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Win back cancelling subscribers with an AI-written retention offer and email sequence triggered by Stripe

A founder describes a tool where a Stripe cancellation triggers an AI strategist that builds a personalised retention offer and a multi-step email sequence, and reports multi-step sequences doubled recovery.

ClaimedConversionSmall SaaSConnected toolsScheduled automation

Evidence: The author reports this. We have not checked it beyond reading the source.

The business problem

A subscription business loses customers who cancel, and a single generic win-back email recovers few of them.

What was tried

A Stripe subscription-deleted webhook starts the process. The tool builds a subscriber profile from plan, tenure, payment history and support tickets, and an LLM picks a tone, offer type, discount level and follow-up timing. A multi-step email sequence is then sent through Resend, adapted to whether earlier emails were opened, clicked or ignored. The stack is FastAPI, MongoDB, Redis and Docker on one server, with retry queues and idempotency keys to make webhooks reliable.

What was reported (mixed)

The author reports a first-email open rate of about 15 to 20%, an AI strategist that beat their earlier rule-based system, and multi-step sequences that 'doubled recovery rates' versus a single email. No customer, saved-subscription or revenue figures are given.

Limitations

The post is promotional for the author's own product and gives no baseline, sample size or method for the doubling claim, nor which model or prompts are used. It does not discuss failure modes, customer complaints or whether discounts hurt long-term pricing. Pricing is only described as a monthly fee plus a share of recovered revenue, and the page does not show a year.

What you need

A Stripe account, a transactional email service, an LLM API, and hosting for the webhook service. Costs are not stated, apart from LLM cost of under a penny per strategy.

Sources

Source published: unknown. Last reviewed here: October 11, 2026. Spot a mistake? Tell us.

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