Podcasts about nrr

This week on Match Paatheengala Boss, Srini and Arun break down South Africa's stunning win over India in the Super 8

Vláda schválila návrh státního rozpočtu se schodkem 310 miliard, který Národní rozpočtová rada (NRR) kritizuje jako protizákonný. Premiér Andrej Babiš (ANO) následně označil orgán za zbytečný, ministryně financí Alena Schillerová (ANO) ale jeho zrušení odmítla. „Je to kontrolní dioda pro veřejnost, může ji svým silným odborným hlasem informovat, když je ve veřejných rozpočtech něco špatně. A je strašně špatně, že na ni vláda útočí,“ říká v Interview Plus ekonom Daniel Münich.

Vládneme, nerušit #47: Poslanecká sněmovna schválila v prvním čtení základní parametry státního rozpočtu, vláda by tak měla letos hospodařit se schodkem 310 miliard korun. Podle názoru Národní rozpočtové rady (NRR) i dalších odborníků je navržený rozpočet v rozporu se zákonem, protože nedodržuje pravidla o rozpočtové odpovědnosti. To ale ministryně financí Alena Schillerová popírá. Jaké důsledky může mít takto navržený rozpočet? Co to znamená pro Česko? A mohou vůbec opoziční strany v tomto ohledu současné vládě něco vyčítat? To rozebírají Kristýna Jelínková, František Trojan a Filip Zelenka v nové epizodě.

Vláda schválila návrh státního rozpočtu se schodkem 310 miliard, který Národní rozpočtová rada (NRR) kritizuje jako protizákonný. Premiér Andrej Babiš (ANO) následně označil orgán za zbytečný, ministryně financí Alena Schillerová (ANO) ale jeho zrušení odmítla. „Je to kontrolní dioda pro veřejnost, může ji svým silným odborným hlasem informovat, když je ve veřejných rozpočtech něco špatně. A je strašně špatně, že na ni vláda útočí,“ říká v Interview Plus ekonom Daniel Münich.Všechny díly podcastu Interview Plus můžete pohodlně poslouchat v mobilní aplikaci mujRozhlas pro Android a iOS nebo na webu mujRozhlas.cz.

Poslanci schválili rozpočet na tento rok se schodkem 310 miliard. Podle Národní rozpočtové rady je to v rozporu se zákonem. Podle ministryně financí Aleny Schillerové je návrh reálný a pravdivý. Jak dlouho takové rozpočty uneseme?Hostem Ptám se já byl předseda Národní rozpočtové rady Mojmír Hampl. Zástupci vládní koalice v noci schválili základní parametry návrhu státního rozpočtu na letošní rok se schodkem 310 miliard korun. Příjmy, výdaje, schodek a způsob jeho vypořádání už tedy Sněmovna nemůže měnit. Poslanci nyní mohou navrhovat jen přesuny uvnitř rozpočtu.Opozice rozpočet označila za nezodpovědný a v rozporu se zákonem o pravidlech rozpočtové odpovědnosti. Opírá se přitom o stanovisko Národní rozpočtové rady (NRR). Pochybnosti vyjádřil i prezident Petr Pavel. Ministryně financí Alena Schillerová (ANO) to odmítá a trvá na tom, že tato pravidla se na její rozpočet kvůli mimořádným okolnostem nevztahují. V posledních dnech několikrát zopakovala, že rozpočet je realistický a pravdivý. S předsedou sněmovního rozpočtového výboru Vladimírem Pikorou (Motoristé) se shodla, že navržený schodek je maximum možného. „Rozhodně jedeme rozpočet, který je na Stanjurově podvozku,“ řekl Pikora s odkazem na předchozího šéfa státní kasy Zbyňka Stanjuru (ODS). „Záleží na tom, jestli bude vláda chtít přidávat nějaké výdaje v průběhu roku. Tohle riziko si člověk uvědomí, když jsme se dozvěděli, že Ministerstvo práce a sociálních věcí chce otevřít zákon o důchodovém pojištění. Chce nejen upravovat parametry důchodového systému, které byly řečeny před volbami. Ale je tam něco, co nás znervózňuje. To znamená, že to má proběhnout rychle a mají tam být nějaké změny už od září letošního roku. Nevíme jaké. Tak pak by byla otázka, jak by se financovaly, jestli by ten problém nebyl větší,“ řekl v Ptám se já předseda Národní rozpočtové rady Mojmír Hampl. Že by státní rozpočet na letošní rok odporoval zákonu o rozpočtové odpovědnosti popřel i premiér Andrej Babiš (ANO) už v sobotním rozhovoru pro televizi Nova, kde odmítl stanovisko Národní rozpočtové rady a označil ji za zbytečnou instituci.„My jsme zřízeni zákonem. Tím zákonem o pravidlech rozpočtové odpovědnosti. Teoreticky by někdo mohl i ten zákon zrušit, byť z našeho pohledu by to bylo v jasném rozporu s evropským právem, které platí. Neexistuje žádná země v Evropské unii, která by něco takového udělala, dokonce ani Orbánovo Maďarsko rozpočtovou radu nezrušilo,“ uzavřel Hampl. Jak se neztratit v číslech a politických proklamacích? Jaký je rozpočet nové vlády? A na co si musíme v příštích letech dát největší pozor?--Podcast Ptám se já. Rozhovory s lidmi, kteří mají vliv, odpovědnost, informace.Sledujte na Seznam Zprávách, poslouchejte na Podcasty.cz a ve všech podcastových aplikacích.Archiv všech dílů najdete tady. Své postřehy, připomínky nebo tipy nám pište prostřednictvím sociálních sítí pod hashtagem #ptamseja nebo na e-mail: audio@sz.cz.

Today I'm joined by Stephanie Blair, Founder of Know & Flourish (https://knowandflourish.com/), for a practical conversation on digital career growth in Customer Success. We dig into how to build a career identity (not just a title), why experimentation matters, and how to expand your lane without burning out. You'll hear a real-world example from my team of turning a scrappy spreadsheet into a lightweight web tool, and what that kind of initiative can do for your brand inside the business.We also talk about the shift in CS org design: the rise of digital program managers, AI-assisted workflows, and yes - why human, IRL moments still win renewals. If you're exploring a pivot into CS (from sales/marketing/product) or within CS (service → expansion, or IC → leader), Stephanie breaks down how to translate your skills, control your narrative, and interview like a peer.Housekeeping: I'll be co-chairing the CS Summit in Austin later this month, and the Digital CX Masterclass is coming soon join the waitlist at https://DigitalCustomerSuccess.com/Masterclass to be first in line. Support the show+++++++++++++++++Like/Subscribe/Review:If you are getting value from the show, please follow/subscribe so that you don't miss an episode and consider leaving us a review. Website:For more information about the show or to get in touch, visit DigitalCustomerSuccess.com. Buy Alex a Cup of Coffee:This show runs exclusively on caffeine - and lots of it. If you like what we're, consider supporting our habit by buying us a cup of coffee: https://bmc.link/dcspThank you for all of your support!The Digital Customer Success Podcast is hosted by Alex Turkovic

Novou ekonomickou strategii vlády poodhalil na TV Nova premiér Babiš, když řekl, že Česká republika je ještě málo zadlužená, a navrhl zrušit Národní rozpočtovou radu (NRR), která ze zákona dohlíží na fiskální politiku vlády. Dodejme, že to byl sám Andrej Babiš, který zákonem z roku 2017 o rozpočtové odpovědnosti tuto instituci zřídil. Za Fialovy vlády to byla právě NRR v čele s Mojmírem Hamplem, která nejvíce kritizovala rozpočtové přeslapy ministra financí Stanjury. Vycházel přitom ze zákona, který jasně určuje mantinely rozpočtové odpovědnosti. Je příznačné, že nejnadšenější čtenářkou analýz NRR byla právě Alena Schillerová. Dnes, kdy se dostala do vlády, nejen její šéf, ale i její náměstek Petr Mach volají po jejím zrušení. Připomíná to situaci, kdy někdo ve fotbale oznamuje, že když se zruší rozhodčí, vyhnou se obě mužstva pískání ofsajdů. Problém je, že šéf NRR Hampl řekl na adresu zákona o státním rozpočtu na rok 2026 zhruba toto: „Tak, jak nová vláda nastavila parametry tohoto zákona, jde o nelegální postup, který je v rozporu se zákonem o rozpočtové odpovědnosti.“ Otázkou je, je dostatečná autorita na to, aby vládě řekl: „Tudy cesta nevede.“ Takže co dělat, když jsou Babišovi voliči zřejmě spokojeni, ale je to v rozporu se zákonem? Zrušíme tedy zákon a s ním i Národní rozpočtovou radu, navrhuje Babiš. Připomíná to perského krále, který zabíjel posly špatných zpráv. Andreji Babišovi ani nic jiného nezbyde, protože on i ministryně financí se pokoušejí o zvláštní voodoo ekonomickou strategii. Jinak řečeno, chtějí snižovat daně (firemní), chtějí zvyšovat sociální dávky a důchody a zároveň musí dodržovat zákon o rozpočtové odpovědnosti, který sám Andrej Babiš jako ministr financí přijal. Neexistuje způsob, jak dodržet jedno nebo druhé. Vlastně ano, existuje. Mohou zkusit se magicky zaříkávat a do zmenšeniny Mojmíra Hampla píchat jehličky v naději, že změní jeho postoje. A když ne, tak ho zrušíme.

We explore how intelligent gifting breaks through AI-filtered inboxes, using psychology, data, and timing to earn real conversations and long-term loyalty. Kris Rudeegraap of Sendoso shares playbooks for stage-based sends, retention strategies, and staying human in an agentic future.• reciprocity, curiosity and tangible novelty driving attention• AI-assisted personalization for interests, timing and delivery channel• stage-based guardrails that unlock premium sends mid-funnel• timely low-cost sends outperforming expensive but irrelevant gifts• CAC, velocity and opportunity cost framing for ROI• shifting marketing metrics toward revenue and NRR• proving value when users never log into your app• human-in-the-loop creativity to avoid AI cringe• retention and expansion use cases for customer successA box at your door still beats the smartest subject line, sparks genuine conversations, and accelerates pipeline without feeling transactional. Kris blends a decade of logistics, a modern data engine, and a human-first ethos to explain why clever, timely sends often outperform expensive swag—and how to scale that tastefulness with AI.We dig into the psychology behind physical sending—reciprocity, curiosity, and the emotional lift of a tangible, personalized moment—and translate it into practical plays for sales, marketing, and customer success. You'll hear how stage-based guardrails in your CRM can unlock premium sends mid-funnel, why delivery confidence (home versus office) matters post‑COVID, and how small, useful gestures—like a rideshare credit on conference day—drive replies that mass email can't. Kris also shares how Sendoso is evolving from pure logistics to a data-rich recommendation layer that helps teams decide what to send, when to send, and where to deliver.We also explore the agentic future: AI agents summarizing inboxes, go‑to‑market engineers orchestrating workflows, and the reality that a human still signs the contract. Kris offers a candid view on pricing models, proving ROI when users never log into your app, and why NRR and expansion deserve a bigger share of marketing's attention. If you're ready to replace noise with nuance—earning meetings faster and strengthening renewals through meaningful touchpoints—this conversation gives you the framework and the guardrails to do it right.Kris Rudeegraap:  https://www.linkedin.com/in/rudeegraap/Kris Rudeegraap, the Co-Founder and Co-CEO of Sendoso, the leading Direct Mail and Gifting Platform which has seen over $250M+ spent on the platform globally.  A self-described "Sales CEO" who is redefining how B2B companies cut through the digital noise to build authentic relationships,  Before founding Sendoso, he was a top-performing Account Executive at Talkdesk and a founding team member at Piqora.  Kris is a California native, an alumnus of California State University, Chico and currently resides in the San Francisco Bay Area.Website: https://www.position2.com/podcast/Rajiv Parikh: https://www.linkedin.com/in/rajivparikh/Sandeep Parikh: https://www.instagram.com/sandeepparikh/Email us with any feedback for the show: sparkofages.podcast@position2.com

In this episode of Nashville Restaurant Radio, we sit down with Jessica Hazard, Owner of NY Pie, to unpack what it really takes to grow a local restaurant brand in a competitive market.Jessica walks us through each of NY Pie's three Nashville locations, sharing how every neighborhood brings its own challenges, opportunities, and lessons. We talk candidly about expansion—what went right, what was harder than expected, and how she's preparing for her newest location opening this spring in Capitol View.If you're an operator thinking about growth, this is a real-world look at scaling without losing your soul.This episode also marks a big milestone for NRR as we welcome Jim Myers as our new host. Jim takes the reins for the first time, bringing decades of experience as Nashville's former food critic and longtime food writer for The Tennessean. His industry insight, curiosity, and deep connection to the local food scene make him a powerful addition to the show.Whether you're a restaurant owner, aspiring entrepreneur, or just someone who loves Nashville's food scene, this conversation delivers practical insight, honest perspective, and a preview of what's next for one of the city's homegrown favorites.

