Podcasts about nrr

When Jean Compeau joined Sonar as CFO in March 2025, AI coding was not yet dominating industry conversations. By the summer and fall that followed, however, the landscape had shifted dramatically. Today, AI agents are producing software code at a pace that humans cannot easily verify, creating both opportunity and risk.That shift sits at the center of Sonar's mission. The company is the global leader in AI code verification and governance in what it calls the agentic-centric development lifecycle, or “ACDC, just like the band,” Compeau tells us. The scale is significant. Sonar is trusted by 7 million developers, processes 750 billion lines of code daily, serves 25,000 paying customers, and counts 75 percent of the Fortune 100 among its customers, Compeau tells us.For Compeau, growth is measured through both financial and operational signals. ARR, NRR, GRR, and EBITDA remain core metrics, she tells us. But she also watches utilization, adoption, lead generation, pipeline activity, and free-to-paid conversion rates because these indicators can reveal future performance before financial results arrive.That perspective shapes how finance participates in strategic decisions. As Sonar invests in new AI-driven products, finance evaluates not only bookings potential but also the company's long-term position in the AI market, Compeau tells us. The finance function remains involved throughout the process, helping operationalize everything from product introduction and revenue tracking to order management and cash collection.For Compeau, finance's role is not simply to measure growth—it is to help shape it.

Women's T20 World Cup 2026, Day 8, Australia v Netherlands, Pakistan v Bangladesh: Australia have never played the Dutch in a T20 before, and the Aussie challenge was whether they could top the NRR boost that India got from the same fixture. After that, Pakistan and Bangladesh scrapped it out in what became a scrappy game but a fierce, compelling contest. Firdose Moonda joins Geoff. Could you support the show? You can send us a Nerd Pledge or become a member at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠patreon.com/thefinalword⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and could win a case of Stomping Ground beer for your trouble. Browse their range at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠stompingground.beer⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Get your This is W̶o̶m̶e̶n̶'̶s̶ Cricket t-shirt here, and learn about Lacuna Sports bespoke cricket wear, created by women for women:⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠lacunasports.co.uk/en/shop/limited-edition/world-cup-t-shirt/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Stop snoring with 10% off a Zeus device: use code TFW2026 at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠zeussleeps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ With Morie Candles you can buy one item, get 30% off the next, with the offer code TFW5. At ⁠⁠⁠⁠⁠⁠morie.com.au⁠⁠⁠⁠⁠⁠ Join England's Test tour of South Africa in 2026 with Gullivers Sports Travel. Learn more or book at ⁠⁠⁠⁠⁠⁠⁠⁠⁠gulliverstravel.co.uk⁠⁠⁠⁠⁠⁠⁠⁠  Check out the Lord's Performance Centre for activities and courses: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠lords.org/lords/performancecentre⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Get your big NordVPN discount: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠nordvpn.com/tfw⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or 10% off ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Duncan Fearnley ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠bats and kit with code TFW10 or 15% off Step One clothes at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠uk.stepone.life/discount/TFW148⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or 10% off BIG Boots UK boots and socks at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠bigboots.co.uk/?ref=thefinalword⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Find more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠finalwordcricket.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Title track by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Urthboy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

We sit down with Bridget Winston to unpack what separates a real Chief Revenue Officer from a bookings-focused sales leader, and why the org chart tells you the truth faster than the job title. We get practical about SaaS metrics, AI-driven go-to-market, and the leadership habits that keep teams performing as the playbook keeps changing.• Evaluating a CRO remit by reporting lines and revenue accountability• Using GRR and NRR to diagnose product-market fit and ICP clarity• Treating revenue as a lagging indicator of customer centricity• Preparing for LLM-driven discovery with brand, PR, and earned media• Testing AI tools that shrink territory and quota planning cycles• Shifting budget from paid ads to community-led growth and local events• Turning customer testimonials into repeatable social proof loops• Managing humans and AI agents with specific, camera-ready feedback• Fixing incentives and systems before blaming the team• Creating urgency with day-five impact expectations instead of tired 30-60-90 plansYour org chart can tell you whether you're hiring a true Chief Revenue Officer or just renaming a VP of Sales. We sit down with Bridget Winston, CRO at Patient Now and a three-time CRO, to get brutally clear on what revenue ownership actually means and why “bookings” is a dangerous north star when retention and expansion are what compound.We dig into the SaaS metrics that expose reality fast: GRR, NRR, LTV to CAC, and how boards interpret dashboards when product-market fit and ideal customer profile are still shaky. Bridget shares a sharp reframing that stuck with us: revenue is a lagging indicator of customer centricity. From there, we zoom out to the “SaaS-pocalypse” conversation and what happens to pricing, planning cycles, and revenue per employee as AI turns some companies into dinosaurs and others into cheetahs.Then we get tactical about the LLM era of B2B discovery. If buyers are finding software through ChatGPT-style answers, Reddit threads, G2-style reviews, and YouTube, we need consumer-grade brand building, PR, and community-led growth that creates earned media AI can't ignore. Bridget also breaks down AI tools she's used to compress territory planning and quota work from months to weeks, plus AI coaching that improves call quality and handoffs without blowing up day-to-day operations.We even take a fun detour into Spark Tank wine trivia, then bring it back to leadership: how to give feedback with real specificity, fix systems before blaming people, and set expectations for day-one impact. Subscribe, share this with a revenue leader, and leave a review so more builders can find the show.Bridget Winston:  https://www.linkedin.com/in/bridgetwinston/Bridget Winston is the Chief Revenue Officer at PatientNow, leading go-to-market and customer-facing teams across a rapidly growing vertical SaaS platform in the fast-expanding $20 billion aesthetics and wellness industry.  A three-time CRO with over 20 years of experience, Bridget was formerly the CRO at Chief, where she led membership growth and helped the company reach a $1.1 billion valuation. During her tenure, Chief was recognized by TIME as one of the 100 Most Influential Companies and by Fast Company as one of the Most Innovative Companies. Before that, Bridget served as the CRO at Shutterstock, growing revenue to $300 million.Website: https://www.position2.com/podcast/Rajiv Parikh: https://www.linkedin.com/in/rajivparikh/Email us with any feedback for the show: sparkofages.podcast@position2.com

