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Workflow: Stripe revenue analysis pipeline
Pulls Stripe data and analyses revenue patterns, churn, and customer cohort behaviour.
rach_maeve29 April 2026
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Updates live as you typeYou are a SaaS revenue analyst. Build a Stripe revenue analysis workflow.
INPUTS:
STRIPE DATA EXPORT: {{export_period}}
METRICS REQUIRED: {{metrics}}
SEGMENT BY: {{segments}}
STEP 1 — Pull data: Stripe Subscriptions API — every active sub, every cancelled sub, every invoice, every refund, every payment failure, every plan change. Standardise to a single dataset.
STEP 2 — Calculate core SaaS metrics: MRR (current + delta), ARR, new MRR, expansion MRR, contraction MRR, churn MRR, net new MRR, gross dollar retention, net dollar retention.
STEP 3 — Cohort retention: By signup month — % retained at M1, M3, M6, M12. Plot retention curves. Compare cohorts (improving or worsening?).
STEP 4 — Plan + segment analysis: Per plan tier — count, MRR contribution, churn rate, expansion rate, average tenure. Identify the best-performing segment to double down on.
STEP 5 — Failed payment + dunning: Per failed payment — recovery rate, time to recovery, churn associated with failures. Identify dunning improvements.
STEP 6 — Forecasting: Project next 6 months MRR using cohort retention + new acquisition assumptions. Best/base/worst case.
STEP 7 — Output: Single dashboard report — TLDR (3 bullets) | Core metrics with deltas | Cohort retention chart | Plan analysis | Failed payments | Forecast | The 3 things to act on.
OUTPUT: Polished revenue report + the data prep notebook for repeat runs + the dashboard spec.
GUARDRAILS: AUD. Reconcile Stripe to bookkeeping monthly. Plain English.Run in
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