I just talked through some of the messiest moments of my career on a podcast. Here’s why I said yes.

When Andrew Capland reached out about coming on Growing Forward, my first instinct was the one most people in this industry have: curate. Lead with the wins. Tell the stories that make the journey look like a straight line.

I didn’t do that.

Because the straight-line version of any career is a lie, and honestly, not a very useful one. The stuff that actually made me a better product leader and manager wasn’t the launches that worked or the growth metrics that looked good in a board deck. It was the moment in Nairobi when I realized every playbook I’d carried over from Silicon Valley was essentially useless. It was the product I insisted on shipping at Rewarder while my own PMs were telling me it wouldn’t work — and then watching it hurt conversion. It was working out a year of tension with a Czech CTO on a Kenya safari, no internet, nowhere to go.

That’s the episode.

Andrew has a gift for getting past the polished version of the story. We talked about what it actually feels like when your expertise stops being the answer and starts being the assumption you need to question. We talked about the transition from player to coach — why the instincts that made you a great IC will actively work against you the moment you’re managing a team. We talked about “front stabbing,” radical candor, and what happens when your leadership values collide with the culture of a company you actually need to make work.

There’s also a section near the end on building range across industries rather than going deep in one vertical that I think most people in product and growth underweight. If the book Range by David Epstein has been on your shelf unread, consider this your nudge.

This is the Growing Forward podcast with Andrew Capland. I’ll drop the link below. If you’ve been following this Substack for a while, a lot of what we cover in the episode connects directly to things I’ve written here — but heard out loud, with the real texture of what it felt like in the moment.

Quick version of what you’ll get from this episode:

• Why “I was hired because I know the answer” is the wrong frame — and what replaces it

• The early management mistake I made that taught me the difference between being the best person and the right person for a given task

• What a Kenyan street-corner DVD vendor taught me about product-market fit

• Why making yourself redundant is actually the goal

Stop Asking Users What They Want

When I think back on the most valuable customer discovery I’ve ever done, none of it happened behind a desk.

When we were working on Zenly, we used to take our prototypes straight to the street. No script, no formal testing setup. Just us, an iPhone build on TestFlight, and a stranger who fit our target demo (usually someone between sixteen and twenty-five). We’d hand them the phone and say, “Try it. Tell us what you feel.”

Then we’d film everything.

It sounds chaotic, but those unfiltered reactions (the confusion, the hesitation, the small flashes of delight) taught us more than any polished usability lab ever could. Watching someone struggle through your onboarding is deeply uncomfortable. That’s exactly why it works.

The Discomfort is the Point

Most founders want validation. What they need is friction.

Because friction tells you where the product actually breaks, not where your hypothesis says it should.

So much of discovery is about getting comfortable being uncomfortable. You’re not there to guide the user to success. You’re there to watch what happens when you don’t.

Film them. Capture both their screen and their face. You’ll see the truth in their expressions before you ever hear it in their words.

The One Thing AI Can’t Replace

Here’s what I remember most from those Zenly sessions:

A sixteen-year-old girl in Paris picked up the phone, opened the app, and her face went completely blank. Not confused. Not frustrated. Just… nothing. She tapped around for maybe ten seconds, then locked the screen and handed it back.

“I don’t get it,” she said.

That moment (that specific emptiness in her expression) changed our entire onboarding flow. We’d been so focused on explaining *features* that we forgot to explain *why you’d care*. An AI could’ve told us our retention numbers were bad. It couldn’t have shown us that look.

AI is incredible for synthesis. You can drop transcripts into an LLM, spot patterns instantly, generate summaries in real time. But if you skip sitting next to users and feeling their confusion, you lose the thing that actually matters: the gut punch of watching someone not understand what you’ve built.

When someone struggles through your flow in person, it rewires something in your brain. You can’t unsee it. You can’t rationalize it away. And you sure as hell can’t ignore it in your next sprint.

That’s not data. That’s empathy. And you can’t automate it.

Iterate in Hours, Not Weeks

At Zenly, we’d run three or four user sessions in a single day.

Build in the morning, test at lunch, rebuild in the afternoon. The moment feedback started to converge, we knew we were close. There’s no reason to wait weeks for a “research readout” anymore. The tools exist to synthesize in real time. But the feedback still needs to come from real humans, not survey panels.

Here’s a trick I still use: If a session goes perfectly and the user never looks confused, it’s probably a waste.

If they frown, hesitate, or ask “Wait, what am I supposed to do here?” That’s gold. Those moments are what you timestamp and dig into later. Because that’s usually where the product is broken, or occasionally, where it’s brilliant.

And the nice thing is that with AI and the ability to rapidly prototype, you can do this even more quickly than we did it just 4-5 years ago. The methodology still matters, but the speed of iteration can be even faster now with the latest tools - this is what we’re doing at Troon to test and rapidly ship.

Context Changes Everything

One of my favorite examples of discovery in action came from Showmax, our streaming video product in Africa.

We assumed we were competing with Netflix. Turns out, we were competing with *the movie guy*. A local who torrented shows, burned them to DVDs, and sold them on the street. He was the entire recommendation engine for Nairobi.

That one discovery changed our roadmap completely: bandwidth optimization, offline downloads, local caching. None of which would’ve come up in a U.S. customer interview.

We only found that out because we went there. We sat in people’s homes. We asked how they actually watched movies, not how they *wished* they watched movies. And we paid attention when the answer didn’t match our assumptions.

You can’t phone that in. You can’t simulate it in a survey. You have to go.

The Real Feedback Loop

Customer discovery isn’t about the perfect script or the right questions.

It’s about being present enough (and humble enough) to watch people use what you’ve built, fail with it, and tell you the truth without words. That blank look. That hesitation. That moment where they almost get it, but don’t.

Most founders are terrified of that feedback. I get it. It’s brutal to watch someone not understand the thing you’ve spent months building.

But that discomfort is the entire point.

Because on the other side of it is a product people actually want to use. Not the one you wanted to build. The one they need.

And the only way to find that gap is to sit in it.

The best education I got throughout high school and college wasn’t in the classroom. It was through competitive debate. I spent years immersed in it—first in high school, and then on a parliamentary debate team in college. While I certainly learned a great deal from formal academics, when I look back, the skills I rely on every single day as a product leader came from those debate rounds.

Quickly responding to complex argumentation. Pre-morteming potential objections. Structuring a compelling narrative under time pressure. Presenting with clarity and confidence in front of a skeptical audience. Debate taught me all of this.

In college debate, the format was fast and intense. You’d get the topic 20 minutes before the round. That meant 20 minutes to determine your position, prep arguments, anticipate rebuttals, and structure a case. You didn’t get hours to plan. You got 1,200 seconds. The pressure forced clarity.

You had to:

• Come up with a strategic argument

• Think two steps ahead of the other side

• Practice mental agility by preparing to argue both sides

• Deliver it with composure and persuasion

If that doesn’t sound like product work, I don’t know what does.

Those foundational skills—structured thinking, anticipation, clarity under pressure—became my superpowers later as a PM and product leader. Whether it’s in a pitch, a team offsite, or an executive review, the same lessons apply.

Now, I’m teaming up with Elena Luneva to teach a FREE 45-minute virtual Lightning Lesson called Master Public Speaking. It’s designed to help senior leaders and professionals become more confident, composed, and clear in external presentations. Whether that’s on stage, in a boardroom, or on a client call.

Enroll here → https://maven.com/p/84a825/master-public-speaking

What We’ll Cover

This isn’t a webinar. It’s a hands-on session focused on tools, not theory. The goal is to give you a structure and a set of habits that help you deliver your message with authority.

Start with Why: Presence = Perception

Your presence is often the first thing people notice. In high-stakes settings, it’s how they decide whether to trust you. We’ll start by unpacking that idea and reframing what presence really means. It’s not polish. It’s being composed, clear, and connected.

Build a Structure That Works

A strong presentation needs to feel effortless, even when it’s not. We’ll break down a practical, four-part structure:

• Understand your audience: Who are they? What matters to them?

• Focus your message: One clear takeaway beats five scattered ideas.

• Reinforce with the right details: Use a few well-placed stories, stats, or analogies.

• Close with intention: Leave people with a point of view, an ask, or a moment that sticks.

Simple structure = better retention.

Prep Smarter, Not Just Longer

Most people under-prepare for external talks. Even fewer prepare the right way. We’ll show you how to:

• Rehearse out loud (yes, always out loud)

• Use video feedback to identify weak spots

• Leverage AI tools like Yoodli and ChatGPT to pressure-test your message

• Anticipate tough questions and map out bridge-back answers

• Tighten up areas where you tend to ramble or over-explain

The goal here isn’t to memorize. It’s to get comfortable and intentional.

Show Up with Authority

How you deliver your message matters just as much as what you say. We’ll cover:

• Eye contact that actually feels like connection (even over Zoom)

• Posture, stillness, and how to avoid distracting habits

• Using your voice as a tool to carry meaning

• How to pause effectively, instead of filling space with “um” or “so”

This is where a lot of people lose the room. But it’s also where small changes create outsized results.

Make Them Care

You can’t influence people if they don’t feel something. That’s why we’ll spend time on emotional connection:

• Tell a short, relevant story that shows what’s at stake

• Use analogies to simplify complex ideas

• Don’t just present information—relate to the audience’s goals or struggles

If you want your message to be remembered, it has to resonate.

Wrap with Intention

We’ll close with a quick recap:

• Clear structure earns attention

• Deliberate prep builds confidence

• How you show up shapes how you’re perceived

• Stories help people connect and remember

And we’ll leave you with a question to reflect on: What’s one change you’ll make before your next talk?

This session is for anyone who wants to become a more effective external communicator. You don’t need to be flashy. You just need to be clear, prepared, and intentional.

Join us for Master Public Speaking. You’ll walk away with a repeatable system and sharper instincts—skills you can use immediately.

Sign up here → https://maven.com/p/84a825/master-public-speaking

• Generative AI is becoming the entry point to many products — not just a backend tool or internal feature.

• Product teams need to rethink UX, success metrics, and team structures to keep up with intent-driven experiences.

• A chatbot isn’t always the right interface — the best experiences embed AI into the natural flow of work.

• PMs who succeed here will focus less on novelty and more on removing friction between user intent and outcomes.

The Shift Is Already Here

Generative AI isn’t just a backend superpower anymore — it’s becoming the front door of the user experience.

Today, products like Notion AI, Perplexity, and Klarna’s shopping assistant aren’t hiding AI in a settings tab. They’re starting with it. The interaction begins with intent, not navigation. The user says what they want, and the product responds in context — sometimes better than a traditional interface ever could.

The traditional UI stack — menus, dropdowns, toolbars — is giving way to interfaces that listen, think, and act.

A big moment happened for us at Figure when we saw Klarna launch their automated support agents. Lending products often require human intervention — people have questions, documents need review, and there are moments where support feels critical to moving the process forward.

But watching Klarna’s approach inspired a new direction. We realized that many of the common questions and core workflows — especially around document verification — could be handled better by AI. That insight led us to an intensive effort to overhaul the support experience, integrating AI more deeply into both borrower interactions and backend review processes. The result? A better experience for users and relief for our operations team, which had been overwhelmed with inbound support.

This shift isn’t just about new technology. It’s a redesign of how we guide users, deliver value, and scale product operations.

When the Interface Starts Thinking for the User

Generative interfaces flip the script. Instead of designing fixed steps and flows, product teams are now building systems that interpret intent and dynamically generate the next best step — often bypassing the need for traditional UX at all.

What’s changing:

• From guided workflows → to adaptive systems

• From user navigation → to AI-led outcomes

• From task completion → to goal fulfillment

Historically, great products solved this through smart UX and a lot of design thinking. Take Turbotax, for example. I didn’t work on it directly, but at Intuit, it was well known how much work went into the filing experience — teams carefully designed every interaction, every edge case, and every possible variation in a tax situation.

But it was a massive undertaking. You needed huge teams to manually map all the scenarios and walk users through them.

Now, imagine applying an LLM to that experience. Instead of rigid flows, you could guide the user to exactly the right step based on what they’ve done before, what they’ve uploaded, or how they describe their situation — dramatically simplifying the experience while handling edge cases more flexibly.

Another example from my own experience: At Booking, I was set to lead efforts around multi-leg trips — a feature we believed had strong potential. The idea was to help users plan more complex journeys by linking destinations. But the challenge was always predicting the next best destination and sequencing the trip in a way that made sense. Without strong signals or user input, it was hard to know where to take the experience next.

With today’s AI capabilities, though, this is entirely different. Now we can start with user intent: “I’m going to Tokyo and want to explore two nearby cities.” AI can take past travel behavior, preferences, proximity, and even seasonality into account to suggest incredible itineraries. That’s a level of product thinking we just didn’t have access to before — and it’s what makes generative interfaces so powerful.