After 122 episodes covering SaaS metrics, GTM analytics, and the evolving world of AI-native software, Dave "CAC" Kellogg and Ray "Growth" Rike announce that The Metrics Brothers podcast is going on hiatus.In this abbreviated special episode, Ray and Dave reflect on what made the show work, what made it hard, and why now is the right time to take a pause. They share their top-performing episodes across 122 weeks, including the all-time most-listened episode on NRR, a breakout episode on pipeline generation, and the Intercom AI transformation episode that set a record for first-week downloads.They also explain the primary driver behind the break: AI changed the subject matter faster than their accumulated operator experience could keep up. What started as two veterans trading war stories about metrics they had lived with for decades became something that required more prep, more research, and more time to do with the quality they demanded. Both hosts decided they would rather spend more time inside AI from an operator's perspective to gain real-life AI experience, then return with better stories to tell.Ray shares his plans to accelerate the AI to ROI podcast and newsletter, expand AI benchmarking initiatives with partners including Scale Ventures, and build out advisory services for companies trying to measure and justify AI business impact. Dave will be putting more time into Kellblog, deepening his work with the Balderton Capital portfolio and his advisory clients.The Metrics Brothers consistently ranked in the Top 25-50 on Apple Podcasts in the Business Management category. All 122 episodes remain available in the archive.Listeners with feedback or ideas for what comes next can reach the Metrics Brothers at metricsbros@benchmarkit.ai.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark was running a startup out of a tiny annex office in Dublin with zero product usage. Then one customer turned it on and overnight he saw usage spike to thousands of simulations. He got to $1M ARR 100% through outbound, by sending 500,000 cold emails. A few months ago he closed a $25M Series A.In this episode, Mark breaks down the pivot from sales roleplay to customer support that unlocked his first real traction, the cold outbound playbook that took him to $1M ARR (500K emails, 250 meetings, 40 customers), and why doorstepping customers in Utah is what drove his net revenue retention to 186%.Why You Should ListenExactly how to use a cold outbound strategy to hit $1M ARR.Why getting on 56 flights last year to visit customers led to 186% NRR.How he closed a $25M Series A in just 6 days.Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, AI startup, customer support, cold outbound, Y Combinator, Series A, enterprise sales, SaaS, Solid RoadChapters00:00:00 Intro00:06:10 The Pivot From Sales to Customer Support00:12:54 Why Moving to SF Changed Everything00:22:34 Cold Outbound to $1M ARR00:32:47 Doorstepping Customers for 186% NRR00:39:17 Closing a $25M Series A in 6 DaysSend me a message to let me know what you think!

