Net Recurring Revenue (NRR) is the cleanest truth-teller in my operating system. When I review NRR, I’m not just looking at whether we renewed accounts—I’m assessing whether our product and customer success motions are compounding revenue from our existing customers. Put simply: good CS teams protect revenue; great CS teams grow it through adoption, expansion, and durable retention.
Here’s how I frame NRR with my teams: it reflects revenue from our current customers after expansion, downgrades, and churn. If it’s at or above 100%, the installed base is self-sustaining; if it’s materially above 100%, the base is funding growth without net-new sales. That’s the holy grail for product-led growth and the benchmark I use to separate good from great.
At HighLevel, I’ve learned that you can’t “wish” your way to high NRR. You operationalize it. We align incentives, dashboards, and rituals so everyone—from PMs to CSMs to Solutions Engineering—owns the same outcome. Our “QBRs vs OKRs” discussions anchor on NRR drivers: activation rates, time-to-value, feature adoption depth, and expansion readiness. Those leading indicators tell me where we’ll land on lagging revenue results.
The best Customer Success teams operate like product teams. They use behavioral analytics and retention analysis to segment customers by use case and maturity, then design journey mapping to move each segment from first value to habitual value. They proactively reduce risk while creating clear expansion paths—new seats, premium features, or higher-tier plans—based on real product usage, not guesswork.
Onboarding is where great NRR trajectories begin. I focus on compressing time-to-first-value and time-to-second-value because those moments create the habit loops that underpin renewal and expansion. In practice, that means targeted in-app guides, contextual product tours, and nudges that drive user activation across the “sticky” features that correlate most with long-term retention.
To make this scalable, we blend human and product-led touchpoints. CSMs run outcome-based playbooks, while the product experience handles education and reinforcement at scale. When usage signals an expansion opportunity—say, a team consistently bumps into plan limits—we generate a product-qualified expansion lead and equip the CSM with the exact value storyline and proof points to close it.
Increase revenue, cut costs, and reduce risk with Pendo’s Software Experience Management platform. Optimize the entire software experience to drive adoption and improve engagement.
I’ve seen this playbook move the needle. After instrumenting our key workflows and deploying targeted in-app guidance, we watched adoption of our highest-retaining features climb, risk flags surface earlier, and expansion conversations become far more data-driven. We didn’t chase shiny objects; we built a reliable pipeline of retained and expanded revenue directly from product usage.
If you’re aiming to level up NRR, start with a crisp blueprint: define the critical events that predict renewal and expansion; set activation milestones per segment; deploy in-app guides and product tours to remove friction; give CSMs a single-pane view of risk and readiness; and review NRR weekly with the same seriousness you apply to new ARR. Consistency beats intensity here.
Finally, keep the narrative simple. Your leadership story isn’t “we shipped features,” it’s “we created customer outcomes.” Tie every CS and product initiative back to NRR drivers—and make the wins visible. When teams see the direct line from great onboarding and adoption to measurable expansion, they naturally operate like a unified, product-led growth engine.
NRR rewards rigor. Treat it as the top-line health metric for your installed base, make the software do more of the teaching, and empower CS to coach to outcomes. Do that well, and you won’t just separate the good from the great—you’ll build a compounding machine.
There’s a moment in every product leader’s career when the bravest decision isn’t to build—it’s to stop. That’s why the “Kill Your Darlings” theme resonated so strongly with me. In this episode of All Things Product, Teresa Torres and Petra Wille dig into the courage and craft it takes to sunset products that look successful on the surface yet quietly block your path to meaningful growth. As someone accountable for portfolio outcomes, I’ve learned that disciplined endings are often the catalyst for exceptional beginnings.
Listen to this episode on: Spotify | Apple Podcasts
The heart of the conversation is that uncomfortable middle ground between obvious failure and runaway success: products that are profitable, loved by customers, but fundamentally flatlining. Teresa shares candid stories from her own business, including a decision to cut 40% of revenue on purpose. I’ve been there—choosing to retire a “working… kind of” product to free up discovery capacity felt risky in the moment, but it created the focus we needed for durable growth.
Here’s the trap: some traction can be more dangerous than no traction at all. Early fans are not the same as durable product–market fit, and “stable but not growing” can lull leaders into maintaining instead of learning. Every hour of design, engineering, and go-to-market attention that props up a flatlining product is an hour not invested in the next breakthrough—an opportunity cost that rarely shows up on a dashboard, yet compounds month after month.
From a portfolio perspective, this is continuous discovery in action. If we want empowered product teams to tackle meaningful outcomes, we have to protect their capacity from zombie work. That means setting clear thresholds for when we double down, shift strategies, or sunset—before attachment and inertia take over. When I’ve institutionalized this discipline, our throughput of high-quality bets increased, and our confidence in what not to do became a strategic advantage.
Organization design can make sunsetting harder than it needs to be. Dedicated, long-lived teams are fantastic for compounding capability, but they also create emotional and structural ties to specific products. Petra’s point lands: leaders need explicit sunsetting conversations and a portfolio decision-making cadence that sits one level above teams. In my org, we treat sunsetting as a strategic reallocation—not a verdict on a team’s talent—so people are celebrated for learning, not punished for outcomes outside their control.
Killing profitable products can be the right strategic move when the growth ceiling is clear and the opportunity cost is high. I’ve chosen to “burn the ships (on purpose)” more than once—retiring add-ons that generated reliable revenue but diluted our value proposition and spread discovery thin. Yes, it stings in the quarter you do it. But it’s astonishing how quickly focus restores momentum when you create intentional space for what’s next.
Practically speaking, I make sunsetting easier and less traumatic by operationalizing it: Regular portfolio reviews focused on outcomes and opportunity cost; a visible “sunsetting” column so everyone sees what’s on the table; the Horizon (H1 / H2 / H3) model to balance core, adjacent, and transformational bets; and making portfolio decisions one level above teams to avoid local optimizations. Add explicit exit criteria and success metrics for endings, the same way we set entry criteria for new bets.
