Devesh Tiwari
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Growth

From Launch to Growth: What to Measure First

Devesh Tiwari11 min read

The metrics that matter before vanity dashboards — activation, retention, and the signals that tell you whether the product is working.

From Launch to Growth: What to Measure First

01

What should you measure in the first 30 days?

Activation rate, time-to-first-value, week-one retention, and support tickets per new user.

Instrument events on day one of launch. I add lightweight analytics and error tracking so founders see truth, not hope. Define activation as a specific action — not 'signed up.' For a project tool, it might be 'created first project and invited a teammate.' For a marketplace, 'completed first transaction.'

02

Which metrics mislead founders?

Total signups, page views, and feature counts without correlation to retention or revenue.

Growth work starts when you know which cohorts stay. Double down on channels and flows that improve those cohorts. A spike from Product Hunt means nothing if day-7 retention is 2%. Celebrate learning, not spikes.

03

How do you set up a simple metrics stack?

Product analytics for funnels, error tracking for stability, and one dashboard with no more than five numbers you review weekly.

Tools like PostHog, Mixpanel, or Amplitude plus Sentry cover most early-stage needs. Wire key events in the codebase during build — retrofitting analytics after launch always misses the first cohort. Keep the weekly dashboard brutal: activation %, D7 retention, paying accounts or pilot commitments, support volume, and p95 API latency.

04

When should you experiment vs fix the core loop?

Fix the loop if fewer than 20–30% of signups reach activation; experiment on messaging and onboarding once the product reliably delivers value.

Founders A/B test landing page colors while users die in onboarding step three. Sequence matters: stability, activation, retention, then acquisition experiments. Growth hacks on a broken product accelerate failure.

05

How do you connect metrics to product decisions?

Run a weekly review: one metric that improved, one that worsened, one ship that addresses the worst bottleneck.

Metrics without decisions are wallpaper. I help teams tie roadmap items to measurable hypotheses: 'Removing the credit card wall before trial should raise activation by X.' Ship, measure, keep or revert. That rhythm beats quarterly planning when you are still finding fit.

Frequently asked questions

When is it time to scale paid acquisition?
When week-one retention is stable across organic cohorts and support load is predictable — usually after 50–100 serious users. Paid channels amplify what already works; they rarely fix product-market fit.
What is a good activation rate?
It varies by product, but if fewer than one in four signups reaches your defined activation event, fix onboarding before scaling. B2B tools with sales-assisted onboarding can accept lower self-serve activation if demos convert.
Should I track revenue or retention first?
Retention first for subscription products — dead revenue churns. For one-time purchase or services, track conversion to paid and repeat purchase. Always know whether users who pay also stay.
How do I measure AI feature success?
Track query success rate (user did not immediately rephrase or abandon), citation clicks, escalation to human support, and qualitative feedback thumbs. Model accuracy alone does not predict product value.