You own activation, but the data team owns the warehouse and the lifecycle tool belongs to marketing. ConversionCRM gives PMs the whole loop — instrument, score, act — without filing a single ticket.
ConversionCRM is a product adoption platform sized for a PM's real authority: one script tag to instrument, a 6-layer per-user engagement score, automatic lifecycle stages, and behavior-triggered emails that act on adoption gaps automatically. Your activation metric finally has an owner — and it's software.
Getting one new event into the analytics pipeline takes a ticket, a sprint, and a favor. By the time it ships, the question changed.
You know activation is 31%. The lever — timely, behavior-based follow-up — lives in a marketing tool you don't control.
User interviews tell you why; nothing tells you who, right now, is stalled one step before the aha moment.
The widget auto-tracks pages, clicks, time, and SPA routes. Custom events are one track() call — or have the AI agent prompt in Settings generate the snippet for your codebase.
Six explainable layers — recency, frequency, depth, key feature, time spent, buying intent — visible per user. When you say “this cohort is healthy,” you can show exactly why.
Set the feature and event that define activation. Scoring weights it 20 points, and the feature-nudge email pushes every Onboarding user toward it — your hypothesis, executing nightly.
Stage changes trigger emails automatically. No brief to marketing, no journey review meeting. You change the aha event in Settings; the system's behavior changes tonight.
Drop the widget in staging, verify events in the dashboard, ship to production. No pipeline work; data appears in seconds.
Set the key feature + custom event. This is your “users who do X convert” bet, now measurable per user.
A week in, the dashboard shows your real funnel: how many users are stuck in Onboarding vs Active vs Conversion ready. That distribution is your roadmap input.
Feature nudges target exactly the users your hypothesis says are stalled. Compare their progression against the rest — a natural experiment, every night.
Per-user score breakdowns, stage history, and email logs turn “I think onboarding improved” into “score median moved from 24 to 41 after the empty-state change.”
Analytics tools answer questions; ConversionCRM also acts on the answers. You get conversion-focused analytics (per-user scores, stages, events, pages, email history) plus the automated response — behavior-triggered emails — in one loop. For deep funnel/path exploration, keep a dedicated analytics tool alongside; they don't conflict.
You control the highest-leverage input: the key-feature layer (20 of 100 points) via the aha-moment feature and custom event in Settings. The other layers — recency, frequency, depth, time spent, buying intent — use fixed, explainable weights so scores stay comparable over time and between users.
It removes work: one script tag instead of pipeline tickets, auto-tracked events instead of instrumentation sprints, and an AI-agent prompt in Settings that generates integration snippets. The event API is hardened (rate limits, validation, key enforcement) so it's safe to add without review cycles.
Yes — send a custom event per feature (feature_used with properties, or named events) and watch depth and key-feature layers move. The per-user activity feed shows exactly which features each user touched, and you can re-point the aha-moment config as your adoption focus shifts.
Day-1 is where the welcome email (instant, on signup) and feature nudge (for stalled Onboarding users) do their work. We wrote up the mechanics on the day-1 retention solutions page, including which score layers predict early drop-off.
Instrument, score, and act on adoption — no tickets, no handoffs.
Free during beta · no credit card · 3-minute install