For customers who belong to specific high value segments and make repeated purchases in your shop, it’s essential to recognize when their engagement starts to decline, which is often an early sign of churn. This workflow is designed to detect when loyal customers begin to show signs of reduced activity and take timely action to re-engage them.

By analyzing historical behavior, such as purchase frequency, time since the last purchase, changes in browsing patterns, and response to previous marketing efforts, we calculate a churn risk score for each customer. This score helps predict the likelihood of them leaving and guides which retention strategies should be applied.

Possible actions to prevent churn include:

• Personalized discounts based on the customer’s past purchases (e.g., offering 10% off their favorite product category)

• On-site personalization by highlighting new arrivals or offers tailored to their preferences (e.g., displaying vegan skincare products for a user who frequently buys cruelty-free items)

• Targeted email campaigns that remind customers of loyalty points, new releases, or exclusive offers (e.g., “It’s been a while since your last order—enjoy early access to our newest collection!”)

This workflows is also interesting for B2B- and SaaS-companies.