainstream.Show Notes00:00 Introduction and Message from our Sponsor, Ultimus01:57 Welcome to the Podcast02:05 Introducing Peter Aliprantis02:20 Peter's Career Background03:31 Early Days in Private Wealth04:25 Changes in Wealth Distribution05:55 Post-Financial Crisis Shifts06:37 Growth of the Wealth Channel07:14 Building a Wealth Business at Angelo Gordon07:59 Convincing Firms to Invest in Wealth08:59 Importance of Investment Teams10:18 Key Skills for Wealth Channel Success12:46 Joining EQT and Brand Building13:07 Building EQT's Wealth Platform14:56 Brand Building in the Wealth Channel15:32 Expanding EQT's Presence16:10 Strategies for Engaging the Wealth Channel16:45 Segmenting the Wealth Channel19:57 Challenges in RIA Relationships20:28 Importance of Relationship Building21:25 Bespoke Products for Wealth Channel22:10 Institutional vs. Wealth Channel Products22:56 Evergreen Structures for Institutions23:20 Future Trends in Wealth Management23:27 Becoming a Solutions Provider in the RIA Channel23:47 Creating Model Portfolios25:31 The Future of Wealth Management27:04 Challenges for Smaller Firms27:38 Importance of Shelf Space28:35 Sales Strategies in Private Banks29:42 The Role of Scale in Wealth Channels30:27 Balancing Growth and Performance31:07 Global Investment Strategies and Performance33:13 Building a Brand in the U.S. Wealth Channel34:29 Differentiating in the Wealth Channel36:43 Advisory vs. Sales Approach38:18 Evergreen Funds vs. Drawdown Structures39:53 Investor Psychology and Evergreen Structures41:41 Changing Dynamics of Private Markets43:01 Family-Owned Business Culture44:30 Nordic Cultural Values45:15 Long-Term Mindset in Private Equity45:53 Building the Wealth Business46:14 Bespoke Products for Wealth Channels46:42 Seeding Evergreen Structures47:08 The Race to Win the Wealth Channel47:29 Manager Diversification47:08 The Race to Win the Wealth Channel47:59 Conclusion and Final Thoughts Editing and post-production work for this episode was provided by The Podcast Consultant.

Welcome to the Grow Your Biz without Social virtual event (April 14-18). Once talks are released, they will be available through April 20 on the podcast. New talks released each day throughout the event! Need to register still or want to share with a friend? (lots of goodies included in the event!)

Send us a textIn this episode of the Customer Success Pro Podcast, host Anika Zubair speaks with Melanie Fay, an enterprise Customer Success Manager at Goldcast. They discuss Melanie's journey in customer success, her transition between various roles, and her innovative approach to customer engagement known as the 'anti-check-in.' Melanie shares her experiences managing a large book of business, the importance of delivering value in customer interactions, and strategies for understanding customer goals and outcomes. The conversation emphasizes the need for CSMs to adapt their approaches to meet the evolving needs of customers and to provide meaningful engagement beyond traditional check-in calls. In this conversation, the speakers delve into the evolving landscape of customer success, emphasizing the importance of understanding customer needs, effective engagement strategies, and the transition from traditional check-in calls to value-driven discussions. They discuss the significance of frameworks for customer conversations, the role of storytelling in enhancing customer relationships, and the necessity of taking ownership and leadership within the customer success domain. Additionally, they explore practical tips for managing a large book of business through segmentation and the importance of being creative and adaptable in communication strategies.Enter the Planhat Giveaway!Win an all-expenses-paid trip to Planhat Open: www.planhat.com/giveawayTimestamps: 00:00 Introduction01:52 Melanie Fay's Journey in Customer Success06:01 Transitioning Between Roles and Companies10:00 The Anti-Check-In Approach13:13 Managing a Large Book of Business17:03 Delivering Value in Customer Interactions21:13 Understanding Customer Goals and Outcomes25:02 Innovative Strategies for Customer Engagement27:00 Understanding Customer Needs and Engagement30:08 Frameworks for Effective Customer Conversations33:04 Transitioning from Check-Ins to Value-Driven Discussions35:06 The Role of Storytelling in Customer Success39:04 Taking Ownership and Leadership in Customer Success43:14 Segmenting and Managing a Large Book of Business47:03 Key TakeawaysConnect with Anika:LinkedInYouTubeTikTokInstagramWebsite: thecustomersuccesspro.comCoaching with Anika: CSM RevUP AcademyConnect with Melanie Faye:https://www.linkedin.com/in/melanie-faye/I'm Melanie, a CSM living on a small island on the East Coast in Canada. After running my own business for years, I knew when I landed my first CS role that it was meant to be. I've been working in Customer Success for nearly 4 years and have been fortunate enough to gain experience in different industries like digital events, HR tech and accounting tech. Most recently, I was supporting mid-market customers at Keeper.app and am now moving into an Enterprise role at Goldcast. I'm excited to get back to my roots in the events industry! When I'm not listening to CS podcasts, meeting with my mentor or having coffee chats with others in tech, you can find me spending time with my two Labradoodles (Charlie and Lottie), on a paddleboard in the summer or hiking through snowy trails in t Podcast Editor: https://podcastmagician.com/

In this conversation, Reggie James and Mark Cann explorethe intricacies of LinkedIn data analysis, focusing on the challenges of cold outreach and the effectiveness of messaging strategies. Mark shares insights from his analysis of nearly 5,000 LinkedIn DMs, revealing key findings regarding message length, timing, and the significance of understanding the recipient's perspective. They also discuss the innovative tool, Clay - which enhances go-to-market strategies by integrating various APIs for personalized outreach.Chapters00:00 - Introduction to LinkedIn DM Analysis05:25 - Challenges in Cold Outreach12:19 - Key Findings from the LinkedIn Analysis17:24 - Exploring Clay: The Go-To-Market ToolKey takeawaysCold outreach is becoming increasingly challenging due toAI advancements.Message length significantly impacts response rates;shorter messages often perform better.Timing matters; outreach is most effective on Mondays andTuesdays.Humor in messages can lead to higher engagement, butresults may vary.Understanding the recipient's problems is more effectivethan offering solutions.Clay is a powerful tool for marketers, akin to GoogleSheets but more advanced.APIs can be integrated into Clay for enhanced dataanalysis and outreach.Personalization in messaging is crucial for effectivecommunication.Segmenting your audience helps tailor messages todifferent personas.DMS should be viewed as conversation starters rather thanplatforms for extended discussions.Sound Bites"Cold email is getting harder.""Personalization is key in outreach.""Segmenting your audience is crucial."LinksGrowth Warriors - https://www.growthwarriors.co/Digital Clarity - https://digital-clarity.com/Reggie James LinkedIn Mark Cann LinkedIn 

Stop confusing creativity with your craft! You practice to clear the path for the muses, and when the muse arrives, you get out the way and run with them. I've thought a lot about this tension while doing the guest pods with far more successful (and far more organized) mixing engineers than I. But we all have our own ways of doing it. Maybe by hearing my way, you'll be inspired to try some new paths. To practice for practices sake. And to leave practice at the door when it's time to be an artist. To use music theory as an (incredible) tool, but not as a crutch or a map.And to work on your craft as often as possible, especially in those moments when you don't feel inspired. I think that will help us both Love Music More!For 30% off your first year with DistroKid to share your music with the world click ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠DistroKid.com/vip/lovemusicmore⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Want to hear my music? For all things links visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ScoobertDoobert.pizza⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to this pod's blog on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Substack⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to receive deeper dives on the regular

Today we're talking about three new ways to use ChatGPT for copywriters and business owners, and another development from another company which is a lot lower priced than ChatGPT's a month for its premium service. We'll also talk a little about some other specific ways to use OTHER AIs, but a lot of our focus is on ChatGPT. Now, to be clear, I wasn't all that hot on ChatGPT 18 months ago. But in the AI world, 18 months is more like a couple of decades. Things have changed and definitely gotten better with ChatGPT. Particularly, in the last few weeks, the introduction of two new versions: Operator, and Deep Research. Now, at $200 a month, the combination of these two new services is 10 times as expensive per month as plain old ChatGPT. But if you need to get a lot more done more quickly in certain areas, they could definitely be an asset for you. We'll go in depth on three ways to speed up key valuable tasks today. Recap: Try Operator for… Segmenting your list, based on what they've done before Coordinating social media posting Collecting and analyzing customer feedback Try Deep Research For… Thorough competitive analysis SEO and keyword strategy Finding content opportunities Try AI Brainstorming For Coming up with content ideas Coming up with email ideas Coming up with social media ideas Call to Action: Find out more about the Chat GPT Operator/Deep Research upgrade and see if it's worth it for you. Download.

Are you reaching all your fans effectively or just casting a wide net and hoping for the best? Segmenting and targeting your fans is a tactic everyone LOVES to talk about but rarely gets right...   In this episode of Creative Juice, Jack and Circa demystify fanbase segmentation in digital marketing, how to do it effectively, and what it means for your music career! Learn the real differences between your customers and subscribers, why the music industry often gets it wrong, and the initial fan segmentation process every artist should follow!   If you've ever felt stuck in the weeds targeting your fans without seeing real impact, this episode is here to help you clear the path and start optimizing your fan engagement like never before!   DISCOVER: How To Split Your Customer And Subscriber Lists Why Most Of The Music Industry Talks To Every Fan The Same Way How To Keep Your Email And Text Marketing Lists Clean What Simple Engagement Segmentation Looks Like And Why It Matters Where To Focus Once You Start Seeing Results From Your Segmentation Efforts When To Get Hyper Targeted In Your Paid Ad Campaigns   RESOURCES: Learn The Top Music Marketing Strategies Inside IndiePRO Looking to expand your team or need marketing help? Apply to work with IndieX! Join Us In The Indepreneur Discord Server!

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Send us a textLet's talk about the critical role of email marketing in driving sales and building customer relationships. We discuss the common pitfalls businesses face, such as neglecting email marketing in favour of social media, and then provide actionable strategies to enhance email effectiveness. Key topics include the importance of having a strategic plan, utilizing templates, focusing on design elements, regularly analyzing performance metrics, and segmenting the email list for targeted communication. I want to encourage businesses to invest time in email marketing to unlock its full potential for growth and customer engagement.Email marketing can generate significant sales for businesses.Many businesses under utilize email marketing compared to social media.A strategic email plan is essential for effective communication.Templates can streamline the email creation process.Design elements greatly impact email readability and engagement.Regularly sending emails helps nurture customer relationships.Analyzing email performance metrics is crucial for improvement.Testing different email strategies can lead to better results.Segmenting your email list allows for more targeted messaging.Building a strong email list is vital for long-term success.Let's actually make money from your Emails.Improve your Emails in 3 days here (FREE)Head here for the Nail Your Email Marketing.00:00The Importance of Email Marketing07:15Creating a Strategic Email Plan15:48Design Elements for Effective Emails22:26Testing and Analyzing Email Performance29:28Building and Segmenting Your Email ListSupport the showI'm Mel Robbins! from @thelotco Want a Roadmap to Building a Profitable Product Business head here for directions! Looking for ongoing support to grow your brand and sell more of your product? Join the Product Business Growth Club here. Find more details at https://www.thelotco.com.au/Business Coach for product-based businesses. Teaching creative business women how to build a scalable and profitable million-dollar product business whether a physical Retail store or Brand.Over 25 years as a Retail and Wholesale Strategist (Sales and Marketing for Brands).Grab my 8 step checklist on building a profitable product business.

Send us a textIn this episode of the Sports Marketing Machine Podcast, host Jeremy Neisser celebrates the 100th episode by discussing the critical role of email marketing in ticket sales. He emphasizes that the real work begins after sending an email blast and highlights the importance of following up with interested customers. Neisser provides actionable strategies for marketing teams to convert email engagement into sales, including how to effectively utilize lists of interested buyers and the significance of personalized follow-ups. He also encourages creative approaches to email promotions to maximize engagement and sales opportunities.TakeawaysEmail marketing has a high ROI, averaging 30 to 1.The real work begins after sending an email blast.Follow up with those who clicked the buy now button.Use the list of interested buyers for personalized outreach.Engagement metrics can guide follow-up strategies.Building relationships through follow-ups enhances customer service.Segmenting email lists can lead to better-targeted promotions.Promote group ticket plans to single game buyers.The sales cycle continues beyond the initial email blast.Creative promotions can attract diverse customer interests.Chapters00:00 Celebrating Episode 10000:59 The Importance of Email Marketing02:59 Turning Email Engagement into Sales05:50 Follow-Up Strategies for Ticket Sales08:53 Creative Approaches to Email PromotionsSports Marketing Machine on LinkedInSports Marketing Machine on InstagramBook a call with Jeremy from Sports Marketing Machine

Market intelligence platform MarketSizer has announced a strategic partnership with eDesk, a globally recognised leader in eCommerce support solutions, which will enable smarter targeting and seamless scalability in eCommerce customer support. Using MarketSizer's real-time insights, eDesk enhances its ability to monitor competitors, enrich customer data, and streamline sales and marketing processes, thereby driving growth and sales more effectively. This partnership comes on the back of MarketSizer's recent €1M raise. eDesk is a leading eCommerce customer service platform that integrates with over 400 channels, including Amazon, Walmart, and TikTok Shop. By centralising operations, eDesk powers over 50 million conversations monthly, helping businesses boost productivity, streamline processes, and drive profitability. Highlights from this partnership include: Tracking 63 competitors, covering 80% of the market volume to refine eDesk's sales and marketing strategies. Processing millions of subscription data points to provide actionable insights for ABM strategies. Enriching 100% of ICP-applicable CRM records with real-time subscription data for sharper targeting and better timing. Delivering competitor-trial intelligence to inform proactive re-engagement strategies for sales and support teams. Segmenting customers by lifecycle stage and prioritising leads using purchase intent scores (High, Medium, Low, Not in Market). Automating workflows in HubSpot to reduce manual effort and accelerate sales and marketing responses. Enabling tailored, intent-driven campaigns with smarter lifecycle and segmentation insights. Niall O'Gorman, Founder and CEO at MarketSizer, commented: "Our partnership with eDesk demonstrates how actionable intelligence and automation can drive smarter decisions and real impact in competitive markets." In MarketSizer, O'Gorman leverages decades of extensive experience in scaling ventures and first-hand knowledge of the challenges businesses face regarding market intelligence, having previously been one of the founders of ChannelSight. Brendan Hughes, CCO of eDesk, commented: "MarketSizer has redefined how we understand and act on our competitive landscape. With always-on intelligence and automation, we've replaced manual processes with precision, turning data into decisions faster than ever. This partnership has empowered us to focus on what matters: identifying opportunities and driving smarter global strategies." See more stories here.

