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Retention campaigns aimed at a generic at-risk list overspend on the wrong customers and miss the right ones. A Retention Campaign Targeting Playbook reads churn risk signals, save-history outcomes, and message fit to match the right campaign to the right customer at the right moment.
The Challenge
The standard save campaign offers a discount, a feature trial, or a CSM check-in. The actual reason this customer is at risk may be none of those. A campaign tuned to one churn driver fired at customers driven by a different driver lands flat.
The retention motion is uniform across the at-risk cohort. The $1M strategic account at risk gets the same automated save sequence as the $5K SMB account. Both receive a calibrated experience that fits neither, and the high-value account often slips because it never got the human attention it warranted.
Retention reporting tracks how many save campaigns ran and how many were marked complete. The metric that matters, incremental retention, rarely gets isolated. Without a control comparison the team cannot tell whether the saves are working or whether retained customers would have stayed anyway.
How eyko Solves It
A Retention Campaign Targeting Playbook reads churn risk signals, prior save outcomes, account value, and message fit (offer type, channel, owner) to recommend the specific retention campaign most likely to succeed on each at-risk customer. It segments the at-risk cohort by driver and value, routes high-value accounts to human-led motions, and matches automated campaigns to the cohorts where they have historically converted.
The Playbook scored 1,840 at-risk customers across 6 save campaign types and matched each to its best-fit campaign. 184 strategic accounts ($4.6M ARR) routed to executive-sponsored save motions. 480 mid-market accounts routed to CSM-led campaigns matched to the dominant churn driver. 1,176 SMB accounts split across 3 automated campaigns by driver. Replacing the generic save campaign with targeted matching projects a 28% lift in incremental retention.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Retention Campaign Targeting matches each at-risk customer to the specific retention campaign most likely to succeed. The Playbook scores every at-risk account on dominant churn driver, account value, save history, and message fit, then routes high-value accounts to human-led motions and matches automated campaigns to the cohorts where they historically convert. Marketing and customer success see who to target with which save rather than running one generic campaign across the at-risk base.
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FAQ
Everything you need to know about Retention Campaign Match.
Retention Campaign Targeting is an AI-driven match of each at-risk customer to the specific save campaign most likely to succeed. The Playbook scores every at-risk account on dominant churn driver, account value, save history, and message fit, then routes high-value accounts to human-led motions and matches automated campaigns to the cohorts where they have historically converted so marketing and customer success see who to target with which save.
The Playbook reads from your customer success platform (health scores, churn risk signals, CSM activity), CRM (account value, segment, lifecycle stage, prior save outcomes), marketing automation (campaign history and response patterns), and product analytics (usage trajectory as a driver signal). At least 18 months of paired save-to-retention data lets the model anchor recommendations in actual save outcomes.
Churn prediction identifies who is at risk. Retention Campaign Targeting takes the at-risk list and recommends which save campaign to run on each customer based on their dominant driver and value. The two are complementary: churn prediction surfaces the cohort, targeting decides the motion. Without targeting, the at-risk cohort gets a generic save that converts well below where matched motions could put it.
Yes. The Playbook recommends a control cohort structure so the targeted save campaigns can be measured against a generic-save baseline. Incremental retention is reported per campaign type, per account value tier, and per dominant driver so leadership sees which targeting decisions are producing lift and which need recalibration. The measurement runs continuously rather than as a one-time test.
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