Ilya Mikin is Vice President of Technology M&A at Corum Group, one of the leading technology M&A advisory firms globally. His background spans more than two decades across enterprise marketing at Intel and Unilever, executive and CEO roles at companies including iHerb, multiple founder exits across AdTech, MarTech, and FinTech, and now advising founders through acquisitions. He has been on every side of the M&A table, which makes his perspective unusually grounded.This episode gets into what has fundamentally changed about how technology and e-commerce companies are built, valued, and sold. The old playbook of raising VC money, growing at all costs, and gunning for IPO has largely collapsed. What replaced it is a market where M&A has become the primary liquidity event for founders, and where the rules for what makes a company attractive have shifted significantly.Eitan and Ilya dig into what acquirers actually look at today: why NRR, GRR, and low churn have become the cornerstones of valuation, why private equity now represents up to 40-50% of buyers in some sectors, and what it means to be an AI-native company versus an AI-enabled one. They also cover the mechanics of the M&A process itself — the four to eight week preparation phase, how Corum builds competitive tension among buyers, why the narrative around a business often matters more than the financials, and the internal deal killers that founders rarely talk about openly.Ilya also shares his take on where shoppable video sits in a world increasingly shaped by agentic AI, why he believes emotional product categories are protected from agent-driven purchasing, and what he is personally watching in the space. Founders who are building toward an exit, or who have never seriously thought about timing one, will find this conversation both practical and clarifying.Website: https://www.vimmi.netEmail us: info@vimmi.netCommerce Untold: https://vimmi.net/commerce-untold/Eitan Koter's LinkedIn: https://www.linkedin.com/in/eitankoter/YouTube: https://www.youtube.com/@VimmiVideoCommerce/featuredGuest: Ilya Mikin, Vice President Technology M&A, Corum Group, Ltd.Ilya Mikin's LinkedIn: https://www.linkedin.com/in/ilyamikin/Corum Group, Ltd.: https://www.corumgroup.com/Watch the full Youtube video here:https://youtu.be/2lFD9JXIjIgKey Takeaways:VC investment in D2C e-commerce collapsed more than 90% from its 2021 peak, while M&A deals in that same sector grew 47% in 2025 — the exit path has fundamentally shiftedIPO is no longer the default liquidity event for most founders; M&A is now the primary outcome to plan aroundAcquirers today prioritize NRR, GRR, and low churn over raw growth rate — the stickiness and profitability of your customer base drives valuation more than top-line momentumPrivate equity now represents up to 40-50% of buyers in some sectors, and PE buyers lead with EBITDA, not vision — a minimum of $2-3M ARR and $500K EBITDA is roughly where serious interest startsBeing an AI-native company can increase your valuation by 20-30% or more; for true AI-native businesses, multiples can reach up to 20x EVFor AI companies, proprietary data sets matter more than the technology itself — the model is the moatMarket consolidation follows a cycle: the first quartile of a consolidation window has the most buyers, the most competition, and the highest multiples. Waiting too long means the music stopsThe narrative you build around your company matters more than your financials in the early stages of a buyer conversation — buyers need to feel fear of missing outRunning a competitive process with multiple interested buyers is the single most powerful lever a founder has in an M&A negotiation — inbound interest from one buyer puts the founder in a weak positionDeal fatigue and co-founder misalignment are the two most common internal reasons M&A deals collapse before closingAgentic AI will likely commoditize purchasing for basic, emotionally neutral products — but shoppable video remains essential for fashion, luxury, and any category where emotional decision-making drives the purchaseMore than 20% of WallID's customers now come through AI search channels like ChatGPT, Gemini, and Claude, with zero marketing spend — a real signal of how discovery is changingChapters:[00:00] Introduction and Guest Background[00:57] Ilya's Path from Intel and Unilever to E-Commerce and M&A[02:07] How the Approach to Building and Exiting Startups Has Changed[03:29] Why VC Investment Collapsed and M&A Deals Are Rising[04:40] What Acquirers Actually Look at Today: NRR, GRR, and Profitability[05:58] The Rise of Private Equity as a Buyer and What PE Wants[07:20] How AI-Native Companies Command a Valuation Premium[08:47] Where E-Commerce Multiples Stand Today[10:32] The Sell-Side Process: Preparation, Positioning, and Narrative[12:06] The Consolidation Window and Why Timing Your Exit Matters[13:38] How Corum Prepares Founders for Market[14:17] Technology Evaluation: AI vs. Non-AI Companies[17:00] Building the Story, Outreach, and Creating Competitive Tension[20:02] How Long a Typical M&A Process Takes[21:44] Deal Fatigue and Co-Founder Misalignment as Internal Deal Killers[23:28] Shoppable Video and Agentic Commerce: Where Emotion Still Wins[26:09] WallID: Solving Checkout Friction and Fraud at Scale[28:13] Managing Multiple Ventures and the Side-Hustle Mindset[29:44] What Ilya Is Watching in E-Commerce Right Now: Know Your Agent[31:04] How to Connect with Ilya and Corum Group

Salesforce made waves in February 2026 by introducing the Agentic Work Unit, or AWU, as a new way to measure and potentially price AI agent activity. The Metrics Brothers, Ray "Growth" Rike and Dave "CAC" Kellogg dig into whether the AWU is a legitimate step toward outcome-based pricing, a vendor-specific adoption metric, or just another awkward intermediate measure in the long, messy history of software pricing models.Episode Highlights:Tokens are not business metrics. Ray and Dave open by drawing a clear line: tokens measure text processing and compute consumption, not business outcomes. Nobody walks into a board meeting announcing they processed 14 billion word fragments, and enterprise buyers should not be priced on that basis.What Salesforce is actually trying to do with the AWU. Defined as "one discrete task accomplished by an AI agent," the AWU is Salesforce's attempt to bridge the gap between low-level compute metrics and business outcomes. The hosts debate whether it is a pricing metric in waiting, an AI adoption signal, or simply the best available approximation of work performed by agents.A short history of bad pricing units. From CPU counts to MIPS to kilocharacters to gigabytes, Ray and Dave trace the long, humbling history of software vendors searching for a pricing metric that maps to value. The Soviet chandelier analogy makes an appearance, courtesy of Appian CEO Matt Calkins.Activity versus outcome: the core tension. Ray argues the AWU is directionally right but fundamentally an activity metric, not a true economic outcome. Dave is more skeptical that outcome-based pricing can scale broadly, pointing out that customers say they want value-based pricing until a vendor actually tries to take a cut of the upside.Vertical AI applications have the clearest path. Both hosts agree that verticals with well-defined, countable outputs, such as cases resolved in customer support or claims processed in insurance, are best positioned to price on outcomes and may not need the AWU at all.The AWU needs a new name, and probably a new definition. Ray and Dave close with the observation that just as NRR took nearly a decade to emerge as a standard SaaS metric, meaningful AI metrics will take time to mature. The AWU, as currently defined, is a Salesforce-specific construct and unlikely to become an industry standard.If you are a B2B SaaS or AI-Native software operating executive, this conversation on one of the first agentic AI metrics to measure work activity is a great listen.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Send us Fan MailGuest: Anthony Nitsos, Founder of SaaS GurusA SaaS company doesn't become fundable because it's growing—it becomes fundable when the financial engine underneath that growth can withstand scrutiny.In this episode of SaaS Backwards, Anthony Nitsos, founder of SaaS Gurus, joins us to discuss what actually makes a SaaS company fundable. Revenue, customer growth, and cash in the bank are all important signals, but they do not always reveal whether the business is healthy, scalable, or ready for diligence.Anthony breaks down the difference between accounting and strategic finance, why ARR and NRR are often misunderstood, and how metrics like cash flow, CAC, and gross margin can give founders a clearer view of their company's health.Key takeaways:Why finance is forward-looking while accounting is backward-lookingThe five SaaS metrics every founder should understandHow ARR can be overstated through discounts, services, or transaction revenueWhy NRR is becoming more important to investors and acquirersHow strong financial infrastructure can improve fundability and valuation---Stalled pipeline? Lost deals? Diagnose your GTM gaps with a free, actionable checkup. 