Daniel Allen is a doctor of clinical psychology and a strength and conditioning coach specializing in preparing candidates for military and special operations service in New Zealand.He spent 6 years as a medic in the NZ Army before leaving to fulfill a dream to compete as a professional Muay Thai and MMA athlete and embark on a decade-long formal training in clinical psychology. He has worked with people ranging from Olympians, professional and world-class athletes, to beginners starting out for the first time to successful New Zealand SAS candidates.Dan's wide-ranging academic background spans undergraduate study in Health Science, Exercise Science, master's and doctoral psychology programs, and much to his wife's dismay, he is currently in a 2-year neuropsychology program.Dan's doctoral research focused on factors that reduced PTSD and increased flourishing among military personnel in the years following deployment, including nutrition, sleep, exercise, social support, and leadership support.His psychology background is similarly wide-ranging, including working as a high-school counselor, in a drugs and addiction service and, more recently, in a private psychology service.Dan is passionate about understanding the relationship between nutrition, psychology, and performance and how these things facilitate resilience.You can learn more about Dan at his website, drdancoach.com/ or on Instagram at @drdancoachingTimestamps:00:00:22 Introduction to Daniel Allen00:01:46 Sidequest to Be Professional Muay Thai Fighter00:06:40 Training in High-Level Gyms Around the World00:09:15 How Did Daniel Allen's Training Impact How He Coaches?00:11:39 How to Separate Pain from Suffering00:14:02 Exercise Science and Psychology Degrees 00:14:59 New Zealand SAS 00:17:49 What Would Daniel Change About How He Coached in the Past?00:21:09 How to Balance Being Good at Running and Rucking00:24:05 Predictors of Success00:26:58 Most Common Mistakes in Prep00:29:31 Test Within a Training Cycle00:31:53 Fundamental Skills to Develop People's Abilities00:34:04 Sponsor Note on Segmenting 00:34:28 Questioning Your Sense of Belonging00:41:02 Common Success Factors from Olympic Athletes to SAS Operators00:45:21 Cognitive Flexibility and Growth Mindset00:47:45 Operational Longevity 00:52:33 Limiting Factors During a Course 00:54:04 Candidates with Cushie Backgrounds00:57:43 Gaining Awareness of the Landscape of Your Mind00:59:43 SAS Candidates Do's and Don'ts01:02:31 Best and Worst Advice Ever Received 01:05:29 Outro

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Growth is essential for businesses. However, new customers with varying needs, preferences, and identities often accompany growth. Worse, these new customers can annoy or alienate your current customers. So, how do you grow without making your current business blow? Today, we explore the central challenge of growth: expanding your customer base without sparking conflicts between different customer segments. Ryan's new book, The Growth Dilemma, which Ryan co-authored with Wharton Senior Lecturer in Marketing Annie Wilson, Ph.D., addresses this dynamic in-depth, and we discuss how companies can better manage these conflicts to keep all customers satisfied and engaged. As brands grow, they tend to attract diverse customer segments with unique expectations and behavior. This diversity can create tensions between groups, especially when one segment's actions or values clash with another's.  For instance, a brand known for its exclusivity may see conflict when a more mainstream audience starts to adopt it, or a company that appeals to one political ideology may face backlash when it attracts customers from an opposing one. We delve into the four main types of conflict that can arise between customer segments and explore solutions for each. For example, these brands dealt with some of them when: Patagonia faced a brand image shift when corporate buyers began over-associating the brand with Wall Street, diverging from Patagonia's environmental ethos. The company responded by limiting corporate orders, thereby preserving its original image. Younger users leave Facebook because their parents' generation heavily uses it. Exclusivity can be key to maintaining engagement from specific age groups or communities on social platforms. New Balance once faced a backlash after a policy stance was misinterpreted by extremist groups, forcing the brand to distance itself from these associations publicly. Ultimately, understanding and managing these potential conflicts requires brands to identify sources of friction early on and employ various strategies to keep segments separate when needed. Segmenting offerings, using sub-brands, or creating distinct product lines are all ways to cater to different groups without diluting brand identity or customer satisfaction.  In this episode, we also offer actionable advice on navigating the complex terrain of customer segments and brand management and setting up companies for smoother, more inclusive growth. Whether you're a business leader or a marketer, this episode is packed with insights into balancing growth with customer harmony, ensuring each segment feels valued without alienating others. This episode also includes ways to: Recognize the importance of managing inter-customer relationships to foster sustainable growth. Understand how Functional Conflicts often arise in omnichannel setups and ways to resolve them. Learn about Brand Image Conflicts and how brands can address image tensions, as Patagonia did. Distinguish between Identity and Ideological Conflicts and why one often influences customer group dynamics more than the other. Gain insights into using segmentation strategies, like sub-brands or distinct service channels, to reduce conflict. Discover how a clear brand identity can attract and repel certain customers and why that might benefit or hinder growth. Be the first to hear about pre-order and launch dates and invitations to exclusive book launch events for The Growth Dilemma, published by Harvard Business Review Press!

Setting Effective Revenue Goals for Medical Aesthetics in 2025In this episode of the Medical Aesthetics Marketing Show, hosted by Pam, the Aesthetics Junkie, the importance of setting clear and achievable revenue goals for 2025 is discussed. The episode emphasizes the necessity of knowing your numbers and developing a collaborative plan where each team member owns a part of the overall goal. Topics covered include lead generation, conversion rates, segmentation of client base, and the importance of innovative and visually engaging marketing efforts. Pam underlines the significance of data-driven strategies and preparing for upcoming marketing activities, with a specific focus on next week's episode on creating a detailed marketing plan for 2025. Listeners are encouraged to download resources such as a holiday marketing calendar to aid in their planning.00:00 Introduction to Setting Marketing Goals00:54 Welcome to the Medical Aesthetics Marketing Show01:28 Setting the Foundation for 2025 Marketing Plan02:46 Understanding Revenue Goals03:58 Lead Generation Strategies04:48 Segmenting and Nurturing Leads06:51 Conversion Rates and Revenue Goals08:34 Leveraging Existing Client Base10:18 Breaking Down Revenue by Treatment12:11 Ownership and Accountability in Goals13:41 The Importance of Knowing Your Numbers15:31 Black Friday Marketing Tips18:13 Conclusion and Next StepsHoliday Calendar: http://theaestheticsjunkie.com/holidayFollow us on Instagram: Instagram.com/theaestheticjunkieAll Podcasts & Resources: https://www.theaestheticsjunkie.com/medical-spa-marketing-show-podcast/

Tired of running promotions that feel like they're falling flat? In this episode, I'm pulling back the curtain on the little-known strategies that can transform your next campaign from “meh” to mind-blowing. And here's the kicker: it's simpler than you think. What you'll uncover: The One Step Most Businesses Skip—and how it's costing them BIG during the holiday rush. Why Your Promotions Might Be Working Against You: Hint—it's not about how often you promote but how you structure them. The Holiday Hustle Hack: My insider formula to crush Black Friday and Cyber Monday without breaking a sweat (or your budget). Your Customers Are Telling You Everything: How to decode what they really want without spending hours in spreadsheets. Quick Wins You Can Implement Today: Simple shifts that get your emails opened, your products flying off the shelves, and your team laser-focused. This isn't about boring, soul-sucking data; it's about finding the magic in your promotions and giving you the tools to keep the momentum going.   --------------------   Measuring Holiday Promotion Success 0:00 Establishing Promotional Goals 2:05 Using Historical and Industry Benchmarks 2:39 Segmenting and Analyzing Data 3:40 Setting Up Regular Reporting 4:55 Actionable Insights from Data 6:08       Full article: https://salenaknight.com/make-your-holiday-promotions-more-successful-doing-this/

This episode breaks down real-world market tests and savvy competitive moves! Get actionable strategies for product changes, budget-friendly consumer research, and the power of understanding your audience.And don't forget! You can crush your marketing strategy with just a few minutes a week by signing up for the StrategyCast Newsletter. You'll receive weekly bursts of marketing tips, clips, resources, and a whole lot more. Visit https://strategycast.com/ for more details.==Let's Break It Down==05:17 Research program analyzes data for insights development.08:12 Humira: versatile drug, profitable for AbbVie, biologics.10:41 Focus on clear benefits to drive change.13:12 Assess market needs; ensure prototype satisfies criteria.16:52 Segmenting meals, not people, by occasion.20:39 Your plant probably eats better than you.24:58 McCormick's packaging change caused customer confusion.26:12 People ignore instructions; follow intuitive methods instead.30:53 Monitor competitors closely; adapt strategy cautiously.33:00 Engage directly with customers for market insights.==Where You Can Find Us==Website: https://strategycast.com/Instagram: https://www.instagram.com/strategy_cast/Facebook: https://www.facebook.com/strategycast==Leave a Review==Hey there, StrategyCast fans!If you've found our tips and tricks on marketing strategies helpful in growing your business, we'd be thrilled if you could take a moment to leave us a review on Apple Podcasts. Your feedback not only supports us but also helps others discover how they can elevate their business game!

Send us a textLet's talk about the critical role of email marketing in driving sales and building customer relationships. We discuss the common pitfalls businesses face, such as neglecting email marketing in favour of social media, and then provide actionable strategies to enhance email effectiveness. Key topics include the importance of having a strategic plan, utilizing templates, focusing on design elements, regularly analyzing performance metrics, and segmenting the email list for targeted communication. I want to encourage businesses to invest time in email marketing to unlock its full potential for growth and customer engagement.Email marketing can generate significant sales for businesses.Many businesses under utilize email marketing compared to social media.A strategic email plan is essential for effective communication.Templates can streamline the email creation process.Design elements greatly impact email readability and engagement.Regularly sending emails helps nurture customer relationships.Analyzing email performance metrics is crucial for improvement.Testing different email strategies can lead to better results.Segmenting your email list allows for more targeted messaging.Building a strong email list is vital for long-term success.00:00The Importance of Email Marketing07:15Creating a Strategic Email Plan15:48Design Elements for Effective Emails22:26Testing and Analyzing Email Performance29:28Building and Segmenting Your Email ListSupport the showI'm Mel Robbins! from @thelotco Register for my FREE webinar here to help you Build a Thriving Product Business https://www.thelotco.com/trainingfreeAnd if you want a Roadmap to Building a Profitable Product Business head here for directions! Looking for specific help with Wholesale? Check out the Transform your Wholesale programFind more details at https://www.thelotco.com.au/Business Coach for product-based businesses. Teaching creative business women how to build a scalable and profitable million-dollar product business whether a physical Retail store or Brand.Over 25 years in Retail and Wholesale Sales and Marketing.Grab my 8 step checklist on building a profitable product business.

Welcome to another episode of the Sleeping Barber Podcast! Join Marc and Vassilis as they dive into the fascinating world of marketing strategy and innovation with a special guest, Peter Weinberg. AI is the biggest topic of the past two years. When you combine that with the science behind evidence-based marketing principles and the discipline of Market Research you get Evidenza. Our Guest: Peter Weinberg Co-Founder, Evidenza https://www.linkedin.com/in/weinbergpeter/ Enjoy the show! Follow our updates here: https://www.linkedin.com/company/sleeping-barber/ Get in touch with our hosts: Marc Binkley: ⁠⁠ https://www.linkedin.com/in/marcbinkley/ Vassilis Douros: ⁠⁠https://www.linkedin.com/in/vassilisdouros/ TimeStamps 0:56 - Introduction to Peter Weinberg 1:59 - What is synthetic research? 3:45 - Three phases of Peter's career 7:03 - Leading on cutting edge thinking & technology 9:30 - 5/95 Rule 10:50 - Segmenting the market for AI-based research 13:04 - Thinking about Category Entry Points for Evidenza 15:38 - How to create synthetic personas 17:58 - A word from our sponsor - Quatical 19:19 - The speed and flexibility advantage of Synthetic-research 22:00 - Augmenting traditional market research 23:35 - Building CFO ready marketing strategy 25:48 - Using AI to solve TAM, SAM and SOM 27:23 - Correcting for hallucinations 30:24 - Error in AI v. traditional surveys 32:01 - Improving accuracy of synthetic research 33:51 - The opportunity and limitations of synthetic research 35:42 - Product Market Fit for Evidenza 37:38 - AI can be used for much more than copywriting 39:03 - How a background in marketing influences business operations 43:29 - Most growth comes from new customers 45:25 - Opportunity to financialize marketing plans 46:57 - Why marketers need to learn financial language 47:58 - Learn more about Evidenza 48:37 - Post pod with V and Marc

Tune in to the Level Up Claims Podcast, where Galen Hair chats with Jason Kramer, CRM expert and founder of a tailored CRM solutions company. Discover why data and customer relationships are crucial for business success and how the right CRM can transform your operations. Perfect for business owners looking to effectively harness data and boost growth. Listen now!   Highlights Importance of customer relationships. Marketing as an investment vs. expense. Value of a CRM for small businesses. Significance of follow-up in sales. Using data to improve timing and communication. Transition from marketing to political involvement. Experience and challenges in local politics. The patience required in politics vs. business. Importance of data in relationship building. Segmenting audiences for effective communication. Importance of micro and macro data management. Challenges of implementing CRM systems. Role of Cultivize in CRM setup and management. Essential steps for a successful CRM integration.   Episode Resources Connect with Galen M. Hair https://insuranceclaimhq.com hair@hairshunnarah.com https://levelupclaim.com/ Connect with Jason Kramer https://cultivize.com/  

Ever wondered how local businesses thrive in a world of big brands? The secret lies in community-driven marketing. In this episode of the Local Marketing Lab, Christin Marvin, a seasoned restaurant executive coach with nearly two decades of hospitality experience, shares invaluable insights on leveraging local connections for business growth. From fine dining to food halls, Christin unpacks strategies that turn community engagement into a powerful marketing tool.Topics discussed in this episode: 1️⃣ Community partnerships for effective local marketing2️⃣ Strategies for successful co-marketing3️⃣ Aligning marketing content with the actual customer experience4️⃣ Engaging customers at local events5️⃣ Segmenting your audience for more targeted marketingResourcesConnect with Christin Marvin on LinkedIn.Check out Christin's website to learn more about her solutions.Listen to an episode of the No Hesitations Restaurant Leadership Podcast.Listen to Eric Knott's episode on the Local Marketing Lab podcast about being the mayor.Other shout-outsSnooze AM EateryPolidori SausageFirst WatchBetter Than ProvisionsOlivia (restaurant in Denver)Danny MeyerGolden MillEatDenver

Segmenting your consumers is crucial for effectively targeting the right audience. Join our experts to learn how to connect with your customers more deeply or expand your audience.In this discussion, you'll hear about three consumer types—Wellness Enthusiasts, Brand Champions and Connected Shoppers—and the factors influencing their purchasing decisions, so you can cater to their preferences.Watch the video here

Chris manages the business strategy, marketing, and financials of Perfect Herbs. Under his leadership, the company has grown revenue 50%+ year-over-year, transforming from a startup into a leading national brand. If you're an entrepreneur who sells herbal products in North America, or who's interested in launching new herbal products, you can contact Chris at chabib@perfectherbs.ca.  His company has licensed herbalists who can consult with you free of charge, make you samples to try, and help you launch your herbal product with high-quality herbs at a low cost, and with no minimum order quantities. Their customers call them "the greatest company they've ever worked with." In This Conversation We Discuss:[00:57] Intro[01:44] Identifying gaps in the herbal and natural markets[02:51] Targeting health practitioners via word of mouth[04:39] Gaining traction by being part of the community[06:42] Turning personal expertise into business success[07:45] Navigating growth with a fail-fast mindset[08:40] Experimenting with new products to validate markets[09:40] Leveraging tech for competitive business advantage[10:37] Episode sponsors[13:49] Offloading manual tasks through innovative tech[15:49] Transitioning from practitioners to retail markets[16:57] Mastering operational excellence for clients[18:30] Exploring multi-channel fulfillment strategies[19:55] Segmenting audiences for targeted marketing[21:13] Differentiating shoppers in diverse marketplaces[22:32] Standing out through authentic self-expression[24:08] Building friendly connections with customers[25:53] Perfect Herbs: for passionate herbal expertsResources:Subscribe to Honest Ecommerce on YoutubeHigh-quality herbal medicine accessible & sustainable for healthcare providers perfectherbs.ca/Follow Chris Habib linkedin.com/in/chris-habib/Book a demo today at intelligems.io/Done-for-you conversion rate optimization service storetester.com/If you're enjoying the show, we'd love it if you left Honest Ecommerce a review on Apple Podcasts. It makes a huge impact on the success of the podcast, and we love reading every one of your reviews!

