GPT-4o
💼 Business
Intermediate
Customer Churn Signal Agent
Build an agent that monitors [USAGE_DATA_SOURCE] for early churn signals in [CUSTOMER_SEGMENT] and triggers automated retention actions.
The Prompt
# Customer Churn Signal Agent You are a customer success automation architect. Design an agent that detects churn risk early for [CUSTOMER_SEGMENT] and acts before accounts are lost. ## Signal Sources Monitor via [USAGE_DATA_SOURCE]: - Login frequency vs. baseline for [CUSTOMER_SEGMENT] - Feature adoption rate for [KEY_FEATURES] - Support ticket volume over [TIME_WINDOW] - Payment and renewal status from [BILLING_SYSTEM] ## Churn Scoring Compute a risk score (0–100) using weights: - Low login frequency: +[WEIGHT_1] points - Declining feature usage: +[WEIGHT_2] points - Open tickets > [TICKET_THRESHOLD]: +[WEIGHT_3] points - Renewal < [RENEWAL_DAYS] days away: +[WEIGHT_4] points ## Interventions - **Score > [HIGH_RISK]**: assign a CSM task in [CRM] and send outreach template to [CSM_CHANNEL] - **Score [MID_RISK–HIGH_RISK]**: enroll in [RETENTION_SEQUENCE] in [EMAIL_TOOL] - **Score < [MID_RISK]**: monitor passively ## Reporting Generate a weekly at-risk accounts list for [CS_TEAM_LEAD] showing score, trend, and recommended action.
📝 Fill in the blanks
Replace these placeholders with your own content:
[CUSTOMER_SEGMENT]
[USAGE_DATA_SOURCE]
[KEY_FEATURES]
[TIME_WINDOW]
[BILLING_SYSTEM]
[WEIGHT_1]
[WEIGHT_2]
[TICKET_THRESHOLD]
[WEIGHT_3]
[RENEWAL_DAYS]
[WEIGHT_4]
[HIGH_RISK]
[CRM]
[CSM_CHANNEL]
[MID_RISK–HIGH_RISK]
[RETENTION_SEQUENCE]
[EMAIL_TOOL]
[MID_RISK]
[CS_TEAM_LEAD]
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