Automated AI-Powered Churn Prevention with Personalized Win-Back Offers
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Proactively safeguard your customer base with this n8n workflow, designed to automatically identify high-risk churn customers daily. Leveraging AI, it generates personalized win-back offers tailored to individual churn scores and preferences, helping you retain valuable customers effortlessly.
About This Workflow
This n8n workflow automates daily customer retention by identifying high-risk churn customers. It pulls predicted_churn_score and preferred_categories from Google Sheets, then filters those above a 0.7 churn threshold. For each eligible customer, an integrated AI (Google Gemini LLM) dynamically generates a personalized win-back offer. Offers are calibrated by churn score, from informational messages to significant discounts. The structured JSON output is ready for communication, transforming reactive churn management into a proactive, AI-driven retention strategy.
Key Features
- Automated Daily Churn Detection: Schedule daily scans of your customer data to catch high-risk customers as soon as they emerge.
- AI-Powered Offer Personalization: Dynamically generate highly relevant win-back offers (informational, bonus points, discounts) using Google Gemini LLM, tailored to each customer's churn risk and preferences.
- Seamless Google Sheets Integration: Easily pull customer data, including churn scores and preferred categories, from your existing Google Sheets.
- Targeted Customer Segmentation: Automatically filter and segment customers based on their predicted churn risk, ensuring resources are focused where they matter most.
- Structured Offer Output: Receive ready-to-use offer details in a clean JSON format, simplifying integration with email, CRM, or other communication platforms.
How To Use
- Schedule Trigger Node (
Scheduled Start: Daily Churn Check): Configure this node to run daily or at your desired frequency. - Google Sheets Node (
Fetch Customer Data from Sheet):- Connect your Google Sheets account credential.
- Specify the
Document IDof your customer data spreadsheet and theSheet Name(e.g., "Customer Data"). Ensure your sheet containspredicted_churn_score,preferred_categories, andcustomer_idcolumns.
- Filter Node (
Filter High Churn Risk & No Campaign Customers): Review and adjust thepredicted_churn_scorethreshold (currently set to> 0.7) to match your definition of "high churn risk." You can also add more conditions here for "No Campaign Customers" if your data supports it. - LLM Chain Node (
Generate Win-Back Offer):- Ensure the
(LLM Model for Offer Generation)node is connected to a Google Gemini (or equivalent) credential. - Review the prompt text within the
Generate Win-Back Offernode to understand the offer generation rules. You can customize these rules to better fit your business logic and offer types. - Verify the
Output Structurein the prompt matches your desired format for subsequent actions.
- Ensure the
- Next Steps (Not in JSON, but implied): After parsing the LLM output, add nodes to send these personalized offers. For example, use an Email node (like Gmail, SendGrid) to send the
offer_detailsto thecustomer_idvia email, or update your CRM system.
Apps Used
Workflow JSON
{
"id": "e1c038c7-1f8f-450b-a9e5-8f393cdc1805",
"name": "Automated AI-Powered Churn Prevention with Personalized Win-Back Offers",
"nodes": 7,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: e1c038c7-1f8f...
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