In this episode, we’re joined by Jeppe Schytte-Hansen, CEO and Co-founder of Omnidocs, a SaaS company that’s moving fast: €22M+ in revenue, 1,500 customers, 155 employees, and four acquisitions in the last 18 months after bringing in private equity for the first time. Jeppe breaks down what it really takes to turn a steady, profitable SaaS into a buy-and-build platform, from product alignment and enablement to the emotional reality of killing someone’s “version 2.0” and managing the slowdown that almost everyone underestimates.

We spoke with Jeppe about choosing PE over VC, building a 14-point M&A framework, and why one plus one rarely equals two in the first year. He explains the “integration foxtrot” (quick–slow–quick–slow), how to preserve culture across six offices and four countries, and why Omnidocs is betting big on the shift from traditional documents to “fluid formats” in the coming years.

Here are some of the key questions we address:

• What is the 14-criteria M&A evaluation framework, and what are the two instant disqualifiers?

• Why does every buy-and-build strategy start with a slowdown, and how do you shorten it?

• What makes product alignment the hardest part of M&A, and how do you decide when to kill a nearly-finished product?

• How do you structure integration squads and seven integration tracks across acquired companies?

• What does it take to enable sales teams to manage multiple products without slowing down new logo acquisition?

• How do you avoid overestimating cross-sell potential, especially in the first 12–18 months?

• Which are key roles and people to drive a successful pre, during and post-acquisition process?

🎧 Tune in to hear how Jeppe is transforming Omnidocs from a steady SaaS into a multi-product, pan-European platform proving that buy-and-build is far more than a financial strategy; it’s an operational discipline.

In this episode, we sit down with Fabian Veit, CEO of Make.com, to talk about what it really takes to scale not just one but two hyperscale SaaS companies - first in a classic enterprise sales-led motion, and now in a PLG + AI/automation world.

Fabian shares how Make has 15x’d revenue and grown from ~50 to nearly 400 people, while racing past 100k+ paying customers and aiming for €100M+ ARR, and why that requires a fundamentally different mindset than selling multi-million euro deals into the Fortune 2000. He contrasts the “one deal can make your quarter” reality of enterprise sales with the high-volume, product-first, self-serve motion of Make, where thousands of users sign up every month and the product has to carry the weight.

We also dig into what it means to build in the middle of the AI & agentic wave when your platform is literally how people wire AI into their business processes. Fabian explains why most AI projects are actually 80–90% integrations & automation, where AI is the smart layer inside the flow, not the whole show, and how Make is evolving from classic “if-this-then-that” workflows into visual AI agents that power real operations.

You’ll hear Fabian talk about:

• PLG vs Sales-Led: What changed when he went from 9–12 month, high-touch enterprise cycles at Celonis to Make’s “sign up free, upgrade yourself” engine.

• Rebuilding While Scaling: Why everything is always breaking in hypergrowth, and how he decides what to fix for 5× future scale, not just today.

• Brand & Positioning Pivots: The risky shift from Integromat to Make.com, losing SEO in the short term to win a much bigger global brand in the long term.

• Culture at Hyperspeed: How they keep their values intact with hundreds of new hires through explicit values & operating principles, and a brutal honesty policy inspired by Radical Candor.

• The AMA Channel: An internal Ask Me Anything Slack channel where anyone can ask leadership anything (even anonymously), and why Fabian believes answering every question publicly is non-negotiable for trust.

We wrap up with Fabian’s view on where we are in the AI hype cycle, why he compares this moment more to the industrial revolution than just another tech fad, and what kinds of human skills will matter even more in an AI-driven world.

In this episode, we’re joined by Pieter Boon, Co-founder at ImpactPilot, the customer success intelligence platform built for HubSpot. Pieter shares how he’s helping SaaS companies turn their CS orgs into true growth engines, measuring impact instead of activity through a framework called the Impact Driver Methodology.

Built on lessons from Google’s 10,000-person post-sales organization, this approach gives CS teams concrete ways to track success before renewal, using impact points tied to real customer outcomes like ROI proof, API adoption, or multi-year deals. It’s about replacing vague check-ins with measurable wins that move both customer and company forward.

We dive deep into how teams implement and operationalize the system, from designing the right impact drivers to setting incentives, avoiding false positives, and keeping customer value at the center. Pieter also reveals data from Impact Pilot users showing that customers with high impact scores are 7× more likely to renew or expand, and how that changes how you coach, measure, and reward CS teams.