Signup for RevUP Academy: https://www.thecustomersuccesspro.com/revupIn this episode of the Customer Success Pro Podcast, host Anika Zubair sits down with Emma Lambert, VP of Customer Success at Ably, to discuss the critical role of customer success in driving revenue. They explore how to turn renewals into predictable revenue forecasts, the importance of understanding customer engagement, and the strategies for effective upselling. Emma shares her insights on building a revenue-focused customer success team, the significance of financial literacy, and the necessity of asking direct questions during customer interactions. The conversation emphasizes the need for a structured approach to renewals and upsells, integrating them into a cohesive NRR strategy, and the value of continuous discovery throughout the customer journey.Chapters:00:00 Introduction 03:00 The Role of Customer Success in Revenue Generation05:55 Understanding Customer Engagement and Value Delivery09:06 The Importance of Forecasting in Customer Success12:10 Navigating the Commercial Landscape of Customer Success15:02 Building a Revenue-Focused Customer Success Team18:10 The Six-Month Renewal Framework21:10 Asking the Right Questions for Renewals24:09 Upselling Strategies in Customer Success26:55 Integrating Renewals and Upsells into NRR Strategy30:02 Best Practices for Revenue-Focused Customer Success32:56 Quick Fire Questions with Emma LambertConnect with Anika Zubair:Website: ⁠https://thecustomersuccesspro.com/⁠LinkedIn:  ⁠https://www.linkedin.com/in/anikazubair/⁠RevUP Academy: ⁠https://thecustomersuccesspro.com/revup⁠Connect with Emma Lampert: https://www.linkedin.com/in/emmalampert/Grab our FREE resources here: ⁠https://thecustomersuccesspro.com/resources⁠Want to be our next podcast guest? Apply here: ⁠https://www.thecustomersuccesspro.com/podcast-guest⁠Book Anika as a speaker at your next team event: ⁠https://www.thecustomersuccesspro.com/team-event

Jason Cohen is a four-time founder (including two unicorns, one being WP Engine) and an investor in over 60 startups, and has been sharing his lessons on company building at A Smart Bear for nearly 20 years. In this episode, Jason shares his methodical five-step framework for diagnosing stalled growth—a problem that faces almost every team.We discuss:1. Jason's five-step framework: logo retention, pricing, NRR, marketing channels, target market2. A small tweak that'll double response rates on your cancellation surveys3. Why “it's too expensive” is almost never the real reason customers cancel4. The “elephant curve” of growth5. How repositioning the same product can increase revenue 8x6. When to reconsider if growth is even the right goal for your business—Brought to you by:10Web—Vibe coding platform as an APIStrella—The AI-powered customer research platformBrex—The banking solution for startups—Episode transcript: https://www.lennysnewsletter.com/p/why-your-product-stopped-growing—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Jason Cohen:• Preorder Jason's book: https://preorder.hiddenmultipliers.com/• X: https://x.com/asmartbear• LinkedIn: https://www.linkedin.com/in/jasoncohen• Blog: https://longform.asmartbear.com• Website: https://wpengine.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Jason Cohen(05:19) Jason's writing journey(08:25) Questions to ask when your product stops growing(18:17) Getting real customer feedback(20:27) Analyzing cancellation reasons(26:54) Onboarding and activation(29:35) Quick summary(35:46) Revisiting pricing strategies(41:46) Positioning strategies(47:52) Why pricing is inseparable from your strategy(52:06) The importance of net revenue retention (NRR)(01:00:25) Asking whether or not this is good for the customer(01:04:34) Leveraging existing customers(01:06:42) Are your acquisition channels saturated? The “elephant curve”(1:09:41) Why all marketing channels eventually decline(01:12:04) Direct vs. indirect marketing channels(1:13:36) Getting creative with new channels(01:19:04) Do you actually need to grow?(01:25:57) Deciding when to quit(01:29:27) Book announcement(01:33:21) AI corner(01:34:35) Contrarian corner(01:37:43) Lightning round and final thoughts—Referenced:• Tyler Cowen's website: https://tylercowen.com• How to Perform a Customer Churn Analysis (and Why You Should): https://www.groovehq.com/blog/learn-from-customer-churn• Linear: https://linear.app• Jira: https://www.atlassian.com/software/jira• Patrick Campbell's post on X about pricing: https://x.com/Patticus/status/1702313260547006942• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/the-art-and-science-of-pricing-madhavan• Pricing your AI product: Lessons from 400+ companies and 50 unicorns | Madhavan Ramanujam: https://www.lennysnewsletter.com/p/pricing-and-scaling-your-ai-product-madhavan-ramanujam• Pricing your SaaS product: https://www.lennysnewsletter.com/p/saas-pricing-strategy• M&A, competition, pricing, and investing | Julia Schottenstein (dbt Labs): https://www.lennysnewsletter.com/p/m-and-a-competition-pricing-and-investing• “Sell the alpha, not the feature”: The enterprise sales playbook for $1M to $10M ARR | Jen Abel: https://www.lennysnewsletter.com/p/the-enterprise-sales-playbook-1m-to-10m-arr• Buffer: https://buffer.com• AG1: https://drinkag1.com• How to find hidden growth opportunities in your product | Albert Cheng (Duolingo, Grammarly, Chess.com): https://www.lennysnewsletter.com/p/how-to-find-hidden-growth-opportunities-albert-cheng• How Duolingo reignited user growth: https://www.lennysnewsletter.com/p/how-duolingo-reignited-user-growth• The Elephant in the room: The myth of exponential hypergrowth: https://longform.asmartbear.com/exponential-growth• HubSpot: https://www.hubspot.com• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Adjacency Matrix: How to expand after PMF: https://longform.asmartbear.com/adjacency/• Ecosystem is the next big growth channel: https://www.lennysnewsletter.com/p/ecosystem-is-the-next-big-growth• ChatGPT apps are about to be the next big distribution channel: Here's how to build one: https://www.lennysnewsletter.com/p/chatgpt-apps-are-about-to-be-the• 10 contrarian leadership truths every leader needs to hear | Matt MacInnis (Rippling): https://www.lennysnewsletter.com/p/10-contrarian-leadership-truths• Breaking the rules of growth: Why Shopify bans KPIs, optimizes for churn, prioritizes intuition, and builds toward a 100-year vision | Archie Abrams (VP Product, Head of Growth at Shopify): https://www.lennysnewsletter.com/p/shopifys-growth-archie-abrams• Geoffrey Moore on finding your beachhead, crossing the chasm, and dominating a market: https://www.lennysnewsletter.com/p/geoffrey-moore-on-finding-your-beachhead• ER on Prime Video: https://www.amazon.com/ER-Season-1/dp/B0FWK5WJQ4• The Pitt on Prime Video: https://www.amazon.com/The-Pitt-Season-1/dp/B0DNRR8QWD• Wispr Flow: https://wisprflow.ai• Anker: https://www.anker.com—Recommended books:• Will: https://www.amazon.com/Will-Smith/dp/1984877925• Monetizing Innovation: How Smart Companies Design the Product Around the Price: https://www.amazon.com/Monetizing-Innovation-Companies-Design-Product/dp/1119240867• Hidden Multipliers: Small Things That Accelerate Growth: https://preorder.hiddenmultipliers.com• On Writing Well: The Essential Guide to Mastering Nonfiction Writing and Effective Communication: https://www.amazon.com/Writing-Well-Classic-Guide-Nonfiction/dp/0060891548• Crossing the Chasm, 3rd Edition: The Updated Version of the Insightful Guide on Bringing Cutting-Edge Products to the Mainstream: https://www.amazon.com/Crossing-Chasm-3rd-Disruptive-Mainstream/dp/0062292986—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Today on the show, we have Matthew Tharp, CEO of Hunter.io, the all-in-one email outreach platform used by over 4 million people to identify prospects and run cold email campaigns. Previously, Matthew was VP of Worldwide Retention at LogMeIn, where he owned NRR across nine products—giving him a rare masterclass in retention challenges at different stages and scales.In this episode, we uncover why retention isn't a problem you solve when growth stalls—it's DNA you build from day one. Matthew shares the paradox of his career: building a company with 95%+ annual retention that got acquired, versus joining a high-growth PLG business with churn issues that needed solving before scaling further.We explore why over-indexing on either growth or retention creates problems, how to identify the usage patterns that predict churn in the first three weeks, and why every company that tries to fix retention late struggles. The lesson: balance from the beginning beats transformation later.We also discuss how Hunter achieved 3X growth this year by going back to basics—running a rigorous ICP analysis, choosing battles they could win instead of markets where competitors were spending $100M, and layering new customer segments without creating product bloat.Finally, we dig into cold outreach data: why email lists under 100 people dramatically outperform larger ones, why shorter emails force the clarity that drives replies, and how constraints—not scale—are the real performance lever in outbound.As always, I'd love to hear from you. You can email me directly at andrew@churn.fm, and don't forget to follow us on X.Churn FM is sponsored by Vitally, the all-in-one Customer Success Platform.

Parable is building an end-to-end intelligence platform that quantifies how organizations spend their collective time—the foundation for measuring real AI impact. With a thousand data connectors ingesting activity and log data across the enterprise software stack, Parable constructs proprietary knowledge graphs that size opportunities and measure outcomes in hard dollars, not adoption metrics. In this episode of BUILDERS, I sat down with Adam Schwartz, Co-Founder & CEO of Parable, to explore why 95% of CFOs see no AI ROI, how his decade running profitable businesses under resource constraints shaped his focus on inputs over outcomes, and why 2026 requires moving AI from CapEx experimentation to measured OpEx. Topics Discussed: Why the 95% CFO stat on AI ROI matters as an arbiter of truth, despite backlash Building knowledge graphs from activity data to quantify collective time allocation across hundreds of people The fundamental problem: enterprises lack quantitative frameworks for operational efficiency pre-AI Running parallel ICP experiments to achieve sales-market fit before product-market fit Why Parable has never lost a POC once leaders see quantitative baselines Market dynamics creating false signals—unprecedented curiosity without buying intent The demarcation between companies treating AI as product work versus those waiting for vendor solutions Why AI transformation demands century-old management structures to be questioned GTM Lessons For B2B Founders: Engineer disqualification in momentum markets: Market-wide AI enthusiasm creates pipeline illusion. Prospects will engage indefinitely for education without purchase intent. Adam's framework: "How do we get people to say no to us and not drag us along... They want to keep talking because they want to learn and they want to know what's going on and they are genuinely interested." In enterprise sales during category shifts, build explicit qualification gates that force prospects to reveal resource commitment or disqualify. Extended evaluation cycles feel like traction but destroy unit economics. Use go-to-market as ICP discovery mechanism: Adam intentionally pursued multiple customer segments simultaneously—different company sizes and AI maturity stages—to let data reveal fit rather than rely on hypothesis. His memo to the team: "We're going to go after these three, you know, many different sizes of companies in order for us to decide like, who we like best." The key insight: get to problem-market fit and sales-market fit validation before optimizing product-market fit. This inverts conventional wisdom but works when TAM is massive and the bottleneck is identifying who feels pain acutely enough to buy now. Qualify on organizational structure, not verbal commitment: Every enterprise claims AI is strategic. Adam's hard filter: "Who in the organization is responsible for AI transformation? And if you don't have a one person answer to that question, you're not serious." Serious buyers have a named owner reporting to C-suite with dedicated budget and team. Buying Gemini, Glean, or other point solutions isn't a seriousness KPI—it's often passive consumption of AI as a byproduct of existing software relationships. Look for companies doing five-year work-backs on industry transformation and cascading effects on their operating model. Target post-experimentation, pre-scale buyers: Adam discovered the sweet spot isn't companies beginning their AI journey—it's those who've deployed initial programs and now need to prove value. "The market of people that have started to build AI into their operating model or into their strategy in like a coherent way, there's a team, there's an owner, there's budget... those are the people that we really want to be talking to." These buyers understand the problem viscerally because they're living it. They do product work daily—talking to stakeholders, generating use cases, building briefs, triaging roadmaps. They need your solution to professionalize what they're already attempting manually. Build measurement into your category narrative: The AI tooling market has over-indexed on soft efficiency claims that won't survive renewal cycles. Adam's warning: "There is too much hand waving around soft efficiency gains... you're going to have to renew and you need NRR and I don't think it's going to be that usage of the tool internally by employees and adoption is going to be enough." The last decade over-rotated to "everything drives revenue" due to VC pressure. This decade requires precision: does your product save time, reduce headcount needs, or accelerate revenue? Quantify it. Partner with measurement platforms if needed. Adam's insight on Calendly is instructive—it clearly saves time, but most buyers can't quantify how much, which weakens renewal economics. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Neste episódio, Paulo Chiodi conversa com Nicole Grossman sobre sua trajetória no mundo das startups e a influência da inteligência artificial no mercado. Nicole compartilha suas experiências desde a formação em engenharia até a construção de produtos inovadores, discutindo os desafios enfrentados em cada estágio de desenvolvimento. A conversa também aborda a importância da experiência do usuário, as métricas essenciais para startups e os conselhos para mulheres na tecnologia.LinkedIn da Nicole: https://www.linkedin.com/in/nicolegrossmann/Texto sobre Builder.AI: https://www.productgurus.com.br/p/o-colapso-da-builderai-e-o-fim-de?r=2jz3x1Texto sobre $400 doláres por usuário: https://www.productgurus.com.br/p/a-conta-dos-400-dolares-para-a-bolha?r=2jz3x1Tópicos PrincipaisNicole começou sua carreira em engenharia e se tornou programadora.O estágio zero para um é desafiador, mas o um para dez também.A inteligência artificial está transformando a eficiência em várias áreas.Existem pressões diferentes em cada estágio de crescimento de uma startup.A integração de IA em produtos traz desafios significativos.A experiência do usuário deve ser priorizada no design de produtos com IA.Métricas como NRR são cruciais para entender a retenção de clientes.A monetização de funcionalidades de IA é complexa e variável.A educação e a formação contínua são essenciais para o sucesso na tecnologia.Mulheres na tecnologia devem se apoiar e buscar oportunidades. Capítulos00:00 Introdução ao Podcast e Apresentação de Nicole02:47 Entendendo o Conceito de 'Zero pra Um'05:14 Inteligência Artificial e Eficiência em Startups08:07 A Bolha da Inteligência Artificial10:27 Desafios da Integração da IA Generativa13:22 Construindo um Roadmap de Produto com IA16:17 Erros Comuns na Experiência do Usuário com IA26:19 Interação Humano-Computador e IA29:47 Construindo um Pitch Convincente35:14 Métricas e KPIs em Startups40:01 Precificação de Produtos com IA45:20 Desafios e Oportunidades para Mulheres em Tecnologia

