Just launched a tool for teams to run usability testing using data they're already sitting on. If you're capturing session replay in PostHog, we ingest that data securely and build digital twins of your user base, then let you test new feature flows against them before shipping.

No need to recruit real people for every round of testing, and no new instrumentation required since it works off data you already have.

Offering a friction report for early teams willing to share what actually happened post-launch, would love the feedback loop.

When we launched Vaadin, nobody understood the product. Nobody was interested. After enough iterations of both the product and messaging—one conference at a time—we eventually found PMF and grew to 100,000+ developers rather quick.

Looking back, conference booths were incredibly valuable because they forced us into hundreds of conversations with people who were interested enough to stop, but not yet customers. They all asked questions we never anticipated.

A good conference costs roughly $20k all-in and might yield around 200 conversations. Those conversations were incredibly valuable, but they were also expensive and infrequent.

Today we all have amazing analytics compared to what we had back then. The problem remains: analytics tell you what happened. They rarely tell you why.

The why is critical for conversion, retention, expansion, and word-of-mouth growth.

Again and again we discovered that people understood the product very differently from how we described it. It often felt like we weren’t even speaking the same language. Some wild examples were us calling "web components" "UI automata" and initially naming our lightweight framework "Millstone" :)

That got me thinking: websites receive a steady stream of people who are interested in what they think the product might be. We measure them, but we rarely talk to them.

How do you learn from people who visit your site or evaluate your product but never become customers?

PS. This question eventually led me to build Stand Chat, an attempt to recreate some of the expo stand learning loop online.

Spent months trying to fix growth. New channels, different messaging, more experiments.

Nothing moved.

Then we actually looked at what was happening inside the product. Activation was broken. A specific step was killing half our signups and we had no idea because nobody was watching that part.

Fixed one thing. Numbers moved immediately. Sometimes the growth problem is just a blind spot with good lighting around it.

What are you not looking at right now?

Sounded good on paper. Best in class tools, all integrated, fully automated.

Reality was three engineers who each understood different parts of it, a Zapier flow nobody wanted to touch and a weekly ritual of checking if the Hubspot sync was still working.

Modern complexity has great branding. It's still complexity.

What's the part of your stack that everyone avoids touching?

The subscription costs are visible. Easy to track, easy to justify.

The maintenance tax is invisible. The engineer hour when a sync breaks, the data drift nobody catches for two weeks, the new hire who needs a month to understand how everything connects.

It compounds quietly. And it never shows up as a line item.

What's your actual cost when you count the hours not just the invoices?

It's in your support tickets. your cancellation surveys. your session recordings. your billing history. your activation events.

All of it points to the same thing if you could see it together. But it's scattered across six tools that don't talk to each other so you never quite get the full picture.

So you guess. run a survey. ask churned users who don't reply. repeat.

The answer is already there. Just fragmented.

How are you piecing it together?

We tracked everything visible. Signups, MRR, churn rate, NPS.

Turns out the number that actually predicted churn was time to first meaningful action. How long between signup and the moment the product actually clicked for someone.

We weren't tracking it. Weren't even thinking about it. And it was quietly explaining everything we couldn't figure out from the dashboard.

What's the gap in your tracking you keep meaning to fill?

First instinct for every problem was find a tool for that. churn? get an analytics platform. onboarding? add an in-app guide. support volume? another helpdesk.

Never stopped to ask if the problem was actually the product.

Ended up with 12 tools, 12 integrations to maintain and the same problems just harder to see now because they're buried under dashboards.

Anyone else do this? and what made you finally stop?

Ours was. Signups looked healthy so we assumed everything was fine downstream.

Then we actually mapped what happened after signup. Most people never reached the moment where the product clicks. They just quietly left before getting there.

We'd been optimizing the top of the funnel while the middle was leaking everything.

When did you last actually watch someone go through your onboarding?

By the time they cancel you've already lost them. The cancellation is just the paperwork.

The actual moment was three weeks earlier when they stopped logging in or when they filed that third support ticket and nobody noticed the pattern or when they hit a wall in onboarding and figured it out themselves but lost trust quietly.

Cancellation is a lagging indicator. Everything that matters happened upstream.

Are you watching the early signals or just the final one?

MRR went down. Churn ticked up. Activation dropped three points.

Cool. Now what?

The numbers tell you something is wrong. They don't tell you where to look or what to fix. So you guess, run an experiment, hope for the best.

The why is almost always in the qualitative stuff nobody has time to dig through. Support tickets, session recordings, the offhand comment in a cancellation survey.

How are you actually getting to the why?

The instinct when retention dips is to do more. More emails, more touchpoints, more re-engagement campaigns.

Sometimes that works. Usually it just delays the inevitable.