Here are some of the key questions we address:

• What is the Impact Driver Methodology, and how does it solve the lagging-indicator problem in CS?

• How do you define and prioritize impact drivers that actually move the needle for customers?

• How can CS leaders design incentive models that balance company outcomes with customer value?

• What KPIs matter between onboarding and renewal, and how do you quantify “impact”?

• How can you use impact scoring to predict churn and expansion before it happens?

• What pitfalls to avoid, like rewarding “touches” instead of outcomes or overemphasizing feature use?

• How can early-stage SaaS teams implement this framework (and even start with a simple spreadsheet)?

• What’s next for CS as a function, and why Pieter believes it’s becoming the new growth engine for SaaS.

🎧 Tune in to hear how Pieter is redefining Customer Success for the revenue era where impact, not activity, drives retention, expansion, and long-term customer health.

In this episode, we’re joined by Jakob Lilholm, Co-founder & CEO at Formalize, the Danish-based compliance SaaS that went from a single-point whistleblowing tool to a multi-product GRC platform used by 8,000+ customers across ~80 countries. Jakob shares how his team timed EU regulatory tailwinds, built whistleblowing software, and then layered products on top, shifting from high-volume transactional sales to a focused, consultative motion for regulated industries.

Fresh off announcing a €30M Series B, Jakob walks through the internal rewiring it took: carving out an innovation pod with its own OKRs, resisting flattering false positives from the existing base, and proving platform demand with new-logo sales first, going from ~€100k ARR on the platform to >50% of company revenue in a year.

Here are some of the key questions we address:

• When do you expand from a point solution to a platform? We discuss the timing model Formalize used (EU roadmap + S-curve “next wave” before the first peaks).

• What’s the right ICP for a platform? Why did they end up narrowing their ICP and say “not yet” to others?

• How do you avoid false positives when you already have thousands of customers? Jakob explains why he decided to validate platform fit with new logos first.

• What org design supports a second act like this?

• How do you shift GTM, pricing, and messaging? What is the process moving from low ACV sales to higher-ACV, consultative deals without breaking the engine?

• Which metrics matter in the first year of a platform bet? How do you prove value creation, track conversion quality, and know when to re-inject the core team?

🎧 Tune in to hear how Jakob and team rewired a fast-growing SaaS from a single product to a multi-product platform play, aligning product, GTM, and finance while keeping the culture hungry enough to chase unicorn status by 2028.

In this episode, we’re joined by Rav Dhaliwal, recovering software exec turned early-stage VC at Crane. A longtime CS leader and board-level advisor, Rav breaks down how AI is reshaping Customer Success, from onboarding and telemetry-driven predictions to agentic workflows, while pushing CS to converge with account management and get far more revenue-centric.

We spoke with Rav about what AI should (and shouldn’t) automate, how to keep relationships authentic, and how leaders actually drive adoption, treating AI not as a tool drop but a behavioral change program.

Here are some of the key questions we address:

• Will AI compress or redefine CS, and where does it create leverage vs. require human expertise?

• What does the CS–Account Management convergence look like in practice (discovery, multi-threading, commercial acumen)?

• Which AI use cases move the needle now: telemetry-based churn/upsell prediction, voice sentiment, and agentic next-best-action?

• How do you avoid the “AI for efficiency only” trap and tie it to revenue, cost, and risk outcomes that customers actually buy?

• What’s the playbook for AI adoption in GTM/CS? How do leaders run a change program (not a tool rollout) and measure progress?

• Where are the authenticity risks and how do you keep the customer relationship human?

• How far can we push AI-led onboarding and what’s the 90% automated vs. 10% bespoke split likely to be?

🎧 Tune in to hear Rav’s pragmatic take on CS in the age of AI: more signal, smarter workflows, tighter revenue alignment and leadership that treats AI as an operating change, not a shiny tool. Also, watch out for his new book coming out shortly on Founder-Led Sales!

In this episode, we’re joined by Inês Lourenco, VP of Growth at Usercentrics, the privacy-led MarTech company that is powering consent on 2M+ websites & apps across 200 countries for 600k customers.