Why Customer Success Can't Be Automated (And What AI Can Actually Do) In this special year-end episode of the FutureCraft GTM Podcast, hosts Ken Roden and Erin Mills sit down with Amanda Berger, Chief Customer Officer at Employ, to tackle the biggest question facing CS leaders in December 2026: What can AI actually do in customer success, and where do humans remain irreplaceable? Amanda brings 20+ years at the intersection of data and human decision-making—from AI-powered e-commerce personalization at Rich Relevance, to human-led security at HackerOne, to now implementing AI companions for recruiters. Her journey is a masterclass in understanding where the machine ends and the human begins. This conversation delivers hard truths about metrics, change management, and the future of CS roles—plus Amanda's controversial take that "if you don't use AI, AI will take your job." Unpacking the Human vs. Machine Balance in Customer Success Amanda returns with a reality check: AI doesn't understand business outcomes or motivation—humans do. She reveals how her career evolved from philosophy major studying "man versus machine" to implementing AI across radically different contexts (e-commerce, security, recruiting), giving her unique pattern recognition about what AI can genuinely do versus where it consistently fails. The Lagging Indicator Problem: Why NRR, churn, and NPS tell you what already happened (6 months ago) instead of what you can influence. Amanda makes the case for verified outcomes, leading indicators, and real-time CSAT at decision points. The 70% Rule for CS in Sales: Why most churn starts during implementation, not at renewal—and exactly when to bring CS into the deal to prevent it (technical win stage/vendor of choice). Segmentation ≠ Personalization: The jumpsuit story that proves AI is still just sophisticated bucketing, even with all the advances in 2026. True personalization requires understanding context, motivation, and individual goals. The Delegation Framework: Don't ask "what can AI do?" Ask "what parts of my job do I hate?" Delegate the tedious (formatting reports, repetitive emails, data analysis) so humans can focus on what makes them irreplaceable. Timestamps 00:00 - Introduction and AI Updates from Ken & Erin 01:28 - Welcoming Amanda Berger: From Philosophy to Customer Success 03:58 - The Man vs. Machine Question: Where AI Ends and Humans Begin 06:30 - The Jumpsuit Story: Why AI Personalization Is Still Segmentation 09:06 - Why NRR Is a Lagging Indicator (And What to Measure Instead) 12:20 - CSAT as the Most Underrated CS Metric 17:34 - The $4M Vulnerability: House Security Analogy for Attribution 21:15 - Bringing CS Into Sales at 70% Probability (The Non-Negotiable) 25:31 - Getting Customers to Actually Tell You Their Goals 28:21 - AI Companions at Employ: The Recruiting Reality Check 32:50 - The Delegation Mindset: What Parts of Your Job Do You Hate? 36:40 - Making the Case for Humans in an AI-First World 40:15 - The Framework: When to Use Digital vs. Human Touch 43:10 - The 8-Hour Workflow Reduced to 30 Minutes (Real ROI Examples) 45:30 - By 2027: The Hardest CX Role to Hire 47:49 - Lightning Round: Summarization, Implementation, Data Themes 51:09 - Wrap-Up and Key Takeaways Edited Transcript Introduction: Where Does the Machine End and Where Does the Human Begin? Erin Mills: Your career reads like a roadmap of enterprise AI evolution—from AI-powered e-commerce personalization at Rich Relevance, to human-powered collective intelligence at HackerOne, and now augmented recruiting at Employ. This doesn't feel random—it feels intentional. How has this journey shaped your philosophy on where AI belongs in customer experience? Amanda Berger: It goes back even further than that. I started my career in the late '90s in what was first called decision support, then business intelligence. All of this is really just data and how data helps humans make decisions. What's evolved through my career is how quickly we can access data and how spoon-fed those decisions are. Back then, you had to drill around looking for a needle in a haystack. Now, does that needle just pop out at you so you can make decisions based on it? I got bit by the data bug early on, realizing that information is abundant—and it becomes more abundant as the years go on. The way we access that information is the difference between making good business decisions and poor business decisions. In customer success, you realize it's really just about humans helping humans be successful. That convergence of "where's the data, where's the human" has been central to my career. The Jumpsuit Story: Why AI Personalization Is Still Just Segmentation Ken Roden: Back in 2019, you talked about being excited for AI to become truly personal—not segment-based. Flash forward to December 2026. How close are we to actual personalization? Amanda Berger: I don't think we're that close. I'll give you an example. A friend suggested I ask ChatGPT whether I should buy a jumpsuit. So I sent ChatGPT a picture and my measurements. I'm 5'2". ChatGPT's answer? "If you buy it, you should have it tailored." That's segmentation, not personalization. "You're short, so here's an answer for short people." Back in 2019, I was working on e-commerce personalization. If you searched for "black sweater" and I searched for "black sweater," we'd get different results—men's vs. women's. We called it personalization, but it was really segmentation. Fast forward to now. We have exponentially more data and better models, but we're still segmenting and calling it personalization. AI makes segmentation faster and more accessible, but it's still segmentation. Erin Mills: But did you get the jumpsuit? Amanda Berger: (laughs) No, I did not get the jumpsuit. But maybe I will. The Philosophy Degree That Predicted the Future Erin Mills: You started as a philosophy major taking "man versus machine" courses. What would your college self say? And did philosophy prepare you in ways a business degree wouldn't have? Amanda Berger: I actually love my philosophy degree because it really taught me to critically think about issues like this. I don't think I would have known back then that I was thinking about "where does the machine end and where does the human begin"—and that this was going to have so many applicable decision points throughout my career. What you're really learning in philosophy is logical thought process. If this happens, then this. And that's fundamentally the foundation for AI. "If you're short, you should get your outfit tailored." "If you have a customer with predictive churn indicators, you should contact that customer." It's enabling that logical thinking at scale. The Metrics That Actually Matter: Leading vs. Lagging Indicators Erin Mills: You've called NRR, churn rate, and NPS "lagging indicators." That's going to ruffle boardroom feathers. Make the case—what's broken, and what should we replace it with? Amanda Berger: By the time a customer churns or tells you they're gonna churn, it's too late. The best thing you can do is offer them a crazy discount. And when you're doing that, you've already kind of lost. What CS teams really need to be focused on is delivering value. If you deliver value—we all have so many competing things to do—if a SaaS tool is delivering value, you're probably not going to question it. If there's a question about value, then you start introducing lower price or competitors. And especially in enterprise, customers decide way, way before they tell you whether they're gonna pull the technology out. You usually miss the signs. So you've gotta look at leading indicators. What are the signs? And they're different everywhere I've gone. I've worked for companies where if there's a lot of engagement with support, that's a sign customers really care and are trying to make the technology work—it's a good sign, churn risk is low. Other companies I've worked at, when customers are heavily engaged with support, they're frustrated and it's not working—churn risk is high. You've got to do the work to figure out what those churn indicators are and how they factor into leading indicators: Are they achieving verified outcomes? Are they healthy? Are there early risk warnings? CSAT: The Most Underrated Metric Ken Roden: You're passionate about customer satisfaction as a score because it's granular and actionable. Can you share a time where CSAT drove a change and produced a measurable business result? Amanda Berger: I spent a lot of my career in security. And that's tough for attribution. In e-commerce, attribution is clear: Person saw recommendations, put them in cart, bought them. In hiring, their time-to-fill is faster—pretty clear. But in security, it's less clear. I love this example: We all live in houses, right? None of our houses got broken into last night. You don't go to work saying, "I had such a good night because my house didn't get broken into." You just expect that. And when your house didn't get broken into, you don't know what to attribute that to. Was it the locked doors? Alarm system? Dog? Safe neighborhood? That's true with security in general. You have to really think through attribution. Getting that feedback is really important. In surveys we've done, we've gotten actionable feedback. Somebody was able to detect a vulnerability, and we later realized it could have been tied to something that would have cost $4 million to settle. That's the kind of feedback you don't get without really digging around for it. And once you get that once, you're able to tie attribution to other things. Bringing CS Into the Sales Cycle: The 70% Rule Erin Mills: You're a religious believer in bringing CS into the sales cycle. When exactly do you insert CS, and how do you build trust without killing velocity? Amanda Berger: With bigger customers, I like to bring in somebody from CX when the deal is at the technical win stage or 70% probability—vendor of choice stage. Usually it's for one of two reasons: One: If CX is gonna have to scope and deliver, I really like CX to be involved. You should always be part of deciding what you're gonna be accountable to deliver. And I think so much churn actually starts to happen when an implementation goes south before anyone even gets off the ground. Two: In this world of technology, what really differentiates an experience is humans. A lot of our technology is kind of the same. Competitive differentiation is narrower and narrower. But the approach to the humans and the partnership—that really matters. And that can make the difference during a sales cycle. Sometimes I have to convince the sales team this is true. But typically, once I'm able to do that, they want it. Because it does make a big difference. Technology makes us successful, but humans do too. That's part of that balance between what's the machine and what is the human. The Art of Getting Customers to Articulate Their Goals Ken Roden: One challenge CS teams face is getting customers to articulate their goals. Do customers naturally say what they're looking to achieve, or do you have a process to pull it out? Amanda Berger: One challenge is that what a recruiter's goal is might be really different than what the CFO's goal is. Whose outcome is it? One reason you want to get involved during the sales cycle is because customers tell you what they're looking for then. It's very clear. And nothing frustrates a company more than "I told you that, and now you're asking me again? Why don't you just ask the person selling?" That's infuriating. Now, you always have legacy customers where a new CSM comes in and has to figure it out. Sometimes the person you're asking just wants to do their job more efficiently and can't necessarily tie it back to the bigger picture. That's where the art of triangulation and relationships comes in—asking leading discovery questions to understand: What is the business impact really? But if you can't do that as a CS leader, you probably won't be successful and won't retain customers for the long term. AI as Companion, Not Replacement: The Employ Philosophy Erin Mills: At Employ, you're implementing AI companions for recruiters. How do you think about when humans are irreplaceable versus when AI should step in? Amanda Berger: This is controversial because we're talking about hiring, and hiring is so close to people's hearts. That's why we really think about companions. I earnestly hope there's never a world where AI takes over hiring—that's scary. But AI can help companies and recruiters be more efficient. Job seekers are using AI. Recruiters tell me they're getting 200-500% more applicants than before because people are using AI to apply to multiple jobs quickly or modify their resumes. The only way recruiters can keep up is by using AI to sort through that and figure out best fits. So AI is a tool and a friend to that recruiter. But it can't take over the recruiter. The Delegation Framework: What Do You Hate Doing? Ken Roden: How do you position AI as companion rather than threat? Amanda Berger: There's definitely fear. Some is compliance-based—totally justifiable. There's also people worried about AI taking their jobs. I think if you don't use AI, AI is gonna take your job. If you use AI, it's probably not. I've always been a big fan of delegation. In every aspect of my life: If there's something I don't want to do, how can I delegate it? Professionally, I'm not very good at putting together beautiful PowerPoint presentations. I don't want to do it. But AI can do that for me now. Amazingly well. What I'm really bad at is figuring out bullets and formatting. AI does that. So I think about: What are the things I don't want to do? Usually we don't want to do the things we're not very good at or that are tedious. Use AI to do those things so you can focus on the things you're really good at. Maybe what I'm really good at is thinking strategically about engaging customers or articulating a message. I can think about that, but AI can build that PowerPoint. I don't have to think about "does my font match here?" Take the parts of your job that you don't like—sending the same email over and over, formatting things, thinking about icebreaker ideas—leverage AI for that so you can do those things that make you special and make you stand out. The people who can figure that out and leverage it the right way will be incredibly successful. Making the Case to Keep Humans in CS Ken Roden: Leaders face pressure from boards and investors to adopt AI more—potentially leading to roles being cut. How do you make the case for keeping humans as part of customer success? Amanda Berger: AI doesn't understand business outcomes and motivation. It just doesn't. Humans understand that. The key to relationships and outcomes is that understanding. The humanity is really important. At HackerOne, it was basically a human security company. There are millions of hackers who want to identify vulnerabilities before bad actors get to them. There are tons of layers of technology—AI-driven, huge stacks of security technology. And yet no matter what, there's always vulnerabilities that only a human can detect. You want full-stack security solutions—but you have to have that human solution on top of it, or you miss things. That's true with customer success too. There's great tooling that makes it easier to find that needle in the haystack. But once you find it, what do you do? That's where the magic comes in. That's where a human being needs to get involved. Customer success—it is called customer success because it's about success. It's not called customer retention. We do retain through driving success. AI can point out when a customer might not be successful or when there might be an indication of that. But it can't solve that and guide that customer to what they need to be doing to get outcomes that improve their business. What actually makes success is that human element. Without that, we would just be called customer retention. The Framework: When to Use Digital vs. Human Touch Erin Mills: We'd love to get your framework for AI-powered customer experience. How do you make those numbers real for a skeptical CFO? Amanda Berger: It's hard to talk about customer approach without thinking about customer segmentation. It's very different in enterprise versus a scaled model. I've dealt with a lot of scale in my last couple companies. I believe that the things we do to support that long tail—those digital customers—we need to do for all customers. Because while everybody wants human interaction, they don't always want it. Think about: As a person, where do I want to interact digitally with a machine? If it's a bot, I only want to interact with it until it stops giving me good answers. Then I want to say, "Stop, let me talk to an operator." If I can find a document or video that shows me how to do something quickly rather than talking to a human, it's human nature to want to do that. There are obvious limits. If I can change my flight on my phone app, I'm gonna do that rather than stand at a counter. Come back to thinking: As a human, what's the framework for where I need a human to get involved? Second, it's figuring out: How do I predict what's gonna happen with my customers? What are the right ways of looking and saying "this is a risk area"? Creating that framework. Once you've got that down, it's an evolution of combining: Where does the digital interaction start? Where does it stop? What am I looking for that's going to trigger a human interaction? Being able to figure that out and scale that—that's the thing everybody is trying to unlock. The 8-Hour Workflow Reduced to 30 Minutes Erin Mills: You've mentioned turning some workflows from an 8-hour task to 30 minutes. What roles absorbed the time dividend? What were rescoped? Amanda Berger: The roles with a lot of repetition and repetitive writing. AI is incredible when it comes to repetitive writing and templatization. A lot of times that's more in support or managed services functions. And coding—any role where you're coding, compiling code, or checking code. There's so much efficiency AI has already provided. I think less so on the traditional customer success management role. There's definitely efficiencies, but not that dramatic. Where I've seen it be really dramatic is in managed service examples where people are doing repetitive tasks—they have to churn out reports. It's made their jobs so much better. When they provide those services now, they can add so much more value. Rather than thinking about churning out reports, they're able to think about: What's the content in my reports? That's very beneficial for everyone. By 2027: The Hardest CX Role to Hire Erin Mills: Mad Libs time. By 2027, the hardest CX job to hire will be _______ because of _______. Amanda Berger: I think it's like these forward-deployed engineer types of roles. These subject matter experts. One challenge in CS for a while has been: What's the value of my customer success manager? Are they an expert? Or are they revenue-driven? Are they the retention person? There's been an evolution of maybe they need to be the expert. And what does that mean? There'll continue to be evolution on that. And that'll be the hardest role. That standard will be very, very hard. Lightning Round Ken Roden: What's one AI workflow go-to-market teams should try this week? Amanda Berger: Summarization. Put your notes in, get a summary, get the bullets. AI is incredible for that. Ken Roden: What's one role in go-to-market that's underusing AI right now? Amanda Berger: Implementation. Ken Roden: What's a non-obvious AI use case that's already working? Amanda Berger: Data-related. People are still scared to put data in and ask for themes. Putting in data and asking for input on what are the anomalies. Ken Roden: For the go-to-market leader who's not seeing value in AI—what should they start doing differently tomorrow? Amanda Berger: They should start having real conversations about why they're not seeing value. Take a more human-led, empathetic approach to: Why aren't they seeing it? Are they not seeing adoption, or not seeing results? I would guess it's adoption, and then it's drilling into the why. Ken Roden: If you could DM one thing to all go-to-market leaders, what would it be? Amanda Berger: Look at your leading indicators. Don't wait. Understand your customer, be empathetic, try to get results that matter to them. Key Takeaways The Human-AI Balance in Customer Success: AI doesn't understand business outcomes or motivation—humans do. The winning teams use AI to find patterns and predict risk, then deploy humans to understand why it matters and what strategic action to take. The Lagging Indicator Trap: By the time NRR, churn rate, or NPS move, customers decided 6 months ago. Focus on leading indicators you can actually influence: verified outcomes, engagement signals specific to your business, early risk warnings, and real-time CSAT at decision points. The 70% Rule: Bring CS into the sales cycle at the technical win stage (70% probability) for two reasons: (1) CS should scope what they'll be accountable to deliver, and (2) capturing customer goals early prevents the frustrating "I already told your sales rep" moment later. Segmentation ≠ Personalization: AI makes segmentation faster and cheaper, but true personalization requires understanding context, motivation, and individual circumstances. The jumpsuit story proves we're still just sophisticated bucketing, even with 2026's advanced models. The Delegation Framework: Don't ask "what can AI do?" Ask "what parts of my job do I hate?" Delegate the tedious (formatting, repetitive emails, data analysis) so humans can focus on strategy, relationships, and outcomes that only humans can drive. "If You Don't Use AI, AI Will Take Your Job": The people resisting AI out of fear are most at risk. The people using AI to handle drudgery and focusing on what makes them irreplaceable—strategic thinking, relationship-building, understanding nuanced goals—are the future leaders. Customer Success ≠ Customer Retention: The name matters. Your job isn't preventing churn through discounts and extensions. Your job is driving verified business outcomes that make customers want to stay because you're improving their business. Stay Connected To listen to the full episode and stay updated on future episodes, visit the FutureCraft GTM website. Connect with Amanda Berger: Connect with Amanda on LinkedIn Employ Disclaimer: This podcast is for informational and entertainment purposes only and should not be considered advice. The views and opinions expressed in this podcast are our own and do not represent those of any company or business we currently work for/with or have worked for/with in the past.