In this week's episode, I'm joined by the brilliant Helen Munshi, and we're diving into the power of quizzes for lead generation and building real relationships with potential clients. We chat about how quizzes can inject your personality into the lead generation process, help you segment potential clients, and even qualify your leads. It's all about personalising your marketing and creating a positive experience from the start. Helen shares her expert tips on crafting quizzes that balance the needs of both your business and the quiz taker. We both agree that quizzes are a brilliant way to speed up relationship building and attract clients who are genuinely excited to work with you. We talk about the importance of starting with a solid strategy and making sure the customer journey flows seamlessly. Your quiz needs to be built around what your audience really wants to know. And don't forget the design! The order of questions and the use of images all play a big part in creating a great user experience. Tune in to learn how to harness the power of quizzes for your business! Takeaways 1. Quizzes are a powerful tool for lead generation and building relationships with potential clients.2. Quizzes allow you to inject personality into the lead generation process and create a positive experience for potential clients.3. Quizzes can segment potential clients and qualify leads, making your marketing more targeted and effective.4. Personalised marketing is more effective and cuts through the noise of generic marketing messages. Find out more about Helen: Instagram: https://www.instagram.com/helenmunshi/ LinkedIn: https://www.linkedin.com/in/helenmunshi/ Blog: https://helenmunshi.com/blog/ Chapters 00:00 Introduction and Queen of Quizzes02:09 The Power of Quizzes for Lead Generation03:22 Segmenting and Qualifying Leads with Quizzes05:20 Injecting Personality and Creating a Positive Experience08:02 The Importance of Personalized Marketing09:05 Creating a Good Quiz Requires Strategy16:58 Quizzes for Different Types of Business Owners18:48 Providing Personalized Shopping Recommendations for Product Businesses19:33 Starting with a Strong Strategy and Smooth Customer Journey21:55 Designing a Quiz for a Positive User Experience

Segmenting your way to Sales Success Are you calling on the right prospects in the right places? Are your salespeople calling on the right prospects in the right places? You might want to double check with them as I find far too many of us in agribusiness are “Fishing in Swimming Pools” Lots of activity […]

In this episode of Rocketship.FM, we dive into an often overlooked but crucial aspect of product management: working effectively with internal partners and stakeholders. Join host Mike Belsito as he interviews John Haggerty, a seasoned product leader and coach, who shares insights on how product managers can build stronger relationships within their organizations. Learn why treating internal collaboration like a product itself can lead to better outcomes, and discover practical strategies for: Conducting "internal partner discovery" Segmenting and customizing communication with different stakeholders Measuring the success of your internal partnerships Avoiding common pitfalls in stakeholder management Whether you're a new product manager or a seasoned leader, this episode will equip you with valuable tools to enhance your influence and effectiveness across your organization. Don't miss this opportunity to level up your internal partnership skills and drive better product outcomes. This episode is sponsored by: Virtual Edition of INDUSTRY: The Product Conference: Join hundreds of Product Managers and Product Leaders from all around the world for a day-long virtual conference experience -- including keynote sessions, interactive discussions, virtual networking and more. Purchase your pass before September 15th, and you can register for just $99 (saving 50% off of the day of show rate). Wix Studio: Designed for agencies, freelancers and enterprises, Wix Studio lets professional web designers and developers unleash their creativity—faster and better than ever. You can create high-end sites at scale while harnessing the robust infrastructure and business solutions that already come with Wix.  Rocketship.FM is brought to you by Evergreen Podcasts.

Message me your 'Takeaways'.In this episode, Lachlan discusses the importance of building your life one day at a time and living intentionally. He shares his personal journey of growth and the lessons he has learned along the way. Lachlan provides practical steps for backward planning, segmentation, nightly planning, feedback and progress tracking, and flexibility. He emphasises the need to have a clear vision, involve family in the process, and adapt to change. Lachlan concludes by encouraging listeners to start today and take the first step towards building a better life.Building your life one day at a time and living intentionally is key to fulfillment and success.Having a clear vision and backward planning can help prioritize goals and actions.Segmenting your day into personal development, relationships, and professional tasks can create balance and fulfillment.Regular feedback and progress tracking, as well as involving family, are important for maintaining balance and addressing concerns.Flexibility and adaptability are crucial in navigating change and achieving goals.Start today by planning your ideal day, setting priorities, and making time for what truly matters.https://www.themanthatcanproject.com/life-design-blueprint Support the Show.Join us in the Strong Men of Value Academy (Waitlist Open)https://www.themanthatcanproject.comFollow Lachlan:Instagram: https://www.instagram.com/lachlanstuart/YouTube: https://youtube.com/@lachlanstuart91Website: https://themanthatcanproject.com/Newsletter: https://lachlan-stuart-tmtcp.ck.page/profileDo Something Today To Be Better For Tomorrow

Karuna, an entrepreneurial brand builder, shares her journey with Nature's Fynd, a company that developed a new protein source from a unique fungus discovered in Yellowstone National Park. 1. From Outer Space to Your Plate: The Unlikely Origin of Nature's Fynd Nature's Fynd's story began with a NASA research project aimed at understanding how life could survive in extreme environments. This research led to the discovery of a remarkable fungus thriving in Yellowstone National Park's volcanic springs. 2. Revolutionising Protein: A New Frontier in Nutrition Nature's Fynd's fungus can produce protein in just 3 to 4 days, compared to the months or years required by animals and plants. This rapid growth makes it a game-changer in meeting the dietary needs of a growing global population. The protein is also incredibly nutritious, containing 50% protein, 30% fiber, and a variety of vitamins and minerals. Additionally, the fungus thrives in an acidic environment, eliminating the need for antibiotics, pesticides, or hormones, making it a cleaner and healthier protein source. 3. Marketing the Unthinkable: Turning Fungi into Food One of the biggest challenges Nature's Fynd faced was convincing consumers to embrace a fungus-based food. The company focused on taste, understanding that no matter how sustainable or healthy a product is, it must taste good to succeed. Nature's Fynd built its brand around the Explorer archetype, a rare identity in the food industry, which aligned perfectly with their innovative story of pioneering new territories in food production. Through strategic branding and storytelling, they successfully shifted the narrative from “weird” to “wonderful.” 4. Launching in a Pandemic: Nature's Fynd's 2020 Debut Nature's Fynd was set to launch in March 2020, just as the COVID-19 pandemic began. While this timing seemed unfortunate, it turned into an opportunity as consumers sought innovative solutions during the crisis. The brand's message of optimism and innovation resonated with consumers, making their launch a symbol of hope in uncertain times. 5. Navigating Consumer Skepticism: Building Trust with Taste Understanding that taste is the top priority for consumers, Nature's Fynd focused on making their products delicious to gain acceptance, even among skeptics of fungi-based food. Early market research revealed that younger, more open-minded consumers were the most interested in the product. By carefully segmenting the market, the company effectively targeted the most promising customer groups. Recognizing the deep cultural connection people have with food, Nature's Fynd introduced their product in familiar forms like yogurt and cheese spreads, easing the transition to fungi-based foods. Karuna Rawal is the CRO & CMO of Nature's Fynd. Karuna is an accomplished brand builder and Emmy award winner with 25 years of success transforming the world's most iconic brands. Connect with her on Linkedin https://www.linkedin.com/in/karunarawal/ Visit Nature's Fynd https://www.naturesfynd.com Jagged with Jasravee is facilitated by Jasravee Kaur Chandra. Jasravee has over 20 years experience as a Strategic Brand Builder, Communications Leader and Entrepreneur. Please visit Jasravee at https://jasravee.com/ Connect with Jasravee on Linkedin at https://www.linkedin.com/in/jasravee/ Email Jasravee at jasravee@gmail.com Index 00:00 Preview & Introduction to Karuna 02:18 NASA Discovery: From Space to Earth's Future 05:23 Fungi Protein: Nature's Fynd Launched During a Pandemic 12:46 Segmenting the Market: Who Wants to Eat Fungi? 21:08 Content Pillars: Education , Lifestyle, Health, Taste 30:06 Challenge of Habit Change: Yogurt, Cheese, and Beyond 45:38 Food, Creativity, and Sustainability: The Explorer Archetype 51:01 Aligning the Brand with Company Values 52:52 Marketer's Journey: #likeagirl 01:04:35 Rapid Fire with Karuna Rawal 01:08:30 Connect with Karuna Rawal

In this episode of The Unstarving Musician, I speak with Tara Brueske, a seasoned musician, composer, and educator. Tara shares her experiences from early days of playing and composing to her current role as an active educator in voice, piano, performance, and gig acquisition. The conversation covers: Tara's new book, "20 Must Have Booking Tips Every Musician Needs" Making connections via social media Strategies for getting gigs and developing educational products Insights on finding an audience for educational content Segmenting and serving supporters and customers Email list engagement and paid social media advertising Collaborative partnerships with content creators Practical tips for musicians, including vocal techniques Whether you're an aspiring musician looking to book more gigs or an established artist interested in diversifying into education, this episode offers valuable insights to help make your music journey easier and more profitable. Visit TaraBrueske.com to learn more about Tara's work and offerings. Support the Unstarving Musician The Unstarving Musician exists solely through the generosity of its listeners, readers, and viewers. Learn how you can offer your support. This episode was powered by Music Marketing Method, a program for independent musicians looking to grow their music career. Music Marketing Method was created by my good friend Lynz Crichton. I'm in the program and I'm learning tons! I'm growing my fan base and learning about many ways that I'll be earning money in the new year. It's also helping me grow this podcast. How cool is that? To lean more and find out if Music Marketing Method can help your music career, visit UnstarvingMusician.com/MusicMarketing. This episode of the was powered by Liner Notes. Learn from the hundreds of musicians and industry pros I've spoken with for the Unstarving Musician on topics such as marketing, songwriting, touring, sync licensing and much more. Sign up for Liner Notes. Liner Notes is an email newsletter from yours truly, in which I share some of the best knowledge gems garnered from the many conversations featured on the Unstarving Musician. You'll also be privy to the latest podcast episodes and Liner Notes subscriber exclusives. Sign up at UnstarvingMusician.com. It's free and you can unsubscribe at anytime. Resources The Unstarving Musician's Guide to Getting Paid Gigs, by Robonzo Music Marketing Method – The program that helps musicians find fans, grow an audience and make consistent income Bandzoogle – The all-in-one platform that makes it easy to build a beautiful website for your music Dreamhost – See the latest deals from Dreamhost, save money and support the UM in the process. More Resources for musicians Pardon the Interruption (Disclosure)  Some of the links in this post are affiliate links. This means I make a small commission, at no extra charge to you, if you purchase using those links. Thanks for your support! Visit UnstarvingMusician.com to sign up for Liner Notes to learn what I'm learning from the best indie musicians and music industry professionals. Stay in touch! @RobonzoDrummer on Twitter  and  Instagram @UnstarvingMusician on Facebook  and  YouTube  

This week Andrew talks with former MLB outfielder Brandon Guyer. Brandon is the founder of Major League Mindset where he helps baseball players of all ages develop winning mindsets to reach their full potential on & off the field. In this conversation, Brandon shares actionable ideas on creating effective routines, succeeding under pressure, overcoming fears, & so much more. You'll also hear Brandon's step-by-step process for taking at-bats in the big leagues. This episode is filled with powerful frameworks all of us can use to strengthen our mindset & become the best version of ourselves in anything. Show Highlights:0:00 - Intro3:20 - Defining mental toughness4:55 - Strong vs weak mindset5:22 - Player 1 vs Player 2 framework8:20 - Target thinking9:58 - Macro vs micro targets11:20 - Wildly Important Targets17:02 - Daily progress20:11 - At Bat “behind the scenes”27:09 - Signal lights28:34 - Big league breath30:01 - Segmenting the game32:25 - Hit by pitch record39:01 - Discipline** Follow Andrew On Social **Twitter/X: @andrewhmosesInstagram: @AndrewMoses123Sign up for e-mails to keep up with Andrew's podcast at everybodypullsthetarp.com/newsletter

In 2024 the UK will overhaul its data protection laws. There are many changes but one could help you to raise more money in the future. In this session we will examine some of those changes and share some early interpretations to help you to start thinking about and planning for the future. Key learnings from this episode include: -Appointing a Senior Responsible Individual, who should it be? -Changes to the way consent will be used in the future. -Segmenting your data under the new rules Join us for our first ever Charity Digital Skills Conference on the 25th September! You can register here. Use discount code FEPODCAST for a 50% discount. https://www.fundraisingeverywhere.com/product/charity-digital-skills-conference/?utm_source=Podbean&utm_medium=Podcast&utm_campaign=2408PODCAST&utm_content=CTA   If you enjoyed this episode, don't forget to hit follow and enable notifications so you'll get notified to be first to hear of future podcast episodes. We'd love to see you back again! And thank you to our friends at JustGiving who make the Fundraising Everywhere Podcast possible.