Redefining Success: New Metrics for Generative UX

Once AI starts taking the wheel in your product, traditional metrics can quickly become misleading.

Time on site? Lower might be better.

Click-through rates? Irrelevant in a dynamic flow.

Funnel conversion? Hard to track when steps are fluid and personalized.

Instead, the new indicators of success include:

• Time to value: How quickly does the user get what they need?

• Response quality: Was the AI accurate, confident, and helpful?

• Trust: Do users accept the AI’s suggestions, or fall back to manual flows?

• Resolution rate: Did the AI complete the task without human intervention?

As these interfaces take shape, you’ll need to rethink your analytics stack and your definition of success. Outcomes matter more than process.

Your Team Needs to Build Differently

You can’t just slap a chatbot onto your product and call it a day. These experiences require cross-functional, AI-native teams.

To build well, you need:

• PMs who understand model behavior, prompting, and fallback UX

• Designers who think in conversation flows and trust states

• Prompt engineers to shape LLM responses and behavior

• Model ops / ML leads to manage fine-tuning, latency, and performance

This isn’t a feature team bolted to your existing product squad. It’s a core product function that spans user experience, system design, and intelligence.

A Framework: Layering AI into the UX Stack

Not every product needs a full conversational interface. Here’s a simple way to think about integrating AI progressively:

1. Assistive Layer

AI provides lightweight support — autocomplete, suggestions, smart defaults.

E.g., Gmail’s Smart Compose or Notion’s writing helpers.

2. Copilot Layer

AI helps the user complete tasks — recommending steps or creating draft content.

E.g., GitHub Copilot writing code as you work.

3. Autonomous Layer

AI handles tasks end-to-end with minimal input.

E.g., AI that generates travel itineraries or books a complete trip based on a few cues.

Most products should start in the assistive or copilot layers, gradually moving toward autonomy as confidence and data improve.

Not Every Product Needs a Chatbot — Pick the Right Interaction

Here’s a mistake I’m seeing across the board:

Teams assume LLMs = chatbots.

But chat is just one interaction pattern — and often not the best one.

Take Miro, for example.

Instead of giving users a chatbot to ask for help, Miro lets you work directly on the canvas. You can highlight a set of sticky notes and ask AI to summarize them. You can select a section of your diagram and generate ideas from that context.

It’s fluid, embedded, and exactly where the user’s attention already is.

• No need to context-switch to a new interface

• No long prompt required

• No guessing what to type into a bot

This kind of embedded, workflow-native AI is what most products should aspire to.

The question isn’t “How do we add a chatbot?”

It’s “How do we help users do less work and get better outcomes?”

Sometimes that means chat. But often, a well-placed AI action or intelligent nudge is far more effective.

Final Thought: Don’t Just Add AI — Rethink the Experience

This moment in product development isn’t just about smarter backends or faster content generation. It’s about rethinking the entire contract between user and product.

Where once we designed screens and flows, now we design systems that respond to intent.

Where we once tracked clicks and completions, now we track trust and outcomes.

The question isn’t whether to use AI. It’s how to use it to remove friction, guide users, and evolve faster than ever.

PMs who embrace this shift — and stay clear-eyed about when chat helps vs when it gets in the way — will build experiences that feel modern, magical, and human.

✅ Key Takeaways

• Generative AI is now part of the user experience, not just a backend tool.

• Not every product needs a chatbot — embedded, contextual AI often works better.

• Rethink metrics — focus on speed to outcome, trust, and value over clicks or time-on-page.

• Your team structure must evolve, with PMs, designers, and ML engineers working in tight loops.

• This space will move fast — optimize for adaptability, not just shipping something “AI-powered.”

When I first wrote about ChatGPT to Commerce a few months ago, I framed the shift as speculative — a future possibility. But the data is catching up fast: ChatGPT is now a top-tier traffic source for major retailers. Walmart reports that 20% of its referral clicks now originate from ChatGPT, up from 15% just one month prior. (Modern Retail) Meanwhile, OpenAI has introduced Instant Checkout and the Agentic Commerce Protocol, enabling users to make purchases directly in chat. (OpenAI)

That means the question isn’t whether ChatGPT will matter for commerce — it already does. The real question for product and growth leaders is: How do we become visible, trusted, and loved inside someone else’s conversation? OpenAI is becoming a distribution channel in its own right — and if your product, catalog, or commerce strategy doesn’t account for that, you’re opting out of the mainstream future.

1. Referral Growth Signals Intent, Not Novelty

The first wave of traffic lifts isn’t a novelty bump — it’s a signal of consumer intent. Walmart’s numbers are staggering: one in five referral clicks came from ChatGPT in August, with Target, Etsy, and eBay also seeing measurable lifts.

This growth is organic and bottom-up. Unlike paid search or display ads, you’re not buying your way into this channel. Users are leaning into ChatGPT to help them decide what to buy. That’s a strong early sign of durable behavior change — and a huge opportunity for those who adapt quickly.

2. From “Search → Site → Cart” to “Conversation → Buy”

OpenAI’s Instant Checkout reshapes the entire transaction flow. A user can now:

1. Ask ChatGPT for a recommendation.

2. Get a specific product suggestion.

3. Tap “Buy” inside the chat.

4. Confirm payment and shipping.

No browser tabs. No endless checkout forms. No bouncing between comparison sites.

And because the Agentic Commerce Protocol is an open standard, merchants can integrate their existing backends seamlessly while OpenAI provides the connective layer. This isn’t replacing e-commerce websites — it’s collapsing the distance between discovery and conversion.

3. Visibility in AI Context = A New Type of Ranking

In Google, SEO and ads determine discoverability. In ChatGPT, visibility is far more opaque. Your product’s presence depends on:

• How well your catalog integrates with the Agentic Commerce Protocol.

• What training data the model has seen.

• How recommendations are weighted within a conversation.

This means classic SEO playbooks don’t apply. Instead, success will come from ensuring your products are structured, accessible, and optimized for AI-first retrieval. Think of it less as “ranking for keywords” and more as “earning trust from a model.”

4. Business Model: From Free Traffic to Transaction Margins

Right now, referral traffic from ChatGPT is free. But OpenAI has already signaled its monetization approach: a small fee per completed transaction.

This is significant. Unlike Google or Amazon, where visibility is often pay-to-play, OpenAI isn’t charging for placement (at least not yet). Instead, it monetizes on the backend — a take rate on the transaction. This sets up a different power dynamic:

• Merchants save on acquisition costs compared to traditional paid channels.

• OpenAI becomes the gatekeeper of checkout flows and consumer data.

• Competition shifts from ad bidding to integration quality and trustworthiness.

5. Your Competitive Wedge Shifts Post-Transaction

Perhaps the most important shift: once the transaction happens inside ChatGPT, you lose control of the front-end funnel. There’s no homepage to showcase your brand, no crafted checkout flow to upsell, no chance to tell your story.

That means your competitive wedge moves downstream:

• Retention becomes the moat: loyalty programs, subscriptions, and reorders.

• Post-purchase experience is the differentiator: fulfillment, customer support, and follow-ups.

• Direct relationships matter more: capturing consent for email, SMS, or app engagement is critical.

The challenge is clear: you may not control how the user discovers you, but you can absolutely control how they remember you.

Closing Thoughts

In 2023, “commerce inside ChatGPT” sounded like a thought experiment. By mid-2025, it’s here — and scaling fast. If ChatGPT already accounts for 20% of Walmart’s referral traffic, it’s no longer a fringe channel. It’s becoming a distribution venue with its own rules, economics, and consumer behaviors.

For product leaders, growth teams, and commerce operators, the next question is strategic: How do we adapt our catalog, integrations, and post-purchase relationships to thrive in an AI-first distribution world?

The companies that treat OpenAI as just another channel will play catch-up. The ones that treat it as a platform will build enduring advantages.

Key Takeaways:

• ChatGPT is already a top referral source for major retailers.

• Instant Checkout and Agentic Commerce Protocol collapse the distance between discovery and purchase.

• Visibility in AI contexts is opaque and requires new playbooks beyond SEO.

• OpenAI monetizes on transaction fees, not placement — shifting the economics of acquisition.

• Your moat moves post-transaction: retention, experience, and direct relationships matter more than ever.

A few weeks ago, Andrew Ng made a provocative point: AI has made coding so fast that the real bottleneck in tech isn’t engineering anymore—it’s product management.

That line stuck with me, because I’ve felt this shift happening firsthand. We used to complain that engineering timelines slowed everything down. Now, with AI copilots, libraries, and frameworks doing the heavy lifting, teams can spin up features and experiments faster than ever. The constraint has moved upstream. Suddenly, the question isn’t “How fast can we build it?” but “Can product figure out what to build, and why, at the pace engineering can now deliver?”

This is a reckoning for product managers. And it’s going to separate those who thrive from those who fall behind.

Why PMs Have to Step Up Now

I’ve always believed that good product managers aren’t measured by the quality of their specs or their ability to run Jira boards. They’re measured by their ability to make great decisions with imperfect information—and to do it fast enough to keep their team moving. That’s more important now than ever.

Here’s where strong PMs can double down:

1. Leverage Customer Insights Relentlessly

When engineering is no longer the bottleneck, the quality of your insights becomes the real advantage. At Rewarder, I remember shipping a feature in record time that we were sure customers would love—only to discover it tanked adoption because we hadn’t done enough discovery upfront. The cost wasn’t in engineering hours (we shipped it in a week), but in opportunity cost. We burned time we could have spent on something valuable. We had a different approach at Zenly, when we launched voice to text, something many others hadn’t nailed at the time, we relentlessly shipped and tested with customers until we knew the quality bar was high and that the feature was delightful. Without key customer insight and feedback loops, we wouldn’t have been able to launch such a successful feature.

Good PMs need to be obsessive about talking to customers, watching analytics, and triangulating data from different sources. That means moving beyond “What feature should we build?” to “What underlying customer pain are we solving, and how will we know quickly if we’re right?”

2. Make Faster Decisions With Limited Data

This is where experience really matters. Senior PMs who have lived through multiple product cycles, pivots, and failures can often spot patterns faster. I’ve seen it play out: a senior PM hears one customer story and immediately connects it to a broader funnel drop-off they’ve seen before, or recognizes that a proposed feature is just another flavor of a failed experiment from five years back.

For younger PMs, this is tough. If you haven’t been through the battles, you don’t yet have the pattern-matching muscles. But that doesn’t mean you’re doomed—it means you need to accelerate your learning. Shadow senior PMs, study failed experiments, and build your mental library of “what works/what doesn’t” as quickly as possible. Your engineers won’t wait around for you to catch up.

Also, become an expert on the latest tools and fail fast. Start doing rapid prototyping leverage LLMs and gain skills that your senior colleagues may take longer to adopt. This can become an unfair advantage for junior and more adaptable people to quickly get up to speeed and become effective product managers.

3. Don’t Hide Behind Technical Complexity

For years, one of the hardest parts of being a PM was keeping up with the technical stack—understanding APIs, databases, architectures, all while trying to maintain credibility with engineers. That knowledge still matters. But when code can be generated, tested, and deployed at lightning speed, the bottleneck shifts away from “how it’s built” and toward “why it’s being built.”

I’ve personally leaned on AI tools recently to fill gaps in technical depth. Whether it’s spinning up a quick mock API or structuring a doc with AI, I can get enough grounding to move faster without slowing engineering down. But the true differentiator isn’t whether I care about the technical design—it’s whether I can articulate the customer need, define success metrics, and prioritize ruthlessly.

4. The Reckoning for PM Titles

The last decade saw an explosion of people with the “Product Manager” title. Some were doing the classic PM work of discovery, prioritization, and decision-making. Others were closer to project managers, business analysts, or even backlog administrators. In a slower world, that ambiguity was tolerable.

Now, it’s unforgiving. If you don’t have instincts rooted in customer knowledge, funnel analysis, or growth loops, you’ll get exposed. I’ve already seen it: some PMs thrive in this new environment, making faster calls, guiding their teams decisively. Others struggle because their muscles were built around process, not product thinking.

This isn’t meant as a critique, but as a reality check. The job has changed. The bar is higher.

5. Stay Embedded With Engineering

One thing that hasn’t changed—and is more important now—is staying close to your engineering team. Not just in standups, but day-to-day, in the trenches. There will also be more delegated decision making that needs to happen. Given the pace, you’ll need to set guidelines for the customer insights and product decisions so that the engineers and designers know how to make the right decision on the fly, without needing to ask for clarification on everything from product.

The lesson: engineers move fast when empowered, but PMs can’t disappear. Be available. Set the cadence. Clarify tradeoffs quickly. The closer you are to the team, the fewer bottlenecks you’ll create.