In this episode of The Metrics Brothers, hosts Ray “Growth” Rike and Dave “CAC” Kellogg provide a critical deep dive into the 2025 SaaS Benchmark Report published by High Alpha. Known for their analytical, and sometimes "crusty" approach, the metrics brothers dissect the data behind 800+ SaaS companies to separate real market trends from report commentary.Key Highlights & BenchmarksThe brothers break down the report's most significant findings with their signature skepticism regarding "correlation vs. causation."The AI Growth Premium: Companies with AI at their core are growing significantly faster than those using AI as a supporting feature. For instance, in the $1–5M ARR band, AI-core companies achieved a median growth of 110%, compared to 40% for their peersThe "Lean Team" Era: Efficiency is surging as headcount falls. Median revenue per employee has jumped to $129K–$173K, with top-tier public companies hitting over $283K. The hosts note that engineering and support have seen the largest headcount reductions due to AI automationVenture Rebound (with a Caveat): While quarterly VC deal value has returned to near 2021 levels (~$80B), the capital is highly concentrated. Over half of all VC funding is currently flowing into AI startups, often in massive "mega-rounds."In-Office vs. Remote: For the second consecutive year, the data suggests that in-office or hybrid teams are growing faster (42% median) than fully remote teams (31% median).As always, Ray and Dave offer practical advice for founders and GTM leaders:"Read the data, but watch out for the commentary." While the data is good, some commentary and conclusions in the report imply causation where there is at best some level of correlation, such as why companies stay private longer or how AI "drives" growth.Retention is King: The strongest growth outcomes are found where high Net Revenue Retention (NRR) meets short CAC payback periods.Outcome-Based Pricing: The brothers highlight the shift toward outcome-based and hybrid pricing models as a primary driver for best-in-class NRR in 2025.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In episode #337 of SaaS Metrics School, Ben breaks down why software revenue categorization is a foundational requirement for strong finance, accounting, and SaaS metrics. He explains the core revenue types every SaaS, AI, or software company should separate on their P&L—and why commingling revenue creates downstream issues in MRR tracking, retention metrics, forecasting, and company valuation. Ben walks through the major recurring and non-recurring revenue categories, then shows how clean revenue segmentation enables accurate MRR schedules, retention analysis, cash flow forecasting, and smoother due diligence with investors and acquirers. What You'll Learn The core revenue categories every SaaS or AI company should clearly define The difference between subscription, usage, overage, services, managed services, and hardware revenue Why overages must be separated at both the SKU and general ledger level How revenue categorization feeds directly into MRR schedules and waterfalls Why recurring and variable revenue must be forecasted differently How clean revenue data improves retention metrics and go-to-market efficiency analysis Why investors and acquirers expect revenue clarity during fundraising and due diligence Why It Matters Accurate MRR and ARR tracking depends on clearly defined revenue streams Retention metrics (GRR and NRR) break when revenue types are mixed together Revenue forecasting and financial modeling require different assumptions by revenue type Cash flow forecasting becomes unreliable without segmented recurring revenue data Company valuation is directly impacted by the perceived quality of recurring revenue Investors and acquirers expect detailed revenue schedules during fundraising and due diligence Strong financial systems and accounting discipline reduce friction in audits and exits Resources Mentioned Ben's SaaS revenue hierarchy framework: https://www.thesaascfo.com/the-saas-revenue-hierarchy-why-defining-your-revenue-streams-matter/ SaaS Metrics course at The SaaS Academy: https://www.thesaasacademy.com/the-saas-metrics-foundation

In this episode of The Metrics Brothers, Ray “Growth” Rike and Dave “CAC” Kellogg take on one of the biggest challenges facing modern SaaS and AI-Native companies: how to measure NRR and expansion when pricing isn't fixed anymore.With the rise of usage-based, user-based-but-variable, and outcome-based pricing, the traditional world of ARR - long the backbone of SaaS metrics has been turned on its head. Contracts no longer tell the story. Spend does.Dave breaks down how to rethink ARR proxies using quarterly or monthly revenue (“implied ARR”) and why longer intervals help smooth volatility, especially for “humpback” or highly seasonal customers whose spend fluctuates dramatically month-to-month.Ray digs into what NRR was originally designed to measure and why many teams misinterpret it—especially in variable-pricing environments where a backward-looking metric can't serve as a forward-looking forecast. The brothers explain why sequential expansion, usage behavior, and real spend patterns now matter far more than traditional ARR bridges.Key topics include:Why ARR no longer maps cleanly to revenue in a variable pricing worldHow to calculate implied ARR using quarterly or monthly software revenueWhy NRR must be interpreted differently—and why survivor bias still mattersHow volatility and seasonality distort short-interval metricsWhy usage is the real leading indicator, not invoicesHow to rethink “expansion ARR” when base + variable spend changes continuouslyPacked with examples, including sinusoidal customers, misleading GRR math, and the dangers of splitting base versus variable revenue, this episode gives operators and investors a practical framework for measuring customer growth when pricing is anything but predictable.A must-listen for CFOs, RevOps leaders, and anyone trying to modernize SaaS metrics for the AI era.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