Another theme I appreciated is designing for the right customers. Teresa highlights intentionally limiting access and pricing to work with customers who show agency and commitment. I’ve applied the same principle: when we’re clear about who we serve and who we don’t, our product–market signal sharpens, churn narratives simplify, and roadmaps get crisper. Focus is a growth strategy.
If you’re leading a product portfolio, running discovery, or wrestling with a product that “works… kind of,” this conversation is permission to act. Product–market fit isn’t binary, and mediocre success can be the most dangerous place to stay. Sunsetting is a portfolio decision, not a team failure; teams shouldn’t be punished for reaching the end of a product’s natural lifecycle. If experimentation isn’t in your DNA, killing products will always feel traumatic—so make space for it intentionally, not passively.
Key moments and themes worth bookmarking: 00:00 – Why “kill your darlings” matters; 04:30 – The dangerous middle ground; 09:30 – The opportunity cost of “okay” products; 14:30 – Sunsetting in product organizations; 19:00 – Real examples of killing revenue streams; 28:00 – Designing for the right customers; 33:30 – Burn the ships (on purpose); 38:00 – Making sunsetting easier with Regular portfolio reviews, a visible “sunsetting” column, the Horizon (H1 / H2 / H3) model, and making portfolio decisions one level above teams; 46:00 – Normalizing product lifecycles.
Resources & Links:
Follow Teresa Torres: https://ProductTalk.org
Follow Petra Wille: https://Petra-Wille.com
Mentioned in this episode:
Ways to Work with Petra Wille
Product at Heart
CDH Membership by Teresa Torres
Product Talk by Teresa
Product Talk Academy by Teresa
Enduring Ideas: The three horizons of growth
Join the Conversation:
Have thoughts on this episode? Leave a comment below.
Full Transcript
Full transcripts are only available for paid subscribers.
Ever feel like your product team is “lost in the woods”? I’ve certainly been there—when strategy gets fuzzy, outcomes drift, or constraints aren’t clear. What helped me reframe the chaos was borrowing “lost person” patterns from search-and-rescue and mapping them to product strategy, product discovery, and team behaviors. The result is a practical playbook for product management leadership that keeps empowered product teams moving toward outcomes—not just outputs.
Listen to this episode on: Spotify | Apple Podcasts
Here are the five patterns I see most often—and how I turn each one into forward motion: settle in place (freeze), chase shortcuts, follow the first visible path, use your own navigation (intuition/taste), and retrace your steps. Each of these has a smart, minimal move that helps teams reorient fast without abandoning continuous discovery or product strategy discipline.
Settle in place (freeze). Sometimes the smartest move is to stop. When my team lacks context or authority, I pause delivery work and escalate instead of improvising fixes. This prevents thrash, protects focus, and creates the air cover we need to realign outcomes vs output OKRs.
Chase shortcuts. Shortcuts can be brilliant—or overconfident. I’ve learned to pressure-test whether the “road” is where we think it is before we commit. That means lightweight experiments, clear exit criteria, and the humility to pivot. Think about big bets like Spotify podcasts: compelling vision, but you still have to validate assumptions step by step.
Follow the first visible path. The obvious option isn’t always the best one. My job as a product leader is to make multiple paths visible before we choose. I lean on opportunity solution trees and KPI trees (or driver trees) to surface alternatives, align stakeholders, and keep empowered product teams focused on customer impact and product-market fit—not just the loudest idea.
Use your own navigation (intuition/taste). Judgment matters, especially for product trios making fast calls—but it’s not a replacement for evidence. When my “compass” conflicts with what we observe, I anchor back to customer interviews, rapid tests, and discovery loops. Intuition should guide where we look, while data validates how we proceed.
Retrace your steps. When we’re drifting, I go back to what used to work: principles, quality practices, and discovery habits as feedback loops. Returning to fundamentals—clear problem statements, crisp value propositions, and disciplined outcomes—rebuilds momentum fast.
Team prompt to try: If your team is “lost” right now, which pattern are you defaulting to—and what’s the smallest move you can make this week to get oriented (escalate, test a shortcut, map options, validate intuition with evidence, or retrace to a principle)? I use this question in weekly reviews to keep us grounded in continuous discovery and product strategy.
Resources & Links:
Follow Teresa Torres: https://ProductTalk.org
Follow Petra Wille: https://Petra-Wille.com
Mentioned in the episode:
Lost Person Behavior: A Search and Rescue Guide on Where to Look – for Land, Air and Water
Robert J. Koester
Examples referenced: Xerox, Nokia, Kodak, Volkswagen emissions scandal, Spotify podcasts, large-org tooling contexts like Oracle and SAP
Opportunity Solution Trees: Visualize Your Discovery to Stay Aligned and Drive Outcomes
KPI Trees: How to Bridge the Gap Between Customer Behavior, Product Metrics, and Company Goals
Let's Read Continuous Discovery Habits Together (January 2026) for Continuous Discovery Habits (and the idea of habits as feedback loops)
Shifting from Outputs to Outcomes: Why It Matters and How to Get Started
I’d love to hear how your team navigates these patterns. Which small move will you try this week? Leave a comment below and let’s compare notes on product discovery, stakeholder management, and product roadmapping that actually drives outcomes.
I’m thrilled to invite you to our March session of the CDH Book Club. Continuous Discovery Habits turns five this year. And to celebrate we are reading the book together. I’ve seen firsthand—leading product trios and empowered product teams—that sharpening our discovery habits is the fastest way to better outcomes vs output OKRs, tighter team alignment, and more confident product strategy.
Each month, I am releasing an in-depth reading guide that includes:
The chapters we will be reading
A preview of the most important concepts we'll be learning about
Short videos you can share with friends and colleagues to help spread the ideas
Individual and team discussion questions to help you absorb and engage with the reading
Team exercises to help you put the ideas into practice
Additional reading to help you go deeper on the core ideas
We’ll be discussing each month’s reading in the comment section and we’ll gather quarterly to discuss on a live call. I’ll be there to trade notes, compare experience maps, and share what’s working across product discovery practices.
Joining late? No problem. I monitor the comments on each reading guide throughout the year. Start with the current month or go back to January—whatever works for you. You can ask for help, share what’s working, and connect with other readers at any point.