6. Organization Is a Competitive Advantage

This sounds simple, but it matters: the best-organized PMs will thrive in this new environment. When things move fast, knowing exactly what’s a priority, who’s accountable, and what tradeoffs you’re making becomes critical.

That said, I think it will change. Whereas historically, the job was to organize priorities and work closely against them with engineering, now your organization becomes more critical in terms of where you’ll focus. What are the bottlenecks engineering is facing? How can you remove them quickly. Where do they need you to weigh in so they can keep moving quickly?

I’ve always had a principle that my job as the product manager is to maximize “hands on keyboard time” for engineering. That is now taken to a whole new level given the speed with which dev moves. Your EPD trio needs to level set in order to keep up.

Organization isn’t glamorous, but it’s a superpower when speed is the game.

7. The Old Basics Still Matter

I’m excited about how AI is helping me as a PM—I use it to structure docs, brainstorm edge cases, and even stress-test a hypothesis. But those are accelerators, not replacements. The fundamentals haven’t changed:

• Understanding funnels and drop-off points.

• Knowing your growth loops and where they break.

• Engaging with customers and business partners.

• Setting clear goals and definitions of success.

The difference is that now, with faster engineering, you can’t hide behind slow cycles. You need to lead from the front. And you need to be leading with prototypes and rapid discovery from customers, not just writing old school PRDS.

Key Takeaways for PMs at All Levels

1. Customer insights are your currency. Don’t ship without them. The cost of wrong calls is now measured in wasted opportunities, not just wasted sprints.

2. Pattern-matching is your edge. Senior PMs have the advantage, but junior PMs can build it quickly by studying failures and shadowing experienced peers. Junior PMs can also learn the new patterns more rapidly and make that an unfair advantage.

3. Clarity and cadence beat complexity. Stay close to engineering, make decisions fast, and keep priorities crystal clear.

Final Thought

The acceleration of engineering is exciting, but it’s also a mirror. It reflects back to PMs where we add value—and where we don’t. If you’ve built your career on process alone, the coming years will be tough. If you’ve built your career on insights, decisions, and leadership, this is your moment.

The bottleneck has moved. The question is: are you ready to move with it?

Snap’s Q2 2025 earnings just dropped, and at first glance, the headline numbers look solid. Daily active users (DAUs) grew 9% YoY to 469 million. Revenue increased 9% to $1.345 billion. Snapchat+ subscriptions rose to nearly 16 million, and Snap’s content ecosystem is seeing record engagement, especially with Spotlight.

But if you’ve been following Snap for a while—or worked there, like I did—the story behind the numbers is more nuanced, and in many ways, deeply familiar.

My Time at Snap: Growth First, Monetization Later

I spent over two years at Snap, primarily working on Zenly, a location-based social app we’d grown to over 20 million DAUs. Zenly was a rocket ship. It had deep engagement, loyal communities, and incredible organic growth. Internally, the mantra was clear: focus on user growth. Monetization could come later. This was also the direction we had from Snap leadership.

That strategy wasn’t unusual, especially in consumer tech. But when the market shifted and Snap faced more financial scrutiny, Zenly was shut down—not due to lack of traction or potential, but because it wasn’t generating cash flow, despite the fact we’d never been given a goal of monetization.

Looking back, that decision said less about Zenly and more about Snap’s broader structural challenge: it’s a company that knows how to grow users, but has long struggled to monetize them.

Snap vs. the Industry: Revenue Per User Tells the Real Story

Let’s look at some benchmarks. Snap reported revenue of $1.345 billion on 469 million DAUs. That’s ~$2.87 revenue per DAU this quarter. For comparison:

• Meta (Q2 2025): Revenue of $47.52 billion on ~3.48 billion DAUs = ~$13.65 per DAU

• TikTok (estimates): Revenue in the $32B annual range with ~900MM DAUs = ~$8.89 per DAU per quarter

Snap lags significantly behind. Even with a strong user base and decent engagement, it's leaving money on the table. And TikTok is slowly stealing share and growing faster.

The issue isn’t just monetization volume—it’s monetization '“relevance.” Snap is still viewed by many advertisers as a brand play rather than a conversion machine. When budgets get tight, brand spend is often the first to go. Direct-response channels—those that show ROI in real time—are where dollars flow.

The AI Gap: Why the Performance Chasm Is Widening

A key reason this gap is growing? AI.

Meta leaned hard into AI-driven ad optimization through Advantage+ campaigns. TikTok is aggressively improving its ad products with machine learning at the core. These platforms not only provide better targeting but better creative optimization and predictive performance.

Snap, on the other hand, is still catching up. While it has introduced new formats like Sponsored Snaps—early data shows promising results like 2x conversion rates and increased dwell time—the infrastructure, tooling, and advertiser trust that fuels scaled performance just isn’t there yet.

Apple’s ATT (App Tracking Transparency) rollout in 2021 was a critical moment. It reshaped mobile advertising overnight. Meta suffered, then innovated. TikTok adapted fast. Snap stumbled—and has yet to fully recover. That delay matters in a world where ad efficacy and optimization are increasingly determined by how well your platform can leverage data, AI, and feedback loops.

A Structural Weakness in the Business Model

The consequences of this are structural, not just cyclical.

Snap’s DNA is user-first, which has driven incredible product innovations: AR lenses, Bitmoji, Discover, Spotlight. It iterates fast and delivers delightful consumer experiences. But the company’s monetization engine—the counterpart to all that user delight—hasn’t kept pace.

In my experience on Zenly, the focus on user experience was unwavering, and that was inspiring. But we also weren’t given the space or resources to build toward monetization because it was never one of the missions Snap asked from us. We were told, in so many words: grow first, we’ll figure out the money later.

But when later came, the company needed revenue *now*. And products that weren’t already contributing to the bottom line—no matter how promising—were deprioritized or shut down.

This speaks to a larger truth: Snap has relied too heavily on user growth as its north star, without pairing that with a long-term monetization strategy that could scale with it.

Bright Spots: Subscriptions, Spotlight, Sponsored Snaps

To Snap’s credit, there are glimmers of progress.

Snapchat+: Now nearing 16 million paid subscribers, the product is a promising bet on consumer revenue. It’s lightweight, easy to adopt, and adds value for Snap’s power users.

Spotlight: With over 550 million MAUs engaging and time spent up 23%, this TikTok-style feed is becoming a core part of Snap’s content ecosystem—and could become a strong monetization surface.

Sponsored Snaps: New ad formats show signs of converting well. If Snap can double down on performance-focused ad units and improve tools for advertisers, it may slowly shift perception.

But these are still early. The platform needs more than a few bright spots—it needs a transformation.

What Needs to Change

To close the gap, Snap needs to:

1. Rebuild Advertiser Trust: The recent glitch in its ad-buying platform that caused underpriced auctions highlights fragility in the core monetization engine. That erodes trust—especially among performance marketers.

2. Invest Heavily in AI-Driven Ad Products: Direct response advertising is now an AI problem as much as a creative one. Snap needs to catch up—fast.

3. Shift Perception from Brand to Conversion: Most advertisers still see Snap as an awareness platform. Until it can consistently deliver measurable ROI, budget allocations will stay constrained.

4. Support Product Teams With Monetization Infrastructure: Future Zenlys shouldn’t be told to just focus on growth with no path to revenue. That split-brain between user teams and monetization teams must be closed.

The Road Ahead

Snap has the user base, the product DNA, and the culture of innovation. But it’s operating in a market that increasingly rewards not just reach, but *revenue leverage*—the ability to turn users into dollars efficiently, repeatedly, and with scale.

Companies like Meta and TikTok have built structural advantages through better ad tech, smarter targeting, and stronger feedback loops. AI is only widening that moat.

Snap still feels like it’s playing offense on product and defense on monetization. And in 2025, that’s a tough combination to scale.

But if the company can take the same rigor it applies to consumer experience and turn it toward advertising—toward helping businesses grow, convert, and measure impact—it still has a shot to close the gap.

Because delighting users is table stakes. In today’s market, delivering ROI is the game.

A quiet but potentially seismic shift is underway: OpenAI is testing a native checkout experience inside ChatGPT.

That might sound small. Another experiment. Another product update.

But this change has huge implications for product managers, growth leaders, and anyone thinking about the future of user experience and distribution. It signals something we’ve talked about in theory for years: AI as the interface layer—not just for information, but for transaction.

If you’re building anything that touches e-commerce, brand visibility, or discovery, it’s time to pay attention.

AI as the New Front Door

Traditionally, commerce flows through platforms—search, marketplaces, apps. Each of these carries friction, yes, but also opportunity: SEO, app store rankings, paid acquisition channels. You optimize for them. You measure your funnel.

But what happens when those front doors collapse into a single entry point—a conversation?

Picture this: A user asks ChatGPT, “What’s the best carry-on luggage for a minimalist traveler?” The assistant responds with a list of vetted options. The user clicks one, reads a short product description, and taps “Buy now”—without ever leaving the chat.

No website. No marketplace. No cart abandonment.

That’s a radically different landscape.

What Product Teams Need to Think About

So what changes when LLMs become the storefront?

Here are five strategic shifts product and growth teams should be thinking about right now:

Discovery ≠ Ownership

In the old model, discovery usually meant a visit to your domain or app. That was your chance to shape the narrative—show your brand, tell your story, differentiate.

In a ChatGPT-powered commerce flow, your product is just one tile in a list. There’s no homepage, no About Us page, no deep brand arc unless the user asks for it.

You need to rethink how you surface what matters most in a single card or paragraph. Think: headline copy meets value prop clarity meets conversion trigger. A/B testing isn’t going away—but the context just got smaller.

Search Ranking Becomes Prompt Ranking

When users find products via LLMs, you’re no longer competing on keywords. You’re competing on training data, model tuning, and maybe (eventually) prompt optimization.

That’s a black box today—but not forever.

Companies will need to invest in understanding how their content and metadata influence LLM responses. That includes structured data, verified reviews, and participation in partner ecosystems. Being “model-visible” will be the new SEO.

Conversion Happens Faster—but Trust Needs to Scale

LLMs are persuasive. When they give a recommendation, it feels authoritative—even if you didn’t ask for it.

That creates a high-conversion surface, but also one that can collapse without trust. If people feel misled, the blowback will be swift.

Brands and platforms need to make transparency a feature—not an afterthought. Where’s this recommendation coming from? Is it paid? Curated? User-reviewed?

PMs will need to build mechanisms that blend speed with safety, helping users feel confident without slowing them down.

Your Moat May Shift to First-Party Relationships

If AI assistants control discovery, your best defense isn’t just ranking well—it’s owning the customer relationship after the first transaction.

Think: post-purchase experiences, personalized onboarding, retention loops that go beyond the sale. In a world where the top of funnel is mediated by a model, mid- and bottom-of-funnel become your lever.

Owning the relationship—email, app install, community—will matter more than ever.

Product Pages as APIs

This might sound wild, but in the LLM commerce world, your product page is no longer for humans. It’s for machines.

You’ll still have human-facing assets, sure—but increasingly, what matters is how your data is structured, how your catalog is indexed, and how your offer shows up in the model’s “thinking.” Think less web design, more schema markup, more product feeds.

The product manager of the future might spend more time tuning a product catalog API than writing UX copy.

Final Thought: Don’t Just Watch—Prototype

This shift won’t happen all at once. But it’s coming fast.

Now is the time to prototype what embedded commerce in AI looks like for your product. Build scrappy GPTs. Run shadow funnels. Think about how your offer lives in a text-only world.

Because in this next chapter, the most valuable real estate may not be your homepage.

It might just be a sentence inside someone else’s conversation.

Cloudflare recently launched a pay-per-crawl framework that lets websites control and monetize how AI crawlers access their content. At first glance, it seems like a niche infrastructure tweak. But in reality, it’s a big deal.

From a product and growth perspective, this isn’t just a technical innovation—it’s a redefinition of the value exchange between content creators and AI companies.

1. Flipping the Script on Value Exchange

For years, the relationship between digital platforms and AI scrapers has been one-sided. Companies pour time, capital, and creativity into building content—and then AI crawlers ingest that content without compensation, attribution, or consent.

Cloudflare’s model introduces a long-overdue shift: value must now flow both ways.

If AI companies benefit from training on a platform’s content, there should be a cost, a contract, or at least a choice. This gives platforms control over who can access their data—and under what terms. That’s not just fair; it’s foundational for a healthier digital ecosystem.

2. Incentivizing Quality and Sustainable Growth

Free, uncontrolled scraping can disincentivize content investment. Why build something valuable if it’s going to be commoditized by LLMs? Pay-per-crawl changes that equation. When content becomes a metered resource, quality becomes a strategic asset again.

