Related Ideas
eyko Ideas
Win-back campaigns aimed at the entire lapsed list spend most of their budget on customers who will not return. A Win-Back Scoring Playbook ranks lapsed customers by recovery likelihood using churn reason, time-since-lapse, and re-engagement signals, focusing resources where they actually convert.
The Challenge
The standard win-back campaign blasts the entire lapsed list with the same offer. Customers who lapsed because of a fixable issue receive the same discount as customers who lapsed because they no longer need the product. The campaign converts a fraction and looks expensive in aggregate.
The CSM left notes when the customer churned. The exit survey captured a reason. The support history shows what went wrong. None of this informs the win-back targeting, so the campaign offer is calibrated to a generic "lapsed customer" rather than the actual reason a specific customer left.
Win-back probability does not decay linearly. Some customers are most recoverable in the first 60 days. Others are recoverable when an external trigger (a competitor failure, a market shift) creates a window. A flat time-decay assumption misses both patterns and the calendar-based win-back wave catches neither.
How eyko Solves It
A Win-Back Scoring Playbook reads churn reason data, time-since-lapse curves, re-engagement signals (return visits, content engagement, social mentions), and historical win-back outcomes to score each lapsed customer on recovery likelihood. It segments the lapsed pool by recoverability tier and dominant churn reason, recommends a different offer per segment, and surfaces the external triggers that move specific cohorts back into a high-recoverability window.
The Playbook scored 1,840 lapsed customers across 4 recoverability tiers. 184 sit in the high-recoverability tier, with projected win-back response rates above 18%. 380 sit in the medium tier with response 6 to 12%. The remaining 1,276 sit in low or unrecoverable tiers with response below 2% historically. The current blanket campaign treats all 1,840 the same.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Win-Back Scoring ranks every lapsed customer on recovery likelihood using churn reason, time-since-lapse, and re-engagement signals. The Playbook segments the lapsed pool by recoverability tier and dominant churn reason, surfaces the high-recoverability cohort worth a targeted win-back motion, and retires the low-recoverability tail from active outreach so marketing budget concentrates on the customers who actually convert rather than spraying the full lapsed list.
Related Ideas
FAQ
Everything you need to know about Win-Back Recoverability Map.
Win-Back Scoring is an AI-driven ranking of every lapsed customer on recovery likelihood. The Playbook reads churn reason data, time-since-lapse, and re-engagement signals to segment the lapsed pool by recoverability tier and dominant churn reason, surfaces the high-recoverability cohort worth a targeted win-back motion, and retires the low-recoverability tail from active outreach so marketing budget concentrates on the customers who actually convert.
The Playbook reads from your CRM (churn reason notes, exit survey responses, lapse dates), product analytics (return visits or re-engagement events on lapsed customers), marketing automation (post-lapse email opens and content engagement), and historical win-back campaign data (offers tested, response by cohort). At least 18 months of paired win-back-to-response data anchors the recoverability model in real outcomes.
A lapsed-customer list treats every churned customer as a single cohort. Win-Back Scoring segments by churn reason and recoverability tier so each customer receives an offer calibrated to why they left and when they are most likely to come back. The two are complementary, but tiered targeting is what shifts the win-back economics from broad-spray-low-conversion to focused-spend-real-recovery.
Yes. For each high-recoverability customer the Playbook recommends an offer matched to the dominant churn reason: pricing-focused offers on price-driven lapses, feature re-introduction on onboarding-stall lapses, executive sponsorship on relationship-breakdown lapses worth recovering at all. Each match projects expected response rate so marketing leadership can prioritize the offer mix that produces the best blended recovery economics.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