If you want to participate, grab a copy of the book (or dig up your old copy), share the "Spread the Love" videos, reserve some time to do the team exercises, and register for the community sessions. Let’s do this!
This Month’s Reading
Chapters:
Chapter 4: Visualizing What You Already Know
Estimated reading time: ~14 minutes
This chapter will introduce you to:
Why starting individually—rather than as a group—is the fastest path to unlocking your team’s collective intelligence
How drawing (even badly) forces you to get specific in ways that words never will
The strategic choice of setting your experience map’s scope—too narrow and you miss opportunities, too broad and you lose focus
How diverse perspectives become your team’s secret weapon when you know how to synthesize them
Why your first experience map isn’t truth—it’s a hypothesis you’ll test and evolve with every customer conversation
Need a copy? Grab the book.
Share the Love with Friends and Colleagues
We learn best in community. Use the following short videos to share the key concepts from this chapter with friends and colleagues. Invite them to participate in the book club with you. In my teams, these quick hits help us align faster before we co-create an experience map or opportunity solution tree.
Visualize your thinking – To bring others along
Unlock team alignment – With visualizations
Reflect & Discuss What You Read
When we reflect and discuss what we read, we absorb more of the material. It helps us put what we learn into practice. Don’t skip this step. In my own practice, the real unlock came when I treated mapping as a living artifact that shapes customer interviews, not a one-off deliverable.
Most of us believe we work collaboratively, but we’ve never truly experienced what it means to build shared understanding from diverse perspectives. This chapter challenges you to get uncomfortable—to draw when you’d rather talk, to work alone before working together, and to see your maps as living documents rather than one-time deliverables.
Individual Reflection
Think about the last time your team tried to align on what you know about your customers. Did everyone start by creating their own perspective first, or did you jump straight into a group discussion? What happened as a result?
When was the last time you drew something at work? What stops you from using drawing as a thinking tool—is it discomfort with your drawing skills, lack of time, or something else?
Look at your current work. If you were to create an experience map right now, what scope would you choose? How does your desired outcome help you determine what to include and what to leave out?
Team Discussion
As a trio, each person should identify one unique perspective they bring to your team’s understanding of your customer. How might these different viewpoints create blind spots if you only relied on one person’s view?
When your team disagrees about what customers need or want, how do you typically resolve it? Do you debate until someone wins, defer to the most senior person, or test your different hypotheses?
Does your team have a current experience map? If so, when was the last time you updated it based on what you’re learning from customers? If not, what’s preventing you from creating one?
Put It Into Practice
Understanding why experience maps matter is different from actually creating one that drives your discovery work. These exercises will help you practice the discipline of starting individually, synthesizing diverse perspectives, and using your map to guide customer conversations. My suggestion: timebox, embrace imperfect drawings, and let the artifact lead your next interview script.
Exercise: Create Your Individual Experience Maps
Time: 20 minutes individually, 45–60 minutes with your team
Do this: Individually first, then share with your trio
Start by agreeing on the scope of your experience map based on your current outcome. Each member of your trio should then independently create their own experience map using pen and paper (or your favorite digital drawing tool).
Focus on drawing the customer’s experience, not your product’s features. Where do they get stuck? What goes wrong? How do they work around problems? Don’t worry about drawing well—boxes, arrows, and stick figures are perfectly fine.
Once everyone has created their individual maps, schedule time to share them with each other. As you explore each person’s perspective, ask questions to understand their thinking. Pay particular attention to the differences between maps—this is where the richest insights emerge.
Exercise: Co-Create Your Shared Experience Map
Time: 30 minutes with your team
Do this: With your product trio
Bring your individual experience maps together and work to synthesize them into a single shared map. Start by identifying all the unique nodes (distinct moments, actions, or events) across all three maps. Arrange them in a comprehensive flow.
Collapse similar nodes, but be careful not to overgeneralize. Add links to show relationships and flow between nodes—including loops, error cases, and abandonment points. Finally, add context about what customers are thinking, feeling, and doing at each step.
As you work, avoid getting bogged down in endless debate. If you disagree about details, draw out the difference rather than debating it. This often reveals you already agree or helps you pinpoint exactly where your understanding differs.
Remember: This map is your current hypothesis about your customer’s experience. Use it to guide your upcoming customer interviews and plan to evolve it based on what you learn.
Go Deeper: Additional Reading
If you prefer an audio summary of this month’s reading, including the book chapters and the following resources, I’ve included an audio version for paid subscribers at the bottom of this post.
Supplementary Reading
Why Drawing Maps Sharpens Your Thinking
Core Concept: Collaborative Decision-Making in a Product Trio
Other Voices
To Draw or Not to Draw: Is Traditional Sketching Still Relevant in the Digital Design Era? by Julia Ku
Journey-Mapping Approaches: 2 Critical Decisions to Make Before You Begin by Kate Kaplan
The Visual Language of Comic Books Can Improve Brain Health by Mary Widdicks
Mapping Your User’s Day with the User Clock Sketch by Ben Crothers
Our Live Discussion Schedule
Our live discussion sessions are for paid subscribers. Sessions are not recorded. Invitations will go out to Supporting Members and CDH Members two weeks before the scheduled event. But reserve the time on your calendar now.
Wednesday, March 18, 2026: 9am–10am PDT and 4pm–5pm PDT
Tuesday, June 16, 2026: 9am–10am PDT and 4pm–5pm PDT
Thursday, September 17, 2026: 9am–10am PDT and 4pm–5pm PDT
Wednesday, December 16, 2026: 9am–10am PST and 4pm–5pm PST
Audio Summary
This summary was produced by NotebookLM. The sources supplied were the book chapters as well as all of the additional reading.
Listen here: March — Draw the User Clock to Build Empathy (audio)
This article is part of the CDH Book Club celebrating the five-year anniversary of Continuous Discovery Habits. See all book club posts.
