SAMPLE REPORT — DEMO DATA. This audit was produced on a simulated business (220 subscribers, 6 months of billing history, 90 days of payment-failure records) so you can judge the format, rigor, and honesty before paying. Every number below was computed by the same analysis tooling used on real audits. No real customer's data appears in this document.
Revenue Leak Audit — Demo Subscription Co.
Business analyzed: $4,263 MRR · 179 active subscribers (of 220 all-time) · ARPU $23.82 · three plans ($9.99 / $24.99 / $49.99)
Data analyzed: 6 months of subscriber/charge history · 90 days of failed-payment cases (60) · 80-response willingness-to-pay survey (70 usable)
Executive summary
Your three largest leaks, ranked by estimated monthly impact:
- $869/month of revenue sits in flagged at-risk accounts — inactive 20–34 days or carrying failed payments — with no win-back motion running (Finding 1).
- Failed payments recover at 60%, but the leftovers are systematic: ~$92/month lost outright, $399 stuck mid-retry, and the retry ladder does almost all its work on the first attempt (Findings 2–4).
- Ten payment cards expire within 30 days — ~$238/month of renewals about to fail for a completely preventable reason (Finding 2).
Do this week: send the pre-dunning card-update email to the 10 expiring-card accounts (Finding 2 — smallest effort, most preventable loss).
Findings
1. $868.59/mo flagged at-risk with no win-back motion · est. $215–$430/mo saveable · effort M
- Evidence (your data): the risk scorer flags accounts worth $868.59/mo combined. Top of the list: your $99/mo account carries 2 failed payments (risk 35), and a cluster of $49.99 accounts have gone quiet for 22–34 days (risk 45–65; two rated critical — one a first-month subscriber, the highest-churn window).
- Estimate & assumption: assumes a win-back sequence saves 25–50% of the flagged cluster — the industry-reported range for retention flows; your audience may differ.
- Fix: three-step win-back sequence at 21 days of inactivity; personal (not automated) outreach for any flagged account over $50/mo.
2. 10 cards expire within 30 days · est. up to $238/mo exposure · effort S
- Evidence: 10 active payment methods expire within 30 days — at $23.82 ARPU, ~$238/mo of renewals headed for "card declined" before dunning even starts.
- Estimate & assumption: exposure = 10 × ARPU; actual loss depends on how many auto-update via card networks (often half or more do not, per industry reporting).
- Fix: pre-dunning email at expiry-minus-21-days with a hosted card-update link. Highest-certainty fix in this report: the failure hasn't happened yet.
3. Retry ladder does 58% of its work on attempt 1, then falls off a cliff · est. $30–$80/mo · effort S
- Evidence: of $652.77 recovered in 90 days, retry #1 recovered $377.90; retry #2 only $14.99 and retry #3 $39.98. The card-update path independently recovered $219.90 (34% of all recovered dollars).
- Estimate & assumption: assumes payday-snapped retries 2–3 lift toward industry retry-curve shapes; small base, so the honest estimate is modest.
- Fix: snap retries 2 and 3 to the 1st/15th; insert the card-update email between retry 1 and 2 (your own channel data says card-update beats late retries).
4. $398.79 currently stuck mid-retry across 22 open cases · monitoring finding · effort S
- Evidence: 22 failure cases open right now ($398.79); 30-day recovery rate on closed cases is 60%; average time-to-recover 4.9 days.
- Estimate & assumption: at the observed 60% rate, ~$239 resolves on its own; the finding is the residual ~$160 that history says will be lost without Findings 2–3.
- Fix: covered by Findings 2–3; track this number weekly — it's your leak dashboard in one figure.
5. First-90-day retention cliff: cohorts lose ~22–28% by month 3 · est. $180–$360/mo at current intake · effort L
- Evidence: the March cohort (47 subscribers) retained 93.6% → 89.4% → 72.3% over three months; February shows the same shape. April's cohort lost 8.7% within month zero — those subscribers never reached a second charge.
