Customers & Research

How do I use the customers I already have to sharpen my ideal customer profile instead of guessing?

A starting point

Once you have even 15 or 20 paying customers, stop guessing and let the data draw the profile: sort them by who onboarded fastest, uses it most, churns least, and refers others. Look for the shared traits of your top decile (industry, role, trigger, size) and write your ICP from that cluster, not from your original pitch deck. Then interview a few of them to understand why they specifically stuck. This turns ICP from a hopeful hypothesis into an evidence-based description, and it should keep updating as your best customers reveal the pattern.

Go deeper

Hand-picked from around the web, each with a note on why it earns your time.

3 resources 3 link-checked Listen Read Use

Listen

🎧 Podcast

✓ Link checked Free Intermediate

Why we picked it If you would rather hear the thinking than read it, this is Rahul Vohra on Lenny's Podcast talking through the same product-market-fit engine in his own voice. He is honest about deliberately ignoring most feedback and building for the narrow set of users who most love the product, which is exactly the discipline of sharpening your profile from real users. It is a repeatable system you can run yourself, explained conversationally with the messy parts left in.

Superhuman's secret to success: ignoring most customer feedback, manually onboarding every user, and positioning around one attribute | Rahul Vohra

On Lenny's Podcast by Lenny Rachitsky

Not all feedback is equal: he weights the people who already love the product far above everyone else when deciding what to build.
Manually onboarding every new user was how the team learned, in person, who the product was actually for.
The survey-and-segment loop is a system you run repeatedly, not a one-time exercise, so your profile keeps getting sharper.

Open lennysnewsletter.com →

Read

📄 Article

✓ Link checked Free Intermediate

Why we picked it Turns the fuzzy phrase 'product-market fit' into a number you can move. Vohra's survey (the '40% would be very disappointed' benchmark) and 4-step engine took Superhuman from 22% to 58% PMF. The most actionable PMF piece on the internet.

How Superhuman Built an Engine to Find Product/Market Fit

From First Round Review by Rahul Vohra (CEO, Superhuman) ~25 min read

Ask users: 'How would you feel if you could no longer use this?' Target >40% 'very disappointed'.
Segment to your highest-expectation users and build for them.
Split your roadmap: double down on what they love, remove what blocks the fence-sitters.

Open review.firstround.com →

Use

🛠️ Tool

✓ Link checked Freemium Intermediate

Why we picked it Once you have a hunch about who your best customers are, you need to check it against behaviour, and Mixpanel is a real analytics tool with a free tier that early startups can actually use. This guide shows how to group users into cohorts by what they did and then watch which cohorts stick around, so the segment that retains best surfaces on its own. That retaining cluster is usually where your ideal customer profile is hiding.

Cohort analysis: how to read the chart, choose a platform, and turn retention into growth

From Mixpanel by Mixpanel

A cohort is just a group of users who share a trait or a behaviour, and cohort analysis tracks how each group behaves over time.
Retention curves by cohort show which type of customer actually sticks, which is stronger evidence than any single vanity metric.
Mixpanel's free tier makes this reachable for a small team building outside the big startup hubs, no data warehouse required.

Open mixpanel.com →