I’ve led product organizations through multiple growth chapters, and the pattern is always the same: the tighter the alignment between product, sales, and marketing, the faster you scale. Reflecting on the journey of Chris Degnan — the first sales hire at Snowflake who spent 11 years helping scale the company from zero to $3.5 billion in revenue as its CRO while partnering with four different CEOs — I’m struck by how consistently the fundamentals win. The playbook isn’t mysterious; it’s disciplined execution, ruthless clarity, and a go-to-market strategy that matures with each revenue stage.
At $10M ARR, the CRO role is hands-on and founder-adjacent. You’re close to the product, running point on key deals, pressure-testing messaging, and building credibility with early customers. By $1B+, the job is organization design: segmentation, international expansion, forecast accuracy, enablement, recruiting, and cross-functional orchestration. The shift is from deal quarterback to system architect — standing up repeatable, auditable processes that produce reliable outcomes across regions, segments, and industries.
Sales leaders who can’t sell the product themselves don’t last. Whether you sit in product management leadership or run the field, you need to master discovery, speak the customer’s language, and translate use cases into value. That also means getting fluent in solutions engineering — understanding integrations, data paths, security, and the operational realities buyers live with. I’ve found this hands-on competence to be the fastest way to earn trust internally and externally, and to keep product strategy grounded in market truth.
The MEDDIC methodology is the foundation for every durable sales org — and, frankly, a founder’s best insurance policy. MEDDIC forces alignment on qualification criteria, from Metrics to Economic Buyer to Decision Process and Identifying Pain. When product and sales both operate to this standard, roadmap bets improve, marketing targets sharpen, and win rates climb. It’s not paperwork; it’s pattern recognition at scale.
High-output CROs obsess over the right numbers. Pipeline coverage by segment and stage; conversion rates through each gate; sales cycle length by use case; average selling price and discount discipline; consumption predictability when you have consumption SaaS pricing; and post-sale expansion velocity. The art is deciding which two or three metrics are the organization’s true north at a given stage — then designing enablement, compensation, and operating cadence around them.
On operating cadence, the week in the life at scale is predictable for a reason. Forecast reviews that surface risk early. Deal reviews that coach to MEDDIC depth, not activity theater. Enablement blocks to uplevel managers and ICs. Recruiting time — always. Customer roadshows to refine value proposition and product positioning. And standing meetings with product, marketing, and finance to keep the GTM motion, roadmap, and unit economics in sync.
Compensation is a force multiplier or a silent saboteur. Keep it simple, consistent, and aligned to the current motion. Early on, weight new logo acquisition and land quality; as you mature, balance new business with expansion, multi-product adoption, and healthy consumption. Guardrails matter — cap over-discounting, reward multi-threading, and avoid plans that create end-of-quarter cliff behavior. The best plans reinforce the behaviors you want your culture to scale.
Technical CEOs often underestimate how much narrative, segmentation, and process discipline great GTM requires. The handoff from founder-led GTM to sales-led growth is where many teams stall. My rule: prove one repeatable motion in one segment before you add complexity. Codify the buyer’s journey, instrument the funnel, and make sure product strategy and enablement move in lockstep.
Culture sets the ceiling. You have to find the fakers, manage-uppers, and passengers quickly — people who look busy but don’t move pipeline, who talk big but avoid accountability, or who ride the momentum of others. The mantra that has saved me endless time: “When there’s doubt, there’s no doubt”. Move fast, but with humanity; be clear on expectations, coach hard, and when it’s not a fit, make the change before the team does it for you.
Feedback is the operating system of a high-performing org. Leaders at every level need to be coachable — on message discipline, on forecast rigor, on how they develop people. I’ve benefited from straight talkers who hold a high bar, and I try to pay that forward. The fastest way to raise organizational IQ is to institutionalize feedback loops across sales, product, and marketing — from post-mortems to win-loss analysis to field-sourced roadmap reviews.
What separates exceptional ICs from the rest? Hunger, intellectual honesty, and a builder’s mindset. They qualify hard, align to customer metrics early, multi-thread to power and value, and partner tightly with solutions engineering. They don’t hide from gaps; they surface them, and they know exactly what they need from product, marketing, and leadership to win.
Executive teams that scale share a few traits: crisp segmentation decisions, single-threaded ownership for outcomes, and healthy conflict that resolves into commitment. Dysfunction, by contrast, looks like metrics roulette, opaque decision-making, and a tolerance for exceptions that become precedent. Make the rules explicit and the exceptions rare.
Leaders like Frank Slootman have popularized intensity, speed, and focus — and there’s real power there when paired with clarity and data. The lesson I carry forward: move fast on people decisions, keep the message simple, and measure what matters. Equally important is knowing where that approach can backfire — when speed outruns learning, or when pressure erodes cross-functional trust. The best operators balance urgency with systems thinking.
Most AI companies will face a go-to-market reckoning. Model quality won’t save a weak motion. The winners will articulate a hard-nosed ROI, solve specific workflow pain, address data governance and security head-on, and show measurable lift — not demo dazzle. In other words, the same fundamentals apply; the stakes and scrutiny are just higher.
If you’re building or rebuilding your revenue engine, start here: define your ideal customer profile and segmentation with ruthless clarity; adopt MEDDIC and teach it across product and sales; align compensation to today’s motion; instrument the funnel and inspect it weekly; and cultivate a culture where feedback is fuel. Do that, and the path from $0 to $3.5B stops feeling like mythology — and starts looking like math.
I’ve learned that the most effective partner product marketing is less about decks and more about decisions. When I collaborate with partner product marketing managers, we translate complex capabilities from a unified analytics platform into crisp, outcome-led narratives that customers can act on. This is where product positioning and go-to-market strategy intersect to create momentum for product-led growth.
In my experience, the strongest partner product marketing managers operate like solution orchestrators. They align value propositions across partners, clarify the problem-solution fit, and articulate competitive differentiation without drowning teams in feature lists. By anchoring messaging in clear customer pains and measurable gains, they help everyone—from solutions engineering to sales—tell the same story with confidence.
My playbook starts with outcomes. We define the “why” in terms customers care about, then quantify it with retention analysis, user activation, and time-to-value. That evidence shapes positioning, enables tighter points of parity and differentiation, and ensures our value proposition resonates in market. The result is faster alignment and fewer cycles spent debating messaging without data.