This episode of Double Tap is brought to you by: C&G Holsters (Code: WLSISLIFE) Gideon Optics (Code: WLSISLIFE) Rost Martin (Code: WLSISLIFE) Night Fision (Code: WLSISLIFE) Blue Alpha Second Call Defense Text Dear WLS or Reviews +1 743 500 2171  Public   Show Titles   GOA GOALS Aug 1-2 in Iowa. https://goals.goa.org/ GunCon.net Tickets on sale now. Use code AGENCY171 DEAR WLS Question from OopsieDaisy from California For double tap by OopsieDaisy I've been listening to a lot of old episodes and started the book One Second After, a book Jeremy talked about and holy fuck it's good. Since an EMP would wreck all of the electronics in vehicles, what EMP-safe vehicle would you guys choose to take into an EMP ridden world? You have 10 grand to spend. Go. Question from Mike in NH 1st: quick positive review for C&G, I've been carrying my CSX-E series in a Covert for a month now, so great. Thank you to Chris and company 2nd: At what point does a used pick up become too nice/collectible to use/carry? I recently purchased a S&W 640-2. I didn't know anything about it apart from it was in excellent condition, and that it was pre-Lock. I thought it was weird for a steel J-frame to be 38spl only. It turns out the -2 was only made 1997-99 for NYPD as an approved back-up/off duty weapon. So it's kind of rare. Thanks for the opinions and the great shows. -Mike in NH Question from Duke of Crude from Texas Duke of Crude Hey fam, Thanks for reading my question on episode 449 about carry guns and meth country. My definition for meth country is either: 1. Urban sprawls (ex. Tulsa, Memphis) where hard drug use is prevalent 2. Rural areas (ex. West Virginia) where high poverty creates new hard drugs and users But going back to my question on 44 special in particular. Why does no one make a 44spc+P? I was looking for something like 1000-1200 fps 200gr out of a 4in barrel and I could not find any factory loads or even Underwood ammo that makes +P rounds. I have a 329PD that I like, but you will snap your wrist before you get through an entire cylinder of factory load 44 magnum. I was looking at that new s&w nightguard 396 but with my mind blown on how anemic 44 special is, I think I might have to pass. Do ya ll have any recommendations on 44mag/ special revolvers for EDC carry? Question from amonymous texas from coward from Texas Where can I find ammo to fight robots? There's a company called roborounds (roborounds.com if you are not familiar) that has a lot of cool bullets you can fire from standard firearms. For instance one fragments iron filings to short out circuit boards and another one creates a localized EMP on impact. The fucking robots are coming and I need this ammo, but I can't find a place to buy it. I see a few online retailers who used to carry it. I tried contacting them and they won't get back to me. Probably because I'm a nobody. If these guys are done, is anyone else making anything similar? Second related question: what about drone defense rounds? They had some cool stuff for 12 ga shells, but I have seen similar stuff from other companies. Are there any specific ones you know of or recommend? -amonymous texas from coward Question from Anonymous Coward from Oregon From No one Your printers are always running. What are you guys printing? Except Jeremy. He don't mess with that nerd shit. Question from Jon W from Washington Jon W I unfortunately live behind enemy lines in Washington state. Years ago when they first became sponsors, I took you up on your advice and signed up for Second call Defense and felt reassured that they had my back if the worst day ever happened. Since that time, our now turd Ferguson governor who used to be the Attorney General made having said insurance illegal in Washington. My question is hypothetically if a person had a close relative in another state could they sign up for Second Call Defense Using that address? They have said that they cover people that are signed up even if an incident occurs in a state like Washington, New York and I forget the other states that think it's murder Insurance. Your wisdom is greatly appreciated Keep up the good work! #wlsislife GUN INDUSTRY NEWS Bond Arms Snake Slayer (BASS) The Bond Arms Snake Slayer is a compact double-barrel derringer designed as an outdoor companion, chambered in .357 Mag/.38 Spl and .45 LC/.410. It features a stainless steel frame with a 3.5-inch barrel, extended rosewood grips, fixed sights, and a 2-round capacity. Key mechanisms include a rebounding hammer, cross-bolt safety, and compatibility with all standard Bond Arms barrels. Q Tall Boy Silencer Q has introduced the Tall Boy, a .30 caliber all-steel silencer optimized for maximum suppression on subsonic .300 Blackout via extended internal architecture that slows, cools, and manages gases for reduced exit pressure. It features a refined baffle structure for consistent performance across cartridges, full-auto rating, and Cherry Bomb/REAREND compatibility. The design prioritizes durability and long-term reliability without unnecessary complexity. Cabot Guns Apex Jurassic 1911 Cabot Guns has produced the Apex Jurassic 1911, a one-of-a-kind precision-engineered Government-size 1911 pistol crafted from Damascus steel, carbon steel, and genuine extraterrestrial meteorite. It features a unique ‘fossil' Damascus pattern resembling a sedimentary fossil bed, hand engraving depicting a Raptor archaeological dig site with 24kt gold inlay, Bulino-engraved Raptor vignette, and grips and trigger incorporating actual meteorite. The custom carbon-steel frame has a Fire and Ice rustic patina finish, with small parts in brushed bronze PVD; this art pistol appears to have already been sold. Berger 217 Grain Elite Hunter .300 PRC Load Berger has released a new .300 PRC ammunition load featuring the 217-grain Elite Hunter bullet with a hybrid ogive profile, G1 BC of 0.702 (G7 0.347), optimized for long-range hunting. It achieves 2,400 FPS muzzle velocity from a 24-inch barrel and retains over 2,500 foot pounds of energy past 300 yards. The load requires a 1:10 or faster twist rate. Palmetto State Armory PSA Sabre Builder Kits Palmetto State Armory announces the return of PSA Sabre Builder Kits as a permanent catalog offering on the AR-15 mil-spec platform. These include complete builder sets, upper receivers, lower receivers, handguards in multiple lengths, and individual components with Cerakote options like Champagne, Titanium Blue, Black, Burnt Bronze, FDE, and Moss Green. The sets launch on May 8 at 4:30 PM EST via Palmetto State Armory. Q Tall Boy Suppressor Q has released the Tall Boy, a .30 caliber suppressor designed for maximum suppression of subsonic .300 BLK using extended internal architecture and steel construction to optimize gas management. It measures 10 inches long, weighs 19.5 ounces, and is full-auto rated with no barrel restrictions. The Tall Boy integrates with Q's QD ecosystem via Cherry Bomb / REAREND mounts and is available now through Q dealers. Modlite Noxon Havok Weapon Light The Modlite Noxon Havok is a new rifle-mounted weapon light series offering premium performance at an affordable price, available in Core (18650 battery) and Mini (18350 battery) sizes with G1 (1350 lumens, 54,000 candela) or T1 (680 lumens, 69,000 candela) emitters. Constructed from 6061 aluminum with Mil-Spec hard anodizing and BOROFLOAT lens, it features a fully potted light engine tested for SCAR 17 recoil and compatibility with scout-pattern mounts, tailcaps, and switches. Released around May 2025 following SHOT Show debut, it provides runtimes of 75 minutes (Core) or 35 minutes (Mini). Walker's Razor Junior Muffs Walker's has launched the Razor Junior Muffs, youth-sized compact electronic ear muffs designed for smaller head sizes with an NRR of 23dB. These muffs feature dual Hi-Gain omnidirectional microphones, full dynamic range HD speakers, low-noise frequency-tuned circuitry, and 0.02-second sound-activated compression for hearing protection and sound enhancement. The product uses sound-dampening composite housing, a padded headband with metal wire frame, and recessed volume controls for durability and usability in range or field settings. Before we let you go – JOIN GUN OWNERS OF AMERICA We'd love if you supported the show, join Agency 171 at agency171.com. Lot's of prizes, rewards and kick ass swag. No matter how tough your battle is today, we want you here fight with us tomorrow. Don't struggle in silence, you can contact the suicide prevention line by dialing 988 from your phone. Remember – Always prefer Dangerous Freedom over peaceful slavery. We'll see you next time! Nick – @busbuiltsystems | Bus Built Systems Jeremy – @ret_actual | Rivers Edge Tactical Aaron – @machinegun_moses Savage – @savage1r Shawn – @dangerousfreedomyt | @camorado.cam | Camorado

