Daily Customer Churn Risk Detection and Automated Personalized Recall Offer Delivery

This workflow implements daily automatic detection of customer churn risk and intelligently generates personalized recall offers for high-risk customers who have not participated in recall activities. Utilizing AI technology, it provides information push notifications, points, or discounts based on customer preferences, which are automatically sent to customers via email. Additionally, the sending records are saved to Google Sheets to ensure automated management and efficient execution of the entire process, enhancing customer retention and repurchase rates. This is applicable in fields such as e-commerce and subscription services.

Tags

Customer ChurnPersonalized Recall

Workflow Name

Daily Customer Churn Risk Detection and Automated Personalized Recall Offer Delivery

Key Features and Highlights

This workflow automates the daily extraction of customer data to accurately identify high churn risk customers who have not previously participated in recall campaigns. Leveraging customer churn prediction scores and preference categories, it utilizes Google Gemini’s AI capabilities to intelligently generate personalized recall offers (such as information notifications, reward points, or discount coupons). These offers are then automatically sent to customers via email. Finally, all sending records are synchronized and stored in Google Sheets, enabling fully automated management and efficient customer recall processes.

Core Problems Addressed

  • Automatically identify customers at high risk of churn, eliminating the need for manual screening
  • Precisely match customer preferences and intelligently generate personalized recall offers to improve recall success rates
  • Automate bulk sending of recall emails, saving labor costs
  • Log each operation in real time to facilitate subsequent data analysis and process optimization
  • Automatically record status when no eligible customers are found, ensuring process completeness and transparency

Application Scenarios

  • E-commerce platforms, membership services, subscription businesses, and other enterprises requiring proactive customer retention
  • Marketing teams automating customer recall campaigns to boost engagement and repurchase rates
  • Data-driven Customer Relationship Management (CRM) systems integrating AI for precision marketing

Main Process Steps

  1. Scheduled Trigger: Automatically start the workflow daily
  2. Data Extraction: Retrieve the latest customer data from Google Sheets
  3. Customer Filtering: Select customers with a churn prediction score greater than 0.7 who have not participated in recall campaigns
  4. Conditional Branching: Determine if eligible customers exist
    • No eligible customers: Log “NOT_FOUND” status in the system log
    • Eligible customers found: Proceed to loop processing
  5. Loop Through Each Customer:
    • Invoke Google Gemini AI to generate personalized recall offers based on churn score and customer preferences (information push, reward points, or discounts)
    • Record the generated offer details in the system log
    • Automatically send recall emails to customers via Gmail
  6. Logging: Regardless of offer delivery, write the corresponding status and timestamp into the Google Sheets system log

Involved Systems and Services

  • Google Sheets (for customer data retrieval and system operation log recording)
  • Google Gemini (AI model invocation for personalized recall offer generation)
  • Gmail (automated sending of personalized recall emails)
  • n8n Automation Platform (for scheduling triggers, data processing, and workflow control)

Target Users and Value Proposition

  • Marketing automation managers and customer relationship management teams
  • Enterprises aiming to reduce customer churn and increase repurchase rates through intelligent methods
  • Marketing professionals seeking AI-generated personalized marketing content to enhance customer experience and campaign effectiveness
  • Technical teams pursuing efficient automated operations with minimal manual intervention

By integrating AI-driven analysis with automated execution, this workflow achieves precise, efficient, and traceable management of customer recall campaigns, empowering enterprises to improve customer retention and long-term value.

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