This opens up entirely new growth levers. Sites can choose to monetize access, strike licensing deals, or restrict usage altogether. It’s a more sustainable way to scale—especially for platforms that rely on high-value content to differentiate.

3. Protecting the Product Experience and Brand Integrity

From a product leadership lens, this isn’t just about monetization—it’s about experience control.

When AI models repackage your content without context, it creates real risk. Outdated, misinterpreted, or off-brand information can reach users via third-party AI tools in ways you can’t track or correct.

With a system like Cloudflare’s, you can decide who can crawl your content, when, and how—which in turn helps protect your UX, messaging, and brand reputation.

4. It’s About Control—and Optionality

Ultimately, this framework is about putting platforms back in the driver’s seat. It doesn’t force you to monetize access—but it gives you the right to choose. And in a landscape where AI’s appetite for data is growing exponentially, that control is everything.

We’re at the beginning of a broader shift in the AI-content ecosystem—one where content creators and infrastructure providers reclaim leverage.

Final Take

Cloudflare’s pay-per-crawl model isn’t just a technical feature. It’s a strategic unlock. For product teams, it offers a way to protect core assets, open new monetization paths, and stay ahead in a world where AI is rewriting the rules of distribution.

We’ve needed a new framework for how value flows between platforms and AI. This might just be the beginning.

The Need for Balance

Much like in investing, product development benefits from a diversified approach. You need both:

• Short-term bets: Initiatives that have a high probability of success and can drive immediate growth.

• Medium-term extensions: Expanding your existing product to unlock new user segments or increase engagement.

• Long-term investments: High-risk, high-reward projects that could fundamentally change your growth trajectory.

An imbalanced portfolio—one skewed too much toward quick wins or only focused on ambitious long-term goals—can stifle sustainable growth. A well-structured roadmap ensures that while you optimize today, you’re also planting the seeds for future breakthroughs.

Short-Term Bets: Maximizing Immediate Impact

Short-term bets should focus on high-confidence opportunities that improve the core product. These include:

• Low-hanging fruit within your existing growth loop: Simple optimizations based on clear user pain points.

• A/B testing (if you have enough traffic): Experimenting with different variations to fine-tune conversion rates and engagement.

• Customer-driven optimizations: Insights from direct interactions with users and data analytics should guide tweaks that enhance the experience.

Everything in this category should be grounded in clear hypotheses and validated through rigorous testing and analysis. The goal here is to generate quick wins that sustain growth while setting the stage for medium and long-term bets.

Medium-Term Extensions: Finding New Growth Opportunities

Beyond immediate optimizations, a strong roadmap should include medium-term initiatives that extend your product in meaningful ways. These typically involve:

• Feature extensions: Adding adjacent functionality that enhances your core offering.

• New user segments: Identifying and targeting customer groups who could benefit from your product with minor modifications.

• Integration opportunities: Understanding how users interact with your product in their broader workflow and addressing unmet needs.

To find the right medium-term bets, you need to talk to customers about how they’re using your product, what alternatives they’re using, and what problems they still face. This helps you identify natural expansion opportunities that deepen engagement and widen your market reach.

Long-Term Investments: Bending the Growth Curve

Finally, long-term investments are crucial for staying ahead of the competition and ensuring future growth. These initiatives include:

• New product categories: Expanding into adjacent spaces that align with your core business.

• Major platform shifts: Exploring emerging technologies that could redefine your industry.

• Disruptive innovations: Pursuing transformative ideas that could become new growth engines.

These bets are riskier and take longer to materialize, but they’re necessary to prevent stagnation. The key is to balance them with your short and medium-term investments so that even if some fail, the business continues to grow.

The Importance of Portfolio Allocation

A well-balanced product roadmap isn’t overloaded with just short-term optimizations or moonshot ideas. If you focus solely on short-term wins, you’re merely optimizing an existing system without laying the foundation for future expansion. Conversely, if you invest only in ambitious long-term projects, you risk missing immediate opportunities and delaying returns for too long.

The goal is to create a self-sustaining innovation cycle: short-term wins drive immediate growth, medium-term investments expand the market, and long-term bets set the stage for future success. Over time, successful medium and long-term projects become the next set of short-term optimizations, continuing the cycle.

Conclusion

By applying modern portfolio theory to product roadmapping, you can ensure a strategic mix of short, medium, and long-term bets. This balanced approach allows you to sustain current momentum while continuously opening up new growth opportunities.

A great product roadmap isn’t just a to-do list—it’s a diversified investment strategy for your company’s future. By thoughtfully allocating resources across different time horizons, you can drive both immediate success and long-term breakthroughs, ensuring that your product continues to evolve and thrive in an ever-changing market.

• Go-to-market is a team sport: Product Managers need to break down the silo mentality and work with marketing, data, and sales throughout the entire product development lifecycle. This avoids last-minute scrambles and ensures everyone is aligned on goals and responsibilities. Barron emphasizes the importance of early and frequent communication, suggesting regular check-in meetings and shared documentation (even a simple spreadsheet!) to track progress and ownership.

• Don't overcomplicate things: While there are fancy tools available, sometimes the most effective solutions are the simplest. Both Elena and Barron highlight the value of clear communication, asynchronous updates, and concise documentation over complex project management systems. This minimizes overhead and keeps the focus on the actual work.

• Think beyond the launch: A successful product launch isn't the finish line. PMs need to be involved in driving adoption and gathering user feedback after launch to inform future iterations. This requires ongoing collaboration with marketing and data teams to track key metrics and identify areas for improvement.

• AI can supercharge GTM: Elena highlights how AI tools like GPT can be leveraged to streamline content creation, analyze customer feedback (from sources like Gong), and even generate sales enablement materials. This allows product teams to be more efficient and data-driven in their go-to-market execution.

Essentially, successful go-to-market requires a collaborative, organized, and customer-centric approach, with a willingness to embrace new technologies like AI to enhance efficiency.

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The full transcript is below:
Elena Luneva: Hi, everybody. I'm excited to have Barron on. He's the head of product at Figure. He's previously been the head of marketing there, and he's worked at Snap, Showmax, and [invalid URL removed], among other great companies. He's also into backcountry skiing like myself, so we'll get into that.

Barron Ernst: Yeah, I'm excited to be here. I think when we first met, backcountry skiing was the common theme that connected us, beyond the product and all the other things that we have shared in common. I'm excited to talk about product and marketing, given all of your experience at Nextdoor and Braintrust, and share some of my experiences as well. I'm excited to learn from you, too.

Elena Luneva: Oh, awesome. Likewise. So it's raining in Marin, so I bet it's snowing in Tahoe. Are you going to hit the slopes right after this?

Barron Ernst: Not right after. The plan is to get out. I am generally a morning person; I try to go in the mornings before work, so I'm usually up there at 6 or 6:30 with a headlamp on—one of those crazy people. So, most days I'll try to do an hour or two and then get home in time for all the excitement of running product here at Figure.

Elena Luneva: Wow. That is hardcore. Yeah. For us, I think we're weekend warriors and go when the kids have school.

Barron Ernst: Yeah.

Elena Luneva: But, yeah, we might be going up to Tahoe this weekend, so we'll see.

Barron Ernst: Yeah, it should be this week. It should be a great weekend. It's supposed to be sunny Saturday and Sunday, so I wish you the best of luck going up to I-80.

Elena Luneva: Yes. That is the big battle. All right, before we get started, do you have a favorite place to ski or a favorite ski line?

Barron Ernst: Probably my... So I lived in Europe for seven years and I fell in love with Chamonix. I skied a lot of lines there. I still, every time I go, do the Vallée Blanche, and usually now I do touring around it and, like, usually add something like going up to one of the peaks or doing a summit. But it's still one of the great ski lines. Even though it's not really that technically challenging to do, there's really nothing else like it in the world where you can ski for, I think it's, you know, four or five thousand meters—basically, you get so much skiing in on one single run. But it also has all these fun other elements. And so I love Chamonix. I'm back in the States now and I love Tahoe desperately as well. But I think Chamonix is like one of my favorite places I've ever been.

Elena Luneva: Amazing. I've been there one time, mostly on the Chamonix mountain itself. But yeah, it was really nice. I really liked Whistler. The musical bumps; you can take the lift up and then go into the backcountry. And I've never seen crystals like that. It just, in the sunshine, the snow makes this sound that I haven't experienced elsewhere.

Barron Ernst: I know what you're talking about. Beautiful.

Elena Luneva: Then I think the storm came in. All the clouds were beautiful. So it's just this being in really big nature with great runs and very cool scenery.

Barron Ernst: That's awesome. I've been to Whistler once and it was an awesome experience. It's a beautiful place up there.

Elena Luneva: Amazing. All right, so let's get into it. Barron and I have both been in product for a really long time, but I think we both really value go-to-market marketing. So we wanted to spend some time there. So throughout your career, what are some of the blind spots that you've seen product managers have when approaching a go-to-market strategy? What are some things PMs get wrong about it?

Barron Ernst: I think the biggest thing I've seen commonly—and this is going to be obvious—is product people are like, "Well, the day that we're code complete and we push the thing out means that it's done and that's like the biggest element of work." And it sounds so common, but it's a mistake that everyone seems to continue to make. And there's a lot of sub-areas of this as well that are important to think about. But when I see my teams thinking about go-to-market, I'm usually asking them questions like, "Who in marketing have you communicated with in terms of getting copy, in terms of building landing pages? Are they thinking about the GTM strategy—are we doing paid search? How are we generating initial traffic? How are we generating ongoing traffic?" And surprisingly, like a lot of PMs, those who maybe aren't as much in the growth side, still tend to think, "My job is to get from point A to point B, get the thing shipped to customers, and then someone else figures out the rest." And I think the best GTM teams tend to be those where that handoff isn't a handoff, but it's more of a partnership and it's done a bit more seamlessly.

A good example, back to the point about skiing. For about a year, I ran the ski and beach businesses at [invalid URL removed], and the PMs who were doing basically... the thing that happens with an OTA like that is the ski bookings all happen in a very tight window. It tends to be the fall, right? Everyone's booking their ski trips in the September, October, November time frame, which means that you actually, for your big changes—and we were doing a bunch of changes, making it more clear where lifts were, making it more clear where hotels were; we had some hotel revenue guarantee programs that we were putting into place, all these things—you basically get one chance to ship it annually. You can iterate throughout the season, but if you don't get it out there by the time that most of the bookings occur, you really miss a massive window of opportunity. And that was one of the things I was seeing with the product team that worked with me. They were very much geared toward getting all these things out—these lifts, these other things—but there wasn't good communication where they were also involving the marketing team and the marketing organization.

While this is not my preferred approach, the approach I found that works a lot in these cases is, sadly, just to force everyone into a weekly or bi-weekly meeting, like, "Who's responsible for what?" And it's almost like a bit of a stick and a carrot, right? It's like, if everyone's doing it well, we don't need this 30-minute check-in every week or every two weeks to make sure we're on track. But I found—and I'm the last person who likes more meetings—that having that check-in in some form, asynchronously, where it's clear who's owning what, becomes a really important thing to do. I think the other thing I found is it's important to do it not a week before launch, but months before launch, so that everyone is on the same page. Because what I found is the thing that causes that last-minute churn is when people were told last-minute, like, "Hey, this is launching in two weeks." But if you have that progressive process to getting a really big thing like that out, it means that the launch doesn't turn into this massive, chaotic, crazy moment, but instead it's more orchestrated. And I think that really matters, and I think that's an important lesson for product people—their job doesn't just end when they ship, their job continues on from there. Just like they need to continue iterating on the feature, they also need to continue iterating with their partners to get the traffic so that they know what to build next. And I think that's a big important piece of GTM.

Elena Luneva: Yeah, no, I've definitely found that as well. It's like the worst thing is those surprises because then the temperature in the room gets higher and people have a shorter fuse. Thinking through lots of foundational things together...

Barron Ernst: Exactly.

Elena Luneva: Yeah, I'm good with that. And so when you organize your teams like this, what are some metric considerations, or how do you know that the teams are working well together for those launches?

Barron Ernst: So I think, from a metric perspective, usually I'm assuming that the PM team working with data and marketing are kind of outlining what success looks like. But it shouldn't just be the PM team that says, "We're going to drive X and Y in revenue." It should be a combined effort of product, data, and analytics, looking together at what we think the opportunity for this new feature is. But then also, if there's a signup goal or a usage or an adoption goal, it's also how we're going to drive enough users or enough new people to actually do that. And so that's where I think the alignment between marketing and product becomes really important. In terms of artifacts that we've used, I'd love to say that there's some beautiful, perfect tool that does this, but sadly most of the time this ends up being a Notion sheet, a Google sheet, a Google document, with clear ownership for who's responsible for what. Who in marketing is writing this copy, who in product is doing this? And it's also just coming with clear ownership and then clear action items every week. And it sounds so simple, but I see this mistake still made so regularly that that's why I go back to basics with it. It's like going back to basics with, "You talk to your customers." This is going back to basics with, "This is how you do a launch." Communication, clear accountability, clear ownership, documented somewhere with some linkage to the expected outcome. And it's surprising, but it's so often not done that way that I tend to go back to basics on it more than I would expect, even having done this for 20-ish years, like you have as well.