Cross-functional execution makes or breaks the strategy. I partner closely with solutions engineering to validate solution patterns, and with sales to balance sales-led motions alongside product-led growth. Strong stakeholder management keeps discovery loops tight: we capture objections early, refine narratives quickly, and reduce friction across the funnel.
On the tactics side, I rely on A/B testing to de-risk bold messaging changes and to optimize in-app guides and product tours. We set a minimum detectable effect upfront, instrument journeys with Amplitude analytics, and iterate quickly. This gives the team statistical confidence while keeping speed high—especially when refining narratives for complex partner solutions.
Ultimately, great partner product marketing illuminates the shortest path from capability to customer value. When we pair disciplined positioning with data-driven learning, we strengthen our go-to-market strategy and build durable competitive advantage. That’s how we turn strong solutions into market-leading stories that win—and keep—customers.
Inspired by this post on Amplitude – Best Practices.
I’m sharing a focused set of insights on analytics, experimentation, and personalization designed to help teams ship smarter, reduce risk, and accelerate outcomes. Drawing on years of leading product teams, I translate complex data practices into practical playbooks you can apply immediately to improve user activation, conversion, and retention.
My approach starts with a strong measurement foundation. I lean on a unified analytics platform—often powered by tools like Amplitude analytics—to centralize product, marketing, and customer success signals. With clear event taxonomies, consistent governance, and trustworthy dashboards, teams gain a single source of truth to prioritize the right problems and sequence roadmap bets with confidence.
Experimentation turns insight into evidence. I emphasize A/B testing discipline, including minimum detectable effect (MDE), guardrail metrics, and pre-registered hypotheses. This repeatable system lifts decision quality, shortens feedback loops, and aligns cross-functional partners around what actually moves the needle, not what merely sounds promising.
Personalization compounds the value of experimentation by delivering the right value to the right segment at the right moment. Thoughtful in-app guides and product tours—rooted in behavioral signals—nudge users through friction points and increase the likelihood of early wins. The result is a more intuitive path to first value, stronger user activation, and healthier long-term engagement.
Retention is the ultimate scoreboard. I rely on retention analysis, cohorting, and leading-indicator metrics to connect feature usage to durable outcomes. When paired with product-led growth motions, teams can identify activation thresholds, build habit loops, and scale what works without overextending sales or support capacity.
If you’re getting started, begin with a crisp instrumentation plan, shared definitions, and a lightweight review ritual. Use continuous discovery practices, opportunity solution tree mapping, and driver trees to tie data signals to real user problems. From there, iterate: test small, learn fast, and scale what is proven. Over time, this system becomes a flywheel for product strategy—fewer debates, more evidence, better products.
In this series, I distill the frameworks, templates, and real-world lessons that have consistently improved outcomes for product teams: how to structure experiment backlogs, how to read funnel breakpoints, how to detect false positives quickly, and how to operationalize analytics for day-to-day decisions. Expect practical guidance you can copy, adapt, and run with immediately.
Inspired by this post on Amplitude – Perspectives.
I’ve been reflecting on why so many revenue leaders are at risk of falling behind, and the conclusion is stark: fewer than 10% of current CROs will thrive by 2028. That isn’t hyperbole—it’s a wake-up call for how quickly go-to-market strategy, organizational design, and AI-driven execution are evolving. From my seat leading product, I see the pressure building on the CRO role to orchestrate the entire revenue system, not just run a sales team.
One story that crystallizes this reality comes from the journey of Stevie Case, the CRO of Vanta, the trust management platform serving everyone from founders to Fortune 100 CISOs. A former pro-video gamer who stumbled into sales through a mentor’s bet, she exemplifies how unconventional paths can drive unconventional insight. Her trajectory underscores a bigger truth I’ve witnessed across companies: the best revenue leaders aren’t just great sellers—they’re builders who understand product, process, and people at scale.
Why do early revenue hires fail? In my experience, it’s rarely about raw talent. It’s about fit, scope, and time horizon. Early-stage teams often hire coin-operated closers to sprint for this quarter’s number, when what they actually need are long-term builders who can shape ICP clarity, pipeline math, and repeatable motion. The trap is simple: you hire for momentum before you’ve validated the motion. That misalignment shows up at 00:00 Why early revenue hires fail and again at 04:16 Coin-operated sellers vs. long-term builders—two ideas every founder-led GTM team should internalize before the first half-dozen sales hires.
What separates a VP of Sales from a top 1% CRO is scope and systems thinking. A true CRO owns the full revenue engine—marketing, sales, solutions engineering, customer success, pricing, channels, and post-sale activation—not just the new-business line. It’s a role defined by precision around 07:44 Metrics, confidence, and velocity and the courage to decide when to centralize vs. decentralize capabilities as you grow. Should CROs lead sales? At 12:04 Should CROs lead sales?, the nuance is clear: yes, if the motion is still coalescing; not necessarily, once the machine is humming and specialization unlocks scale. My rule of thumb: start consolidated for speed of learning; split functions only when interlocks are provably robust.
There’s a humbling lesson in 16:36 Learning to scale at Twilio and 19:58 Stevie’s scaling mistake at Vanta: copying another company’s operating system, even a world-class one, is an easy way to blunt your edge. Context is king. What worked at Twilio won’t automatically work at a trust management business. That’s why the line at 17:44 “There is no CRO playbook” resonates so deeply. There are principles—org design, segmentation, enablement, compensation, customer activation—but your playbook must be bespoke to your product, pricing, cycle time, and buyer power map.
22:16 Why Vanta stays 100% sales-led is a reminder that not every high-growth motion demands product-led growth. In categories where compliance, security, and risk shape buying behavior, a consultative, sales-led approach builds trust and shortens time to value—especially when solutions engineering, onboarding, and customer success are tightly choreographed. I’ve seen teams chase PLG headlines while ignoring the higher-ROI path right in front of them: nailing the sales-led experience, from first touch to first value.
