Daily Prompt Pack: Churn Rescue – Win Back At-Risk Customers Before They Leave
Churn rarely surprises you if you watch the right signals. This pack gives you three prompts to find the accounts about to leave, figure out why, and build a rescue plan that actually lands.
[Claude]
[Claude] You are a retention analyst for a B2B SaaS with 400 customers. Given my churn-risk data (login frequency, support tickets, feature usage, payment history) pasted below, rank the top 10 accounts most likely to cancel in the next 30 days. For each, list the 3 strongest warning signals and a one-line reason. Output as a table sorted by risk score, then a short paragraph on the single biggest pattern you see across all 10.
[ChatGPT]
[ChatGPT] I run a subscription box business and my 90-day cancellation rate just hit 8%. Given my cancellation reasons from the last 3 months (pasted below), group them into 5 root causes and rank them by frequency and revenue impact. For the top cause, write a 200-word win-back email I can send to churned customers, with a subject line under 50 characters and one concrete offer.
[Cursor]
[Cursor] In this repo, find the code that flags inactive users (no login in 30 days). Refactor it so it also scores accounts by a churn-risk heuristic: login recency, support ticket volume, and feature adoption. Add a new function that returns the top 20 at-risk accounts with their risk score and top signal. Keep the existing API shape, add tests, and print a sample output.
Full archive at aicofounderstack.com/tag/prompt-pack.