#354 | Sue (Head of Lifecycle Marketing, Monarch Money), Jonathan (VP of Marketing, Seamless.AI), and Naomi (Senior Product Marketing Manager, Customer.io) join Dan for a live Exit Five session on customer marketing. Sue breaks down how Monarch discovered that the best time to promote their referral program was during trial and the data behind a 64% lift in referral shares and half a million dollars in incremental ARR. Jonathan shares how Seamless.AI stopped treating customer engagement like a campaign and built a full 365-day behavioral program, including an AI chatbot that deflected 55% of support tickets and live trainings that flattened their churn curve. Then Naomi walks through how she uses plain-text emails asking for replies to close the feedback loop on new features and shape the product roadmap.Timestamps(00:00) - - Intro (07:15) - - Sue: Why the best time to promote a referral program is during trial, not after (10:15) - - The results: 64% lift in referral shares and $500K in incremental ARR (17:15) - - Sue's background: 16 years in lifecycle marketing from online dating to Calm to Monarch (20:15) - - Jonathan: Stopping treating customer engagement like a campaign (26:15) - - Building a 365-day behavioral multi-channel customer engagement program (27:15) - - The AI chatbot that deflected 55% of support tickets (35:20) - - Live customer training 4x a week and how it flattened the churn curve (40:20) - - Growth plays for NRR: marketing to users inside existing accounts (42:20) - - Jonathan's results: 24% decrease in cancellations year over year (43:20) - - Naomi: Using lifecycle marketing to close the product feedback loop (49:20) - - The MCP server onboarding flow and why she asks for replies instead of clicks (56:20) - - Using beta email campaigns to shape the product roadmap (59:20) - - Live Q&A Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:Knak - A no-code, campaign creation platform that lets you go from idea to on-brand email and landing pages in minutes, using AI where it actually matters. Learn more at knak.com/exitfive, or check out the MCP server by clicking this link. Vector - A contact-level ads platform that lets you build audiences from actual people on your site, clicking your ads, and checking out your competitors. Learn more at vector.co, and get on the waitlist for their new MCP server by clicking here. Compound Growth Marketing - A full-funnel demand generation agency that helps high-growth cybersecurity, DevOps, and enterprise software companies drive more pipeline through AI SEO, paid media, and go-to-market engineering. Visit compoundgrowthmarketing.com and tell them Dave sent you.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