Elena Luneva: Yeah, I agree with you. I mean there's all these tools, and there are a different level of fancy, but really a spreadsheet with who's doing what by when, and what do we do if that didn't happen in the conversations? Yeah, I agree.

Barron Ernst: I'd love to... you know, I've tried—and this isn't for lack of trying—I've tried so many of the tools—Airtable, Notion, et cetera—I've tried so many of these different things and I usually just end up coming back to "simple is more important." Simple and understandable is more important than learning a new tool because you add an overhead and a burden when it's, "Hey, we have to learn this tool in addition to just doing the thing to get the product out."

Elena Luneva: Exactly. And then you run into permissions or somebody can't access something.

Barron Ernst: Yeah, exactly.

Elena Luneva: Has your perspective changed? So you've been in so many leadership positions, at some point you were a wee tiny PM. Has your perspective changed over that time?

Barron Ernst: I would say that the things that I took early in my career that were some of the best advice I got was—and this is related—make sure every meeting has a clear agenda. Make sure that if there's no need for the call, you find a way to cancel it. I think earlier on in my career I would probably just have had these calls on a regular basis and not focused as much on what can happen asynchronously before. And I think as we've evolved and also as more hybrid, remote, multi-office situations have been created over time, whether you're in an RTO or you're not, you still have probably multiple offices to communicate with.

Elena Luneva: Absolutely.

Barron Ernst: In that scenario, you need to have some form of clear asynchronous communication, which I think is an evolution that has happened since earlier on in my career. Getting really good at identifying it, sharing the notes out in advance, making these conversations about not just, "I'm going to read to you an update of statuses," but instead, "We're going to have the discussions that came out of this," as the way to start... I think that's a really important way for these things to start and evolve.

I'd say the other evolution from when I was more junior is realizing that there's often a tendency when you're younger to involve everyone. And I think as you get more advanced, trying not to take everyone's time with these sorts of conversations but having it be a small, short meeting with the key people becomes really important, and then having some mechanism to share out what decisions were made in those conversations. Even if you don't want everyone to attend, sharing action items in a Slack channel or email... I know that's boring, but... or in some way to keep people accountable, some sort of board, et cetera, so everyone knows who's responsible for what coming out of that call. That transparency I think really matters as you're driving toward a launch over time, and that can take whatever form is best, but it has to take some form is what I would say.

Elena Luneva: Yeah, I agree with you that asynchronous communication... I feel like we almost don't do it enough. So I always work with my teams to where there's always feedback. But I've already told them that I'm like, "Well, how many times did you tell them?" My magic number is seven because frequently at three or four we all give up and we think it's done. People consume information in different ways, in different channels. So keeping that cadence and pushing yourself and your team goes a long way.

Barron Ernst: I have found that part of my job is reminding people to get the asynchronous document out. That is a thing I do and it's not the most exciting part of my job, but it actually matters a lot because there's a very marked difference between how these types of conversations for GTM go when there is content to read in advance versus when people have to consume and then ask questions about the content all in a single 15 to 30-minute meeting. I think you're making more productive use of your time if you're giving people something beforehand to think about and to react to.

Elena Luneva: I agree with that. We went even more pedantic at Nextdoor where the first five to ten minutes would be spent on reading the docs. I think we adopted it from Amazon, but we're all busy. We're all probably in back-to-back meetings. And so that assumption that people have read your docs is generally a wrong one. And so a lot of the fluff or the circular conversations are because people don't have that same foundation.

Barron Ernst: Yeah.

Elena Luneva:...In having a productive discussion. So, I agree with sending it out before if you can and potentially spending that extra time within the meeting having people read the information you shared with them.

Barron Ernst: Yeah, absolutely.

Elena Luneva: Yeah. We're not children, but sometimes we act like it.

Barron Ernst: You know, it's like one of my things that I'm always surprised by is, back to basics, it turns out, a lot of times solves many more problems. It's easy to assume, I find, that there's a tool or something that's going to solve it. But a lot of times solving these problems really just comes down to who needs to be there, what sort of communication needs to happen to get people aligned, and then also who's the owner. Who's the owner matters so much because if no one owns it, then nothing happens. And I think that's... I mean, these sound like such basic things, but I wish that they weren't as basic. But honestly, the more I do this, the more it turns out that a lot of these things are practices that both senior people, but also junior people, can come into an organization and introduce and have an immediate impact. I find a lot of times that's the other thing, is that this isn't just tips for senior product leaders or senior GTM leaders. But a lot of times if you're the PM and you come in and you see that these practices aren't happening, it's a really unique opportunity where you can immediately add value, where you're not stepping on other people's toes or criticizing how the organization works. You're just trying to get everyone organized to get an important feature out. And it's a really good way, I think, as a more junior person, to build your internal reputation, but also to get an important skill set down the line.

Elena Luneva: Yeah. And you mentioned valuable, and I absolutely agree with that because you'll actually reach your outcomes if everyone's aligned to get there together. So, yeah.

Barron Ernst: I think it's my turn to ask you a question. Having been at a variety of different companies, from B2B to B2C to B2B2C, how have you navigated GTM in those different types of organizations? What are the similarities? What are some of the differences that you've seen when it comes to shipping to a partner versus shipping directly to customers versus the in-between, where you're shipping to partners and their customers?

Elena Luneva: Yeah, absolutely. I think the similarity is knowing your ICP—who you're building this for—and that frequently dictates the channels or how you get to them, so that stays consistent. I think for B2C, because generally there are more customers and there are more emotional drivers or that immediate value, there's a focus there on mass-market messaging. For example, I worked at Nextdoor on overhauling their navigation. We had to take pieces out of the application, move things around, and change how the posting button worked. We had a lot of upset prospective customers because we had a pet directory and Fluffy was no longer on the front page of the pet directory, and people were very upset about that. So we really needed to work with my PMM to send those communications, share where things were moving or, if they were moving out, why they were moving out, and share some of those principles: we're trying to declutter the app; we're going to try to clean things up because the feedback is that it's becoming complicated to use. Having that communication with our neighbors early and often—almost six months before the changes were going to happen—really helped set that precedent and get neighbors along for that ride.

I think for B2B2C things get slightly more complicated because you have multiple value propositions. You have that dual value proposition. You've got your decision-makers and then you have your product users. As a product manager, you're frequently building for that product user, but as a go-to-market team—as a sales or marketing team—you're trying to convince that decision-maker to buy your product. So some of the tension I see is that tension between product—"I fulfilled the needs of the user"—and then the sales and marketing teams being like, "But our decision-makers are asking for different features." Having those ICPs clearly defined and making sure that GTM teams and product teams are working off that same data set, that same information set, and understanding those differences have been critical for launching B2B2C products because the go-to-market motions for the decision-maker are different and they also need to be complemented with the B2C motions.

And then for B2B companies, the sales cycles are just so long. Having that clear partnership between product and sales early on, to have that empathy for each other—that building and shipping takes time, but so does sales—is important. Focusing on tools to accelerate sales, perhaps even before the product is built, but then building in conjunction with that feedback from your sales team and being in those sales conversations really helps both teams to not be surprised and to have that empathy for each other's work.

Barron Ernst: Yeah, makes sense. One of the things that we've seen is... so Figure has a good combination of D2C and B2B2C. Maybe one of the things we've been working on is how do we learn things in the D2C channel that we can apply to the B2B2C channel? Do you have any learnings there, or have you had businesses where there were those similarities, and how have you made them work? For example, we experiment a lot on the D2C channel and then, based on what works, we apply it to the B2B2C channel. I'm curious if you've had similar insights with businesses where you maybe had multiple ICPs like that.

Elena Luneva: Yeah, I think the biggest one for me is that agile methodology, where even though B2B channels take longer to get to the right product, or maybe the shipping cycles are longer, the conversations can be shorter and the incremental value chunks can be shorter. Some of the things that we've applied were coming up with a customer advisory board. You get a cohort of customers to work with you, so at least you're not having those individual conversations, and you're kind of A/B testing but on a much smaller scale than millions of users.

Barron Ernst: I think that's helpful.

Elena Luneva: So you're moving faster than traditionally possible. For example, I was at a company called Nuna, which was in HealthTech. We were building data systems for value-based care for government and insurance clients. Traditionally, the contracts were very organized around, like, "Here are the features you will deliver to us." My suggestion was, "Hey, let's change this structure to, 'Here are the outcomes we're going to get you,' but let's determine the structure of how we talk about it together and how we review the progress so we actually get to those outcomes instead of shipping you the features we think are right six months ahead of that." That really changed the conversation.

Barron Ernst: That's awesome. That's a really good learning. We've done something kind of similar, but I think we could do better with having more tight feedback cycles like that. I think a lot of times these GTM teams get framed as part of growth or one of these other organizations. How do you think about growth and GTM teams if they're all owned inside of the product organization? How do you organize the product team to include GTM functions and growth functions alongside the classic product—core product—types of functions? And then also, in your case, when you're managing design and data and other areas, how do you include those as well?

Elena Luneva: Yeah, I think this depends on the stage of the company. At a startup level, where you have fewer people, there are functions that do multiple things. At Braintrust, for example, I thought of the product team more as a general manager. They not only owned the shipping, but they also owned the go-to-market and the outcomes. I think that really helped align R&D and GTM because they were all on the same team; they were all going for outcomes. That changed that "passing the baton" mentality of many companies I've been at before, where product is responsible for shipping, and then it's not their problem anymore. That changed the mindset. We did have a growth team that was separate. The growth team was really focused on experimentation, top-of-the-funnel acquisition metrics, and was able to run in parallel to the product work that was going on. How you structure a growth team really depends on the stage of the company. Do you have the people? Do you have the resources to align a growth team around various channels? At Braintrust, for example, we didn't. There was just one awesome IC who was responsible for content, for SEO, for landing page experimentation, et cetera. She was amazing and was able to supercharge that team, but we also didn't need more people at that point. However, in larger organizations, it tends to be either a fully formed growth organization or just specialized teams for different parts of the funnel. At Nextdoor, we had folks focused on retention, folks focused on engagement, folks focused on activation. There's a benefit to that specialization as long as there's somebody who's responsible for the end-to-end experience, because otherwise you have these surface owners that run into each other and some of that decision-making gets marred.

Barron Ernst: Yeah, that makes sense. The other thing, related to company size that I've experienced, is do you even have enough traffic from a growth team perspective? I know that's an obvious one to throw out, but it's...

Elena Luneva: You can't A/B test, you can't...

Barron Ernst: It trips up a lot of companies, right? Based on stage, they say, "I'm going to build a growth team," and it's like you don't have enough traffic to even start A/B testing. So I think that's another good one to throw in.

Elena Luneva: I love that. Like your point of going back to basics, like who's your ICP?

Barron Ernst: Yeah.

Elena Luneva: Do you know what they want?

Barron Ernst: I'm a bit of a broken record, which is sometimes... I feel like we all jump to "everything is different," and it turns out that a lot of times the "back to basics" pieces still make such a difference. With all the advances in AI, how has AI changed how you think about go-to-market, or has it? Has it made a difference, and how have you used it?

Elena Luneva: Yeah, I think it really has. I think the opportunity for me was at Braintrust and sort of seeing the light early on because we had to; there was pressure to keep the team small and to be able to do more things. But at the same time, we were building a full AI recruiting suite: job description generation, matching, AI avatars to do the screening... And so I think there's a lot of push right now in product management. People say that managers are not going to be around in ten years; they're all going to be coders. I have a counter-vision to that: what are product managers good at? Understanding the customer, figuring out what they want, building for them, and generating a lot of content along the way. What's AI good at? Content. So my dream for product managers is that they become general managers and really lean into that—"I know the customer and I can generate content and AI will help me"—and we were able to do that at Braintrust. For growth, content marketing, SEO, blog post generation, all of that, we were able to really lean into GPT and other tooling to have only a few people really focus on what the strategy is, how do we recombine pages instead of having human writers, how do we leverage AI to generate that mass amount of content for us so that we can stay very lean and still have the metrics and outcomes that we want.