FOLLOW US: LinkedIn: https://www.linkedin.com/company/inside-commerce/ ABOUT THIS EPISODE: Ecommerce personalisation tech has progressed rapidly, with a wide range of vendors to choose from. However, personalisation is often reliant upon pushing product recommendations based on prior and current browsing, and purchase behaviour. But... Not everyone visiting your website has purchase intent, and those that do will be in different stages of their decision cycle. Continuing to treat everyone as a high intent buyer isn't an optimal customer experience and is likely to be losing you potential customers. In this podcast we talk about predicting user intent to improve on-site segmentation and conversion. Our guest, David Mannheim, is the founder of Made With Intent, a tool focused on understanding user intent. The conversation covers topics such as the problems with generic pop-ups and blanket discounting, the importance of segmenting customers based on intent, and the integration options for the tool. David's vision for the future is to embed predictive intent in ecommerce and change the perspective of the industry. Key takeaways: 1. Understanding user intent is crucial for effective on-site segmentation and conversion. 2. Generic pop-ups and blanket discounting are not always the best approach and can be annoying for users. 3. Segmenting customers based on their intent allows for more personalised and targeted communication. 4. Made With Intent integrates with various platforms to provide data insights and improve customer experiences. 5. The future vision is to change how businesses optimise their websites. Tune in for an interesting and lively debate on user intent. Make sure you're following Inside Commerce on LinkedIn and have subscribed to the Inside Commerce newsletter.