Top CROs plan 24–26 months ahead. 23:16 The value of planning 24-26 months ahead isn’t about creating perfect forecasts; it’s about designing optionality. That means hiring with stage gates, building enablement before you feel “ready,” instrumenting activation and retention early, and pressure-testing your pricing and packaging quarterly. In my org reviews, I push for scenario modeling: what breaks at 2x volume, what centralizes again at 600 headcount, and what competencies must be grown vs. bought.
On judgment and decision quality, 29:54 When trusting intuition was the wrong call is a familiar leadership tax. Pattern recognition is powerful—until it isn’t. I’ve learned to pair intuition with a data backstop and a lightweight pre-mortem: what would have to be true for this to fail? It’s the same posture I take with AI in GTM. At 30:49 Do humans still have a place in the future of GTM? and AI vs. humans in go-to-market, the answer is yes—but augmented. Humans set narrative, negotiate ambiguity, and build trust; AI accelerates research, writing, discovery, and coaching. The winning motion fuses both.
I’m often asked which tools materially shift outcomes. For revenue intelligence and operational rigor, I look to systems that compound learning: Gong: https://www.gong.io/, Salesforce: https://www.salesforce.com/, and Cursor: https://cursor.sh/. To study benchmark operating models and developer-led growth infrastructure, Twilio: https://www.twilio.com/ remains instructive. And to understand why trust, security, and compliance can define the entire GTM architecture, Vanta: https://www.vanta.com/ is a useful case study.
Leadership non-negotiables matter more as you scale. 33:33 Stevie’s leadership non-negotiables reminded me to be explicit about standards: clarity over activity, customer outcomes over internal wins, and auditability over anecdotes. 36:36 The myth of hiring for industry expertise shows up again and again—I’d rather hire for learning velocity, systems thinking, and builder DNA than narrow domain familiarity. And at 40:00 What stays centralized in a 600-person company, remember: centralize what must be consistent (data, tooling, pricing guardrails, core enablement), decentralize what benefits from speed and context (segment plays, partner motions, field marketing).
If you prefer a structured digest, here’s the operating checklist I use with revenue and product peers: define your ICP and value proposition crisply; hire builders over coin-operated sellers; instrument the first 30 days post-sale (47:09 The hidden leverage of a customer’s first 30 days); align pricing, packaging, and onboarding to activation; model capacity and hiring plans on 24–26 month horizons; decide early what stays centralized; use AI to amplify discovery, coaching, and content while keeping humans front-and-center for trust-building; and cultivate an unvarnished CEO–CRO pact (01:02:30 Unpacking the CEO-CRO dynamic) that aligns on strategy, segmentation, and sequencing.
For those who want a few timeline highlights: 00:00 Why early revenue hires fail; 02:23 Who to hire at $5M in revenue; 05:57 What excellence looks like in the CRO role; 17:44 “There is no CRO playbook”; 22:16 Why Vanta stays 100% sales-led; 23:16 The value of planning 24-26 months ahead; 47:09 The hidden leverage of a customer’s first 30 days; 53:42 Why the CRO role will face enormous changes by 2028; 58:42 What leaders must do now to stay relevant.
The throughline is simple and urgent. 53:42 Why the CRO role will face enormous changes by 2028 isn’t a forecast—it’s a present-tense mandate. 58:42 What leaders must do now to stay relevant: build a revenue system, not a sales team; plan further out while executing faster; let AI handle the mechanical so your people can master the human. Those who internalize this shift will be the fewer than 10% of current CROs who thrive by 2028. The rest will be outpaced by change they could have anticipated—and designed for.
I write from a place many product leaders know well—the moment when the data you need to make decisions simply doesn’t exist, and you have to build the capability from the ground up. That firsthand experience with gaps in analytics shaped how I think about product strategy, product discovery, and the relentless pursuit of product-market fit lessons.
In my work, I lean on continuous discovery to surface the most meaningful problems, then translate those insights into outcomes vs output OKRs that keep teams focused on impact. When we anchor roadmaps to real user behavior and business results, we avoid vanity metrics and create a durable plan that compounds learning over time.
Execution matters just as much as insight. I rely on rigorous A/B testing, clear minimum detectable effect (MDE) thresholds, and retention analysis to separate signal from noise. This discipline ensures that every iteration—whether it’s a small UX nudge or a bold bet—moves us closer to measurable value for customers and the business.
None of this works without empowered product teams. I build around product trios that partner tightly across design, engineering, and product, and I foster a product-led growth mindset so we earn activation, engagement, and expansion through the experience itself. The goal is to create a system where learning is fast, ownership is clear, and the user’s job-to-be-done stays front and center.
On the tooling side, I favor a unified analytics platform so insights are consistent from discovery to deployment. Whether I’m instrumenting funnels with Amplitude analytics or stitching together qualitative and quantitative inputs, the principle is the same: give teams trustworthy, real-time visibility so they can make better decisions, faster.
If you’re looking to operationalize these practices, you’ll find practical playbooks, decision frameworks, and real-world examples here—built for leaders who want clarity, speed, and confidence in how they discover, ship, and scale products.
Inspired by this post on Amplitude – Best Practices.
I hear the same refrain from product leadership peers everywhere: we’re overwhelmed. Shrinking headcount, constant AI disruption, economic uncertainty, and relentless context switching make it feel like we’re carrying two jobs—setting strategy while shielding our teams. I recently listened to an episode of All Things Product that zeroes in on what a real support system for product leaders looks like, and it resonated deeply with my day-to-day.
Want to listen to the conversation yourself? Find it on Spotify or Apple Podcasts.
Here’s the core tension I see (and felt early in my own leadership journey): product leaders tend to underinvest in themselves. We hold onto work because it feels faster, safer, or “just easier if I do it.” But that pattern quietly taxes strategy, slows learning, and caps team throughput. The hidden cost of “doing it all yourself” is real.
Early in my tenure leading product, I tried to keep every plate spinning—roadmap reviews, stakeholder prep, user research, executive updates—while protecting my team’s focus. I was busy and useful, but not maximally valuable. The turning point came when I started building a lightweight support stack: a few hours of executive assistant help each week, targeted research support for bet sizing, and a personal cadence with a leadership coach. The result wasn’t just more time; it was better time.