The other piece is just product development efficiency. As a manager, you're constantly pinging your team to send you updates or update a doc, or, based on all the dots of information you've collected, put together a strategy doc. Claude has become my very underpaid but very competent assistant in helping me collate all of that information and operate much more efficiently as a manager. My team has also been able to use it to create not only the product specs of what we're going to build, but also to work off the information sales is getting—in Gong, for example—and really come up with the patterns of what customers are actually asking for in their own words and then be able to create that sales enablement documentation and content for GTM teams to be effective in positioning the product that we're putting out there. So instead of a salesperson coming to you saying, "Oh my gosh, I just talked to a really large customer and they want the following things," you're still taking that in, but extracting patterns from the 300 conversations rather than the most memorable one just because it has that recency bias. I think that has helped us, and I'm seeing more and more product teams adopt some of that tooling to just be much more effective at understanding the customer, building for the customer, and figuring out how to position that more effectively.

Barron Ernst: Yeah, I agree. The trend tracking across all the different points of feedback... in a weird way it's another "back to basics" thing, which is, "Are you talking to your customers?" AI makes it a lot easier to talk to your customers, but also to generalize the insights that should help inform the roadmap, which has been really beneficial for us as well, in addition to other areas that it makes easier to automate. But that whole process of making it easier to get to the insights, which was always important but a very time-consuming thing, making that cycle time faster is really important. I totally agree.

Elena Luneva: I love that. Well, I know we have a couple of folks on the call. If anyone has questions, just put them into messages. Otherwise, any closing thoughts?

Barron Ernst: I've probably broken the record. Think about who your stakeholders are when it comes to GTM. If you're a product person, who are your key partners that you need to work with to get something shipped? I like to think about this in terms of... I had a good learning from our CEO at Showmax, which sounds obvious, but it was not something I thought about actively. He was big on pre-morteming a release or pre-morteming something going on, and his general concept was, "We're going to ship this thing in a month. What are all the things that could go wrong and how would we either prevent them from going wrong, or if they went wrong, how would we respond to it?" I think that's a really good mindset to use when it comes to thinking about GTM. You think about what you want your ideal launch to be, but then you also think about what are all of the most likely variants of launches that could happen, and how do you either make one more likely or make one less likely and use that to feed into your planning methodology for this? That goes back to who should own what, what are the key channels, how does this all work together? That mindset of, "I'm going to think about where I want to be before I get there" has been a really important lesson I've learned in my career.

Elena Luneva: I love that. Getting back to basics, getting past that launch date and figuring out how you can really drive that outcome, and who it takes besides just you to get those people involved early. That's awesome.

Barron Ernst: Yeah.

Elena Luneva: Yeah, it sounds like there are no questions from the audience. Thanks so much, Barron, for joining.

Barron Ernst: Yeah, thanks for having me. It's been great.

Elena Luneva: Awesome. Have a good one. Bye.

Barron Ernst: You too. Bye.

Creating a design system can feel like building a house while still living in it—daunting, messy, and constantly evolving. Yet, the long-term benefits of consistency, scalability, and efficiency make it a worthwhile investment. Here’s how to navigate some of the common challenges product teams face when developing a design system.

1. Challenge: Lack of Time

Designers often juggle multiple priorities: product deadlines, stakeholder requests, and user testing. Carving out time to build a design system may seem impossible.

Solution: Create Space for Allocation

Treat the design system like a product in its own right. Advocate for dedicated time by articulating its ROI: reduced duplication, faster design cycles, and improved cross-functional collaboration.

• Start small with incremental contributions—e.g., updating a component during a project redesign.

• Consider assigning a “design system advocate” within the team to prioritize system updates and champion its value. It’s important to give this person access to key meetings to think through critical design elements across projects that are re-usable.

• Schedule sprints or cycles specifically for system development, even if it’s just a few hours a week.

• Create alignment between the product leaders and design leaders. The product team needs to be bought in on this concept - if design feels like they are working against product, it’s going to be hard to achieve success.

2. Challenge: Integration and Collaboration with Engineering

A design system isn’t just for designers—it lives and breathes through engineering. Misalignment or lack of buy-in from devs can lead to inconsistencies and a system no one wants to use.

Solution: Co-create with Engineers

Involve engineering from the start, treating them as co-owners of the design system. Their input can help shape components for ease of implementation.

• Host workshops to define shared goals and standards.

• Use tools like Storybook to make components accessible and interactive for developers.

• Build processes that prioritize dev feedback to keep the system usable and lightweight.

• Ask the engineers which components are the hardest to build and how the design system could help them the most. Build with them in mind and they will be supportive and want to work together on the system.

3. Challenge: Doing It in Phases

The temptation to build the perfect design system upfront is strong, but waiting for perfection often means waiting forever.

Solution: Start with Critical Components

Focus on the 20% of components that account for 80% of your design needs (e.g., buttons, typography, spacing). These foundational elements will bring the most immediate impact.

• Draft a high-level vision or "north star" for the system to guide priorities.

• Adopt a project-by-project approach: each time you work on something new, make it scalable and repeatable. Try to find small areas to apply the design system with each project rather than just trying to swap everything out in one massive workstream.

• Set milestones for progress, not completion—e.g., publishing a component library MVP or standardizing typography by the next sprint.

4. Challenge: Strive for Progress, Not Perfection

Sending a team off to build a design system in isolation is a recipe for irrelevance. Without user feedback and iteration, the system risks being out of touch with real-world needs.

Solution: Build in Public and Iterate

The best design systems evolve alongside the teams that use them. Share early drafts and gather input from designers, engineers, and even stakeholders.

• Establish regular feedback loops to identify gaps or pain points in the system.

• Create clear documentation and templates to onboard users quickly.

• Monitor adoption metrics—are teams actually using the system? What’s working or not?

Final Thoughts

Building a design system is as much about process as it is about the end product. Prioritize collaboration, focus on incremental progress, and don’t shy away from messy starts. Over time, the investment pays off, delivering a unified and efficient way for teams to create user experiences at scale.

Key Takeaways:

1. Allocate time strategically and start small.

2. Partner with engineering to create a system that’s easy to implement and maintain.

3. Tackle critical components first; let perfection emerge over time.

4. Keep the system alive through iteration, feedback, and real-world use cases.

In the aftermath of the 2008 financial crisis, the world was gripped by economic uncertainty. Consumers, battered by the downturn, became acutely deal-conscious, looking for ways to stretch every dollar. This shift in behavior created fertile ground for a new wave of e-commerce: flash sale websites.

Companies like Groupon, LivingSocial, Gilt, and One Kings Lane emerged to capitalize on this trend. Their pitch was simple but compelling: limited-time, deeply discounted offers on everything from spa experiences to luxury home goods. For a time, these businesses thrived, attracting billions in venture capital. At One Kings Lane, we rode this wave, raising a $112 million Series E funding round in early 2014 that valued the company at nearly $1 billion. (Source)

But what looked like a gold rush turned out to be fool’s gold. Flash sale and discount websites were destined to crash. Here’s why:

The Problem with Flash Sales

1. Email Overload and Consumer Burnout

At the core of the flash sale model was urgency. Shoppers were bombarded with daily emails advertising “exclusive” deals that would expire within hours. Initially, this sense of scarcity worked well to drive conversions. But over time, the constant barrage of offers led to email fatigue. Consumers started tuning out. The excitement and novelty of flash sales wore off, and shoppers simply couldn’t keep up with the relentless pace.

2. Shoppers Treated Us Like Discount Shops

Even for premium flash sale sites like One Kings Lane and Gilt, the fundamental problem was consumer perception. Shoppers came to these platforms to find deals on high-end products, whether it was luxury furniture or designer apparel. The problem? They only came for deals. The business model made it nearly impossible to shift customer behavior toward full-price shopping or cultivate a sense of brand loyalty. Consumers didn’t think of One Kings Lane as a furniture brand; they thought of us as a place to get a discount. That perception was hard to break.

3. Unsustainable Profitability

The deep discounts offered on these platforms didn’t just attract deal hunters—they eroded profitability. At One Kings Lane, like many others, we operated on the assumption that we could eventually increase customer lifetime value (LTV) enough to justify our high customer acquisition costs (CAC). But this proved difficult in practice. It was hard to drive LTV to levels that made customers truly profitable.

Compounding this was the long payback period. For many flash sale sites, it could take two or three purchases before a customer’s spend offset their acquisition cost. This slow payback meant we needed significant amounts of capital to sustain growth. With cash tied up for long periods, the business model became increasingly capital-intensive, but we weren’t achieving the scale required to make the economics work.

A Business Model That Couldn’t Support VC Valuations

The challenges above created a vicious cycle. Flash sale companies needed ever-increasing amounts of capital to grow, but the growth was coming at a steep cost. From a venture capital perspective, this made the business model unsustainable.

Investors who had once been enthusiastic about the promise of rapid customer acquisition and billion-dollar exits began to realize that these businesses couldn’t scale profitably. The valuations that had once seemed reasonable now looked wildly optimistic. In 2016, One Kings Lane was sold to Bed Bath & Beyond for what was described as a “not material” amount—an extraordinary drop from our nearly $1 billion valuation just two years earlier.

The Intensity of Flash Sales

Running a flash sale business was exhausting. Every day required lining up new deals to keep customers engaged. There was no consistent, evergreen revenue stream to fall back on. If the daily deals weren’t compelling, sales would slump. It was a relentless treadmill, and stepping off it—even to pivot to a new model—was nearly impossible without sacrificing the revenue streams keeping the business afloat.

The Rise of Direct-to-Consumer E-Commerce

Around the same time flash sale companies were floundering, a new wave of direct-to-consumer (DTC) e-commerce brands began to rise. Companies like Casper, Warby Parker, and Glossier built their businesses on strong branding, influencer partnerships, and direct relationships with customers.

Unlike flash sale sites, which were saddled with their discount-driven reputations, DTC brands focused on storytelling, quality, and value—not urgency or price. They developed loyal customer bases and repeat business without relying on relentless email promotions. Flash sale sites, constrained by their business models, struggled to adapt and missed out on this opportunity.

Why Flash Sale Companies Couldn’t Pivot

One of the greatest challenges facing flash sale companies was their inability to innovate away from the flash model. Successfully pivoting would have required giving up the very revenue streams the business relied on. With significant VC funding and the accompanying growth expectations, walking away from the flash sale model was almost unthinkable.

Even if we had wanted to pivot, the brand perception was a major obstacle. For One Kings Lane, consumers associated us with discounted furniture. Convincing them to think of us as a full-price, evergreen retailer was an uphill battle we couldn’t win.

Lessons Learned

The collapse of the flash sale trend offers several important lessons for entrepreneurs:

1. Sustainable Models Matter: Building a business entirely reliant on discounts and urgency can drive short-term growth, but it’s incredibly difficult to sustain. Focus on long-term customer value instead.

2. Customer Perception Is Hard to Change: Once consumers associate your brand with discounts, it’s nearly impossible to shift their perception.

3. Beware of Capital-Intensive Growth: Businesses that require constant injections of capital to grow risk collapse if the economics don’t eventually stabilize.

4. Revenue Consistency Is Key: Flash sale businesses struggled without a predictable revenue stream. Models that rely on one-off spikes in sales are inherently risky.

Final Thoughts

Flash sale sites like One Kings Lane enjoyed their moment in the sun, fueled by a post-recession appetite for deals and an abundance of venture capital. But the very factors that drove their early success—deep discounts, consumer urgency, and high-intensity deal-making—ultimately led to their downfall.

While these companies may not have achieved long-term sustainability, they left behind valuable lessons for today’s e-commerce entrepreneurs. The next wave of online businesses must prioritize sustainability, customer loyalty, and adaptability over quick wins and rapid growth.

When we set out to build Showmax, the first Sub-Saharan African SVOD (subscription video on demand) streaming service, we were entering a market filled with challenges but also incredible opportunities. Like many streaming services at the time, we launched with premium content from international giants like HBO and Showtime. It was a solid starting point—globally acclaimed shows like Game of Thrones and Billions gave us credibility and attracted early adopters. But it wasn’t long before we realized that simply curating international hits wouldn’t be enough.

To truly connect with our audience—to make Showmax not just a streaming service but their streaming service—we needed to lean into something far more powerful: local content.

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Why Local Content Matters

Sub-Saharan Africa is a region rich in diverse cultures, languages, and storytelling traditions. Yet, for many years, those stories weren’t being adequately represented on streaming platforms. International shows might have global appeal, but they often felt distant or out of touch with the day-to-day experiences of our audience.

We quickly realized that showcasing local content was not just a nice-to-have; it was a must-have. Here’s why:

• Cultural Relevance: Local stories reflect local realities. They resonate on a deeper level because they showcase the experiences, humor, and struggles that are uniquely African.

• Affordability: Producing local content was often far more cost-effective than licensing international titles. It allowed us to create more shows for less, without compromising on quality.

• Audience Connection: We saw tangible improvements in viewing times, engagement, and retention when we added local content. People didn’t just watch—they relished these stories because they felt seen and heard.