Inês unpacks how she built a 50-person growth org of cross-functional pods (Monetization & Pricing, Acquisition & Virality, Activation, Partner Experience, CMS Integrations, and Retention) around a simple thesis: growth = product distribution. She details the early, scrappy phase with manual signal detection, nightly queries, and “product specialist” outreach - through to a scalable system that routes users to self-serve, low-touch, or high-touch paths based on predicted AOV, with a hard-earned lesson to start with activation before everything else.

We spoke with Inês about turning signals into revenue, structuring pods, and creating an operating cadence where every pod owns its metric such as ARPA growth, NRR/GRR, activation time, and virality share, while collaborating tightly with Product, Marketing, Sales, and CS.

Here are some of the key questions we address:

• How do you define growth as product distribution and design pods that actually move revenue, not vanity metrics?
• What signals predict AOV early, and how do you route users to self-serve vs. low/high-touch experiences accordingly?
• Why did “product specialist” outreach outperform SDR-style messaging, and how do you structure those “baby-step” nudges?
• If you’re starting from scratch, why begin with an Activation pod and what are the first experiments to run?
• How do you set pod-level metrics (ARPA growth, activation time, virality share, NRR/GRR) and avoid cross-metric collateral damage?
• What collaboration model keeps Growth aligned with Product, Marketing, Sales, and CS, and who should Growth report to?
• When shouldn’t you build a growth team (and what to do instead if your top of funnel is small)?
• How do you evolve from consent management to a privacy-led marketing platform, while staying profitable and fast?

🎧 Tune in to learn how Inês turned signals into a system, building a growth engine that’s rigorous, cross-functional, and activation-first, proving that modern growth isn’t a channel, it’s product distribution by design.

In this episode, we’re joined by Peter Sunna (ex-Contentful, Commercetools), now leading product at Kognic, an annotation platform that helps cars “see” via camera & LiDAR for ADAS and autonomous driving. Peter shares why he downplays traditional roadmaps in favor of a company-wide “How We Win” operating system, aligning teams on target segment, differentiation, and the strategic power to compound.

We dive into the automotive software shift, safety-critical AI, and how to build defensibility when AI keeps redefining what’s feasible, sometimes in months. Peter explains how to keep Sales, Product, Marketing, and CS selling and building the same thing so strategy drives the plan, not a feature laundry list.

Here are some of the key questions we address:

• How do you replace feature roadmaps with a "How We Win" system that aligns every team and still tells customers what matters next?

• What does differentiation look like in practice and which power are you compounding (process, network effects, brand, switching costs, etc.)?

• When you’re early and have no moat, how do you use counter-positioning and when do you evolve to a more durable power?

• Depth vs. breadth: should you go deeper on a few use cases or widen to adjacent ones, and how do you decide?

• How do you sell a new workflow into enterprises (crossing the chasm) when existing org structures resist change?

• With AI rapidly changing what’s feasible, how do you plan, defend your margins, and avoid being automated away?

🎧 Tune in to hear how Peter turns strategy into an everyday operating cadence proving that in B2B, roadmaps don’t win markets; clarity on how you win does.

In this episode, we’re joined by Frida Ahrenby, CMO at Rillion, the AP automation platform expanding aggressively in the US with a new Austin hub. Frida breaks down how she rebuilt marketing from zero to a lean, 10-person, high-output team, starting with a performance+ops backbone, overhauling content/SEO, and leaning hard into field marketing for CFO buyers, while keeping creativity human in an AI-accelerated org.

We spoke with Frida about sequencing the first hires, structuring around three pods (Demand Gen incl. Field, Brand/Content/Design, Product & Customer Marketing), and using AI to multiply output without outsourcing originality. She shares how to avoid silos and title inflation, decide what must be owned in-house to truly own the number, and what it really takes to crack the US market from a European base.

Here are some of the key questions we address:

• How do you build a lean, unsiloed marketing org that still scales output (and keeps standards high) with AI in the mix?

• What’s the exact hiring sequence from a blank slate: why start with performance/ops, then content/SEO, then expand demand?

• Own it in-house or outsource? A simple rule for speed, agility, and true metric ownership and when agencies still help.

• Which marketing roles will compress vs. which remain decisively human in the AI era?

• What skills win now: how to hire for smart, analytical, creative demand gen, and deeply curious content that drives revenue?

🎧 Tune in to hear how Frida designed a tighter, faster marketing engine and why cracking the US is a marathon you run with data, creativity, and relentless focus, not headcount.