Product Analytics

RevenueCat Analytics: Tracking Trial Conversion, Churn, and LTV Without Building Your Own Pipeline

6 min read | Analytics · Subscriptions

MRR is the number founders watch and the number that lies to you longest — it can hold steady for months while trial conversion quietly erodes underneath it. By the time MRR moves, the problem is usually eight weeks old. The metrics that actually predict whether a subscription business works are upstream: trial-to-paid conversion, early churn, and LTV by cohort.

1. The Metrics That Actually Predict Outcomes

Trial-to-paid conversion rate

The single earliest signal that your paywall, onboarding, and value proposition are aligned — or aren’t. Moves weeks before revenue does.

Day-1 and day-7 churn

Early churn is a different problem than late churn — usually onboarding or expectation-setting, not product depth. Track them separately from your steady-state monthly churn rate.

LTV by acquisition cohort

Blended LTV hides the fact that one channel is subsidizing another. Segment by acquisition source before you trust a payback-period calculation.

Revenue by product and offering

Which price point, which trial length, which packaging is actually converting — not just in aggregate, but broken out enough to inform the next pricing experiment.

2. What RevenueCat’s Dashboard Gives You Out of the Box

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Charts overview

Revenue, active subscriptions, trials, and churn trended over time, split by store and by product — enough for a daily read without touching a BI tool.

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Individual subscriber history

Full transaction and entitlement timeline per user — the first place to look when a support ticket says “I paid but don’t have access.”

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Cohort views

Retention curves grouped by signup period, useful for spotting whether a recent onboarding or pricing change moved retention in either direction.

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Event integrations

Subscription lifecycle events can be piped to analytics and marketing tools you already run, so billing events join the rest of your product data.

3. Where We Still Build a Custom Pipeline

RevenueCat dashboard is enough for

Daily revenue & churn readYes

Single-subscriber debuggingYes

Basic cohort retentionYes

Needs a custom pipeline

Blended CAC/LTV across paid channelsCustom

Billing joined to in-app usage eventsCustom

Exec dashboards blending multiple sourcesCustom

The pattern we default to: RevenueCat’s dashboard for the day-to-day operational read, webhooks feeding a warehouse (or an analytics tool like Amplitude or Mixpanel) for anything that needs to sit next to product-usage data or ad-spend data. Most teams don’t need the second half until they’re spending real money on acquisition — build it when that’s true, not before.

Gotcha

RevenueCat webhooks can arrive out of order or, rarely, be delivered more than once. Design your event handler to be idempotent — key on the event ID, not just “process whatever arrives” — or a replayed renewal event can double-count revenue in your own pipeline.

The engineering work of getting entitlements and webhooks wired up in the first place is covered in our RevenueCat + Flutter integration guide — this piece assumes that’s already done and picks up at “now what do we do with the data.”

Not sure which subscription metrics actually matter for your product?

Send us what you’re tracking today and we’ll tell you what’s missing before it becomes an expensive blind spot.

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