• Highlighting Local Creators: By investing in local talent—writers, actors, directors, and producers—we were able to elevate the entire creative ecosystem. Shows like Tali’s Wedding Diary weren’t just hits; they won awards and became cultural touchpoints.

Building a Sustainable Model for Local Content

Once we saw the impact of local content, it was clear we needed to build a sustainable mechanism for creating and delivering these stories. This wasn’t a simple task. Producing original content requires infrastructure, investment, and commitment. It also required a mindset shift: we had to embrace the fact that we were not just a streaming platform but also a content creator.

The work was demanding, but the payoff was undeniable. By doubling down on local productions, we achieved several key outcomes:

1. Subscriber Growth: Local content became a major driver of new subscriptions. People were drawn to Showmax because it offered something they couldn’t find anywhere else—high-quality, homegrown stories.

2. Retention and Engagement: Our audience spent more time on the platform, binge-watching shows that felt personal and familiar. The more local content we produced, the stronger their loyalty became.

3. Differentiation: While competitors relied heavily on international content, Showmax stood apart as a platform that championed African stories. This became our key differentiator in the market.

The Success Stories: Tali’s Wedding Diary and Beyond

One of the standout successes was Tali’s Wedding Diary, a hilarious and brilliantly crafted show that quickly became a favorite among viewers. It wasn’t just a hit in terms of viewing numbers; it also won awards and solidified Showmax as a platform capable of producing premium, culturally relevant content.

Tali’s Wedding Diary was proof that we were on the right path—that local stories had both the creative potential and the audience demand to succeed. And it wasn’t an isolated example. Over time, we produced and showcased a wide range of local content—from dramas to comedies to documentaries—all of which contributed to making Showmax the biggest streaming service in Sub-Saharan Africa.

Content as a Competitive Advantage

In the crowded streaming market, where global players compete for attention and wallets, content remains the most powerful competitive advantage. At Showmax, our journey taught us that:

• The right content doesn’t just attract viewers; it creates connection.

• Investing in local content isn’t a cost; it’s an investment in long-term differentiation and growth.

• By telling local stories, you not only build a stronger business but also empower local creators and audiences.

The success of Showmax was never just about streaming. It was about belonging. By giving a platform to African stories, we gave people a reason to choose Showmax over and over again.

Final Thoughts

Content is, and always will be, king—but context is queen. At Showmax, we learned that the most valuable content is the kind that reflects the culture, values, and experiences of its audience. Local content was our secret weapon—a way to differentiate, connect, and grow.

For anyone building products in competitive markets, the lesson is clear: don’t underestimate the power of relevance. Whether you’re streaming TV shows, building software, or launching a new app, the closer you get to understanding your audience’s needs and aspirations, the more successful you will be.

At Showmax, local stories helped us create something more than just a streaming platform. We built a home for African creativity—and that made all the difference.

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Q: How do I move from working in Growth internationally to the United States or from the U.S. to an international market?

Today’s newsletter is based on a question I have been asked dozens (maybe hundreds) of times in my career - moving between the U.S. and international locations as a growth practitioner.

Because I’ve never actually lived and worked internationally myself I invited Barron Ernst to write a guest newsletter on this topic. 

Barron has held growth and product leadership roles at international companies like Snap, Booking.com, and Naspers. He has lived in Amsterdam, France, and launched products all over the world, including South America and Sub-Saharan Africa. He has also worked as a PM and product leader in the U.S. at companies like Intuit, Rewarder, and One Kings Lane. Today, he is back in the U.S. and holds the title of Chief Marketing Officer at Figure. 

In today’s post, he’ll explain:

• The differences between the U.S. and International markets for Growth roles.

• Why you might consider pursuing an international role if you are practicing in the U.S. or why you might consider a U.S.-based role if you are working internationally.

• How to break into Europe as a Growth practitioner

• How to break into the U.S. as an international Growth practitioner

Hi - I’m Barron. I worked in Europe for 7-8 years across a variety of product and growth roles for Snap, Booking, and Naspers/Prosus. I led multiple different Growth and Product organizations internationally. I also have run growth and product teams in the United States for Figure, One Kings Lane, and IMVU.

Let’s begin!

I started working in Europe in 2015 for Naspers, which is a large international investor in companies like OLX, Byjus, PayU, Delivery Hero. They also owned more than 30% of Tencent at the time and continue to be one of their largest stakeholders.

When I first arrived I was exposed to Growth across their portfolio of businesses. In 2015 many international markets were behind the Growth trend in the United States, but the gap was closing fast. I had specific exposure to Europe, Africa, and South America. That’s where I’ll focus my energy for this article. If you are trying to break into India or China, I think there are more similarities with Growth in the United States due to the large levels of investment and competition in those markets.

In terms of a talent base, there were a small number of very senior product leaders, many senior PMs, and a lack of people in the mid tier (Group PMs and Directors). It meant that a very small number of people had deep experience with Growth in 2015.

Because of this, I ended up introducing the growth function at most companies where I worked. This usually consisted of hiring a growth product manager and making sure they were well resourced with design, analytics, and engineering. But growth was just the product side and marketing was still a self-contained, separate unit. 

A lot of my time was spent educating the executive team of companies that I was advising or working for on the value of product-led growth and how it could change their organization. For example, I had multiple presentations introducing simple concepts like growth models, metric measurement, and how to build teams focused on growth that were used for companies of all different types.

By 2022, there were more growth roles in Europe than when I initially arrived in 2015, but it still did not have a seat at the table in the same way as a CMO, CPO or CTO. However, it is starting to become more common for companies to hire for Growth, especially in certain geographies where burgeoning communities exist.

There are pockets within Europe where the growth focus is strong. There’s a great growth community in Berlin, largely driven by Andy Carvell and the ex-Soundcloud crew. Paris has a strong growth community, many of whom I worked with at Zenly, but also at companies like BeReal, amo (ex-zenly), Voodoo, Ankorstore, and many more. The Family is also a great incubator that regularly brought in Growth experts to help educate and up-level people. These centers of Growth excellence were much less common in other international markets like Africa and South America.

To compare it to the United States, there are a few key differences that still exist:

• Growth was not adopted widely throughout Europe. Certain cities or geographies had a stronger practice where you’d more commonly see Growth roles, like Berlin or Paris.

• The vast majority of the time Growth doesn’t have a seat at the leadership table; especially at the C level.

• There remains a lack of experienced practitioners, especially at the middle layer. 

• Many companies and executives were introducing Growth for the first time. This also meant there was some natural skepticism towards the function, especially regarding terms like growth hacking [AF Note: I have thoughts on this]. 

• If you get hired for a Growth role in Europe it’s key to bring a strong methodology. You are not only proving yourself, but the function as well.

Why might you want to explore a growth role abroad?

The biggest advantage I found for pursuing a Growth role abroad is to get exposure to the different cultural, linguistic, and behavioral differences that exist between the United States and other markets. As you expand your Growth experience, international expansion becomes key. However, most U.S.-based Growth practitioners assume that they can apply the same growth model that worked in the US to all other markets. I found that this was not often the case.

If you are trying to grow a product in Sub-Saharan Africa, you will rapidly learn that the competitive set, the technological infrastructure, and the Growth methods often are very different.

When I was the Chief Product Officer at Showmax—the largest streaming video on demand (VoD) platform in Sub-Saharan Africa—I initially assumed I could leverage a similar Growth playbook to what we’d seen done at Netflix as they expanded into new markets.

I was wrong. We learned that in markets like Kenya, South Africa, and Nigeria, we often had to innovate just to get our product adopted. Many people relied on incredibly expensive data plans for the internet and wired infrastructure was only just being installed (and was quite expensive). This meant that to achieve growth, the key was finding ways to limit data costs to enable streaming video to work. Growth through partnerships with telcos like Vodacom (South Africa) and Safaricom (Kenya) proved much more valuable than Direct to Consumer channels because we could leverage free or limited cost data bundling. Also, it meant we could use an existing payment channel for the user.

We also weren’t only competing with typical, known competitors. In Kenya, we interviewed many people to understand how they consumed content. For many, the way they got media and entertainment was from the “movie guy” in their neighborhood. This was usually someone who had a good enough data connection to torrent content and then sell it on burned CDs and DVDs. Over time, his recommendation algorithm was that he would ask his customers what they liked and didn’t and tailor his content for each user accordingly.

That is not the typical competitor you would think of if you are based in the United States. It requires taking time to understand the market and local dynamics abroad. Through being on the ground and having that lived experience we were able to craft the right type of offering that could solve for those unique challenges.

In Europe, you will get experience dealing with a much more complex localization challenge. Europe is smaller in total area than the United States, but it’s more populated and there are far more linguistic and cultural differences to navigate. 

At Zenly, we localized the product in over thirty languages to account for the growing number of European and Asian audiences we were attracting. We did this by working closely with local language experts in those markets to match our unique linguistic style with slang and other wording that would attract our predominantly 18-30 year old audience. 

As with Showmax, I found it much easier to understand the distinction linguistically and culturally by being there on the ground. When you are in the United States you don’t viscerally understand how different it can be country to country and region to region.

Why might you pursue a role in the United States if you are practicing Growth abroad?

I think this is a much more obvious answer. Some of the best thought leaders and Growth leaders are in the United States. Abroad, you are often learning how to do Growth on your own or from a limited and often less experienced set of practitioners.

In the United States, there are a number of incredibly strong leaders and companies that defined Growth like Meta, Uber, Dropbox and many others. The practice is generally recognized as a key function at most technology companies. It’s an invaluable opportunity to learn from the best and hone your technique.

Additionally, after two or three years practicing growth in the United States, you will have significantly more market power abroad. There is still a market for people who trained at great companies in the United States. You’ll often find that people with five or six years of experience in the United States can get much more senior roles in Europe than they would be able to in the United States. This leads to rapid opportunities for career advancement.

How to get into Growth internationally

Although this is a limited sample size, I searched for “growth product manager” in both Paris and Amsterdam at the beginning of February 2024. The results were quite sparse:

This doesn’t mean you can’t break into Europe in a growth role. You just have to get more creative.

I found that the easiest way to get into Growth was to start on the product side and build the function out over time. One approach for more junior folks is to start by finding a product role with an aspect of Growth to it—funnel conversion, CRM, virality—then work to grow that into an overall function. Once you have this background you can leverage that to move to other companies as well.

I think that anyone who is a strong Growth person from the United States could find a product job in Europe and then build the Growth function over time. Since many companies won’t be hiring for Growth leaders you can create a pitch that positions you as both a product leader and a growth leader (or as a marketing leader and a growth leader). 

There are also some companies, like Booking, that are very conversion and optimization focused. That can be a great training ground and help you build the foundation before transitioning to another company and a more senior role.

If you want to go straight into smaller startups first, look to Paris. Paris's scene is very up to date on the latest Growth trends, so exploring something like Station F will lead to startups that understand the role.

One note is that it is common for Growth to be a marketing function in Europe. Sometimes, this will manifest more as a traditional marketing function with a Growth title. Other times, it will be a more Growth-centric role. Ask these questions before you accept the job (AF note: I’ve got a whole newsletter on Reverse Interviewing):

• Who leads Growth at your organization? What is their background? You want to make sure the person has some knowledge and background in the space, that they know that there’s a product and marketing element to this role, and that they don’t just want you to optimize marketing channels.

• Is there a development team and data team to work with? If the answer is no, be careful. Without these functions or plans to build them you might be setting yourself up for failure.

• Is there a belief in Product Led Growth at the organization? Does the company believe that the product itself should be a key driver of Growth, or are they just looking for hacks and marketing spend?

What about Growth people who want to come to the United States?

Transitioning to the United States is all about framing the work you did in Europe properly and then finding the right Growth fit over time. There is a better understanding of Growth roles in the United States and as long as you can demonstrate you have the skillset you can find your way in. Additionally, if you have done Growth in Europe or other locations internationally, that is often a skillset that’s in high demand for a lot of U.S.-based companies. Leverage that to your advantage, especially if you have experience with localization, dealing with the challenges of multiple different cultures, and currencies.

Some of the key growth tools I learned in Europe were:

• The value of localization beyond just basic translation. At Zenly, we had networks of locals in our top markets who would help us understand the sentiment on the ground and would also help to make sure our product had the right tone and feel that fit our local, target audience. We had a playbook we could leverage to build this in each country, but we also had to build an adaptable localization framework to make it possible.

• Rapidly developing markets present unique challenges. For companies trying to expand to Africa, India, LATAM, and many other markets, international growth roles will give you direct exposure to those challenges. As discussed above, you’ll learn that data connectivity and internet infrastructure vary a lot by region. You’ll need to build unique solutions to market problems. For example, in a number of markets, you can’t rely perfectly on address data from Google or Apple because they won’t be as up to date. Local delivery companies, e-commerce companies, and Uber have all had to modify or build custom data sets to enable their businesses to scale efficiently. This knowledge is hard to acquire while sitting in San Francisco, New York, or somewhere else with good internet access and reliable addresses.