Because of the nature of SAM, this is more video heavy than usual. See our YouTube!Because vision is first among equals in multimodality, and yet SOTA vision language models are closed, we've always had an interest in learning what's next in vision. Our first viral episode was Segment Anything 1, and we have since covered LLaVA, IDEFICS, Adept, and Reka. But just like with Llama 3, FAIR holds a special place in our hearts as the New Kings of Open Source AI.The list of sequels better than the originals is usually very short, but SAM 2 delighted us by not only being a better image segmentation model than SAM 1, it also conclusively and inexpensively solved video segmentation in just an elegant a way as SAM 1 did for images, and releasing everything to the community as Apache 2/CC by 4.0.“In video segmentation, we observe better accuracy, using 3x fewer interactions than prior approaches. In image segmentation, our model is more accurate and 6x faster than the Segment Anything Model (SAM).”Surprisingly EfficientThe paper reports that SAM 2 was trained on 256 A100 GPUs for 108 hours (59% more than SAM 1). Taking the upper end $2 A100 cost off gpulist.ai means SAM2 cost ~$50k to train if it had an external market-rate cost - surprisingly cheap for adding video understanding!The newly released SA-V dataset is also the largest video segment dataset to date, with careful attention given to scene/object/geographical diversity, including that of annotators. In some ways, we are surprised that SOTA video segmentation can be done on only ~50,000 videos (and 640k masklet annotations). Model-in-the-loop Data Engine for Annotations and Demo-first DevelopmentSimilar to SAM 1, a 3 Phase Data Engine helped greatly in bootstrapping this dataset. As Nikhila says in the episode, the demo you see wasn't just for show, they actually used this same tool to do annotations for the model that is now demoed in the tool:“With the original SAM, we put a lot of effort in building a high-quality demo. And the other piece here is that the demo is actually the annotation tool. So we actually use the demo as a way to improve our annotation tool. And so then it becomes very natural to invest in building a good demo because it speeds up your annotation. and improve the data quality, and that will improve the model quality. With this approach, we found it to be really successful.”An incredible 90% speedup in annotation happened due to this virtuous cycle which helped SA-V reach this incredible scale.Building the demo also helped the team live the context that their own downstream users, like Roboflow, would experience, and forced them to make choices accordingly.As Nikhila says:“It's a really encouraging trend for not thinking about only the new model capability, but what sort of applications folks want to build with models as a result of that downstream.I think it also really forces you to think about many things that you might postpone. For example, efficiency. For a good demo experience, making it real time is super important. No one wants to wait. And so it really forces you to think about these things much sooner and actually makes us think about what kind of image encoder we want to use or other things. hardware efficiency improvements. So those kind of things, I think, become a first-class citizen when you put the demo first.”Indeed, the team swapped out standard ViT-H Vision Transformers for Hiera (Hierarchical) Vision Transformers as a result of efficiency considerations.Memory AttentionSpeaking of architecture, the model design is probably the sleeper hit of a project filled with hits. The team adapted SAM 1 to video by adding streaming memory for real-time video processing:Specifically adding memory attention, memory encoder, and memory bank, which surprisingly ablated better than more intuitive but complex architectures like Gated Recurrent Units.One has to wonder if streaming memory can be added to pure language models with a similar approach… (pls comment if there's an obvious one we haven't come across yet!)Video PodcastTune in to Latent Space TV for the video demos mentioned in this video podcast!Timestamps* [00:00:00] The Rise of SAM by Udio (David Ding Edit)* [00:03:07] Introducing Nikhila* [00:06:38] The Impact of SAM 1 in 2023* [00:12:15] Do People Finetune SAM?* [00:16:05] Video Demo of SAM* [00:20:01] Why the Demo is so Important* [00:23:23] SAM 1 vs SAM 2 Architecture* [00:26:46] Video Demo of SAM on Roboflow* [00:32:44] Extending SAM 2 with other models* [00:35:00] Limitations of SAM: Screenshots* [00:38:56] SAM 2 Paper* [00:39:15] SA-V Dataset and SAM Data Engine* [00:43:15] Memory Attention to solve Video* [00:47:24] "Context Length" in Memory Attention* [00:48:17] Object Tracking* [00:50:52] The Future of FAIR* [00:52:23] CVPR, Trends in Vision* [01:02:04] Calls to ActionTranscript[00:00:00] [music intro][00:02:11] AI Charlie: Happy Yoga! This is your AI co host Charlie. Thank you for all the love for our special 1 million downloads Wins of AI Winter episode last week, especially Sam, Archie, Trellis, Morgan, Shrey, Han, and more. For this episode, we have to go all the way back to the first viral episode of the podcast Segment Anything Model and the Hard Problems of Computer Vision, which we discussed with Joseph Nelson of Roboflow.[00:02:39] AI Charlie: Since Meta released SAM 2 last week, we are delighted to welcome Joseph back as our fourth guest co host to chat with Nikhila Ravi, Research Engineering Manager at Facebook AI Research and lead author of SAM 2. Just like our SAM 1 podcast, this is a multimodal pod because of the vision element, so we definitely encourage you to hop over to our YouTube at least for the demos, if not our faces.[00:03:04] AI Charlie: Watch out and take care.[00:03:10] Introducing Nikhila[00:03:10] swyx: Welcome to the latest podcast. I'm delighted to do segment anything to our first, one of our very first viral podcasts was segment anything one with Joseph. Welcome back. Thanks so much. And this time we are joined by the lead author of Segment Anything 2, Nikki Ravi, welcome.[00:03:25] Nikhila Ravi: Thank you. Thanks for having me.[00:03:26] swyx: There's a whole story that we can refer people back to episode of the podcast way back when for the story of Segment Anything, but I think we're interested in just introducing you as a researcher, as a, on the human side what was your path into AI research? Why, you know, why did you choose computer vision coming out of your specialization at Cambridge?[00:03:46] Nikhila Ravi: So I did my undergraduate. Degree in engineering at Cambridge university. The engineering program is very general. So first couple of years, you sort of study everything from mechanical engineering to fluid mechanics, structural mechanics, material science, and also computer science.[00:04:04] Nikhila Ravi: Towards the end of my degree, I started taking more classes in machine learning and computational neuroscience, and I really enjoyed it. And actually after graduating from undergrad, I had a place at Oxford to study medicine. And so I was. Initially planning on becoming a doctor, had everything planned and then decided to take a gap year after finishing undergrad.[00:04:28] Nikhila Ravi: And actually that was around the time that sort of deep learning was emerging. And in my machine learning class in undergrad, I remember one day our professor came in and that was when Google acquired DeepMind. And so that became like a huge thing. We talked about it for the whole class. It kind of really stuck.[00:04:48] Nikhila Ravi: And I was kicked off thinking about, okay, maybe I want to try something different other than medicine. Maybe this is a different path I want to take. And then in the gap year, I did a bunch of coding, worked on a number of projects. Did some sort of freelance contracting work. And then I got a scholarship to come and study in America.[00:05:06] Nikhila Ravi: So I went to Harvard for a year, took a bunch of computer science classes at Harvard and MIT, worked on a number of AI projects, especially in computer vision. I really, really enjoyed working in computer vision. I applied to Facebook and got this job at Facebook, and I've now at Facebook at the time, now Meta, and I've been here for seven years, so very circuitous path, probably not a very unconventional, I didn't do a PhD, I'm not like a research, typical research scientist, definitely came from more of an engineering background, but since being at Meta, Have had amazing opportunities to work across so many different interesting problems in computer vision from 3D computer vision.[00:05:50] Nikhila Ravi: How can you go from images of objects to 3D structures and then going back to 2D computer vision and actually understanding the objects and the pixels and the images themselves. So it's been a very interesting journey over the past seven years.[00:06:05] swyx: It's weird because like, I guess with segment anything too, it's like 4D because you solve time, you know, you started with 3D and now you're solving the 4D.[00:06:14] Nikhila Ravi: Yeah, it's just going from 3D to images to video. It's really covering the full spectrum. And actually, one of the nice things has been, so I think I mentioned I, Wanted to become a doctor, but actually Sam is having so much impact in medicine, probably more than I could have ever had as a doctor myself. So I think, you know, hopefully Sam too can also have a similar sort of impact in medicine and other fields.[00:06:39] The Impact of SAM 1 in 2023[00:06:39] swyx: Yeah. I want to give Joseph a chance to comment. Does that also mirror your, we know your story about going into, into vision, but like in the past year, since we did our podcast on Sam what's been the impact that you've seen?[00:06:51] Joseph Nelson: Segment anything. Set a new standard in computer vision, you know recapping from from the first release to present Sam introduces the ability for models to near zero shot meaning without any training identify kind of perfect polygons and outlines of items and objects inside images and that capability previously required a Lots of manual labeling, lots of manual preparation, clicking very meticulously to create outlines of individuals and people.[00:07:25] Joseph Nelson: And there were some models that attempted to do zero shot segmentation. of items inside images, though none were as high quality as segment anything. And with the introduction of segment anything, you can pass an image with SAM1, SAM2 videos as well, and get perfect pixel perfect outlines of most everything inside the images.[00:07:52] Joseph Nelson: Now there are some edge cases across domains and Similar to the human eye, sometimes you need to say, like, which item maybe you most care about for the downstream task and problem you're working on. Though, SAM has accelerated the rate at which developers are able to use computer vision in production applications.[00:08:13] Joseph Nelson: So, at RoboFlow, we were very quick to enable the community of computer vision developers and engineers to use SAM and apply it to their problems. The principle ways of using SAM, you could kind of use SAM as is to like pass an image and receive back masks. Another use case for SAM is in preparation of data for other types of problems.[00:08:37] Joseph Nelson: So, for example, in the medical domain, let's say that you're working on a problem where you have a bunch of images from a wet lab experiment. And from each of those images, you need to count the presence of a particular protein that reacts to some experiment. To count all the individual protein reactions, You can go in and lab assistants to this day will still like kind of individually count and say what are the presence of all those proteins.[00:09:07] Joseph Nelson: With Segment Anything, it's able to identify all of those individual items correctly. But often you may need to also add like a class name to what the protein is. Or you may need to say, hey, like, I care about the protein portion of this. I don't care about the rest of the portion of this in the image.[00:09:26] Joseph Nelson: And, or what it encourages and asks for the user to do is to provide some visual prompting to say, hey, which part, like, Sam says, hey, I can find segments of anything, but which segments do you care about? And so you can do visual prompting, which is kind of a new primitive that Sam introduced. And so at RoboFlow, we have one portion of our tool stack enables users to very quickly label data.[00:09:48] Joseph Nelson: With segment anything, Sam can already provide, hey, here's where I see the outlines of objects. Or a user can click to prompt to say, Hey, here's where the outlines of objects matter. And I recently pulled statistics from the usage of SAM in RoboFlow over the course of the last year. And users have labeled about 49 million images using segment anything on the hosted side of the RoboFlow platform.[00:10:12] Joseph Nelson: And that's like 5 million in the last 30 days alone. And of those images, We did kind of like a rough bafka napkin calculation of like how much time that has saved. Because, again, the alternative is you're clicking individual points to create a polygon, and with SAM you just click once and it guesses where the polygon is.[00:10:32] Joseph Nelson: And I'm sure in a bit we can maybe screen share and show some examples of what this experience is like. And in that time estimation, it's like, On average saves, you know, maybe a dozen or so seconds. And we estimate that this is probably saved on the order of magnitude of 35 years of time for users.[00:10:53] Nikhila Ravi: That's incredible.[00:10:54] Joseph Nelson: So, I mean, basically like in the first, the first year of a model being available, not only can you say, Hey, I'm just going to go use this model, those numbers that like 49 million images. is an estimate directly related to just the hosted side. So imagine all of the users that are self hosting or using SAM for robotics applications or out in the field or offline where it's not even, like, the time or the image counts are tabulated.[00:11:20] Joseph Nelson: And we're probably talking about, you know, just a fraction of the amount of value that's actually being produced for a number of downstream tasks. So to say that the impact has been You know, people use terms like game changing and these sorts of things. It has changed the industry. It's set a new standard.[00:11:36] Joseph Nelson: And with the release of SAM 2, I think we're about to see an acceleration of those capabilities for a lot of reasons.[00:11:42] Nikhila Ravi: That's really great to hear. I think one of the, really SAM 1 was. How many fields actually rely on manual segmentation? I think we're not really exposed to that. Maybe you are at Roboflow because you get to see all the users of these tools.[00:11:57] Nikhila Ravi: But for me, it was, you know, people working on understanding coral reef bleaching or farmers counting their cows and so many different applications that as a researcher. You never get exposed to, but you can have impact towards. So I think that was really awesome to hear.[00:12:15] Do People Finetune SAM?[00:12:15] swyx: So as sort of audience surrogate, who knows less than the two of you, I'm going to ask a really dumb question maybe, but is everyone using stock, a segment, anything?[00:12:23] swyx: Are they fine tuning for the medical domain? Like how on earth could it work for the medical field without fine tuning, right? Like, is that a thing?[00:12:32] Nikhila Ravi: So I mean, I can give a quick perspective from the research side. So one of the things, design decisions we made in SAM was to not have class labels. And so all the data is annotated in a class agnostic way.[00:12:48] Nikhila Ravi: So anything that has a boundary, we consider to be an object. So for example, in any image, there's lots of small objects. We might not know what the name of them are, but they're If you can draw a boundary around it, so you can imagine that we have 11 million images in the SA 1B dataset, we annotated all the objects, there's many, many small objects.[00:13:12] Nikhila Ravi: And so if you think about cells, they're also kind of small objects, there's probably things in the training data. That looked like it, but we didn't have to label it. And so that means that even when you use SAM for applications that it wasn't really trained for, because we didn't restrict it to a certain set of categories, you can actually use it out of the box without custom adaptation.[00:13:35] Nikhila Ravi: But having said that, there's probably certain domains where you need some expertise in order to be able to segment something properly. And for those use cases, Having some extra fine tuning data would probably help, and we've sort of seen that there's some papers that have come out that do this, and, you know, we'd love to hear, Joseph, how people are collecting data with SAM and fine tuning for their use cases.[00:13:59] Joseph Nelson: Once SAM came out, there were adaptations that said, could we use SAM to be, you know, like, efficient SAM? Like, basically take SAM and maybe accelerate it. And then there were domain adapted SAMs, like CellSAM, for example, out of the UC system. Now, what's interesting is, there's, like, adapting SAM to a domain, there's kind of two ways by which that's done.[00:14:21] Joseph Nelson: One is, as you mentioned, like, potentially SAM doesn't have a good concept of The objects of interest. And so you need to do domain adaptation and increase the accuracy for zero shot prediction. The second way though, is it's not fine tuning. It's actually just prompting. It's just guiding the model existing knowledge.[00:14:42] Joseph Nelson: to say which segments you care about. And both those are actually kind of equally important on the application side. You need to, like, a priori ensure that the objects of interest can be correctly segmented and maybe collect data to do that. But even if you had, like, a perfect SAM, like an omniscient SAM that could see every segment in every domain with all pixels perfectly outlined, in production, you would still need some way to Almost like signal to the model what you care about like to paint this picture if you are like a retailer and you are providing Photos of models wearing your clothing on your retail site You may care about you know only the shirt and Sam by default might segment the full person And so there's you know visual prompting that you can do to ensure that you only outline Maybe the shirt for the purposes of swapping in and out different shirts for displaying a given model on a retail page You And so I think what's interesting is that's where, like I wouldn't call it domain adaptation, but that's where, like, when you apply to industry, like, one thing that's particularly important with tooling and enabling SAM to reach its full potential.[00:15:51] swyx: That's really encouraging to hear. I should also think, like, you know, the last time we talked about this, we wanted to, the very natural addition on the class labeling side is the grounding Dino work, right? So I think people, built a grounding SAM and all the other extensions.[00:16:05] Video Demo of SAM[00:16:05] swyx: I think it's, it's probably a good time to cut to a quick demo of SAM2 for people who are, who are tuning in for SAM2 and who better to demo SAM2 than Nikki.[00:16:15] Nikhila Ravi: Sure. So I'll try to narrate what I'm what I'm doing. So audio listeners can also understand. So we have a web demo where anyone can try SAM2 on a video. Here we have a video of someone kicking a football, and I'm going to click on the football to select the object in the first frame. But you can actually select the object in any frame of the video, and this will work.[00:16:40] Nikhila Ravi: The next step is to hit track. So the model's now tracking this in real time. We don't save any of this, it's all running in real time. And now you can see the ball has been tracked throughout the entire video. There's even like a little bit of a challenging case here where the shoe covers the football.[00:16:59] Nikhila Ravi: And actually, you know, the model makes a little bit of a mistake, but that's okay. Because we can actually, here, the model makes a little bit of a mistake here. But you know, we can actually add a refinement click. You can add negative clicks until we get the mask that we want on this frame. And then you can hit track again, and the model will track the object, taking into account the additional information I've provided at that frame.[00:17:25] Nikhila Ravi: We've also added a couple of other fun things you can do on top of the track, like add effects. We can add you know, foreground effects, background effects. And these are just ways of showing how we can use the output from SAM2 as part of other tools like video editing tools. Other systems, so this is just a preview of what you can do with SAM2, but the really cool use cases are places where we might not have even imagined SAM2 being useful.[00:17:54] Nikhila Ravi: So we have a number of examples of things you might want to use it for. There's like underwater videos that it works actually really well for even though we, models never really seen an octopus before and octopus have a lot of moving parts that SAM2 can actually quite effectively. Keep track of all the different tentacles and we can probably see it more clearly if I desaturate the background.[00:18:18] Nikhila Ravi: We can see that actually the tracking of all the different tentacles is Quite accurate. Another challenge with video is that objects can actually become occluded. They can disappear from view and reappear. And a really fun example here is the shuffling cup game, which many of you might have seen. And so here I can click on the ball in the first frame.[00:18:41] Nikhila Ravi: I can also, You know, click on a different cup. And so here, the additional challenge is that there's three cups that look exactly the same. And then there's the ball that will get occluded by the cup. So the ball's no longer visible, the cups are all moving around, they all look the same. But the model actually keeps track of the cup that we selected.[00:19:02] Nikhila Ravi: And, as you can see at the end, here I'll jump to the end so you can see. It actually finds the cup again. I wanted to point out a couple of fun demo UX features that we added that actually really helped with this. So if you can see at the bottom, there's these swim lanes and then the swim lanes, actually the thickness of the swim lane tells you if the object's visible or not.[00:19:22] Nikhila Ravi: So at the beginning, the object's visible,[00:19:25] swyx: the object[00:19:26] Nikhila Ravi: disappears, and then the object comes back. So you can actually visually tell. When the object's being occluded and when it's not, and so it's a nice way of like, knowing if you need to go in and fix the model prediction or not. And so these are some of the UX innovations that we came up with, as well as the model innovations.[00:19:46] Joseph Nelson: One thing that I think is really notable here, there's two things. One is that like, I'd love to have a little bit of a discussion about how the models keeping track of the embedded scene to keep track of the ball and the cup in different places. Put a pause on that for a second.[00:19:59] Why the Demo is so Important[00:19:59] Joseph Nelson: One thing that Meta has put an emphasis on here in a much greater degree than other model releases is the demo experience of recognizing that in addition to having a model that can do zero shot segmentation, you've created a web experience that allows folks to kind of experience both the video effects but the types of UX innovations that encourage usage and adoption.[00:20:23] Joseph Nelson: It's actually kind of reminiscent of The underlying technology of ChatGPT was available prior to the web experience of ChatGPT. Can you talk a bit about why that was a consideration to your team and how you thought about the creation of The demo experience in tandem with training and releasing a new model.[00:20:41] Nikhila Ravi: Yeah, absolutely. I think that's a really great example of how, you know, Chad, GPT was really more of a UX innovation. Obviously it was like a number of research innovations that helped to get to this point. But as you said, like the underlying technology was around for a while. And, you know, putting this UX around as a chat interface helped tremendously with the.[00:21:03] Nikhila Ravi: Adoption and people understanding how it could be useful for real world use cases. And in computer vision, especially, it's so visual. The best way to show how these models work. Is by trying it on your own image or your own video with the original SAM, we put a lot of effort in building like a high quality demo.[00:21:23] Nikhila Ravi: And the other piece here is that the demo is actually the annotation tool. So we actually. Use the demo as a way to improve our annotation tool. And so then it becomes very natural to invest in building a good demo because it speeds up your annotation and improves the data quality and that will improve the model quality.[00:21:43] Nikhila Ravi: With this approach, we found it to be really successful. And obviously externally, people really liked being able to try it. I think, you know, people in fields outside of machine learning would never have tried SAM if we didn't have that demo. And I think that definitely led to a lot of the adoption in, like, diverse fields.[00:22:05] Nikhila Ravi: And so because we saw that with SAM 2, like, the demo was a priority first class citizen from day one. And so we really invested in making that. And I think with SAM2 as well, we wanted to have like a step change in the demo experience. Interactive video segmentation, I think that experience is something that maybe has not had much thought given to it.[00:22:27] Nikhila Ravi: And we really wanted to be like, okay, if we are to design a step changing video segmentation experience, what would that look like? And that really did influence our model. And annotation design as well.[00:22:40] Joseph Nelson: It's a really encouraging trend for not thinking about only the new model capability, but what sort of applications folks want to build with models as a result of that downstream.[00:22:49] Nikhila Ravi: I think it also really forces you to think about many things that you might postpone, for example, efficiency.[00:22:55] Joseph Nelson: Yes.[00:22:55] Nikhila Ravi: For a good demo experience. Making it real time is super important. No one wants to wait. And so it really forces you to think about these things much sooner and actually makes us think about how to, what kind of image encoder we want to use or like other hardware efficiency improvements.[00:23:13] Nikhila Ravi: So those kinds of things, I think, become a first class citizen when you put the demo first.[00:23:19] SAM 1 vs SAM 2 Architecture[00:23:19] Joseph Nelson: That's one thing I was going to ask about, and this is related to the architecture change. So SAM1 and the SAM1 demo experience. You have the encoder that's creating the embeddings of all the potential spaces.[00:23:31] Joseph Nelson: That needs to be run on a GPU. That's a relatively intensive operation. But then the query of those embeddings can be run independently and on a cheaper process. So in the SAM1 demo, the way that it was structured, and also this is the way that we have our SAM tool structured in Robloflow as well, is images go to a GPU to get all the SAM based embeddings.[00:23:53] Joseph Nelson: But then for querying those embeddings, we do that client side, in the browser, so that the user can very quickly, you know, you can move your mouse over and you get the proposed candidate masks that Sam found for that region of the image. In SAM 2 you dropped that in the web demo. And I think that's because you made some notable improvements to the rate at which encoding happens.[00:24:16] Joseph Nelson: Can you talk a bit about what led to those speed increases and, again, how that interplays with providing a fast encryption? user experience for interacting with the model.[00:24:29] Nikhila Ravi: Yeah. So the SAM2 web demo is primarily focused on video. We, we decided to just keep it simple and focus on video and on GitHub, we have a Colab notebook that shows how to run SAM2 on images.[00:24:41] Nikhila Ravi: So if you're interested in using, replacing SAM with SAM2 for images, check out GitHub, but on the SAM2 demo, it's not as straightforward to adopt the same architecture as SAM. For video, because we can't send the per frame image embeddings for an entire video back to the front end. In SAM, each frame embedding was like four megabytes, but if you have a long video and that's like per frame, it would become impossible to send that back to the front end.[00:25:11] Nikhila Ravi: So, SAM 2 actually, in terms of the architecture details, I was actually just looking at this earlier, but SAM1 model was around 630 million parameters. It's a fraction of the size of these large language models, but very small. Actually, SAM2, the largest model, is around 224 million parameters. So it's actually One third the size of the SAM original model.[00:25:38] Nikhila Ravi: So we changed the imaging coder from A-V-I-T-H and SAM to a higher model, which has also developed by by meta. So that definitely was something that helped. And in terms of the efficiency compared to sam, so if we were to run SAM per frame on a video or run SAM two, it's around six times faster to run SAM two versus run SAM per frame.[00:26:03] Nikhila Ravi: A number of things improved the efficiency of SAM2 such that we were actually able to run this entirely on the server and not have any component in the front end. But I am very curious to see who puts this on device, like I'm pretty sure soon we'll see like an on device SAM2 or, you know, maybe even running in the browser or something, so.[00:26:25] Nikhila Ravi: I think that could definitely unlock some of these edge use cases that we were able to make a compelling web demo without having to do that.[00:26:34] swyx: Hugging face is probably already working on Transformers. js version of it, but totally makes sense. I want to talk about more about things from the paper, but I think we're still in this sort of demo section.[00:26:42] Video Demo of SAM on Roboflow[00:26:42] swyx: And so I want to hand it to Joseph for his demo to see what the RoboFlow site looks like.[00:26:47] Joseph Nelson: So I can, I can give some context into one key area that Nicola, you mentioned earlier, which is. Sam has made the decision, both Sam 1 and Sam 2, to be class agnostic in terms of its predictions. And that, you then have the ability to have a generalizable, model for zero shot capability.[00:27:05] Joseph Nelson: However, in a lot of domain applications, you do want the class wise name. And so a lot of the challenge can be adding that class wise name for the, at least the annotation to an experience that we've created. That's one of the key considerations. So I will similarly Share my screen and show an example.[00:27:27] Joseph Nelson: Here, I have a bunch of images, and there's a number of ways that I could annotate things, like I could prompt a large multimodal model with like grounding capabilities, you know, you could outsource it, or I can do manual labeling. And with the manual labeling, this is where we make use of models like segment anything.[00:27:45] Joseph Nelson: to propose candidate masks and make it faster. So we have, you know, this annotation pane and what we call the smart poly tool, which is powered by Segment Anything. This is currently Segment Anything 1. We're accelerating and seeing improvements from similar to what the paper shows of Segment Anything 2 performed better on E3.[00:28:06] Joseph Nelson: Images as well as video, but with a segment, anything I'm able to basically prompt regions of my image of interest. So for example, if like, I wanted to say, I want to like add the drum set. You'll see here that like, the original candidate proposal is just the base drum, but let's say I wanted the whole drum set.[00:28:26] Joseph Nelson: So the UX primitive of being able to add and subtract candidate regions of interest is really intuitive here. And now, great, I have this outline, but in fact what I want is, I want to name that as a class. Because maybe for the model that I'm building, I want to build like a task specific model, you know, like an object detection model or an instant segmentation model.