How will SaaS Companies scale in 2026? The next era of SaaS growth won't be won by adding more reps, more tools, or more noise. In this episode, go-to-market operator Koen Stam (Personio) breaks down why 2026 will mark a decisive shift from people-heavy scaling to process-first, data-driven, efficiency-led growth—and what founders must do now to stay ahead.Koen oversees international revenue operations across Benelux, DACH, the Nordics, Spain, and beyond, and he brings a rare operator's lens to the future of GTM. He unpacks how founder-led, sales-led, and hybrid motions will evolve; why RevOps is about to become one of the most strategic functions in SaaS; and why fixing the data layer is the non-negotiable prerequisite to making AI actually work.You'll learn why the biggest upside in 2026 will come from retention, expansion, and word of mouth, how to design motions that scale with simplicity and discipline, and what it really takes to build from 0 to 10K MRR and to 10M ARR with one product, one audience, and one crystal-clear process.A must-listen for founders, operators, and GTM leaders building for the next wave of SaaS.Key Timecodes(0:00) - Intro: B2B SaaS go-to-market 2026, RevOps, AI, retention, expansion(1:13) - Guest intro: Koen Stam, Personio, international RevOps, HR tech(2:04) - 2026 GTM strategy: process-first, data-driven, efficiency-led growth(2:47) - GTM motions: founder-led vs sales-led vs hybrid, authenticity, efficiency(4:02) - Efficiency in SaaS: bow tie model, customer journey mapping, root causes(5:35) - RevOps priority: data layer, metrics, RevOps to CRO(6:38) - AI in GTM: fix data foundations, process over people(7:26) - Retention & expansion: word-of-mouth, NRR, customer-led growth(9:20) - Sponsor: Reditus affiliate and referral platform for B2B SaaS(10:14) - Word-of-mouth playbook: product value, customer success, community events(12:06) - Build GTM from scratch: founder-led content, AI amplification, simplify(13:59) - Referrals & partners: partner ecosystem, trust, incentives, win-win(15:26) - Zero to 10K MRR: one offer, one ICP, focus, execution(16:54) - Scale to 10M ARR: one product, one market, process-first, data model(17:37) - Connect with Koen: LinkedIn, Substack, AI learnings(17:55) - Audience building: LinkedIn vs Substack, creator-led growth(18:27) - Outro: subscribe, sponsor, Reditus, Grow Your B2B SaaS podcast

Scrappy ABM brings together host Mason Cosby and Yann Sarfati, CEO and Co-founder of Userled, to talk about ABM, AI, field marketing, and events that actually bring the bank. The conversation starts with the problem statement: ABM is a strong buzzword, but finding the accounts you really want to go after is actually the hardest thing. Many teams say they have a narrow ICP and still end up with a list of 10,000 accounts.ㅤYann shares how Userled spent almost six months building a list of 1,000 accounts with clear commonality, strong conviction, and ethical belief that life will be better for those accounts. Mason highlights the mental headache and wasted 10 to 20 hours per bad deal when the ICP is wrong. Together they walk through NRR in MarTech, repeatable GTM motion, small events where the persona actually shows up, personalized event invites, and doing things that do not scale to win enterprise deals and keep customers for the long term.ㅤ

In this episode, "The Metrics Brothers," Growth (Ray Rike) and CAC (Dave Kellogg), dive into a critical challenge for modern SaaS and AI-Native companies: accurately calculating Net Revenue Retention (NRR) in environments that utilize variable pricing models (usage-based, outcome-based, etc.).They begin by defining NRR, emphasizing its importance as a key metric and its high correlation with Enterprise Value-to-Revenue multiples.The brothers then dissect the primary challenge: the absence of traditional Annual Recurring Revenue (ARR) in non-annual contract models. They explore different proxies for ARR, including MRR x 12 and Implied ARR (Quarterly Revenue x 4), and discuss the pitfalls of each, particularly the risk of overstating annual revenue due to seasonality or significant one-time deals.Finally, they offer their preferred, cohort-based method for calculating NRR—the "Snowflake Method" or "Two-Year Look Back"—which compares the current revenue of a specific group of customers (cohort) to their revenue from a year ago. They conclude with a discussion on how this method helps dampen the "noise" and variability inherent in usage-based data when trying to measure expansion and contraction.

How can you effectively prepare your SaaS for an exit? And what should you know about the valuation drivers, buyer types, and metrics that matter most? In a live episode of the Grow Your B2B SaaS podcast recorded at SaaS Summit Benelux, host Joran sat down with René de Jong to unpack what it takes for SaaS companies to scale and prepare for a successful exit in 2026. René helps entrepreneurs—specifically SaaS founders—design effective exit strategies and navigate the full process of selling their businesses to third parties. Across the conversation, he offered clear and pragmatic insights on what separates the SaaS businesses that grow and sell well from those that struggle, how buyers evaluate companies in the current market, and why topics like the rule of 40, net revenue retention, AI-driven scalability, and deal structure matter now more than ever. From early-stage focus at 0 to 10K MRR to strategies for moving toward 10 million ARR, René shared guidance grounded in what he sees every day in the market.This episode turns the full discussion into a clear, actionable narrative that stays true to the original conversation and is easier to follow and revisit.Key Timestamps(0:00) - SaaS Summit Benelux intro, B2B SaaS scaling 2026, Rule of 40, NRR, ARR multiples, Earnouts, Strategic buyers, 0-10K MRR, 10M ARR(0:50) - Guest intro, SaaS M&A advisor, SaaS exit strategy, SaaS acquisition process(1:14) - Scaling your SaaS for 2026(1:20) - What separates SaaS winners in 2026(1:26) - Rule of 40, Efficient growth, ARR multiple valuation(2:18) - Go-to-market strategy, New business team, Net Revenue Retention (NRR), Expense efficiency(3:05) - NRR benchmarks, Churn, Customer concentration, Market standards(4:01) - Efficient growth vs spend, AI scalability, Revenue per employee(5:06) - AI native SaaS costs, VC vs mature SaaS valuation, EBITDA vs ARR(6:38) - VC backing for AI native startups(6:48) - Freemium model 2026, Valuation cycles, EBITDA focus, AI hype, ARR multiples(8:05) - Sponsor: B2B SaaS affiliate marketing, Reditus(8:49) - SaaS valuation benchmarks, ARR multiples range(9:01) - 3.5x ARR cash at close, Earnout, Reinvest, Deal structure(10:34) - Venture capital vs Private equity(10:43) - Strategic buyers, One plus one equals three, Synergy valuation(11:22) - Build list of strategic acquirers, Exit planning(11:29) - Headline valuations vs reality, Purchase price, Earnouts, Deal terms(11:51) - Earnout as bonus, Cash at closing, Burnout risk(13:05) - 2026 growth loop, AI in land and expand, Product-led growth, AI agents(14:10) - 0–10K MRR advice, Founder mindset, Learn fast, Mentors, SaaS community(15:35) - Smart capital, Operator investors, Non-dilutive help(16:06) - 10K MRR to 10M ARR, Focus, Buy-and-build strategy, Autonomous growth, 3–5 year plan(17:43) - Contact info, LinkedIn, anno9082.nl(18:03) - Outro, Subscribe, Sponsor the show, Reditus call-to-action

おはようございます、社長参謀の小島です。今朝のテーマは「顧客の声の『詰まり』を解消する」です。日経MJの記事から、選挙戦で躍進した「パブリックリスニング」という手法を読み解きます。多くの企業が集めた声を「データ」として倉庫に保管し、腐らせてしまっている現状に警鐘を鳴らします。AIは自動化のためではなく、顧客の痛みに「即応」するために使うもの。たった1%の改善が、顧客との信頼関係（NRR）を劇的に変える理由とは？明日から現場で使える「ワン・クエスチョン」の問いかけと共に、泥臭くも温かい事業開発のヒントをお届けします。早朝の10分間、御社の未来を変える戦略会議を始めましょう。#夜明けの戦略会議 #社長参謀 #新規事業 #経営戦略 #顧客の声 #パブリックリスニング #AI活用 #日経MJ #中小企業経営 #事業開発

David Schreiber, ehemals Stripe & Trade Republic, heute Gründer von Duna, spricht über die Kunst der Produktentwicklung. Er teilt, warum europäische und amerikanische Produktphilosophien unterschiedlich sind, wie man zwischen Vision und Pragmatismus balanciert und warum Europa der ideale Standort für komplexe B2B-Infrastruktur ist. Was du lernst: Produktphilosophie Unterschiede zwischen B2C und B2B US vs. EU Denkweisen Vision vs. Pragmatismus Go-to-Market Co-Development als Strategie Die richtigen ersten Kunden Warum Vertrauen entscheidend ist Pricing & Value Business Case basiertes Pricing Success-Based Modelle Wie man NRR richtig denkt Product Market Fit Segmentierung & Geografie Von "Gut genug" zu "Magic" Warum PMF mehrdimensional ist Alles zu Unicorn Bakery: https://stan.store/fabiantausch Mehr zum Gast: LinkedIn: https://www.linkedin.com/in/ds-berlin/ Website: https://duna.com/ Join our Founder Tactics Newsletter: 2x die Woche bekommst du die Taktiken der besten Gründer der Welt direkt ins Postfach: https://www.tactics.unicornbakery.de/ Kapitel: (00:00:00) Intro: Produktentwicklung in der KI-Ära (00:02:12) Was macht ein richtig gutes B2B-Produkt aus? (00:04:44) US vs. Europa: Unterschiedliche Produktphilosophien (00:08:23) Von der Vision zur Realität: Der richtige Ansatz (00:12:59) Wie KI die Produktentwicklung fundamental verändert (00:17:12) Der Burggraben-Mythos: Wie baut man heute Wettbewerbsvorteile? (00:38:09) Dune: Von der Idee zur Identitäts-Infrastruktur (00:49:14) Die ersten Kunden: Zwischen Weihnachten und Launch (00:59:24) Co-Development als Go-to-Market Strategie (01:04:43) Pricing-Philosophie: ROI statt versteckte Gebühren (01:18:32) Product-Market Fit ist nicht binär (01:21:23) Die nächsten 3 Jahre: Vom Produkt zum Netzwerk (01:24:45) Warum Europa der richtige Ort für bestimmte Businesses ist

We weigh the promise and peril of the AI agent economy, pressing into how overprovisioned non-human identities, shadow AI, and SaaS integrations expand risk while go-to-market teams push for speed. A CMO and a CFO align on governance-first pilots, PLG trials, buyer groups, and the adoption metrics that sustain value beyond the sale.• AI adoption surge matched by adversary AI• Overprovisioned agents and shadow AI in SaaS• Governance thresholds before budget scale• PLG trials, sandbox, and POV sequencing• Visualization to reach the aha moment• Buying groups, ICP, and economic buyer alignment• Post‑sales usage, QBRs, NRR and churn signals• Zero trust limits and non-human identities• Breach disclosures as industry standards• Co-sourcing MSSP with in-house oversightSecurity isn't slowing AI down; it's the unlock that makes enterprise AI valuable. We dive into the AI agent economy with a CMO and a CFO who meet in the messy middle. The result is a practical blueprint for moving from hype to governed production without killing momentum.We start by mapping where controls fail: once users pass SSO and MFA, agents often operate beyond traditional identity and network guardrails. That's how prompts pull sensitive deal data across Salesforce and Gmail, and how third‑party API links expand the attack surface. From there, we lay out an adoption sequence that balances trust and speed. Think frictionless free trials and sandboxes that reach an immediate “aha” visualization of shadow AI and permissions, then progress to a scoped POV inside the customer's environment with clear policies and measurable outcomes. Along the way, we detail the buying group: economic buyers who sign and practitioners who live in the UI, plus the finance lens that sets pilot capital, milestones, and time-to-value expectations.We also challenge sacred cows. Zero trust is essential, but attackers increasingly log in with valid credentials and pivot through integrations, so verification must include non-human identities and agent-to-agent controls. Breach disclosures, far from being a greater threat than breaches, are foundational to ecosystem trust and faster remediation. And while MSSPs add critical scale, co-sourcing—retaining strategic oversight and compliance ownership—keeps accountability inside. If you care about ICP, PLG motions, PQLs, NRR, or simply reducing AI risk while driving growth, this conversation turns buzzwords into a playbook you can run.Vamshi Sriperumbudur: https://www.linkedin.com/in/vamsriVamshi Sriperumbudur was recently the CMO for Prisma SASE at Palo Alto Networks, where he led a complete marketing transformation, driving an impact of $1.3 billion in ARR in 2025 (up 35%) and establishing it as the platform leader.  Chithra Rajagopalan - https://www.linkedin.com/in/chithra-rajagopalan-mba/Chithra Rajagopalan is the Head of Finance at Obsidian Security and former Head of Finance at Glue, and she is recognized as a leader in scaling businesses. Chithra is also an Investor and Advisory Board member for Campfire, serving as the President and Treasurer of Blossom Projects.Website: https://www.position2.com/podcast/Rajiv Parikh: https://www.linkedin.com/in/rajivparikh/Sandeep Parikh: https://www.instagram.com/sandeepparikh/Email us with any feedback for the show: sparkofages.podcast@position2.com

FinPod: Subscription Economics: Mastering LTV, Churn, and Recurring RevenueThe Subscription Economy has fundamentally reshaped corporate finance, moving the focus from one-time sales to long-term customer relationships. For professionals in FP&A, IR, and Corporate Strategy, understanding this shift is critical for forecasting and valuation.In this episode of Corporate Finance Explained on FinPod, we break down the unique financial mechanics of recurring revenue, examine key metrics, and explore how the most successful companies manage this model.The Core Shift: Value & Metrics: The subscription model swaps short-term cash hits for long-term predictability, which investors reward with higher valuation multiples.The Critical Ratio (LTV:CAC): We break down the relationship between Customer Lifetime Value (LTV) and Customer Acquisition Cost (CAC). Learn why the benchmark is LTV ≥ 3x CAC and the pitfalls of inflating LTV with non-recurring revenue.The Accounting Challenge: We explain revenue recognition (ASC 606/IFRS 15) and the concept of Deferred Revenue. Cash is received upfront, but revenue is recognized over time, which can make financial statements appear less profitable during high-growth periods.The Cautionary Tale: Analysis of MoviePass reveals the danger of fundamentally broken unit economics, where the cost to serve the customer (CoGS) was higher than the subscription fee, accelerating the path to bankruptcy.Strategic Playbooks & Success Stories: Successful companies master the mechanics of growth and retention, managing complex P&Ls and investor expectations:The Content Giant (Netflix): The challenge of balancing liquidity and leverage while managing billions in content amortization to drive retention and reduce churn (even a half-percent increase means millions in lost ARR).The SaaS Pioneer (Salesforce): Leveraging deferred revenue as an interest-free loan and obsessively tracking Net Revenue Retention (NRR), measuring if existing customers increase their spending over time.The Strategic Pivot (Adobe): The painful but successful transition from a lumpy license model to the predictable Creative Cloud subscription, which required transparent communication to manage market expectations.The Hybrid Model (Peloton, Amazon Prime): Understanding that the high-cost hardware sale is primarily a customer acquisition channel for the much more valuable, low-cost recurring content stream.The Modern Finance Mandate: Mastering the subscription model requires blending traditional corporate rigor with data science:Cohort Analysis: Shifting forecasting models to track groups of customers based on sign-up time, revealing granular insights into renewal rates, upgrades, and churn patterns.Proactive Scenario Modeling: Forward-looking planning (FP&A) must run rigorous sensitivity analyses, modeling the impact if CAC jumps 15% or if churn spikes, to prepare leadership for potential volatility.Communication is Strategy: Clearly articulating metrics like NRR and the path for LTV expansion to maintain premium public market valuations.