Ryan Burke, VP of Worldwide Sales at Crogl, joins Sam Jacobs, AJ Bruno, and Asad Zaman on the new economics of enterprise cyber risk. Topics include Anthropic's Mythos model, AI for the security operations center, why vibe-coded apps are far more likely to have security issues, why Claude Design tanked Figma's stock, and what the Elon Musk versus OpenAI lawsuit signals for AI governance. Key takeaways: AI has crashed the cost of running sophisticated attacks, putting nation-state-grade tooling in the hands of low-skill operators. As Ryan Burke, VP of Worldwide Sales at Crogl, put it on Anthropic's Mythos model: "Mythos has lowered the cost to like the dollar menu equivalent of...running an attack...so more people can do it." Enterprises are staring down a multi-year patching backlog that runs from now until the end of time. Non-technical teams in finance, ops, and HR are shipping internal tools using Replit and Claude, and almost none of them are securing what they build. Ryan Burke flagged the research: "vibe-coded software is almost 3 times as likely to have security issues." When the employee who built the agent quits, the agent stays behind with no owner, no documentation, and quiet access to systems it never should have had in the first place. For founders eyeing an exit, security has joined revenue, IP, and hitting your numbers as a non-negotiable diligence pillar. As Ryan Burke explained: "lack of security can kill an acquisition...a fourth pillar now is you're secure." Acquirers like JPMorgan Chase will not buy a fintech startup that turns into a vector for attackers to walk straight into their environment. The market case for NRR-fortress legacy SaaS may be weaker than the last decade made it look. As Asad Zaman, CEO of Sales Talent Agency, argued: "there was a generation of software companies that had signs that they had really good customer relationships...but their customers felt more like prisoners." If AI makes switching cheap and a new generation of software actually delights users, the moats around system-of-record incumbents start to compress fast. Connect with the hosts and guest:  Host: Sam Jacobs, CEO at Pavilion - https://www.linkedin.com/in/samfjacobs/  Host: AJ Bruno, CEO at QuotaPath - https://www.linkedin.com/in/ajbruno3/  Host: Asad Zaman, CEO at Sales Talent Agency - https://www.linkedin.com/in/azaman1/  Guest: Ryan Burke, VP Worldwide Sales at Crogl - https://www.linkedin.com/in/ryan-burke-bos/ Topline is more than a YouTube Channel:  Subscribe to Topline Newsletter: https://toplinemedia.substack.com/  Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast  Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack Chapters:  00:00 Introducing Ryan Burke 03:14 Anthropic Mythos and Cyber Risk 04:20 How Attackers Use AI at Scale  07:00 Dollar Menu Attacks Explained  10:41 AI for the Security Ops Center  14:53 Why Claude Tanks Figma's Stock  18:30 Sam's Advice on Falling Stocks  20:50 Are Legacy SaaS Companies Back?  24:04 The Vibe-Coding Risk Surface  27:56 Quiz Pro: Cybersecurity Edition  33:46 Replit Apps Inside Enterprises  40:18 Security as the M&A Fourth Pillar  44:17 Personal Data and Digital Legacy  47:24 Bulls vs Bears: Elon vs OpenAI  52:03 Will ServiceNow Hit $32B?

Dave "CAC" Kellogg and Ray "Growth" Rike tell the full story of how Intercom, a $400M ARR company that stalled at 4% growth, executed one of the most dramatic AI-first transformations in B2B SaaS. From writing off tens of millions in ARR to building a proprietary vertical AI model, this episode breaks down what it actually took to reinvent a mature SaaS business from the ground up.Topics CoveredFrom 4% to 26% Growth: The Numbers Behind the Turnaround. Intercom hit rock bottom with five straight quarters of declining net new ARR before founder Eoghan McCabe returned and went all in on AI following the ChatGPT launch in November 2022. Ray and Dave walk through the growth trajectory and what made the timing of the reset both urgent and actionable.The "Burn the Ships" Organizational Decision. Intercom rotated roughly 80% of its R&D team onto the new AI product, deliberately wrote off 50 to 60 million in ARR, and created small startup-like teams of 10 to 15 people with directly responsible individuals leading each workstream. Ray and Dave discuss why half-measures fail and how a stuck business actually has an advantage: very little to lose.Board Dynamics and Why Committees Kill Bold Moves. Dave shares a candid take on how PE boards versus VC boards respond differently to dramatic pivots, and why the committee nature of multi-partner VC boards tends to drive toward measured, middle-ground responses that often produce no real outcome.AI Economics: Gross Margins, Inference Costs, and Building Your Own Model. The shift from SaaS to AI-native changes the cost structure fundamentally. Ray puts current gross margin ranges in context (40 to 55% for pure AI-native, 55 to 70% for blended), explains why inference spend is actually rising despite lower per-token costs, and discusses why Intercom built its own vertical customer agent model for both performance and COGS optimization.Outcome-Based Pricing and the 99-Cent Resolution. Customer support is one of the clearest use cases for outcome-based pricing because the natural unit is obvious: a resolved ticket. Ray and Dave break down how Intercom priced Fin at 99 cents per resolution, validated the model against an 81% internal resolution rate, and watched NRR climb from 112% to 146% as adoption scaled across 8,000 customers.Never Waste a Good Crisis. Dave frames the broader lesson for SaaS CEOs: two paths exist now, dramatic AI reinvention or a Rule of 60/70 efficiency play. The Intercom story illustrates what the reinvention path actually demands. Ray adds that many SaaS companies sitting at 10% growth and 25% EBITDA are already in a slow-moving crisis and just haven't admitted it yet.If you lead a B2B SaaS company navigating the shift to AI, this episode is the most concrete case study available on what full commitment actually looks like in practice. Ray and Dave go beyond the headlines to examine the organizational design, board dynamics, cost structure, pricing model, and retention metrics behind Intercom's transformation. Whether you are considering an AI-first pivot or trying to understand why incremental approaches tend to stall, this episode gives you the analytical framework and the real numbers to think it through.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What if preventing hearing loss wasn't just about PPE… but about truly understanding how people experience it?In this episode, we sit down with Jenn Holliday, CIH, to unpack a powerful real-world case study on occupational noise exposure, and how a shift in thinking led to measurable results.Jenn walks us through a scenario many safety professionals know all too well: high noise environments, reliance on hearing protection, and the challenge of ensuring it actually works in practice, not just on paper.In this conversation, we explore:Why traditional hearing protection approaches often fall shortThe difference between NRR and real-world protectionHow HPFT can proactively prevent hearing loss (even though it's not required)Practical ways to integrate fit testing into your programAnd how small changes can unlock big cultural shiftsThis is a must-listen for safety professionals who want to move beyond compliance and create real, measurable impact.Jenn Holliday: https://www.linkedin.com/in/jennholliday/