[00:28:50] Joseph Nelson: Or, you know, maybe I'm even using like a multimodal model and I want that multimodal model to refer to regions of interest in the images as a specific thing. And so I think what's, you know, really powerful is, of course, like, I get this really rich zero shot prediction. And here we have our friend Rick.[00:29:10] Joseph Nelson: So I get this really rich candidate set of predictions. But then by adding the class wise label, I can, you know, very quickly make sure that any downstream tasks are aware not just of the segment, but also of the, what is inside that segment. Which actually takes me to A separate point of something that I predict that's probably going to happen and Nikhil, I'm actually kind of interested why maybe your team made a conscious decision to not do this initially with SAM2.[00:29:40] Joseph Nelson: There's been an emergent set of models that are also adding open text prompting capabilities to grounding models. So for example, like you've seen models like Grounding Dino or Owlvit, which, you know, you can do. Even image to image or text to image based prompting to find regions of interest. And maybe maybe I can actually give an example of that even in the context of this same data.[00:30:05] Joseph Nelson: So if I wanted to try out, you know, grounding dino on this same set of images, I could try out, you know, prompting grounding dino for a set of different classes. And what's notable is let's do, I don't know, let's prompt for person and we'll prompt for person and prompt for I don't know, microphone.[00:30:26] Joseph Nelson: NLASC or microphone. Here I can text prompt the image and then the understanding, in this case Grounding Dino's understanding, of where people are in this image allows me to create, in this case, bounding boxes, but, you know, soon you can do segmentations or in tandem with SAM do segmentations. And, you know, we've already seen applications of using SAM2 in tandem with models like Grounding Dino or Florence 2.[00:30:54] Joseph Nelson: So that people can basically text prompt and then get the benefits of the zero shot segmentation at the same time as getting the open form querying. And in doing so, you know, we maintain a framework called like autodistill so like folks can very quickly, you know, bring some images and then using autodistill to find some ontology and then prompt and say what you want from that ontology.[00:31:19] Nikhila Ravi: So you already do this for video as well?[00:31:21] Joseph Nelson: You can apply videos or groups of images, yes. So this is using a project called Autodistill. And the concept of Autodistill is, use a base model, like a big base model, which could be like SAM or Grounding Dino, and then you pass a directory of images, which also could be video, broken into individual frames, and you pass an ontology as well.[00:31:43] Joseph Nelson: So an example I was just showing was like the hello world we have, which is like a shipping container. And then the combination of the grounding capabilities of, in the example I was showing, Florence 2 plus SAM, looks for the concept of container, and then SAM does the rich segmentation of turning that concept of container into the candidate proposal of the region, so that a user could just say, hey, I want all the shipping containers, run this across a bunch of images or video frames, And then get back the class wise labels plus the regions of interest.[00:32:17] Joseph Nelson: And this feels like a natural extension. And in fact, like the open form grounding capabilities between SAM1 and SAM2 became something the field was broadly doing. So I'm curious, like, from your perspective, one of the things I thought maybe SAM2 would do is actually add this capability natively. So I'm curious to hear, like, the conscious decision to say, hey, we want to continue to be class agnostic.[00:32:39] Extending SAM 2 with other models[00:32:39] Joseph Nelson: We don't want to add yet maybe open form text prompting as a part of finding the segments and parts of images. And I'd love to hear about like the decision to think about it that way. And if you are encouraged or if you want kind of like what's happening here where people are naturally combining these capabilities as something that you would expect and encourage to happen despite not having it.[00:33:00] Joseph Nelson: In the base model itself.[00:33:02] Nikhila Ravi: Yeah, it's a great question. So I think it's really cool that the community is taking SAM and taking SAM 2 and building on top of it and coming up with cool applications. We love to see that. That's exactly why we open source our work. And then in terms of why we didn't put it into SAM 2, so as you've probably seen with SAM and SAM 2, it's a fairly narrow problem.[00:33:25] Nikhila Ravi: But we really tried to make it a step change in the capability. And so with each version, we are trying to limit the focus on one thing that we can know we can do really well. And in this case, like the first SAM, it was class agnostic segmentation, but can we do it so well that it's effectively solved?[00:33:47] Nikhila Ravi: And similarly, can we do that same thing, but with Video segmentation. So one step at a time, we are working on each of these problems one at a time so that we can actually deliver something that's really world class and step changing.[00:34:03] Joseph Nelson: So does that mean SAM 3 will have the text prompting? Problem is like the next challenge.[00:34:09] Nikhila Ravi: Who knows, who knows? Maybe the community will, will we'll build that too. So[00:34:15] Joseph Nelson: it makes sense to like very narrowly do something very well. And that's, I think, proven to be well accomplished.[00:34:21] Nikhila Ravi: It's like taking the, the, both the data, the model and the demo, and how can we push all three towards solving one thing really well?[00:34:30] Nikhila Ravi: So we found that. That's like a good recipe and that's what we've limited the focus of these, of each of these models.[00:34:38] swyx: This development reminds me of how, you know, when you do, and you break out the interpretability of ConvNets and you can see like, Oh, this is the edge detection one. I feel like SAM is the edge detection version equivalent.[00:34:51] swyx: And then you build up to whatever the next feature is on top of that.[00:34:54] Limitations of SAM: Screenshots[00:34:54] Joseph Nelson: Can I bring up one? Limitation of SAM. So like we've like even SAM one, SAM two, and the monitor is released at 4 PM Pacific on Monday. We're recording this on 11 AM Pacific on, on, on Thursday. So the, it's very fresh for a lot of the capabilities and.[00:35:09] Joseph Nelson: It is so clear that it is a stepwise change in the capability that, Nikhila, you mentioned your team wants to do, which is extend SAM's zero shot class agnostic capability to video, like, A plus, kind of mission accomplished. One thing that's interesting is finding, like, domain problems where there might be still domain applicability and domain adaptation that is available.[00:35:32] Joseph Nelson: One benchmark that we introduced at CBPR is this thing called RF100, which is like, seven different domain type problems that the industry commonly is working on in vision, like underwater document processing, aerial examples, medicine examples. And one place where interestingly segment anything maybe less performant than other models is handling screenshots.[00:35:57] Joseph Nelson: For example, like a lot of folks that are building agents to interact with the web are particularly interested in that challenge of given a screenshot of a computer, what are all the buttons. And how could I autonomously navigate and prompt and tell it to click? And I can show an example of like maybe what, how like Sam kind of performs on this challenge just to outline some of the context of this problem.[00:36:23] Joseph Nelson: But I'm curious like how you think about limitations like this and what you would expect to want to be the case. So here I just have a notebook where I run Sam on the source image on the left. Or the source image on the left and then Sam output is on the right. And this is just a screenshot of, of a website where we just grab like the top 100 websites by traffic and grab screenshots from them.[00:36:42] Joseph Nelson: One example of a place where I could see the community improving on Sam, and I'm curious how you think about this challenge and maybe why Sam is less well adapted for this type of problem. Is processing screenshots. So I'll share my screen to give an example for, for viewers that are participating here, you see like an example, a screenshot of a website on the left, and then right is SAM two running on that image.[00:37:06] Joseph Nelson: And in the context of agents, folks usually want to have like, Hey, tell me all of the buttons that a, an agent could press. Tell me like maybe the headlines of the articles tell me the individual images and Sam two behaves perhaps predictably, where it outlines like people in the images and like some of like the, the screen text.[00:37:22] Joseph Nelson: I'm curious, like, how you think about a challenge like this for a model that sees everything in the world, what about handling digital contexts? And Why maybe it could perform better here and how you would expect to see improvement for domains that might have been out of distribution from the training data?[00:37:40] Nikhila Ravi: Yeah, this is a good question. So fair, we don't really build with a specific use case in mind. We try to build like these foundational models that can be applied to lots of different use cases out of the box. So I think in this kind of example, potentially people might want to annotate some data.[00:37:59] Nikhila Ravi: Fine tune on top of what we release. I think we probably won't build things that are very custom for different use cases. I think that's not a direction we'll go in, but as you said, like the model is an annotation tool to improve the model. And so I think that's definitely the approach we want to take is we provide the tools for you to improve the model as well as the model itself.[00:38:27] Joseph Nelson: That makes sense. Focus on like as many. Multi or zero shot problems and then allow the community to pick up the torch for domain adaptation.[00:38:34] Nikhila Ravi: Yeah, absolutely. Like, we can't solve all the problems ourselves. Like, we can't solve all the different domains. But if we can provide a sort of base hammer tool, and then people can apply it to all their different problems.[00:38:48] SAM 2 Paper[00:38:48] swyx: If you don't mind, I guess we want to transition to a little bit on like asking more questions about the paper.[00:38:53] Udio AI: Sure.[00:38:54] swyx: There's a lot in here. I love the transparency from Meta recently with like LLAMA 3 last week and then, and was it last week? Maybe, maybe a little bit less than last week. But just like just really, really well written and a lot of disclosures, including the data set as well.[00:39:08] SA-V Dataset and SAM Data Engine[00:39:08] swyx: I think the top question that people had on the data set, you know, you release a diverse videos and there was, there's a lot of discussion about the data engine as well, which I really love. And I think it's innovative if you wanted. I think the top question is like, how do you decide the size of data set?[00:39:22] swyx: You know, what were you constrained by? People are asking about scaling laws. You had some ablations, but as a research manager for this whole thing, like how do you decide what you need?[00:39:32] Nikhila Ravi: Yeah. I mean, it's a great question. I think it's, as with all papers, you write them at the end of the project, so we can put these nice plots at the end, but going into it, I think, you know, the data engine design really follows.[00:39:47] Nikhila Ravi: So, this is sort of the model design, how we thought about the task, how we thought of the model capabilities. You can really see it's reflected in the different phases of the data engine. We started with just SAM, we apply SAM per frame. That's like the most basic way of extending SAM to video. Then the most obvious thing to do is to take the output masks from SAM and then provide it as input into a video object segmentation model that takes the mask as the first frame input.[00:40:19] Nikhila Ravi: And that's exactly what we did. We had SAM plus a version of SAM2 that only had mask as input. And then in the last phase, we got rid of SAM entirely and just had this one unified model that can do both image. And video segmentation. And I can do everything in just one model. And we found that, you know, going from each phase, it both improved the efficiency and it improved the data quality.[00:40:46] Nikhila Ravi: And in particular, when you get rid of this two part model, one of the advantages is that when you make refinement clicks, so, You prompt the model in one frame to select an object, then you propagate those predictions to all the other frames of the video to track the object. But if the model makes a mistake and you want to correct it, when you have this unified model, you only need to provide refinement clicks.[00:41:14] Nikhila Ravi: So you can provide maybe a negative click to remove a region or a positive click to add a region. But if you had this decoupled model, you would have to Delete that frame prediction and re annotate from scratch. And so you can imagine for more complex objects, this is actually adding like a lot of extra time to redefine that object every time you want to make a correction.[00:41:39] Nikhila Ravi: So both the data and the data engine phases really follow, like how we thought about the model design and the evolution of the capabilities, because it really helped us to do that. improve the data quality and the annotation efficiency as well.[00:41:54] swyx: Yeah, you had a really nice table with like time taken to annotate and it was just going down and down.[00:41:58] swyx: I think it was like down by like 90 percent by the time you hit stage[00:42:02] Joseph Nelson: three, which is kind of cool. We joke that when SAM 1 came out at RoboFlow, we're like, was this purpose built for our software? Like you have like the embedding, you have the embedding take like a big model and the querying of the embeddings A smaller model that happens in browser, which felt remarkably aligned.[00:42:18] Joseph Nelson: Now hearing you talk about how you think about building models with a demo in mind, it makes sense. Like, you're thinking about the ways that folks downstream are going to be consuming and creating value. So, what felt like maybe a coincidence was perhaps a deliberate choice by Meta to take into account how industry is going to take Seminal advances and apply them.[00:42:36] Nikhila Ravi: Yeah. And it's not just humans. Like it could also be a model that outputs boxes that then get fed into this model. So really thinking about this as a component that could be used by a human or as a component, as part of a, of a larger AI system. And that has, you know, a number of design requirements. It needs to be promptable.[00:42:56] Nikhila Ravi: It needs to be, have the zero shot generalization capability. We, you know, need it to be real time and. Those requirements really are very core to how we think about these models.[00:43:08] Memory Attention to solve Video[00:43:08] swyx: I cannot end this podcast without talking about the architecture, because this is your, effectively the sort of research level, architecture level innovation that enabled what I've been calling object permanence for SAM.[00:43:22] swyx: And it's memory retention. What was the inspiration going into it? And you know, what did you find?[00:43:27] Nikhila Ravi: Yeah, so at a high level, the way we think about extending SAM to video is that an image is just a special case of a video that just has one frame. With that idea in mind, we can extend the SAM architecture to be able to support segmentation across videos.[00:43:45] Nikhila Ravi: So this is a quick video that shows how this works. So SAM architecture, we have the image encoder, we have a prompt encoder, we have a mask decoder. You can click on an image. And that basically is a prompt, we use that prompt along with the image embedding to make a mask prediction for that image. Going to SAM2, we can also apply SAM2 to images because we can, you know, as I said, treat an image as a video with a single frame.[00:44:15] Nikhila Ravi: And so when we, in the SAM2 architecture, we introduce this new memory mechanism that consists of three main components. There's memory attention, there's a memory encoder, and then there's a memory bank. And when we apply SAM2 to images, these are effectively not used. And the architecture just collapses down to the original SAM architecture.[00:44:35] Nikhila Ravi: But when we do apply this to video, the memory components become really useful because they provide the context of the target object from Other frames. And so this could be from past frames. It can be from, there's two types of memory. So there's like the condition, conditional frames or the prompted frames, which are basically the frames at which a user or a model provides input like clicks.[00:45:01] Nikhila Ravi: And then there's like the surrounding frames. And say we use six frames around the current frame as memory of the object. So there's, there's those, those, both those types of memory that we use to make the prediction. Going into a little bit more detail about that, there's like two kinds of memory that we use.[00:45:18] Nikhila Ravi: So one is like spatial memory. So it's like this high resolution memory that captures the spatial details. And then we also have this like longer term object pointer memory that captures some of the sort of higher level concepts. And I think Swyx, you had a comment about how does this relate to sort of context window and LLMs.[00:45:37] Nikhila Ravi: And both of these types of memories have some relation to context window, so they both provide different types of information on the spatial side or in terms of the concept of the objects that we want to track. And so we found that having like six frame length for the spatial memory, Coupled with this longer period of the object pointer memory provides strong video segmentation accuracy at high speed.[00:46:01] Nikhila Ravi: So, as I mentioned, the real time aspect is really important. We have to find this speed accuracy trade off. And one way in which we sort of circumvent this is by allowing additional prompts on subsequent frames. So even if the model makes a mistake, maybe it loses the object. After an occlusion, you can provide another prompt, which actually goes into the memory.[00:46:24] Nikhila Ravi: And so the prompted frames are always in the memory. And so if you provide a prompt on a frame, we will, or the model will always remember what you provided. And so that's a way in which we can sort of avoid some of the model failure cases that actually is a big limitation of current models, current video object segmentation models.[00:46:45] Nikhila Ravi: Don't allow any way to recover if the model makes a mistake. And so, Joseph, going back to your point about the demo, that's something that we found just by playing with these models. There's no way to make a correction, and in many real world use cases, like, it's not going to be a one time prediction, but you actually want to be able to intervene, like, if an LLM makes a mistake, you can actually be like, no, actually do it this way, and provide feedback, and so, We really want to bring some of that thinking into how we build these computer vision models as well.[00:47:16] "Context Length" in Memory Attention[00:47:16] swyx: Amazing. My main reaction to finding out about the context length of eight input frames and six pass frames as their default is why not 60? Why not 600? In text language models, we're very used to severely extending context windows. And what does that do to the memory of your model?[00:47:35] Nikhila Ravi: So I think maybe one, one thing that's different is that the object in video, it is challenging.[00:47:41] Nikhila Ravi: Objects can, you know, change in appearance. There's different lighting conditions. They can deform, but I think a difference to language models is probably the amount of context that you need is significantly less than maintaining a long multi time conversation. And so, you know, coupling this. Short term spatial memory with this, like, longer term object pointers we found was enough.[00:48:03] Nikhila Ravi: So, I think that's probably one difference between vision models and LLMs.[00:48:09] Object Tracking[00:48:09] Joseph Nelson: I think so. If one wanted to be really precise with how literature refers to object re identification, object re identification is not only what SAM does for identifying that an object is similar across frames, It's also assigning a unique ID.[00:48:25] Joseph Nelson: How do you think about models keeping track of occurrences of objects in addition to seeing that the same looking thing is present in multiple places?[00:48:37] Nikhila Ravi: Yeah, it's a good question. I think, you know, SAM2 definitely isn't perfect and there's many limitations that, you know, we'd love to see. People in the community help us address, but one definitely challenging case is where there are multiple similar looking objects, especially if that's like a crowded scene with multiple similar looking objects, keeping track of the target object is a challenge.[00:49:03] Nikhila Ravi: That's still something that I don't know if we've solved perfectly, but again, the ability to provide refinement clicks. That's one way to sort of circumvent that problem. In most cases, when there's lots of similar looking objects, if you add enough refinement clicks, you can get the perfect track throughout the video.[00:49:22] Nikhila Ravi: So definitely that's one way to, to solve that problem. You know, we could have better motion estimation. We could do other things in the model to be able to disambiguate similar looking objects more effectively.[00:49:35] swyx: I'm just interested in leaving breadcrumbs for other researchers, anyone interested in this kind of architecture.[00:49:41] swyx: Like, are there papers that you would refer people to that are influential in your thinking or, you know, have, have other interesting alternative approaches?[00:49:49] Nikhila Ravi: I think there's other ways in which you can do tracking and video. You might not even need the full mask. I think that's it. Some other works that just track like points on objects.[00:49:59] Nikhila Ravi: It really, really depends on what your application is. Like if you don't care about the entire mask, you could just track a bounding box. You could just track a point on an object. And so having the high fidelity mask might not actually be necessary for certain use cases. From that perspective, you might not need the full capabilities.[00:50:19] Nikhila Ravi: of SAM or SAM2. There's many different approaches to tracking, I think I would encourage people to think about like what actually they need for their use case and then try to find something that that fits versus, yeah, maybe SAM2 is too much, you know, maybe you don't even need the full mask.[00:50:37] swyx: Makes total sense, but you have solved the problem that you set out to solve, which is no mean feat, which is something that we're still appreciating even today.[00:50:44] The Future of FAIR[00:50:44] swyx: If there are no further questions, I would just transition to sort of forward looking, future looking stuff. Joseph already hinted at, like, you know, our interest in SAM and the future of SAM, and obviously you're the best person to ask about that. I'm also interested in, like, How should external people think about FAIR, you know, like there's this stuff going on, this llama, this chameleon, this voice box, this image bind, like, how is, how are things organized?[00:51:09] swyx: And, you know, where are things trending?[00:51:11] Nikhila Ravi: Yeah, so in FAIR, we, you know, we have a number of different research areas. I work in an area called perception. So we built vision systems that solve basically, Look at all the fundamental problems in Compute Division. Can we build a step change in all of these different capabilities?[00:51:29] Nikhila Ravi: SAM was one example. SAM2 is another example. There are tons of other problems in Compute Division where we've made a lot of progress, but can we really say that they're solved? And so that's really the area in which I work on. And then there's a number of other research areas in language and in embodied AI.[00:51:49] Nikhila Ravi: And more efficient models and various other topics. So fair in general is still very much pushing the boundaries on solving these foundational problems across different domains. Well,[00:52:07] swyx: fair enough, maybe just outside of fair, just the future of computer vision, right?[00:52:10] CVPR, Trends in Vision[00:52:10] swyx: Like you are very involved in the community. What's the talk of the town at CVPR? Both of you went, who's doing the most interesting work? It's a question for both of you.[00:52:19] Joseph Nelson: I think the trends we're seeing towards more zero shot capability for common examples will accelerate. I think Mutu modality, meaning using, you know, images in tandem with text for richer understanding or images and video in tandem with audio and other mixed media will be a continued acceleration trend.[00:52:43] Joseph Nelson: The way I kind of see the field continuing to progress, the problem statement of computer vision is making sense of visual input. And I think about the world as the things that need to be observed follow your traditional bell curve, where like things that most frequently exist out in the world are on the center of that bell curve.[00:53:05] Joseph Nelson: And then there's things that are less frequently occurring that are in those long tails. For example, you know, as back as like 2014, you have the Cocoa data set, which sets out to say, Hey, can we find 80 common objects in context, like silverware and fridge and these sorts of things. And we also conceptualized the challenge of computer vision in terms of breaking it down into individual task types, because that's like the tools we had for the day.[00:53:29] Joseph Nelson: So that's why, you know, you have the origination of classification, object detection, instant segmentation. And then as you see things continue to progress. You have models and things that need to observe areas in the long tails. And so if you think of the Cocoa dataset as the center of that bell curve, I think of like the long tails, like really edge case problems.[00:53:49] Joseph Nelson: Some of our customers like Rivian, for example, only Rivian knows what the inside of like a Rivian should look like as it's assembled and put together before it makes its way to a customer and they're making custom parts. Right? So how could a model you've been trained on the things that go inside the componentry of producing a vehicle and Andreesen, What's kind of happening with computer vision is you're seeing models that generalize in the middle of the bell curve push outward faster.[00:54:17] Joseph Nelson: That's where you see the advent of like open text models or the richness of understanding of multimodal models. To allow richer understanding without perhaps any training, or maybe just using pre training and applying it to a given problem. And then, there's like, you know, kind of like the messy middle in between those two, right?[00:54:38] Joseph Nelson: So like, Akila kind of talked about examples where SAM does well out of distribution, where like, it finds an octopus, even though there wasn't octopi in the training data. I showed an example where, like, screenshots, where Sam isn't yet super great at screenshots, so maybe that's, like, in the messy middle or in the longer tails for now.[00:54:54] Joseph Nelson: But what's going to happen is there needs to be systems of validating the point of view that I think about, like, tooling to also validate that models are doing what we want them to do, adapting to datasets that we want them to adapt to. And so there's a lot of things on a forward looking basis that allow propelling that expansion of generalizability.[00:55:14] Joseph Nelson: That's for open text problems. That's where scaling up of training, of dataset curation, continues to play a massive role. Something that's notable, I think, about SAM2 is it's, what, 57, 000 videos? 51,[00:55:30] Nikhila Ravi: 000 videos? About 51, 000, yeah.[00:55:32] Joseph Nelson: And 100, 000 internal datasets. That's, like, not Massive, right? And the model size also isn't, you know, the largest, largest model being a couple hundred million parameters.[00:55:43] Joseph Nelson: The smallest model is 38 million parameters and can run at 45 FPS on an A100, right? Like the capabilities of, we're going to see more capable, more generalizable models. Being able to run on a higher wide array of problems with zero or multi shot capability on a faster, a faster rate. And I think the architecture innovations and things like SAM2 of memory, of increasingly like transformers making their way into division and probably blended architectures increasingly too.[00:56:15] Joseph Nelson: So my viewpoint of like on a go forward basis is we will have that bell curve of what humans can see both in the center of that curve and the long tails. And architectural changes allow richer understanding, multi and zero shot, and putting those into systems and putting those into industry and putting those into contexts that allow using them in practical and pragmatic ways.[00:56:38] Joseph Nelson: Nicola, I'd love to hear like your thought and perspective of like how you think the research trends map or don't map to that. And like maybe some of the key innovations that you saw at CVPR this year that, you know, Got you excited about the direction and maybe some promising early directions that you're thinking about researching or pushing the boundaries of further.[00:56:56] Nikhila Ravi: Yeah, I just wanted to actually reply to a couple of things that you said about so actually in video object segmentation, the number of classes. that are annotated in these, and then the size of these datasets are really small. So with SAM, it's, you know, we had a billion masks, we had 11 million images, didn't have class labels.[00:57:17] Nikhila Ravi: But even before that, there were a lot of datasets that have class labels and are annotated. With significantly more with, with like a lot of class labels, whereas in video datasets, the number of class labels are very small. So there's like YouTube VOS, which has 94 object categories, there's Mose, which has around like 30 or so object categories.[00:57:38] Nikhila Ravi: And they're usually like people, there's cars, there's dogs and cats and all these common objects, but not really, they don't really cover a very large number of object categories. And so while Sam learned this general notion of what an object is in an image. These video tracking models actually don't have that knowledge at all.[00:58:01] Nikhila Ravi: And so that's why having this data set is really important for the segment anything capability in video because if you just provide the mask as the input to an off the shelf Video object segmentation model. It might not actually be able to track that arbitrary object mask as effectively as a SAM2 model that's actually trained to track.[00:58:24] Nikhila Ravi: Any object across the entire video. So doing these sort of combining two models together to try to get a capability that will actually only get you so far and being able to actually create that the dataset to enable that anything capability, it was actually really important and we can actually see that when we do comparisons with baselines where we provide some two with the same input mask and the baseline model with the same input mask.[00:58:53] Nikhila Ravi: For example, the t shirt of a person, SAM2 can track the t shirt effectively across the entire video, whereas these baselines might actually start tracking the entire person, because that's what they're used to doing, and isolating it to just one part of the person is not something they were ever trained to do, and so those are sort of some of the limitations.