Alex Lieberman and Arman Hezarkani, co-founders of Tenex, reveal how they're revolutionizing software consulting by compensating AI engineers for output rather than hours—enabling some engineers to earn over $1 million annually while delivering 10x productivity gains. Their company represents a fundamental rethinking of knowledge work compensation in the age of AI agents, where traditional hourly billing models perversely incentivize slower work even as AI tools enable unprecedented speed. The Genesis: From 90% Downsizing to 10x Output The story behind 10X begins with Arman's previous company, Parthian, where he was forced to downsize his engineering team by 90%. Rather than collapse, Arman re-architected the entire product and engineering process to be AI-first—and discovered that production-ready software output increased 10x despite the massive headcount reduction. This counterintuitive result exposed a fundamental misalignment: engineers compensated by the hour are disincentivized from leveraging AI to work faster, even when the technology enables dramatic productivity gains. Alex, who had invested in Parthian, initially didn't believe the numbers until Arman walked him through why LLMs have made such a profound impact specifically on engineering as knowledge work. The Economic Model: Story Points Over Hours 10X's core innovation is compensating engineers based on story points—units of completed, quality output—rather than hours worked. This creates direct economic incentives for engineers to adopt every new AI tool, optimize their workflows, and maximize throughput. The company expects multiple engineers to earn over $1 million in cash compensation next year purely from story point earnings. To prevent gaming the system, they hire for two profiles: engineers who are "long-term selfish" (understanding that inflating story points will destroy client relationships) and those who genuinely love writing code and working with smart people. They also employ technical strategists incentivized on client retention (NRR) who serve as the final quality gate before any engineering plan reaches a client. Impressive Builds: From Retail AI to App Store Hits The results speak for themselves. In one project, 10X built a computer vision system for retail cameras that provides heat maps, queue detection, shelf stocking analysis, and theft detection—creating early prototypes in just two weeks for work that previously took quarters. They built Snapback Sports' mobile trivia app in one month, which hit 20th globally on the App Store. In a sales context, an engineer spent four hours building a working prototype of a fitness influencer's AI health coach app after the prospect initially said no—immediately moving 10X to the top of their vendor list. These examples demonstrate how AI-enabled speed fundamentally changes sales motions and product development timelines. The Interview Process: Unreasonably Difficult Take-Homes Despite concerns that AI would make take-home assessments obsolete, 10X still uses them—but makes them "unreasonably difficult." About 50% of candidates don't even respond, but those who complete the challenge demonstrate the caliber needed. The interview process is remarkably short: two calls before the take-home, review, then one or two final meetings—completable in as little as a week. A signature question: "If you had infinite resources to build an AI that could replace either of us on this call, what would be the first major bottleneck?" The sophisticated answer isn't just "model intelligence" or "context length"—it's controlling entropy, the accumulating error rate that derails autonomous agents over time. The Limiting Factor: Human Capital, Not Technology Despite being an AI-first company, 10X's primary constraint is human capital—finding and hiring enough exceptional engineers fast enough, then matching them with the right processes to maintain delivery quality as they scale. The company has ambitions beyond consulting to build their own technology, but for the foreseeable future, recruiting remains the bottleneck. This reveals an important insight about the AI era: even as technology enables unprecedented leverage, the constraint shifts to finding people who can harness that leverage effectively. Chapters 00:00:00 Introduction and Meeting the 10X Co-founders 00:01:29 The 10X Moment: From Hourly Billing to Output-Based Compensation 00:04:44 The Economic Model Behind 10X 00:05:42 Story Points and Measuring Engineering Output 00:08:41 Impressive Client Projects and Rapid Prototyping 00:12:22 The 10X Tech Stack: TypeScript and High Structure 00:13:21 AI Coding Tools: The Daily Evolution 00:15:05 Human Capital as the Limiting Factor 00:16:02 The Unreasonably Difficult Interview Process 00:17:14 Entropy and Context Engineering: The Future of AI Agents 00:23:28 The MCP Debate and AI Industry Sociology 00:26:01 Consulting, Digital Transformation, and Conference Insights

Alex Lieberman and Arman Hezarkani, co-founders of Tenex, reveal how they're revolutionizing software consulting by compensating AI engineers for output rather than hours—enabling some engineers to earn over $1 million annually while delivering 10x productivity gains. Their company represents a fundamental rethinking of knowledge work compensation in the age of AI agents, where traditional hourly billing models perversely incentivize slower work even as AI tools enable unprecedented speed.The Genesis: From 90% Downsizing to 10x Output The story behind 10X begins with Arman's previous company, Parthian, where he was forced to downsize his engineering team by 90%. Rather than collapse, Arman re-architected the entire product and engineering process to be AI-first—and discovered that production-ready software output increased 10x despite the massive headcount reduction. This counterintuitive result exposed a fundamental misalignment: engineers compensated by the hour are disincentivized from leveraging AI to work faster, even when the technology enables dramatic productivity gains. Alex, who had invested in Parthian, initially didn't believe the numbers until Arman walked him through why LLMs have made such a profound impact specifically on engineering as knowledge work.The Economic Model: Story Points Over Hours 10X's core innovation is compensating engineers based on story points—units of completed, quality output—rather than hours worked. This creates direct economic incentives for engineers to adopt every new AI tool, optimize their workflows, and maximize throughput. The company expects multiple engineers to earn over $1 million in cash compensation next year purely from story point earnings. To prevent gaming the system, they hire for two profiles: engineers who are “long-term selfish” (understanding that inflating story points will destroy client relationships) and those who genuinely love writing code and working with smart people. They also employ technical strategists incentivized on client retention (NRR) who serve as the final quality gate before any engineering plan reaches a client.Impressive Builds: From Retail AI to App Store Hits The results speak for themselves. In one project, 10X built a computer vision system for retail cameras that provides heat maps, queue detection, shelf stocking analysis, and theft detection—creating early prototypes in just two weeks for work that previously took quarters. They built Snapback Sports' mobile trivia app in one month, which hit 20th globally on the App Store. In a sales context, an engineer spent four hours building a working prototype of a fitness influencer's AI health coach app after the prospect initially said no—immediately moving 10X to the top of their vendor list. These examples demonstrate how AI-enabled speed fundamentally changes sales motions and product development timelines.The Interview Process: Unreasonably Difficult Take-Homes Despite concerns that AI would make take-home assessments obsolete, 10X still uses them—but makes them “unreasonably difficult.” About 50% of candidates don't even respond, but those who complete the challenge demonstrate the caliber needed. The interview process is remarkably short: two calls before the take-home, review, then one or two final meetings—completable in as little as a week. A signature question: “If you had infinite resources to build an AI that could replace either of us on this call, what would be the first major bottleneck?” The sophisticated answer isn't just “model intelligence” or “context length”—it's controlling entropy, the accumulating error rate that derails autonomous agents over time.The Limiting Factor: Human Capital, Not Technology Despite being an AI-first company, 10X's primary constraint is human capital—finding and hiring enough exceptional engineers fast enough, then matching them with the right processes to maintain delivery quality as they scale. The company has ambitions beyond consulting to build their own technology, but for the foreseeable future, recruiting remains the bottleneck. This reveals an important insight about the AI era: even as technology enables unprecedented leverage, the constraint shifts to finding people who can harness that leverage effectively.Full Video EpisodeTimestamps00:00:00 Introduction and Meeting the 10X Co-founders00:01:29 The 10X Moment: From Hourly Billing to Output-Based Compensation00:04:44 The Economic Model Behind 10X00:05:42 Story Points and Measuring Engineering Output00:08:41 Impressive Client Projects and Rapid Prototyping00:12:22 The 10X Tech Stack: TypeScript and High Structure00:13:21 AI Coding Tools: The Daily Evolution00:15:05 Human Capital as the Limiting Factor00:16:02 The Unreasonably Difficult Interview Process00:17:14 Entropy and Context Engineering: The Future of AI Agents00:23:28 The MCP Debate and AI Industry Sociology00:26:01 Consulting, Digital Transformation, and Conference Insights Get full access to Latent.Space at www.latent.space/subscribe

Early-stage founders often claim they've reached product market fit, but when you look closer, it's usually built on vibes, not data. In this episode of In Demand, Asia and Kim unpack what real product market fit looks like, how to measure it quantitatively, and why most early-stage SaaS companies are too quick to assume they've found it.  If you've ever wondered how to know when you've actually hit product market fit, or if you might be fooling yourself, this episode gives you the frameworks and numbers to tell the difference. Got a question you'd like Asia to unpack on the podcast? Record a voicemail here. Links:  DemandMaven Previous In Demand Episodes that discuss NRR: episode 46 and episode 37 Superhuman Product Market Fit Survey ProfitWell Chart Mogul Chapters (00:02:20) - What is product market fit, and how was it historically measured?(00:07:00) - The product market fit survey and its limitations.(00:11:30) - Gross customer retention (GCR) as an underrated metric for measuring product market fit.(00:16:00) - Net Revenue Retention (NRR) as a deeper sign of product-market alignment.(00:20:10) - How GCR and NRR tell different parts of the story.(00:26:05) - Secondary indicators: churn rate, close rate, and trial-to-paid conversions.(00:28:05) - Why cohorting/segmenting reveals where PMF actually exists.(00:34:50) - You might have PMF for one segment but not another.(00:36:45) - The cautionary tale of assuming PMF too soon and how DemandMaven sets expectations with new clients.(00:44:30) - The reality check: if you've never charged customers, you don't have PMF.

“SaaS metrics are dead.” You've probably seen that post on LinkedIn or X lately. In episode #325, Ben Murray cuts through the noise to explain why SaaS metrics aren't broken — they're just evolving to match modern recurring revenue business models. Whether you're running a SaaS, AI, software, or managed services company, the same financial principles apply. The key is understanding your revenue types — subscription, usage, consumption, or transaction — and applying the right metrics framework for each. What You'll Learn Why SaaS metrics still work — and why the confusion exists. The difference between SaaS as a delivery model and recurring revenue as a financial model. Why the most important question isn't “Are you SaaS?” but “What are your revenue types?” How financial systems and P&L design should reflect these revenue categories for accurate unit economics and valuation. Why It Matters For Operators: The framework for recurring revenue metrics applies whether you sell software, data, or AI services. For Finance Teams: You can't manage what you don't measure — ensure your financial modeling captures all recurring components. For Investors: Strong recurring revenue visibility (ARR, NRR, margins) still drives valuation multiples — regardless of your label. For Founders: Stop worrying about the buzz — focus on measuring what matters for your business model. Key Takeaways SaaS metrics = recurring revenue metrics. Focus on revenue types, not just labels like “SaaS” or “AI.” A clear chart of accounts and a well-designed financial system enable accurate SaaS metrics. The fundamentals of finance, accounting, and valuation haven't changed — only the packaging has. Resources Mentioned

Dheeraj built Nutanix into a $20B public company—then walked away to start DevRev. He just raised a $100M Series A.This episode breaks down why most founders "sell and run" (chase new logos instead of delivering value), why that strategy fails, and how Dheeraj thinks about building platforms with use cases instead of just features. He explains why the biggest opportunities come from bundling and why you need to hit 130%+ NRR to scale in B2B.Dheeraj also shares the two near-death experiences at Nutanix in the first 5 years, how they survived, and what he's building differently at DevRev in the AI-native world.If you're wondering whether you have real PMF, how to think about platforms vs features, or why your existing customers matter more than new ones—this is mandatory listening from someone who's done it twice at massive scale.Why You Should Listen:Learn why PMF at $1M doesn't mean PMF at $10M—and why you have to find it again at every milestoneWhy "sell and run" kills startups—the real work starts after you close the dealSee how platform thinking (not feature thinking) took Nutanix to $1B ARRUnderstand why 30-40% of revenue from existing customers is real PMF Keywords:startup podcast, startup podcast for founders, product market fit, platform thinking, Nutanix founder, enterprise SaaS, net dollar retention, PMF milestones, fastest to $1B, second-time founder00:00:00 Intro00:01:58 Starting Nutanix00:14:24 Why he left a $20B company00:18:53 The DevRev thesis00:27:39 Pre-AI vs post-AI product strategy and the agent shift00:40:57 Platform vs features00:46:25 PMF is not a destination00:48:10 #1 AdviceSend me a message to let me know what you think!