Today on the show, we have Alex Raymond, founder of AMplify and author of The Growth Department, a book reframing how post-sales teams think about their role inside B2B companies.In this episode, we dig into why customer success and account management are in an identity crisis — and why the answer lies in orienting the entire function around one core purpose: helping the company win. We explore the “keep, grow, no surprises” framework, how NRR as a North Star metric can align sales and CS around shared incentives, and why consolidating all revenue under a true CRO is becoming a more common org design move.We discuss the confidence gap in CS teams when it comes to commercial conversations, why over-indexing on relationships is one of the most common mistakes in post-sales, and why parachuting an AE back in at renewal is a poor experience for the customer — and for the team.Finally, we tackle the economics hiding in plain sight: why 100% of a company's profits come from existing customers, how resource allocation between new business and existing accounts is wildly mismatched, and why the language CS and account management professionals use to describe their work has a direct impact on their standing inside the business.​​​​​​​​​​​​​​​​Churn FM is sponsored by Vitally, the all-in-one Customer Success Platform.

What happens when a multifamily CEO with 18,000 doors under his belt jumps into single-family… and says SFR is the bigger opportunity?!Dan French nearly went bankrupt during the Great Financial Crisis, slept in vacant units, ruined his credit for a decade, and used every lesson to eventually scale a multifamily platform from 2,500 to 18,000 doors. Now he's CEO of Northpoint, one of the largest SFR management companies in the country, and he's building something fundamentally different: separate divisions for scattered-site SFR, BTR, and small multifamily - all running on a shared platform.We discuss:(00:00:00) - Intro(00:01:45) - Dan's background and career(00:08:39) - Northpoint(00:14:54) - Sponsor - Enterprise Bank & Trust(00:16:18) - SFR following in the footsteps of multifamily(00:26:07) - The difference between BTR and SFR(00:30:47) - The division of labor in PM(00:34:28) - Sponsor - Haven AI(00:35:57) - How a PM would implement a BTR community(00:40:51) - Northpoint and their acquisition strategy(00:45:43) - Separating unit churn from revenue churn(00:50:27) - The melting iceberg problem(00:58:19) - Dan's experience with Crane(01:00:44) - The competitiveness of MF property management(01:04:26) - The lack of ‘scaffolding' in SFR(01:10:15) - Getting in touch with DanWe get into the "melting iceberg" problem that's killing PM roll-ups (and why most buyers underestimate churn), how to build a trust layer with owners that actually reduces churn, why he thinks tech is not a moat (and what is), and why the Innovator's Dilemma means SFR operators are better positioned to move upmarket than multifamily firms are to come down.Dan also shares his take on NRR vs. logo churn, the talent scaffolding gap between MF and SFR, and why North Point is keeping acquired brands intact instead of rebranding day one.Learn more and connect with Dan here: NorthpointLinkedinResources for Property Managers & Real Estate EntrepreneursCrane – Private PM Owner Community → Join a private network of property management owners and operators: https://joincrane.co/Free Weekly Newsletter → Property management insights, strategies, and industry updates direct to your inbox: https://peter.beehiiv.com/subscribeRL Property Management → Learn more about Peter's company and services in Columbus, Ohio: https://rlpmg.com/___Disclaimer: The content of this podcast is for informational purposes only and does not constitute professional advice. I may have consulting agreements with, or financial interests in, companies mentioned in this podcast. Additionally, some of the links included may be affiliate links, meaning I may earn a commission if you purchase through these links. Always perform your own due diligence before making any financial or business decisions.

12 years. $53M raised. One acquisition. Zach Scheel is talking about all of it.Zach Scheel, co-founder of Rhubmix, sat down with Owen the day after Autodesk officially closed its acquisition of the 12-year-old construction labor tracking platform. He didn't hold back.Tune in to find out about:✅ Why Autodesk acquired Rhubmix — and what gap in their product suite it fills✅ The financial metrics (110% NRR, 94% GRR) that made the deal happen✅ What a term sheet getting pulled post-signing actually feels like — and how they survived it✅ Why 10 years is probably a realistic median exit timeline for construction tech founders and investorsWatch now on Spotify and YouTube