In this episode, Branda takes us on a ride through the email marketing world, armed with nothing but her wits and a spreadsheet full of data! She shares a behind-the-scenes look at a nine-month journey with a unique client—a pair of Texas real estate developers. Discover how she navigates from initial market research to refining messages that truly resonate. Branda reveals her strategic thought process, the results of her experiments, and actionable insights you can implement in your own business.Tune in as Branda discusses:Crafting an email marketing strategy from the ground up.Experimenting with different types of content to see what resonates.Segmenting audiences and refining messages to maximize engagement.___________________________________Enter to win the Free Copy Giveaway: https://therelevantcolletive.ck.page/giveaway-too________________________________________CONNECT WITH MELANIE:www.duxburydigital.cowww.instagram.com/duxburydigitalCONNECT WITH BRANDA:www.therelevantcollective.comwww.instagram.com/therelevantcollective

SEO becomes easy when you connect traffic to leadds and sales in a passive income mode strategized way. Listen to this email marketing masterclass which went for almost 3 hours on Clubhouse Audio. Enjoy. SEO Resources For You ⁠⁠⁠⁠⁠⁠⁠Join the PGA Newsletter here!⁠⁠ >>⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Get all the episodes in the academy ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠! Book a call with Favour Obasi-ike

What's up, basketball trainers? I wanted to share how a series of seven emails, written by a highly competent high school senior intern, generated a couple of thousand dollars for our upcoming league. Some takeaways from this short podcast: Email Campaigns Can Be Profitable The effectiveness of how an email list is used is more important than the size of the list. Segmenting the list and ensuring high deliverability and engagement rates are crucial. Selling through email can increase earnings per hour since the effort to set up emails is minimal compared to the potential revenue generated. Regularly sending out offers helps gauge audience interest and preferences, providing valuable data beyond just generating sales. It's essential to fully utilize the features of email campaign tools to maximize their potential and benefit the business. Finding and mastering tools that can be game-changers for the business, such as CRM, chat widgets, automation tools, and email campaigns, can significantly impact success. Hiring capable and precocious interns, especially those with relevant interests and experiences, can greatly benefit the business. By optimizing and mastering the tools we already have, we can make a big difference in our basketball training business. Enjoy your week, everybody!

Ian and his crew at Connecticut Watersports maintain a steady stream of customers every summer. But now, five years into the business, he's wondering if there's a way to keep customers engaged year-round with a consistent email marketing strategy. Ian also wants to segment his customers so everyone gets the most relevant messages. In this episode, we brought our best email tips aboard to help Ian provide more value to his customers and generate more bookings.Shoestring is produced by SimpleTexting, a Sinch company. Does your small business need marketing help? Text us at (954) 419-3657.Here's the full presentation of ideas we shared with Ian. (Warning: spoilers!)