• Diversity of devices. This is still relevant in the United States, but internationally, you need to be much more active in using and testing on multiple Android devices and across a wide variety of browsers as well. The dominance of iOS does not extend everywhere. In Africa, it was common to see a number of cheap Android devices and to see a device split closer to 60% Android 40% iOS. You can’t just deliver a singular great mobile experience. Building a great Android experience that works across 20-40 different reference devices matters to achieve growth. If you are building a streaming video product this gets even more complex with a variety of different TV and set-top boxes.

For anyone working in international growth, I would recommend thinking about the key areas of expertise you have acquired. What is your niche? What markets do you know better than anyone else? What devices do you understand? Did you build a playbook that enabled rapid expansion for language, audience, and user experience that you can bring to a U.S. company looking to expand rapidly to another part of the globe? To start, build out a growth portfolio that you can share with American companies to set yourself apart.

Closing Thoughts

There are a number of key takeaways whether you are trying to get a growth role abroad or in the United States.

If you are pursuing a growth role in Europe:

• Highlight your experience growing a company in the United States. Leverage that background as a domain expert to come in and build and/or lead a growth function

• Be ready to build out the growth function from within the product and sometimes the marketing organization.

• Ask hard questions of the company leadership to make sure they understand the value of product led growth. Make sure you aren’t just accepting a role where you’ll be stuck doing performance marketing or funnel optimization.

• You may have to start with a more traditional product role at first while you help the company understand the value of a Growth organization

If you are coming from Europe and pursuing a growth role in the United States

• Leverage the unique Growth learnings you acquired abroad. Focus on localization, cultural understanding, and depth of user knowledge as differentiating factors

• Search for companies with strong growth functions. A great way to level up is to work with the incredible growth leaders in the United States to build a refined growth framework that combines your unique local knowledge with repeatable frameworks

• Leverage networks like Reforge and other Growth communities to get in touch with Growth referral opportunities

As a last bit of advice, many people ask me if moving abroad was worth it from an experience perspective. To anyone who has the desire, I found it a deeply rewarding experience both professionally and personally. It’s scary and also wonderful to be thrown into a new culture. You have an incredible opportunity to advance personally by gaining new viewpoints, making new friends, and having a number of new cultural experiences.

Professionally, it exposes you to different mindsets about work and to different cultural perspectives as well. There’s probably an entire additional newsletter to be written about this, but I think it will make you a more well-rounded professional.

We had to get new jobs and we spent a lot of time helping the team find roles as well.

And despite the pain, it was one of the most important lessons of my career.

Rewarder was a marketplace that focused on helping people find answers to home, auto, travel and tech questions from a community that could help. If that sounds overly broad, it definitely was. We built a product that tried to do too many things for too many verticals. Looking back, we were doing a mediocre job solving lots of problems rather than getting really good at solving a specific problem.

I left before the end. I’m not sure if it’s because I had a feeling we weren’t going to make it or my time was just up. It definitely didn’t feel like a sustainable business and that played a large part in leading me to depart, despite the fact that I was part of the founding leadership team.

Looking back, it’s very clear. We didn’t have product-market fit. We hadn’t nailed a single vertical and instead were trying to be far too broad, meaning we couldn’t solve anything well. The team did a great pivot after I left and started to focus on tech help - connecting people who were not tech savvy with younger people who could help them out. It had real promise, but unfortunately it came when funds were running out and there wasn’t enough traction to raise more money.

The learnings:

• Product market fit is the only path to a successful startup. Spray and pray, even with a good idea, is just too hard to execute with a small team

• Sometimes it’s ok to leave before the end. In my case, because I had a new job, I was able to help out multiple members of the team and hire them into my new company, providing them with a path to earnings

• Don’t grow too fast or put too much money into the marketing engine until you start to see profitable and/or retained interactions that give you a reason to believe

• It’s incredibly important to stay focused as a leadership team. Pivoting is fine, but it should be a decision based on lack of product-market fit, not because there are endless opportunities. If you pursue every opportunity, you won’t nail anything well and you won’t have a viable business in the long run

  .

Despite it all, I’m grateful I had the experience. We made a lot of mistakes, and they are mistakes I can see now often before they happen and that I can try to avoid in new companies and with new teams. We didn’t make it big, but the learnings were invaluable and the reality is that everyone went on to great careers.

Do you have similar experiences or learnings? I’d love to hear about them.

However, I had to re-arrange my work and personal life to make it happen. Here are some of the lessons I learned from doing this:

Re-organizing your day to sleep even earlier and wake up earlier provided structure. I tend to be an early riser and early to bed person. However, to do backcountry skiing before work, I usually needed to leave my house by 530AM to be at the trailhead by 6AM. This required building a structured sleep schedule and a plan in the morning to be out the door on time. However, I really liked the structure. It was stressful some mornings, but overall, it ensured a great workout before starting work most days.

Being in nature before work really makes it easier to be in front of a screen all day. I found that having a few hours in nature working uphill and skiing down to be a great mental and physical cleanse. It meant my body had already accomplished something but it was also a clarifying way to clear your brain and get priorities well aligned. There’s something incredible about seeing the sunrise before starting your day.

It’s great to do something really hard before you start working. Most days I’d climb 1500-2000 feet when skiing before work. That’s not a crazy amount, but it’s pretty hard work at 6am with a headlamp on. It also makes work things that you perceive as hard feel a bit easier. You’ve already done one of the hardest things you’re going to do all day, figuring out growth and marketing plans feels less daunting.

Forced prioritization becomes key. I found the fact that this compacted my morning to be a great thing. I have a tendency to wake up and spend some time going through work early before starting workouts. However, inevitably that will involve google/wikipedia deep dives and general wastes of time. The great thing about this was that it cut down on some of that wasted time and re-directed it towards physical activity. It also meant that I was much more purposeful with my time for work and I often found myself more efficient with better results.

I of course don’t recommend that everyone undertake something this extreme. But if you can make it outside or at least to a meditation or workout session that allows you to reset and disconnect before the day, it can add a lot of value.

In the world of product management, there's often pressure to deliver quick results and speed up the development process. However, there are times when investing in a longer build-out can actually be more beneficial in the long run. In this blog post, I’ll explore a situation we had at IMVU, where a longer build-out led to greater success and business impact.

The Challenge: Revamping the Checkout Experience

IMVU's checkout experience was outdated and hadn't been updated in years. A lot of the UX was nearly original, and we were growing quickly, adding new payment options, and needing to test our checkout experience. 

One of our main goals was to improve the checkout experience to increase conversion rates and boost revenue. Initially, the plan was to run a simple A/B test with a new, more streamlined concept for the checkout process.

The Decision: Short-Term vs. Long-Term Build-Out

When it came to implementing the new checkout concept, the team faced two options:

• Execute the current test quickly, taking about 2-3 weeks to deliver.

• Re-build the entire checkout code to support ongoing testing and optimization, which would take 5-6 weeks to complete.

The obvious answer for many would be the first option. It was a quick way to execute a test and determine if we could get signal. Also, IMVU was the home of Lean Startup thinking, meaning we had a culture of rapid testing based on MVPs. 

However, there was no question that we would run to want many tests on our checkout experience. It was a core part of the product and we were not trying to achieve product-market fit. We were profitable and making millions of dollars a month, so the opportunity was to grow that revenue base rather than to experiment with new features. 

Additionally, we considered the fact that we wanted to conduct extensive testing on the checkout flow and that most tests on flows have a relatively low success rate (10-20% in most cases). Consequently, we predicted we would be running a large volume of tests in order to successfully optimize this part of the product. 

The Benefits of a Longer Build-Out

By investing in the longer build-out, the team was able to create a more scalable and efficient process for future tests. The new code made it easier to introduce new products, change the store's featured items, and adjust prices more quickly.

The decision to take a longer approach was made through open conversations between engineering, product, and design teams. We considered not only the immediate impact of the decision but also the potential long-term gains and opportunities that the new code would unlock. In this case, speed to market of a single test did not outweigh the longer term upside we would get from a slighter longer build that would enable more rapid ability to iterate.

The Results: Incremental Revenue and Testing Opportunities

The results of the initial redesign were promising. The revamped checkout experience led to an immediate increase in incremental monthly revenue, totaling around $1 million in annual run rate. More importantly, the new code opened the door for numerous incremental tests and offerings, which further multiplied the revenue gains.

Conclusion: The Importance of Nuanced Decision-Making

The key takeaway from this case study is not that a longer build-out is always the right choice. Instead, it highlights the importance of having open conversations between different teams and considering the expected current and future costs and benefits of a decision. By taking a more nuanced approach to decision-making, businesses can make better choices that ultimately lead to greater success and growth.

It also makes it clear that you need to consider the feature or product area when deciding on short term or longer term thinking. If you have no data that the feature or area will have product-market fit or if you aren’t sure it will be accretive to the business, faster cycles to get signal are preferred. For parts of the product where you know they are important and you expect to iterate for months or years, having a conversation about the benefits of a slightly longer cycle to unlock more velocity is worth considering.

IMVU, the 3D avatar-based social platform, has always had a unique economy where users can create and sell virtual goods, making real money in the process. In this blog post, we will dive into the complexities of IMVU's economy, exploring how creators were paid, the role of sales and promotional credits, and the challenges faced while managing the creator community.

The Unique Economy of IMVU:

IMVU's economy allowed creators to be paid a percentage of sales in credits, as long as the items were purchased with non-promotional credits. Each item sale removed some credits from the economy, but it took multiple sales for credits to exit the system. Creators could resell their credits through third parties, with some making over $100,000 annually. IMVU maintained an arms-length relationship with resellers, allowing them to exist for the sake of the economy without explicit endorsement. It was more of a symbiotic relationship that enabled credits to be removed from the economy while allowing creators to cash out and earn money.

Running Sales and Credit Influxes:

Sales were crucial to IMVU's business but posed challenges in understanding their impact on the economy. For example, 50% off credit sales would nearly double daily revenue, but the long-term effects were hard to gauge. These sales acted like a central bank, injecting massive amounts of credit into the economy. Balancing sales against revenue demands was tricky, as relying too much on sales created a cycle of dependence and made it difficult to maintain normal pricing.

Think of it like a central bank, we created a massive influx of credit into the economy on a one time basis, but there wasn’t a good way to measure when there was too much saturation of credits in the economy. Therefore, we had to be constantly watching daily sales to ensure we didn’t become overly dependent on credit sales and also watch credit sinks out of the economy.

We had to balance this against revenue demands - if we were behind plan for a given month, the instinct was to run a sale. But doing this often just created a cycle of dependence on sales and made it hard for us to keep things at the normal price. Therefore, we had to stay disciplined in how often we ran sales.

Promotional Credits and Creator Community Management:

Ensuring new users had enough credits to get started without upsetting creators was a delicate balance. Providing too few promotional credits resulted in a poor user experience, but giving too many risked angering creators, who didn't receive monetary value for items sold with promotional credits. Outreach to creators was essential, but finding the right balance was challenging.

The main thing we had to figure out was how to give enough promotional credits to a new user so they wouldn’t be perceived as a noob by others in the community. However, if we gave too many promotional credits, creators could be upset because they would see sales for their items that wouldn’t result in monetization.

We constantly iterated on the right amount of promotional credits. If we didn’t give enough, a new user would have a terrible avatar and outfit and many of the others in the community wouldn’t befriend them. Our core retention metric was linked to finding friends in the community within the first few weeks.

We tried an experiment where we gave away a massive amount of promotional credits - it looked like it was creating a lot of onboarding for the new users, but the reaction from creators was so negative that it risked a key part of the economy. Building IMVU was not as simple as just optimizing for onboarding - the whole cycle needed to be considered with key changes or experiments that we were running. You had to balance a focus on the core retention metric for new users while also making sure that the creators who generated all the content and goods were happy.

Building a Credit System to Address these Challenges:

Several key principles guided IMVU's credit system development:

1. Promotional credits needed to be limited to an amount sufficient for outfitting a new avatar, allowing users to onboard without upsetting creators.

2. IMVU facilitated the creation of affordable looksets (complete avatars with outfits) by working with creators and sometimes compensating them separately.

3. Sales were crucial but had to be carefully managed to preserve the value of credits and prevent economic collapse.

Conclusion:

IMVU's unique economy presented numerous challenges in balancing creator interests, sales, and promotional credits. By learning from their experiences and adapting their credit system, IMVU managed to create a thriving ecosystem that benefited both creators and users. This serves as an interesting case study in understanding the complexities of virtual economies and the importance of finding the right balance to ensure the sustainability of the platform.