One word can reveal a lot about someone's analytical depth, and on this episode of The Metrics Brothers, Dave "CAC" Kellogg and Ray "Growth" Rike break down one of the most commonly misused pair of terms in metrics analysis: segments and cohorts.Dave shares what sparked this topic, a Norwest benchmark report that used the word "cohort" when it clearly meant "segment," and explains why the mix-up matters far more than a simple vocabulary error. In this episode, Ray and Dave cover:Segments vs. Cohorts Defined: A segment is a slice of data defined by a shared attribute such as company size, vertical, or deal size. A cohort is a group anchored to a shared event and tracked over time, such as all opportunities created in Q1 or all customers acquired in a given year. The two are orthogonal concepts, not synonyms, and confusing them can signal a lack of the numerical fluency that sharp operators and investors expectSnapshot vs. Cohort Analysis: Standard dashboard win rates are fast and stable, but they only capture what crossed the finish line in a given period with no visibility into where those deals came from or how long they were in the pipeline. Cohort analysis rides along with a group of opportunities from creation to resolution, revealing how process and personnel changes actually affect outcomes over timeWin Rates and Pipeline Coverage: Ray walks through a real example where cohort-based win rate analysis exposed a breakdown in discovery quality after a Q3 process change, something a standard dashboard completely masked. Dave explains why pipeline coverage goals should not simply be calculated as the inverse of a snapshot-based win rate, and how close rate (a cohort-based metric) gives a more accurate picture of both yield and timingNRR, GRR, and Customer Expansion: Dave makes the case that tracking ARR by customer acquisition cohort over time is far more predictive of long-term retention and expansion behavior than NRR alone, which only looks back one year. Ray adds how cohort analysis helped him identify a high-value expansion window between months 18 and 30 of the customer lifecycle, enabling smarter allocation of sales resources towards existing customersCombining Both for Maximum Insight: The most powerful approach is a segmented cohort analysis, tracking time-based behavior across meaningful attribute-based cuts of your customer or pipeline data. Segments tell you what kind of customer. Cohorts tell you what happened over time. Together, they tell the full story.If you use metrics to help inform decisions in your company, and have a goal to help build a culture of numeracy in your company, this is a great listen!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Send us Fan MailGuest: You Mon Tsang, Co-Founder & CEO of ChurnZero  --  In this episode of SaaS Backwards, Ken Lempit talks with ChurnZero co-founder and CEO You Mon Tsang about why retention and expansion are becoming core drivers of SaaS growth, not just post-sale activities. As investors put more weight on metrics like NRR and GRR, founders need to rethink how they build and scale their companies. They discuss why customer success should be designed into the product and operating model from the beginning, and why too many companies still underinvest in their existing customer base. The conversation also explores how AI is reshaping customer teams—removing low-value work while making teams more strategic—and why trust, proof of ROI, and customer context are critical in a crowded SaaS market. Key takeaways Retention is now a primary driver of SaaS growth.  Customer success needs to be built in early, not added later.  AI is most valuable when it enhances human decision-making.  Strong customer context leads to better outcomes and expansion.  Trust and proof matter more than ever in the AI era.---Stalled pipeline? Lost deals? Diagnose your GTM gaps with a free, actionable checkup. 

This episode felt like a reunion.Caroline Galzin — former co-host of Nashville Restaurant Radio — is back behind the mic along with her husband Tony Galzin, chef and owner of Nicky's Coal Fired. Since we hadn't seen each other in a while, the conversation starts with some catching up, a little fantasy football talk (Tony is part of the NRR league), and reflecting on Caroline's time helping build the podcast in its early days.From there, the conversation shifts into something that recently put Nicky's in the spotlight.Caroline and Tony hosted an event at their event space, The Maxwell Room, featuring California Governor Gavin Newsom. While they were excited to host the gathering and open their doors to a political figure, the reaction from the public was far more intense than they expected. We talk candidly about what it's like when a restaurant suddenly finds itself in the middle of a political conversation — and how operators navigate those moments.We also zoom out into a bigger conversation about local politics, public perception, and the role restaurants play as community gathering spaces.To end on a more fun note, we announce an upcoming event for the hospitality community happening May 12th at Nicky's Coal Fired — a chance for restaurant folks to get together, connect, and enjoy a night with their peers.This one is part catch-up, part real talk about running restaurants in a politically charged world, and part invitation to come hang out with the Nashville hospitality community.In This EpisodeCaroline's return to the NRR mic and what she's been up toTony's life in the NRR fantasy football leagueHosting Governor Gavin Newsom at The Maxwell RoomThe unexpected public reaction and what it felt like on the insideRestaurants as community spaces in political momentsLocal politics and hospitality cultureAnnouncement: Hospitality community event at Nicky's Coal Fired – May 12

In this episode of In Demand, Asia and Kim break down what value decline is, how it silently erodes net revenue retention, and why many SaaS companies are unknowingly creating long-term churn.  They explore the forces that drive declining value, including market shifts, competitive moves, and self-imposed product constraints. If your NRR is stuck below 80 percent, or if growth feels harder than it should, this episode will help you diagnose whether value decline is the hidden culprit. Got a question you'd like Asia to unpack on the podcast? Record a voicemail here. Links:  DemandMaven Continuous Discovery Habits by Teresa Torres In Demand episode pricing Chapters (00:00:30) - What value decline is and how it shows up in NRR and long-term retention.(00:04:00) - Market forces change the value your product or service creates.(00:06:30) - Signs that you're in value decline vs. value status quo.(00:09:20) - Mapping jobs to be done to uncover missed opportunities for value expansion.(00:16:10) - The three root causes of preventable value decline inside SaaS companies.(00:26:30) - Why good processes are key for avoiding value decline.(00:32:00) - Why customers will likely only tell you about quality of life improvements and bugs, but not real value generators.(00:38:00) - Sprint discovery versus continuous discovery and how to structure validation.

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

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

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

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.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

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

“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.”