One provocative point that landed hard: product leaders rarely have executive assistants—and that’s a problem. If your calendar is your operating system, an EA is an extension of your leverage. Mine now handles scheduling, meeting hygiene, prep packets, and post-meeting artifacts. That shift moved me from “calendar triage” to “strategic curation.” It also reinforced a core principle: delegation is a leadership skill, not a weakness. When I delegate outcomes (not just tasks), my team learns, ownership grows, and we ship decisions faster.
Support for strategy work shouldn’t stop at the calendar. Research and data enable better bets. Lightweight research ops, access to product analytics, and brief synthesis sprints keep me anchored in evidence without drowning in artifacts. Paired with a strong community of practice, I get a steady stream of comparative patterns—how other leaders delegate, scope advisory boards, or run decision reviews—which short-circuits trial-and-error.
Coaches were framed as shortcuts for clarity, accountability, and skill-building—and I agree. A good coach compresses cycles, sharpens decision quality, and holds the mirror up when you drift into doer mode. Two quotes captured the mindset perfectly: “You are a pro athlete. It makes sense to think about how you scale your impact without adding more to your calendar.” — Petra Wille. “As you get busier, it becomes more important to focus on the value only you can bring.” — Teresa Torres.
There’s also a helpful nudge to let go of perfectionism: “80% done by someone else is 100% awesome.” — Dan Martell (quoted). In practice, that means I accept great drafts from others, then add the 10–20% only I can contribute—context, narrative, and the sharp edges of the decision.
What about AI? The conversation hits a practical middle ground I share: use AI where it compounds leverage—meeting summaries, research synthesis starters, doc outlines, and backlog triage. But keep humans where judgment, alignment, and context truly matter—strategy framing, stakeholder management, and the final decision-making loops. In other words, apply an AI Strategy that respects product leadership’s uniquely human work.
Key themes I took away: why product leaders struggle to scale themselves; the true cost of “doing it all yourself”; why not having executive assistants limits impact; delegation as a core leadership capability; how to identify and protect the work only you can uniquely do; using research and data to inform strategy; coaches as accelerators for clarity and accountability; communities of practice as a force multiplier; adopting a “professional athlete” mindset; when AI helps—and when humans still matter; and the liberating mantra that “80% done by someone else is 100% awesome.”
If you’re wondering where to begin, start small and practical. Audit your time: what work truly requires you? Experiment with small amounts of support (even a few hours a week). Delegate outcomes, not just tasks. Keep the hands-on work you love—but be intentional. Use peers, coaches, and communities to learn how others delegate. Don’t wait until burnout to build your support system.
Resources mentioned if you want to go deeper: Follow Teresa Torres: https://ProductTalk.org. Follow Petra Wille: https://Petra-Wille.com. Petra’s Coaching for Product Leaders: https://www.petra-wille.com/coaching-packages. Dan Martell’s book Buy Back Your Time: https://www.buybackyourtime.com.
I’m curious: what’s one outcome you’ll delegate this week, and what support would make it stick? Share your thoughts in the comments—your playbook might be exactly what another product leader needs right now.
I keep a simple mantra front and center: Figma is not the source of truth. The customer is. In practice, that means the only thing that truly counts is what we ship, how it performs, and whether users come back for more. Mockups are hypotheses; production usage is evidence. When my teams adopt this lens, velocity improves, judgment sharpens, and quality rises where it matters most.
So what does design actually do in a software company? At its best, design builds leverage for the whole system—engineering, product, and marketing—by clarifying problems, raising the quality bar, and making complex decisions legible. The standard I hold is ancient and still essential: products must be useful, usable, and desirable — and above all, used. When we calibrate around “used,” debates about pixels give way to outcomes, and cross-functional partners feel the difference.
I often trace the roots of our craft back well beyond the digital era. The lineage from industrial design to software is real; constraints, ergonomics, affordances, and systems thinking didn’t start with screens. If you’ve ever mapped delight, performance, and reliability in a Kano Model, you’ve touched this lineage. The translation to software is simple: design the full journey, not just the interface—prioritize what improves time-to-value, reduces cognitive load, and earns habitual use.
One lesson I’ve learned the hard way: why design leaders who stop designing stop leading. I still sketch flows, write UX copy, and prototype when it unblocks the team or sets a decisive quality bar. The altitude changes constantly—one hour I’m in a strategic roadmap review, the next I’m in a critique or poking at a prototype. Great design leaders jump up and down in altitude to connect vision to details without becoming a bottleneck.
Over time, I’ve come to rely on four pillars every design manager must master: craft (raising taste and execution), product strategy (clarifying choices and trade-offs), people leadership (coaching, feedback, and hiring), and systems (processes, rituals, and design ops that scale). Neglect any one of these and either quality, speed, or team health will eventually falter.
Perfectionism is a double-edged sword. Over-indexing on quality can paralyze decision-making, but lowering the bar indiscriminately is worse. I’ve seen moments where relaxing standards to “go faster” actually cost the business—rework piled up, trust eroded, and customer value stalled. The answer is principled delegation: I define what “must be true” at each milestone, delegate ownership with clear guardrails, and reserve my veto power for moments where product integrity is genuinely at risk.
Measuring success as a design leader starts with outcomes vs output OKRs. I care about activation, retention, time-to-first-value, NPS verbatims tied to key journeys, and the operational metrics that earn the right to build the next thing. Design output is visible; design outcomes are durable. When trade-offs are needed, I optimize for the smallest shippable surface that still proves the core value proposition, then expand with data.
Scaling judgment is the multiplier. I build it through pattern matching—studying enduring product systems from companies like Airbnb, Amazon, Apple, Asana, Notion, Stripe, Nest, and others—to distinguish where polish compels usage versus where it’s ornamental. Strong opinions matter, but so does being easy to convince with new evidence. I encourage designers to articulate the pattern they’re invoking, why it fits the job-to-be-done, and how we’ll know it worked.