Dave Kellogg, EIR at Balderton Capital, wrote an explosive piece on the reality of modern startups in 2025. Dave walks us through the winners and losers in the AI era. Read Dave's Article Here: https://topline.beehiiv.com/p/the-era-of-haves-and-have-nots Thanks for tuning in! Catch new episodes every Sunday Subscribe to Topline Newsletter. Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech. Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast!   Chapters: 00:47 Introduction & editorial setup 03:03 Defining winning: market share as goal 07:09 Marathon vs sprint; growth tradeoffs 12:02 Switching costs, returns, and herd dynamics 21:42 Disruption resets order; capital to #1 25:06 Easy-come growth vs durable ARR 28:18 Creative destruction and incentives 33:31 Winning by ownership type 36:39 Strategy over grind; #2 playbook 40:33 Labor leverage, RTO, and 9-9-6 culture 53:31 Stalled SaaS: valuations, NRR, and growth 1:01:00 Consolidation, moats, domain expertise 1:04:45 Outro & where to follow  

Does Net Revenue Retention (NRR) really move your company's valuation multiple? Absolutely — and the difference can be worth tens of millions of dollars. In episode #319, Ben Murray breaks down new data from Meritech Capital and Benchmarkit.ai to show exactly how changes in your NRR directly impact your revenue multiple and SaaS valuation. You'll also learn why ACV segmentation matters when benchmarking NRR and Gross Revenue Retention (GRR), and how top-performing SaaS companies are using retention metrics to drive investor confidence and higher valuations. What You'll Learn The link between NRR and valuation multiples — a 7-point jump in NRR can double your multiple. How a $5M ARR company can see a $25M valuation swing from retention improvements. The latest SaaS benchmarks from Ray Rike (Benchmarkit.ai) for NRR and GRR. Why you must benchmark NRR by ACV, not company size or industry averages Why investors prioritize retention when evaluating durability, efficiency, and predictability of revenue. Why It Matters For SaaS Founders: NRR improvements can directly increase your exit or fundraising valuation. For CFOs & Finance Leaders: Retention trends reveal the sustainability of your revenue model and influence your ARR growth forecast. For Investors: High NRR signals strong customer economics, pricing power, and efficient growth. For Operators: Knowing your NRR by ACV cohort allows smarter resource allocation and customer success planning. Resources Mentioned The SaaS CFO Academy: https://www.thesaasacademy.com/#section-1744932157830 Quote from Ben “A 5X difference in valuation multiple can come down to just a few points in your net revenue retention. That's the power of strong SaaS metrics.”

Even small errors in your MRR schedule can have a massive impact on your retention metrics, and in due diligence, that can destroy investor confidence. In episode #318, Ben Murray explains why gaps in your monthly recurring revenue (MRR) schedule create inaccurate gross revenue retention (GRR) and net revenue retention (NRR) results — and how poor invoicing and renewal practices are often the root cause. You'll learn how to identify, fix, and prevent these gaps so your SaaS financial reporting and valuation metrics remain accurate and investor-ready. What You'll Learn ✅ What causes gaps in your MRR schedule (and how to spot them). ✅ How MRR gaps distort your retention, expansion, and churn calculations. ✅ Why these data issues raise red flags in due diligence. ✅ How to align renewal dates, contracts, and invoicing to eliminate data breaks. ✅ What a clean, accurate MRR waterfall should look like for SaaS and AI companies. ✅ Why you need at least three years of clean retention data before a fundraise or exit. Why It Matters For CFOs & Finance Teams: Gaps cause misleading GRR/NRR trends that erode trust in your data. For Founders & CEOs: Bad MRR data can hurt company valuation and slow down fundraising or acquisition. For Investors: Clean MRR schedules provide transparency into predictable revenue and retention strength. For Accountants: Accurate MRR waterfalls enable stronger financial modeling and forecasting. Resources Mentioned SaaS Metrics Foundation Course: https://www.thesaasacademy.com/the-saas-metrics-foundation Quote from Ben “If there are gaps in your MRR schedule, your retention story falls apart — and investors will notice.”

In this episode, host Dan Sixsmith interviews Marilee Bear the CRO at Gainsight. Marilee reflects on her first year at the helm, discussing the company's impressive growth trajectory, recent strategic acquisitions, and the challenges and opportunities presented by a major leadership transition. Marilee shares actionable strategies for improving net revenue retention, such as leveraging data-driven insights, fostering cross-functional collaboration, and investing in customer education. The conversation also explores the impact of AI on sales processes. Marilee offers candid leadership insights, discussing the importance of transparency, adaptability, and building a culture of continuous learning. She also recounts her career journey, from her early ambitions and formative experiences to the pivotal moments that led her to lead a major SaaS company, offering advice for aspiring leaders in the tech industry.Timestamps:Welcome and Introductions (00:00:01) Dan welcomes Marilee Bear who reflects on her first year at Gainsight, company growth, and recent leadership changes.Company Growth, Acquisitions, and Leadership Transition (00:00:30) Marilee discusses acquisitions, repositioning Gainsight for growth, and the CEO transition from Nick Mehta to Chuck Apathy.Team Structure and Business Unit Model (00:02:04) Explanation of new hires, business unit model, and leadership structure within product and customer success teams.Integrating Customer Success into Revenue Organization (00:03:21) Describes shifting customer success under the revenue team and the industry trend of CS as a revenue driver.Defining Roles and Realigning the Revenue Team (00:05:25) Outlines the jobs-to-be-done exercise, clarifying roles across sales, CS, and other go-to-market functions.Customer Success as a Pipeline Engine (00:06:24) Details how CS now contributes to pipeline generation and the metrics used to measure CSM impact.Net Revenue Retention (NRR) Challenges (00:07:29) Discussion of industry-wide NRR declines and the need for strategic retention and value delivery.Retention Strategies and Multi-threading (00:08:21) Emphasizes proactive retention, business value demonstration, and multi-threading within customer organizations.Competitive Landscape and Expansion Focus (00:12:29) Explains how competition now includes internal build vs. buy, and the importance of expansion within existing customers.Convergence of Sales and Customer Success Roles (00:13:53) Observes the merging responsibilities of CS and sales, with CS teams adopting more sales-like approaches.State of B2B Sales and Impact of AI (00:14:25) Explores ongoing challenges in B2B sales, the impact of generative AI, and the need for business acumen.Reaching C-level Executives and Sales Best Practices (00:17:00) Shares the difficulty of accessing executives, the importance of detective work, and value-driven outreach.Effective Sales Outreach to Executives (00:19:12) Marilee describes what makes sales outreach compelling: offering choices, concise meetings, and understanding executive preferences.Marilee's Career Journey (00:21:31) Covers her early ambitions, work history from restaurants to Oracle, Akamai, Zendesk, and her path to Gainsight.Retention and Customer Success Experience (00:25:54) Highlights her experience with retention at Akamai, building CS teams, and her initial exposure to Gainsight.Key Career Lessons and Leadership Growth (00:28:54) Shares lessons on authenticity, operational rigor, and the importance of direct feedback and self-improvement.Leadership Philosophy and Team Management (00:33:58) Discusses leading diverse teams, empathy, balancing encouragement with accountability, and fostering a feedback culture.Definition of Success (00:36:00) Marilee defines success as delivering the best outcomes for customers, company, and self, in that order.Closing Remarks (00:36:43) Dan thanks Marilee, wraps up the episode, and previews future collaborations.

Is renewal rate just another way of saying retention? Not exactly. In episode #316, Ben Murray breaks down the difference between renewal rate and the classic retention metrics—gross revenue retention (GRR), net revenue retention (NRR), and customer/logo retention. Ben explains why the renewal rate is the leading indicator of retention, especially when running annual or multi-year contracts, and why investors, private equity buyers, and your board will want to see this number alongside your standard SaaS metrics. If you're a SaaS or AI operator looking to better understand your unit economics and improve your company's valuation, this episode will help you put renewal rate into context as part of your financial metrics toolkit.

https://constraintcalculator.scoreapp.com/In this episode, host Jordan Ross interviews Peter Tams, co-founder of Clever Digital Marketing, who scaled his agency from side-hustle beginnings in 2019 to breaking $10M+ in annual revenue within just three years of going all-in.Peter shares how niching down into the home improvement space, restructuring his team around client consultants, and making Net Revenue Retention (NRR) the North Star metric transformed his agency into a referral-driven growth machine. Alongside this, he dives into how Kaizen culture, infrastructure, and incentivized systems helped build a team that thrives and a business that compounds.If you're an agency owner stuck between $1–3M or dreaming of eight figures, this episode will give you a clear playbook on how to scale with focus, culture, and courage.Chapters – Why only 0.4% of agencies reach 8 figures – Meet Peter Tams & the early days of Clever Digital Marketing – From generalist services to specializing in home improvement – Lessons from niching down: depth vs breadth – Breaking $10M: the three anchors of growth – Specialization & hyper-focus as a scaling strategy – Creating long-term goals and 10-year vision planning – Transforming client success managers into client consultants – Referrals as a leading KPI & NRR as the North Star metric – Incentivizing the team with rewards & culture-building – The power of Kaizen (continuous improvement) in agency growth – Building infrastructure: reporting, onboarding, and L&D systems – Why 65% of their revenue comes from referrals – Diversifying channels beyond referrals for sustainable growth – Reverse-engineering metrics and building meticulous systems – Courage, persistence, and leadership through challenges – Staying two steps ahead in business & client relationships – Where to connect with Peter onlineTo learn more go to 8figureagency.co

In this episode of RevOps Champions, host Brendon Dennewill interviews Vince Chiofolo, SVP of Revenue Strategy at Dash Solutions and President of the Incentive and Engagement Solutions Providers (IESP). The conversation explores the critical but often overlooked connection between payment experiences and customer retention. Vince reveals that 76% of customer churn can be traced back to poor payment experiences, whether inbound or outbound.The discussion dives deep into how RevOps teams can drive alignment across organizations by focusing on shared metrics like lifetime value (LTV), net revenue retention (NRR), and customer health. Vince shares practical insights on building loyalty through three key pillars: emotional, structural, and behavioral loyalty. The episode provides actionable frameworks for reducing churn, improving customer experience, and creating sustainable revenue growth through better operational alignment.What You'll LearnWhy 76% of customer churn relates to payment experience failures and how to address themThe three-pillar framework for customer loyalty: emotional, structural, and behavioralHow to align entire organizations around shared revenue metrics and outcomesThe surprising ROI of retention: how a 1-2% drop in churn can increase company valuation by 12%Practical strategies for moving beyond "new logo obsession" to focus on customer expansionCommunication frameworks that scale with business growth: metrics, rhythms, and strategic focusHow outbound payment solutions can transform from cost centers to revenue driversResources MentionedDash Solutions - B2P (Business-to-Person) payment platformMcKinsey study on organizational silos as growth barriersEinstein's problem-solving methodologyNet Revenue Retention (NRR) as a key alignment metricCustomer Lifetime Value (LTV) optimization strategiesAbout Vince ChiofoloTitle: SVP of Revenue Strategy Company: Dash SolutionsIs your business ready to scale? Take the Growth Readiness Score to find out. In 5 minutes, you'll see: Benchmark data showing how you stack up to other organizations A clear view of your operational maturity Whether your business is ready to scale (and what to do next if it's not) Let's Connect Subscribe to the RevOps Champions Newsletter LinkedIn YouTube Explore the show at revopschampions.com. Ready to unite your teams with RevOps strategies that eliminate costly silos and drive growth? Let's talk!