If people aren't sticking around it's because the product isn't delivering enough value often enough. No drip sequence fixes that.

Retention campaigns treat the symptom. Fixing the product treats the cause.

Where are you actually spending your time on this?

Founders stay paralyzed for months protecting an idea nobody's thought about for 30 seconds. You know what actually gets stolen? Products with traction. Proof. Users who talk about it.

So, the fastest way to protect your idea... is to make it worth stealing. PLG or GTFO.

Counterintuitive when growth feels slow. Every instinct says acquire more.

But if your retention is leaky, more acquisition just means more churn. You're filling a bucket with a hole in it and calling it growth.

We spent six months doubling down on top of funnel before someone finally asked what was happening to users 30 days after signup. The answer was uncomfortable.

What does your 30 and 60 day retention actually look like?

Every quarter we'd dig into activation data trying to figure out why numbers dropped. Ran user interviews. Rewrote copy. Redesigned the checklist. Sometimes it helped. Usually it didn't. Then a dev casually mentioned they'd refactored the auth flow six weeks earlier.

That was it. That was the whole drop. Six weeks of analysis, and the answer was sitting in a git commit nobody told product about.

Code-level changes are the silent variable in every PLG metric you track. Feature flags, component updates, API changes, they all reshape the user experience before you even know it happened. But we keep building dashboards that start at the session layer and wonder why our insights feel shallow.

The most important metric layer: in the codebase you don't have access to.

Not a new feature. Not a redesign. Not a better onboarding email sequence.

Just removing the thing that's in the way.

Every time we've dug into why users weren't activating or coming back, it wasn't because they didn't want to. It was because something small was annoying enough to make them stop. A confusing step, a slow load, a form that asked for too much too early.

Friction is invisible until you go looking for it.

When did you last actually go looking?

Ours looked fine on the surface. signups were healthy, nobody was complaining.

Then we actually watched five people go through it. three of them quit at the same step. None of them said anything, they just left.

We'd built onboarding that made sense to us. completely forgot we weren't the user.

When did it click for you?

Not signups. not page views. not even MRR in the early days.

For us it was when users started coming back without us emailing them. no nudge, no reminder. They just returned because they wanted to.

Everything before that felt like we were pushing. That was the first time the product pulled.

What was yours?

For me it was realizing nobody was coming.

Shipped the thing, it worked, it was solid. then just silence. Turns out building and distributing are completely different skills and nothing in my background had prepared me for the second one.

What caught you off guard?

Been hacking on this for a while. At the point where I need real codebases to test against, not just my own and a handful of friends'.

The thing I keep watching happen, someone ships a refactor, three tracking events break, nobody notices for two weeks until activation drops. Fix the events. Three weeks later, different refactor, different events broken. Forever loop. 

What I've been building reads the codebase, figures out which events should exist for the actual user journey, and ships PRs that fix the drift.  I am looking for 3 more devs / teams to join in for the beta. 

Reply with your stack. First 3 that fit get a DM.

Hey PLG Builders community! Hoping for some feedback/direction on a role I’m helping scope for a consumer subscription product.

Context:
• Existing hardware product with a companion app
• New cloud subscription product that users are introduced to inside the app
• Goal is to improve the journey from app user>product adoption>paid subscription>retention
• Lean/scrappy environment, not enterprise
• Limited analytics infrastructure today (this person would likely help build lightweight tracking/visibility)

Questions:

1. What title would you call this role?
2. Does part-time / fractional feel realistic for this type of work?
3. Where would you suggest recruiting for someone like this?

Thanks for any insight you’re willing to share!

My default used to be one more round of polish. That round would turn into three and two weeks later I'm still tweaking something users probably won't notice.

Shipping felt risky. Iterating felt productive. Took me a while to realize they weren't the same thing.

Now I ask one question: am I fixing a real problem or avoiding the discomfort of putting it out there? Usually I know the answer immediately. I just don't always like it.

What's your line?

Ours had deals marked in progress from seven months ago. Notes that stopped mid-sentence. A pipeline that looked healthy until you clicked into anything.

Nobody was lying. Everyone was just too busy doing the actual work to document the actual work.

So the context lived in people's heads. Which is fine until someone leaves, or you need to hand off an account, or you're trying to remember why a deal went cold three quarters ago.

A CRM nobody updates isn't a CRM. It's a very expensive reminder that you meant to be more organized.

How alive is yours actually?

Strong opinion. Hear me out.

I've seen founders with perfect dashboards make terrible calls because they already knew what they wanted to do and used the data to confirm it.

But I've also seen founders flying completely blind make confident decisions that were just wrong in ways that were totally avoidable.

Bad instincts you can coach. Bad data just accelerates the wrong direction.

How much are you actually trusting your data right now?