First Customers (GTM)

How do I actually measure whether a launch worked, beyond the vanity upvotes and traffic spike?

A starting point

Traffic and upvotes tell you almost nothing; the questions that matter are how many people did the one action you care about (signed up, paid, replied) and how many were still active a week later. Before you launch, write down the single metric that would make you call it a success, so you're not moving the goalposts to feel good afterward. A launch that brings 30 people who stick beats one that brings 3000 tourists who bounce, and only retention data tells the difference.

Go deeper

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

3 resources 3 link-checked Read Use

Read

📄 Article

✓ Link checked Free Beginner

Why we picked it This is the piece that named the problem you are asking about: the difference between numbers that make you feel good and numbers you can actually act on. Eric Ries (the Lean Startup guy) wrote it as a guest post, and it is still the clearest short read on why a traffic spike or an upvote count tells you almost nothing. Treat it as a starting point for deciding which one or two numbers your launch should live or die by.

Vanity Metrics vs. Actionable Metrics

From The Blog of Tim Ferriss by Eric Ries 10 minute read

A metric is only useful if a change in it tells you what to do next. Total hits and signup counts almost never pass that test.
Cohort analysis (following a group of users through registration, trial, and purchase over time) shows whether your launch actually changed behaviour, or just briefly inflated the top of the funnel.
Look at per-customer and per-segment numbers, not one big aggregate, because a healthy total can hide the churn and drop-off that decide whether a launch worked.

Open tim.blog →

📖 Book

✓ Link checked Paid Intermediate

Why we picked it If the article gives you the idea, this book gives you the framework: pick the One Metric That Matters for your kind of business and your current stage, and judge your launch by that instead of a dashboard full of noise. It maps the right metric to each business model (SaaS, marketplace, e-commerce, media, and more) so you are not guessing which number is real. Use it as a starting point to choose the single number your launch is really trying to move.

Lean Analytics: Use Data to Build a Better Startup Faster

From O'Reilly Media by Alistair Croll and Benjamin Yoskovitz 440 pages

The One Metric That Matters forces focus: at any given stage you track one number, which stops you from hiding behind a wall of vanity charts.
The right metric depends on your business model and your stage (empathy, stickiness, virality, revenue, scale), so a launch that worked for one type looks different from another.
It is backed by 30-plus case studies and interviews with 100-plus founders and investors, so the guidance is grounded in what real teams measured, not theory.

Open goodreads.com →

Use

🛠️ Tool

✓ Link checked Freemium Beginner

Why we picked it PostHog gives you product analytics and session replay in one place, so you can see both what people did (events, funnels) and watch a real session to understand why they got stuck. It is open source and self-hostable, and the free tier (1 million events and 5,000 session recordings a month) covers most MVPs without a card. That mix of numbers plus watching real sessions is exactly what keeps you from over-instrumenting: you track a few events, then watch replays to fill in the story.

PostHog

From posthog.com by PostHog

One tool covers both quantitative events and qualitative session replay, so you learn the what and the why without stitching together two products.
The free tier is generous enough for a real MVP, and self-hosting is an option if you want full control of your data.
Start by tracking a handful of key actions (signup, activation, the core action), then use session recordings to understand the drop-offs instead of adding more and more events.

Open posthog.com →