India beat Pakistan in the Super 4 after outclassing them in Dubai. BP boys share their thoughts on the game and much more.Use code "BP15" for an exclusive 15% off your purchase at Yashi Sports: https://www.yashisports.com

Many usage-based companies like Twilio don't disclose ARR as their North Star metric. So, what do they track instead to communicate growth and efficiency to investors? In episode #314, Ben Murray shares his research from 10-Q filings, press releases, and earnings calls to uncover the seven most common financial metrics that usage-based companies highlight. From revenue growth and gross margin improvements to AI adoption and RPO (Remaining Performance Obligations), you'll learn what matters most to analysts, investors, and acquirers when ARR isn't the headline. This is a must-listen if you're building a usage-based business model and want to understand how to position your company for valuation and fundraising success. What You'll Learn Why many usage-based companies don't lead with ARR or MRR. The 7 key metrics How AI adoption is becoming a narrative driver in earnings calls. Why RPO is gaining importance as a measure of forward visibility and future revenue. Why It Matters For Investors: These metrics provide confidence in growth and scalability, even without ARR disclosures. For Founders: Tracking and segmenting these numbers helps communicate the right story to Boards and potential buyers. For Valuation: Metrics like RPO and NRR are increasingly driving company valuations in usage-based models. For Finance Leaders: Understanding which financial systems and SaaS metrics to track ensures more effective reporting and better alignment with investors. Resources Mentioned The SaaS Metrics Academy: https://www.thesaasacademy.com/ Quote from Ben “If usage-based companies aren't tracking ARR, what are they tracking? The answer is seven key metrics that investors want to see — from gross margin to RPO.”

What does it really take to scale a SaaS from a tiny Barcelona startup to a global leader protecting brands like major clubs and top electronics companies? In this candid conversation, Laura Urquizu (CEO, Red Points) shares hard-won lessons on going from SMB to enterprise, hiring fast in NYC (and fixing the fallout), balancing long-term strategy with short-term execution, and why the best CEOs become “irrelevant” day-to-day as teams outperform.We dive into go-to-market, NRR as the north star, fundraising mistakes after a big round, building in the U.S. from Europe, and the AI behind Red Points (95% automated detection, 30M checks/day). If you're a founder, operator, or investor, this one's a masterclass in scaling under permanent uncertainty.Support the show

On this episode of The SaaS CFO Podcast, host Ben Murray sits down with Idan Bar-Dov, co-founder and CEO of Heka. Idan shares his unique journey from working in finance and law—starting out at an international law firm advising fintech companies—through the challenges of founding a startup during the pandemic, to leading a fast-growing SaaS company transforming how financial institutions use open source data. Together, they dive into Heka's evolution from its early focus on reconnecting consumers with their assets amid widespread data gaps, to becoming a global platform that provides advanced fraud detection, contact recovery, and enriched credit decisioning for major banks, fintechs, payment processors, and alternative lenders. Idan also opens up about the company's fundraising milestones, lessons learned from raising $16 million to date, building credibility with Fortune 500 clients, and the importance of sticky revenue metrics as the business scales. Tune in to hear more about Heka's mission to become the gold standard in consumer data, outpacing industry giants, and what's next for their growing team headquartered in New York and Israel. Plus, Idan shares practical advice for founders tackling enterprise sales, go-to-market strategy, and fundraising in the financial technology space. Show Notes: 00:00 Fintech Pivot During COVID Lockdown 04:15 Global Financial Reconnection Solutions 07:20 Insightful Investors Drive Series A 11:59 Navigating Investment Deals Efficiently 14:42 Investors Drive Financial Innovation 18:48 "Metrics for Growth: Revenue & NRR" 20:49 "Conquer Fortune 500 Market" Links: SaaS Fundraising Stories: https://www.thesaasnews.com/news/heka-raises-14-million-in-series-a Idan Bar-Dov's LinkedIn: https://www.linkedin.com/in/idan-bar-dov/ Heka Global's LinkedIn: https://www.linkedin.com/company/heka-global/ Heka Global's Website: https://hekaglobal.com/ To learn more about Ben check out the links below: Subscribe to Ben's daily metrics newsletter: https://saasmetricsschool.beehiiv.com/subscribe Subscribe to Ben's SaaS newsletter: https://mailchi.mp/df1db6bf8bca/the-saas-cfo-sign-up-landing-page SaaS Metrics courses here: https://www.thesaasacademy.com/ Join Ben's SaaS community here: https://www.thesaasacademy.com/offers/ivNjwYDx/checkout Follow Ben on LinkedIn: https://www.linkedin.com/in/benrmurray

This week's episode comes live from SaaStock USA 2025. Join special guests Greg Head (Practical Founders) and Josh Turley (CEO, RTA) as they discuss the story of transforming RTA from a 1970s COBOL-based business into a thriving SaaS company with a $100M valuation. Josh shares: - Why a fanatical focus on culture and clarity fueled RTA's growth. - The challenges of replatforming legacy software (and migrating customers.) - How narrowing their niche to government fleets led to 95% retention & 120% NRR. - Lessons from bootstrapping, using debt strategically, and closing a growth equity round. Guest links: LinkedIn - https://www.linkedin.com/in/josh-turley/ Website: https://rtafleet.com/       Check out the other ways SaaStock is helping SaaS founders move their business forward: 

SUMMARY In this episode, Gil shares the raw journey of building Metadata — from validating the idea through consulting, to nearly running out of cash, to eventually raising a $35M+ Series B. He explains how doubling prices unlocked product-market fit, why retention beats new logos, and how adopting AI transformed the company. This is a candid look at the highs, lows, and lessons every founder needs to hear. FOUNDER: Gil Allouche https://www.linkedin.com/in/gilallouche/

Most SaaS founders pay attention to churn, but beneath the surface of a good or bad churn number, many important details are missed.   In this episode of In Demand, Asia and Kim break down the real story behind churn. What the numbers do and don't tell you and how to dig deeper to uncover the patterns driving customer retention (or loss).  From understanding net revenue retention to running effective churn interviews, this is the ultimate primer on diagnosing and solving churn for your SaaS. Got a question you'd like Asia to unpack on the podcast? Record a voicemail here. Links:  DemandMaven ProfitWell ChurnKey ChartMogul Chapters (00:01:30) - Why a 5% churn rate may not be as healthy as you think.(00:03:55) - How do you measure churn? And getting detailed with qualified vs. unqualified churn and why you need to measure both.(00:06:05) - How to set up onboarding to keep track of qualified vs. unqualified churn.(00:07:30) - Understanding cohort-based churn and net revenue retention (NRR).(00:09:19) - How to interpret NRR and what benchmarks really mean.(00:13:35) - Why getting into segmented NRR is valuable.(00:16:30) - Churn is nuanced. If you are looking at a monthly churn number, you could be missing the bigger picture.(00:17:00) - If you collect cancellation reasons, you may miss the real reasons your customers are churning.(00:21:15) - How to conduct effective churn interviews (with participants who will actually attend) and the churn matrix: qualified/unqualified vs. activated/inactivated.(00:26:45) - What churn interviews can reveal: product confusion, missing features, poor product marketing.(00:27:30) - Product management issues that can come up in churn interviews.(00:31:15) - How to pre-select who to interview to give yourself the best chance of finding meaningful insights.(00:35:00) - Why churned customers are more talkative than trial users.(00:37:05) - What good churn research uncovers: acquisition, pricing, activation, product gaps.

In episode #297, Ben Murray tackles a common SaaS metrics question: How should reactivations be treated when calculating gross and net revenue retention (GRR & NRR)? Key takeaways: Reactivated customers (e.g., those who churned quickly but later update payment info) should not be included in new revenue — doing so skews CAC and CAC payback metrics. Gross Revenue Retention (GRR) only accounts for contraction and churn — reactivations don't belong here. Net Revenue Retention (NRR) is where reactivations should be recorded — they're essentially recovered revenue from existing customers. SaaS companies with high first-month churn (e.g., due to onboarding issues) may consider calculating an adjusted retention metric. Ben also highlights his new AI chatbot on TheSaaSCFO.com — trained on his blog content for instant SaaS finance answers. Level up your SaaS knowledge here: https://www.thesaasacademy.com/

What if your next wave of growth isn't about chasing new logos—but mining gold from the clients you already have? In this cepisode, CMO Courtney Baker challenges the traditional growth mindset with Knownwell's CEO David DeWolf and Chief Product and Technology Officer Mohan Rao. Together, they break down why net revenue retention (NRR) is the real growth lever, especially for professional services firms. They explore the inefficiencies of over-investing in new sales and reveal how failing to rigorously manage and measure existing relationships is holding companies back from true scalability and predictable growth. Meanwhile, Pete Buer dives into the latest AI in the Wild: Meta's audacious push toward artificial general intelligence, led by Scale AI's Alexander Wang. Is this the next paradigm shift or just Metaverse 2.0? And back by popular demand—it's the return of the AI Snake Draft! Courtney, David, and Mohan face off with their must-have AI tools for 2025. Which apps have become indispensable? Which tools are heading to the D-League? Find out who steals the draft with surprises, strategy, and a little smack talk. Plus, download the new Knownwell playbook for AI-powered strategies to scale your professional services firm: www.knownwell.com/scalingwhitepaper  Watch this episode on YouTube: https://youtu.be/N8b_AtMIM2E 

In episode #286 of SaaS Metrics School, Ben Murray breaks down one of the most common — and costly — mistakes SaaS founders and CFOs make when building their Monthly Recurring Revenue (MRR) schedules: netting contraction and expansion. This seemingly small error can break your ability to calculate key SaaS metrics like Gross Revenue Retention (GRR) and Net Revenue Retention (NRR). What You'll Learn: The essential structure of an accurate MRR waterfall schedule Why separating expansion, contraction, and churn is crucial for calculating SaaS metrics How to calculate GRR and NRR using distinct MRR layers Why trailing 3- and 6-month annualized retention rates offer deeper insights Pro tips on segmenting your MRR by product, ICP, or geography Who This Is For: SaaS founders, CFOs, FP&A leaders, and revenue ops teams looking to improve their SaaS financial reporting and ensure clean, actionable SaaS metrics that stand up to investor scrutiny. Resources Mentioned: Join Ben's private SaaS metrics community: https://www.thesaasacademy.com/offers/ivNjwYDx/checkout Subscribe to Ben's newsletter: https://mailchi.mp/df1db6bf8bca/the-saas-cfo-sign-up-landing-page Free SaaS Metrics Tools & Templates at TheSaaSCFO.com Enjoying the show? Please rate and review the podcast — it helps more SaaS professionals discover how to build better businesses with metrics that matter.

This week's guest was a New Orleans kid whose life changed overnight when Hurricane Katrina struck. After being separated from his Mother/Brother for 2 months, he reunited with them as they began their new life in Houston. He took a first job at Church's Chicken at 14 to help pay the bills, then later held other roles leading up to studying Mass Communications/Media Studies at Stephen F. Austin. Now, he is on the GTM team at Lumopath, the AI coach that increases NRR and efficiency. This week's guest is the Heart of Houston Texas, Mr. Jamal Hamilton. In this week's episode, we discussed:Jamal's Hurricane Katrina survival story and getting his first job at 14How an accidental sales call led to his career-changing tech opportunityHis cold calling philosophy: conversations over bookingsWorking across different startup stages and his AI work at Luma PathMental health importance in high-stress sales careersPlease enjoy this week's episode with Jamal Hamilton.____________________________________________________________________________I am now in the early stages of writing my first book! In this book, I will be telling my story of getting into sales and the lessons I have learned so far, and intertwine stories, tips, and advice from the Top Sales Professionals In The World! As a first time author, I want to share these interviews with you all, and take you on this book writing journey with me!Like the show? Subscribe to the email: https://mailchi.mp/a71e58dacffb/welcome-to-the-20-podcast-communityI want your feedback!Reach out to 20percentpodcastquestions@gmail.com, or find me on LinkedIn.If you know anyone who would benefit from this show, share it along! If you know of anyone who would be great to interview, please drop me a line!Enjoy the show!

#updateai #customersuccess #saas #businessRimple Patel, Chief Customer Officer at Eightfold.ai, joins host Josh Schachter, Co-Founder & CEO of UpdateAI, as she walks us through her strategic approach to leadership, including evaluating teams, aligning missions, and fostering a customer-first culture. Josh and Rimple also explore the role of AI in scaling business processes, covering innovations like agentic AI and AI recruiters while emphasizing the irreplaceable human element in the workplace. Finally, Rimple shares her insights on driving GRR and NRR growth at Eightfold and her strategy for scaling the company.Timestamps00:00 - Preview & Intros01:35- Overview of Eightfold.ai04:30 - AI in Talent Management08:00 - Rimple's Journey, Career Path & Industry Experience17:43 - Challenges & Insights from Her Role as CCO 20:03 - Evaluating Leadership, Talent, and Cultural Shifts 21:05 - Building a Customer-First Value System 22:09 - Team Principles & Leadership Accountability28:50 - Customer Segmentation & Health Assessment Strategies 31:13 - Revamping Customer Health Assessment33:05 - Yearly Growth Strategy: Stabilize, Scale, Soar___________________________