⚡Limited time!⚡ Book a free 20-minute Zoom call with me to talk about your digital product strategy!  ______________________________________ In my newest episode of The Blogger Genius Podcast, I sat down with Tammy Overhoff food blogger at Organize Yourself Skinny and digital product shop owner at Reset and Flourish. Tammy shares her experiences and strategies for transitioning from traditional food blogging to selling digital products, offering valuable insights for anyone looking to diversify their online business. In this episode you'll hear her actionable advice and expert tips to help you succeed in the digital product space. Show Notes: MiloTreeCart Book a FREE 20-minute call with me Reset and Flourish Organize Yourself Skinny MiloTree Pop-Up App Personality Quiz: What Digital Product Should I Create? Join My Blogger Genius Email List Become a Blogger Genius Facebook Group All Blogger Genius Podcast Episodes Subscribe to the Blogger Genius Podcast: iTunes YouTube Spotify The Journey from Food Blogging to Digital Products Tammy Overhoff's journey began with her food blog, Organize Yourself Skinny, where she shared meal prep tips and healthy eating advice. Over time, she realized the potential of digital products to provide additional value to her audience and generate revenue. Here are the main steps she took to make this transition: Identifying the Right Digital Products Tammy started by identifying the types of digital products that would resonate with her audience. She focused on creating products that aligned with her blog's theme and addressed her readers' needs. Some of the digital products she developed include: Meal Prep Lessons: Using her expertise in meal prep, Tammy created a series of lessons to help her audience plan and prepare meals efficiently.   Ebook Bundles: She compiled her best recipes and meal prep tips into ebooks, offering them as bundles for added value.   Healthy Eating Challenges: Tammy designed a ten-day healthy eating challenge kit, providing her audience with a structured plan to kickstart their healthy eating journey. Leveraging Existing Content One of Tammy's key strategies has been repurposing existing content to create digital products. This approach not only saves time but also ensures that the products are relevant and valuable to her audience. For example: Repurposing Blog Posts: Tammy turned her most popular blog posts into comprehensive ebooks, adding additional content and resources to enhance their value.   Creating Mini Products: She used the Meal Pro app to offer mini products, such as meal prep lessons, which were derived from her existing content. Building and Nurturing an Email List Tammy emphasizes the importance of having a robust email list to sustain long-term success in selling digital products. She shares her strategies for building and nurturing her email list: Lead Magnets: Tammy offeres free resources, such as meal planning templates and healthy eating guides, to attract new subscribers.   Regular Communication: She maintains regular communication with her email list, providing valuable content and updates about new products and offers.   Segmenting the Audience: Tammy segments her email list based on subscribers' interests and behaviors, allowing her to send targeted and relevant content. Creating a Strong Sales Funnel A well-designed sales funnel is crucial for converting leads into customers. Tammy shares her approach to creating an effective sales funnel: Front-End Offers: She uses her ten-day healthy eating challenge kit as a front-end offer to attract new customers and introduce them to her products. Upselling and Cross-Selling: Tammy offers additional products and services, such as yearly memberships and workshops, to existing customers. Retargeting with Facebook Ads: She successfully uses Facebook ads to retarget website visitors and email subscribers, driving them back to her sales funnel. Adapting to Changes and Challenges Tammy's journey has not been without challenges. She shares her experience of being hit by a Google algorithm update in November 2019, which significantly impacted her traffic and revenue. Despite this setback, she pivoted her business and found new ways to engage her audience: Hosting Challenges in Facebook Groups: Tammy hosts challenges in her Facebook group, which helps her maintain engagement and drive sales.   Diversifying Traffic Sources: She diversifies her traffic sources by leveraging social media, email marketing, and paid advertising. Expert Tips for Selling Digital Products Based on Tammy's experiences and insights, here are some expert tips for successfully selling digital products: Understand Your Audience To create products that resonate with your audience, it's essential to understand their needs, preferences, and pain points. Conduct surveys, engage with your audience on social media, and analyze your website analytics to gather insights. Start Small and Scale Up Begin with small, manageable products, such as ebooks or mini-courses, and gradually scale up to more comprehensive offerings. This approach allows you to test the market and refine your products based on feedback. Focus on Quality and Value Ensure that your digital products are high-quality and provide real value to your audience. Invest time in creating well-designed, informative, and actionable content that addresses your audience's needs. Build a Strong Brand A strong brand can help you stand out in a crowded market. Develop a consistent brand identity, including your logo, color scheme, and messaging, and ensure that it reflects your values and resonates with your audience. Utilize Multiple Marketing Channels Diversify your marketing efforts by utilizing multiple channels, such as social media, email marketing, and paid advertising. This approach can help you reach a broader audience and drive more traffic to your sales funnel. Continuously Optimize Your Sales Funnel Regularly review and optimize your sales funnel to improve conversion rates. Test different offers, landing pages, and email sequences to identify what works best for your audience. Stay Adaptable and Resilient The online business landscape is constantly evolving, and it's essential to stay adaptable and resilient. Be prepared to pivot your strategies and explore new opportunities to stay ahead of the competition. Tammy Overhoff's journey from food blogging to selling digital products offers valuable lessons for anyone looking to diversify their online business. By leveraging her expertise, repurposing existing content, and nurturing her audience, Tammy successfully transitioned into the digital product space. Her experiences highlight the importance of understanding your audience, building a strong sales funnel, and staying adaptable in the face of challenges. Whether you're a seasoned blogger or just starting, these insights and tips can help you create and sell digital products that resonate with your audience and drive long-term financial success. Other Related Blogger Genius Podcast episodes You'll Enjoy: #336 Master Email Tripwires: Convert Subscribers into Customer with Jillian Leslie #326 Essential Traffic Strategies for Food Bloggers with Madison Wetherill​ #324 How to Make Money Blogging in 2024 (New Trends) with Jillian Leslie​ MiloTreeCart, the Best Tool for Non-Techies to Sell Digital Products I also want to introduce you to the MiloTreeCart, a tool designed for non-techies to sell digital products easily. It comes with features like fill-in-the-blank sales pages, check-out pages, a sales dashboard, upsells, and customer support. Milo

In this episode, Eric shares with us how to effectively tailor marketing messaging, why it's important to push the boundaries of content design, and leveraging tools like ChatGPT for brainstorming ideas. Eric also talks about why fighting pieces of collateral to get to the point is often done in vain and his approach to creating better content. Key Takeaways:Balance products and personas: You need to adeptly balance different products, verticals, and personas to create a cohesive marketing strategy. Segmenting your audience based on their product install base allows you to tailor your messaging and approach more effectively, fostering stronger connections and driving better results.Be innovative with design: Emphasize innovative and boundary-pushing design in your content. Think of new ways to deliver your message and make your content stand out from the competition. Creativity in design can significantly enhance your brand's appeal and memorability.AI is a tool - use it: Use tools like Chat GPT for brainstorming ideas. AI can help you generate creative concepts and refine your strategies, making your campaigns more dynamic and innovative.Quote: “I think the design is so important, and as someone who, I run the marketing team here, I'm personally probably on a lot of sales lists and distributions. I get hit up constantly by SDRs who are sending me things.  If it doesn't look good, I'm not going to open it. I don't really care what it is. Like I'm so busy drifting between emails and Slacks and meetings. And then, my personal life as well, that if it's not designed in a compelling, intuitive way, I'm not going to fight with a piece of collateral to get to the point. And so I think we have really tripled down on brand, visual identity, how the different pieces of our story come together…But when you're getting into thought leadership, I think the era of attaching a PDF or a static white paper, one pager, like those are so long gone. And I think in an industry that is a bit old school as well, I think standing out as a more dynamic marketing function where we're putting out pieces of collateral that not only does the user want to read the insight because the data we have is so unique to us, no one else is putting out content that looks like ours does.” Episode Timestamps: *(03:57) - Trust Tree: It's all about balance*(16:20) - The Playbook: The data is the hook*(41:56) - The Dust Up: Approaching product launches thoughtfully*(44:02) - Eric's Quick HitsSponsor:Pipeline Visionaries is brought to you by Qualified.com, the #1 Conversational Marketing platform for companies that use Salesforce and the secret weapon for pipeline pros. The world's leading enterprise brands trust Qualified to instantly meet with buyers, right on their website, and maximize sales pipeline. Visit Qualified.com to learn more. Links:Connect with Ian on LinkedInConnect with Eric on LinkedInLearn more about VTSLearn more about Caspian Studios

The key to clear communication is segmenting your list.And what that means is really just separating your main email list into different buckets on how they might have found you.Because as you do this and you have different lists with different people, you can have different kinds of conversations with them.This is going to really allow you to connect with them at a deeper level and resonate with them because you are not treating everybody the same.You will have more individual conversations with your audience that will make them really feel heard and understood.Resources:Adaptive Inner Circle - The Adaptive Inner Circle with Paul & Melissa Pruitt is an epic 12-month experience for online business owners, coaches, course creators, and membership site owners who aspire to create financial freedom and a lifestyle they want for themselves and their family and also create a positive impact in their community and the world.Adaptive Marketing Program - Adaptive Marketing Program is an exclusive opportunity for online business owners, coaches, course creators, and membership site owners to play bigger and bolder in their business and explode their bank account with more clients!For a list of our resources & recommendations visit: https://onlinemarketingpodcast.com/learn-with-paul-melissa/Connect with us on social!Instagram: @realpaulpruitt & @realmelissapruittFacebook: @realpaulpruitt & @realmelissapruitt

Rate, Review, & Follow on Apple Podcasts In this episode of the Duct Tape Marketing Podcast, I interviewed Mikael Dia, a digital marketing expert and founder of Funnelytics. Through Funnelytics, Mikael Dia revolutionizes the way marketers optimize their strategies. He simplifies complex marketing concepts, making it easier for businesses to understand and enhance their customer journeys. In this episode, we unravel the evolution of marketing funnels as he offers practical techniques to increase conversions.   Key Takeaways Marketing Funnels or the Customer Journey? The concept of Marketing Funnels lies in viewing them as dynamic customer journeys rather than static paths. Mikael Dia explains that marketing funnels have evolved into orchestrated journeys that guide potential customers from awareness to conversion and beyond. He emphasizes the importance of continuously optimizing and testing your funnels, advising against the common misconception that a funnel is a one-time setup; you dust your palms, and that's it. Regular analysis and adjustments are essential to improve performance and adapt to changing market conditions. Furthermore, Segmenting your audience is crucial for effective funnel optimization. Mikael Dia suggests that businesses collect and analyze data to identify their ideal customers, tailoring their approaches to meet specific needs and behaviors better. Utilizing the right tools, like Funnelytics, can significantly enhance this process by helping marketers visualize data, run experiments, and make data-driven decisions. Businesses can increase their conversion rates and create seamless, engaging customer journeys by focusing on continuous improvement and leveraging the right tools. More About Mikael Dia: Connect with Mikael Dia on LinkedIn - linkedin.com/in/mikaeldia/ Visit his Website - funnelytics.io/ If you liked this episode please consider rating and reviewing the show. Click here - https://podcasts.apple.com/us/podcast/the-duct-tape-marketing-podcast/id78797836 scroll to the bottom, tap to rate with five stars, and select “Write a Review.” Then be sure to let me know what you loved most about the episode. Connect with John Jantsch on LinkedIn - linkedin.com/in/ducttapemarketing/ Stuck trying to figure out your marketing strategy? Get Your Free AI Prompts To Build A Marketing Strategy HERE - dtm.world/freeprompts

Josh Schachter sits down with Damien Howley, author of "Control Your Customer: A Guidebook for Customer Success Managers". Damien explains the concept of "controlling your customer", the STO framework for segmenting customer contacts, the importance of celebrating every win, and the value of quantifying the customer's gain from a product. Timestamps 0:00 - Preview & Intros 4:00 - Control Your Customer 5:50 - Interpreting customer experience 8:17 - STO framework 11:30 - Segmenting customer accounts and tracking engagements 15:40 - Customer happiness is over-rated? 18:40 - Celebrating every customer win as a CSM Damien has spent the last 20 years building, selling, and implementing SaaS. Since the inception of CS, he has worked to develop and refine best practices for revenue-focused customer success teams, helping hundreds of CSMs master their trade. He has served as a leader and advisor in Customer Success. "The richest relationships I've ever formed with customers have come on the heels of exceptional value delivery." — Damien Howley ___________________________

Chris Harmse, co-founder and VP of Revenue at BVNK joins the show. In this episode we discuss: Chris' career and the path to founding BVNK. The origin story of BVNK and how the company has evolved over time. The key drivers behind the adoption of stablecoins. Segmenting the stablecoin market. Interest bearing stablecoins and the impact that this category will have on the overall market. Tokenized money funds and the future of securities settlement. How stablecoins will refactor the global FX market. The regulatory landscape and how stablecoin adoption is evolving in various regions. To learn more about BVNK visit their website.

In this episode, Jessica Farmer shares tips for teaching heart words. She explains the importance of blending and introduces the concept of continuous blending. Jessica defines heart words as high-frequency words with irregular or temporarily irregular spellings. She emphasizes the need to follow a scope and sequence and provides a routine for introducing new heart words. Jessica also discusses the process of orthographic mapping and suggests engaging activities for teaching heart words. She concludes by recommending additional resources for teaching heart words.TakeawaysBlending is the process of putting sounds together to form words, and continuous blending is a method that connects phonemes without breaking between the sounds.Segmenting is important for spelling, while continuous blending is effective for decoding words.Heart words are high-frequency words with irregular or temporarily irregular spellings, often involving vowel sounds.Teaching heart words should be done in a systematic and routine-based manner, following a scope and sequence.Engaging activities for teaching heart words include coloring by sounds and unscrambling the spelling.Resources Find Jessica at Farmer Loves Phonics on social! Connected Phonation Research A New Model for Teaching High-Frequency WordsBlending PyramidsHeart Word Cards30 Early High Frequency Words for Beginning Readers Connect with us Facebook and join our Facebook Group Twitter Instagram Don't miss an episode! Sign up for FREE bonus resources and episode alerts at LiteracyPodcast.com Helping teachers learn about science of reading, knowledge building, and high quality curriculum.

So this is the 4th episode in our special Greatest Hits List Building series. This week and next, we're going to focus on strategy, so buckle up my friend. My guest is Amy Goldmacher. Amy helps aspiring nonfiction authors go from book idea, to proposal, to draft to getting to a publishable book. Her clients are often experts who just need help taking all of their expertise and putting it into a book. Amy has a super fun lead magnet. It's a bookmark that walks would-be writers through 4-ways to nail down the title of their book. What's been missing for Amy is a concrete and repeatable strategy to actually get her lead magnet out in the world. Not only to build her list, but test the effectiveness of her lead magnet marketing, opt-in page conversion, and how well the lead magnet leads to paying clients. So, Amy and I walk through 4 simple and repeatable ways she can start promoting her lead magnet and get more aspiring authors on her list. Get ready to take some notes because I know you can try out at least one of the strategies we discuss in this episode. Key Takeaways Data-Driven Optimization: Tracking key data points is essential for evaluating lead magnet effectiveness Contextual Clarity: Provide clear context and value proposition on lead magnet landing pages Consistent List-Building Habits: Implement a repeatable lead magnet promotion plan monthly Authentic Direct Messaging: Be transparent and concise when reaching out to followers and focus on providing value rather than pushing for a sale Four-Week Promotion Plan: Implement a structured approach to promote your lead magnet Segmentation for Effective Communication: Tag subscribers appropriately to segment your email list for future promotions Timestamps & Key Topics [01:50] Introduction and setting the agenda [03:30] Tracking data points for lead magnet effectiveness [06:06] Amy describes her audience and services [06:48] Overview of Amy's lead magnet concept/span> [11:05] Review of Amy's landing page [16:23] Exploration of Amy's current lead magnet marketing efforts [19:29] Four-step monthly list-building plan [20:40] Leveraging social media platforms for lead magnet promotion [21:44] Using direct messaging for sharing lead magnets [25:42] Dallas outlines a four-week lead magnet promotion plan [27:40] Segmenting your email list for different audiences [30:40] Reviewing Amy's action items [31:32] Dallas and Amy discuss accountability for implementing the strategy and measuring success List building is a major priority for the majority of Hive members this year, so we're focusing on building easy habits to build your list without feeling overwhelmed. We'd love to welcome up to six new members into The Hive this month and we've got a spot with your name on it. You can apply for The HIVE at dallastravers.com/apply CONNECT WITH AMY: INSTAGRAM: @solidgoldmacher WEBSITE: amygoldmacher.com FACEBOOK: facebook.com/amy.goldmacher CONNECT WITH ME: INSTAGRAM: @dallastravers