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Customer Win-Back Agent

MarketingCustomer Lifecycle Marketing

Identifies churned or lapsing customers, segments them by churn reason, and runs tailored win-back campaigns with dynamically adjusted offers.

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Process steps
5
Integrations
3
Data inputs

Win-back campaigns are frequently sent as a single generic discount blast to everyone who has churned in the past year, ignoring the fact that a customer who left due to price sensitivity needs a very different message than one who left due to a product gap that has since been fixed

Building segmented win-back campaigns manually requires pulling churn reason data from support tickets, cancellation surveys, and usage history, work that's rarely prioritized until a broader reactivation push is already underway

This agent segments lapsed customers by inferred or stated churn reason, matches each segment to a relevant win-back message and offer (a fixed limitation, a new feature, a loyalty incentive), and monitors reactivation performance to continuously refine what's working per segment

It also identifies the optimal timing window for outreach based on historical win-back conversion patterns

The agent pulls churned and lapsing customer records along with cancellation survey responses, support ticket history, and product usage data leading up to churn, then classifies each customer into a churn-reason segment (price, missing feature, poor onboarding, low engagement, competitor switch) using pattern matching against known signals. It selects a tailored win-back message and offer type per segment from an approved library, times outreach based on historical reactivation-window data, and sends the campaign through the connected email/SMS platform. Reactivation outcomes are tracked per segment and offer type, feeding back into the segment-to-offer matching logic for continuous refinement.

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Segment Churned Customers

  • Pull churned/lapsing customer records
  • Ingest cancellation survey and support ticket data
  • Classify each customer into a churn-reason segment
  • Flag customers with insufficient data for confident classification
Outcome: Lapsed customers are segmented by likely churn reason.
2

Match Segment to Offer

  • Select win-back message and offer type per segment from approved library
  • Reference any product changes relevant to the customer's stated churn reason
  • Personalize messaging with account-specific context
  • Exclude customers on suppression or do-not-contact lists
Outcome: Each segment receives a tailored, relevant win-back message and offer.
3

Time and Launch Outreach

  • Determine optimal outreach window based on historical reactivation patterns
  • Schedule sends per segment via email/SMS platform
  • Sequence follow-up touches for non-responders
  • Track delivery and engagement per send
Outcome: Win-back outreach is delivered at the timing and channel most likely to convert.
4

Track and Refine

  • Monitor reactivation rate by segment and offer type
  • Compare against historical win-back baselines
  • Refine segment-to-offer matching based on outcomes
  • Report win-back campaign ROI
Outcome: Reactivation performance is measured and the model improves with each cycle.
CRM/billing systems (Salesforce, Stripe, Chargebee)
Source churn and cancellation data
Support/ticketing (Zendesk, Intercom)
Pull churn-reason signals
Product analytics (Amplitude, Mixpanel)
Source pre-churn usage data
Email/SMS platforms (Klaviyo, Twilio, Braze)
Execute win-back sends
BI tools
Report reactivation outcomes by segment