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Churn Prediction Identified

Upload Stripe subscription data, identify at-risk accounts and MRR at stake. Free.

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Running stripe subscription churn analysis analysis...

Running stripe subscription churn analysis analysis...

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How it works

Identifies at-risk subscriptions from billing data by analyzing churn rates, MRR at risk, and patterns by plan tier and subscription age. Segments customers by churn risk to prioritize retention efforts.

Use this when you have Stripe subscription data and want to understand churn patterns and identify which subscriptions to save.

If you need revenue decomposition (not churn), use MRR Analysis. If you need general customer retention curves, use Cohort Retention.

Built for: Customer success manager, SaaS founder, retention marketer, VP Growth

Typical data source: Stripe subscriptions export with plan details, trial info, cancel dates, and billing method

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What data do you need?

Stripe subscription billing data

plan_name (categorical) sub_status (categorical) plan_amount (numeric) created_date (date) canceled_date (date)
Pro Monthly active 49 2023-06-01
Enterprise Annual canceled 299 2023-09-15 2024-03-01
Starter past_due 19 2024-01-20

Minimum 50 rows · Best with 200-5000 subscriptions

What's in the report?

Analyzes Stripe subscription data to measure churn rates, identify at-risk subscriptions, calculate MRR at risk, and segment churn patterns by plan tier and subscription age. Provides actionable insights to reduce subscriber attrition.

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Subscription Status Distribution

Current subscription status distribution. High past_due count is an early warning — these often convert to canceled.

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Plan-Level Summary

Active subscriptions and MRR by plan tier. Shows where revenue is concentrated and which tiers have the highest churn.

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Churn Risk Analysis

Subscriptions segmented by churn risk level. Focus retention resources on the high-risk segment with the most MRR at stake.

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MRR Breakdown

MRR at risk from each risk segment. Sometimes saving 10 high-value subscriptions matters more than 100 low-value ones.

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Churn by Subscription Age

Churn rate by subscription age. Most churn happens in the first 90 days. If yours extends beyond that, onboarding may be the problem.

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At-Risk Subscriptions

Subscriptions currently in at-risk statuses with MRR exposure

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Trial Conversion

Trial-to-paid conversion rate. Below 40% means the trial isn't demonstrating enough value. Above 60% is best-in-class.

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AI Insights

Plain-English interpretation — what the numbers mean, what's significant, and what to do next.

Related tools

Need something simpler? Cohort Retention — Need retention curves, not churn prediction

Need more power? Proportional Hazards — Need survival analysis with hazard ratios and time-to-event modeling

Similar: Mrr Analysis, Churn Prediction

Questions?

See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.

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