Operating cadence matters. My week is anchored around recruiting, crits, and staff meetings that actually make decisions. In critiques, I use the Do/Try/Consider framework to give actionable direction without micromanaging. On one-on-ones, the question isn’t “Should one-on-ones exist?” but “What are they for right now?”—coaching, performance, or clearing execution blockers. If a meeting doesn’t increase clarity or commitment, it gets redesigned or removed.
Execution-wise, I’ve taken inspiration from Rippling’s operating system—especially its emphasis on speed, precise ownership, and hard commitments. The lesson is timeless: go fast on the right things, make clear promises, and instrument your work so you can see reality quickly. When speed is paired with crisp decision rights and observable outcomes, momentum compounds rather than frays trust.
Hiring your first design leader? Look for someone who can set standards, scale judgment, and ship. They should be able to zoom from company narrative to interaction copy in a single afternoon, coach product trios, and build rituals that make taste and trade-offs explicit. Above all, they should have a point of view on where quality moves the business and where speed is the quality.
Here’s how my team’s approach differs from many: Figma is not the source of truth. We design in Figma, but we learn from production. We pair designers with engineering early, prototype in code when it reduces risk, and wire telemetry into every critical path. Product trios use discovery to validate “useful, usable, desirable — and used,” then commit to outcomes with clear, testable definitions of success. The result is faster iteration, fewer surprises, and experiences customers actually adopt.
The throughline is simple and demanding: design for reality, not for the board. Keep your standards where they create business value, scale judgment with explicit patterns, and instrument everything so learning never stops. When teams embrace that, the work gets better, customers feel it, and the roadmap starts to pull you forward.
Executive function, for me, is the art and discipline of building systems that make high-quality decisions without my constant involvement. The real unlock isn’t personal heroics; it’s institutionalizing judgment. When I do my job well, teams move faster, ambiguity shrinks, and the organization compounds learning even when I’m not in the room.
Operating simultaneously at 30,000 feet and ground level is the defining muscle of executive leadership. I deliberately switch altitudes. At 30,000 feet, I obsess over strategy, architecture, and resourcing. On the ground, I validate core assumptions with firsthand data, listen for weak signals, and spot process cracks before they widen. Altitude changes are not random; they’re triggered by variance from plan, critical customer moments, or leading indicators that deviate from expected ranges.
The leap from frontline manager to manager of managers is where many rising leaders stall. As a manager of managers, my primary value shifts from personal execution to system design. I move from answering questions to installing mechanisms that ensure questions get answered well by others. This includes clear decision rights, shared metrics, and repeatable, lightweight rituals that scale across teams.
What is an executive actually accountable for? Outcomes over output, talent density, and the clarity of the operating system. That means defining strategy, aligning resources, creating a cadence of review that exposes truth, and ensuring incentives reward the behaviors we want. My barometer: if I step away, do priorities hold, do metrics behave as expected, and do tradeoffs land where I would have landed?
Knowing when to dive deep versus when to step back is a craft. I dive deep when risks are existential, when metrics have no credible owner, or when narrative and numbers diverge. I step back when leaders demonstrate consistent judgment, metrics sit inside control limits, and learnings are documented. The principle I return to again and again: context is everything. Senior leaders operate on context, not control.
To scale judgment, I teach people how I think. I externalize my mental models: how I construct decision trees, how I stress-test assumptions, and how I weigh time horizons. I rely heavily on driver trees for metrics because they force causal clarity. If we can’t map how a top-line goal decomposes into controllable levers, we’re managing by hope, not design.
Creating a shared language across the business is a force multiplier. I standardize definitions for our core metrics, codify what “good” looks like, and make it easy to repeat the system. We align around outcomes versus output, and we use cadences like MBRs and QBRs to unify narrative and numbers. Shared language makes decisions legible across functions and reduces rework.
My COO playbook emphasizes owning the full customer experience end to end. When marketing rolls up under a COO in certain stages, the upside is coherence: one narrative from awareness to activation to expansion, one set of metrics, one growth engine. The point isn’t org charts; it’s removing seams customers can feel.
Demanding and supportive is not a contradiction. I set ambitious, unambiguous bars and back them with coaching, resourcing, and fast feedback. The combination builds trust: expectations are clear, and help is immediate. I expect leaders to bring problems paired with proposed solutions and to escalate early, not perfectly.
Inside my executive interview process, I’m assessing altitude agility, operating cadence, and taste in metrics. I use structured interviews and live case workshops to see how candidates frame ambiguous problems, build driver trees, and prioritize tradeoffs. The best prompts are simple and revealing: design the operating system for a 3x scale scenario; diagnose a broken funnel with incomplete data; align two teams with conflicting incentives. The workshop prompts that reveal everything surface thinking speed, humility, and the instinct to make context legible.
The common thread in failed executive hires is a mismatch between the company’s operating system and the leader’s default mode. Some leaders can’t stop doing the work themselves. Others stay too abstract and never build mechanisms. I look for demonstrated ability to change systems, not just run them—leaders who can both author and evolve the playbook.
On metrics, I practice the driver tree philosophy. I begin with the North Star, decompose it into controllable levers, instrument each node, and assign single-threaded owners. We design review cadences where deviations trigger targeted diagnostics, not thrash. Each tree has documented assumptions, data sources, and thresholds that prompt action. This is how teams learn to anticipate, not react.
High-functioning executive teams are visibly collaborative. We clarify decision rights, disagree and commit quickly, and conduct post-decisions to harvest learnings without blame. My favorite litmus test is simple: can 30 people operate as one team when it matters? When we get this right, information flows, execution accelerates, and customers feel consistency.
One of the most counterintuitive leadership lessons is working yourself out of a job. If the system cannot run without you, you have a key-man risk, not a leadership strength. I aim to build successors, codify judgment, and design mechanisms that make good decisions the default state. That’s how you create durable, compounding advantage.
And the review feedback you can’t unhear? Mine was brutally honest: my bar was high, but my mechanisms were implicit. Once I wrote them down—how I decide, what I expect, where I dive deep—the organization moved faster, and I actually became less central. If there’s a throughline to extraordinary leadership, it’s this: make your judgment teachable and your systems inevitable.