- Estimate & assumption: assumes onboarding/activation work cuts early-cohort decay by a quarter, scaled by ARPU at ~40 signups/month.
- Fix: a product/onboarding project, not a billing tweak — first-week activation checklist + cancel-flow question capturing why month-0/1 leavers go. Largest long-term lever here, and the most work.
6. Your $99 account is your most valuable at-risk dollar · est. $99/mo · effort S
- Evidence: the single $99/mo account carries 2 failed payments — the strongest churn predictor in the scoring model.
- Estimate & assumption: full plan value; one account, so binary, not statistical.
- Fix: don't automate this one. A personal email today is disproportionately worth it on whale accounts.
7. Plan mix is bottom-heavy: 55% of subscribers on the $9.99 tier · est. $150–$300/mo · effort M
- Evidence: ~120 of 220 subscribers sit on Starter ($9.99), producing only ~28% of MRR; ARPU $23.82 is dragged well below the mid-tier price.
- Estimate & assumption: assumes packaging/upgrade prompts move 8–15% of Starter accounts to Pro over a quarter — verify against your feature usage.
- Fix: one upgrade trigger tied to a usage threshold, surfaced in-product, no discounting.
8. Scale tier is priced at the ceiling of measured willingness-to-pay — raise with care · est. +$93/mo if pursued · effort M
- Evidence: the 70-usable-response pricing survey puts the acceptable range at $31.47–$51.12 (optimal point $34.32); the Scale tier ($49.99) already sits at the top edge. The simulator models $49.99 → $59.00 at 0.5 elasticity: 3 of 30 Scale subscribers churn, net +$93.30/mo (+2.1% total MRR) — but $59 is outside the measured range, so the elasticity assumption is doing heavy lifting.
- Estimate & assumption: simulator output at elasticity 0.5; the grandfathered variant gains only as new signups arrive — slowly.
- Fix: honest verdict — not a clean "raise prices" recommendation. Safer sequence: annual option first, re-survey at the higher anchor, then test $59 for new signups only (grandfather existing). Flagged because the $93/mo is real in the model but the survey says you'd price past the measured range.
9. Dunning-message A/B test is a tie so far — keep it running, don't act on it · monitoring finding · effort S
- Evidence: variant A recovered 65.2% (15 of 23 closed), variant B 66.7% (10 of 15). At this sample size the difference is noise.
- Estimate & assumption: none — the honest finding is that there is no finding yet.
- Fix: run to ~100 closed cases before declaring a winner. Included so you know we report thin data as thin data.
10. Average customer lifetime is ~3.1 months — annual plans are your compounding fix · structural · effort M
- Evidence: lifetime value per customer is $74.74 against $23.82 ARPU — roughly 3.1 months of average paying life. Findings 1–5 attack this number from different angles.
- Estimate & assumption: no standalone estimate — this is the summary statistic the other findings move.
- Fix: once Findings 1–3 are live, introduce an annual option at 10× monthly.
Method appendix
- Data: 6 months of subscriber and charge history (220 subscribers, ~550 charges); 90 days of payment-failure cases (60); 80-response Van Westendorp pricing survey (70 usable, 10 excluded for inconsistent answers).
- Lenses: failed-payment recovery (retry/decline/channel attribution), retention (cohort decay, risk scoring), pricing (willingness-to-pay intersections + elasticity simulation).
- Tooling: purpose-built recovery, retention, and pricing analysis software operated by Code Name Amuri; all figures computed, none estimated by eye.
- Out of scope: ad spend, SEO, financial modeling, anything requiring write access.
Disclaimer: dollar figures are estimates derived from the analyzed data, each with its assumption stated inline. Recovered revenue depends on which fixes ship. This report is operational analysis of the business's own billing data; nothing in it is financial, investment, legal, accounting, or tax advice.