Promotions for customers at risk of churning
Create promotions for customers who are most likely to churn
Difficulty: Medium · Modules: Experience Hub, AI Hub
Channels
- website
- mobile application
Industries
- Books
- Cosmetics
- Electronics
- Fashion & Apparel
- FMCG
- Home & Furniture
- Jewelry
- Multi
- Retail
Challenges addressed
Tags
- Promotions
- Segmentation
- Predictions
Summary
This use case focuses on creating precise customer segments using Synerise's real-time segmentation engine that combines behavioral, transactional, and demographic data for targeted marketing. Specifically, "Promotions for customers at risk of churning" enables your team to create promotions for customers who are most likely to churn. This implementation balances ease of setup with meaningful business impact.
Example Scenario
Your marketing team needs to identify high-value customers who have purchased in the last 30 days, have a preference for premium brands, and have engaged with email campaigns in the past week. Using Synerise's segmentation tools, this complex query runs in real time across millions of profiles, producing a dynamic segment that updates automatically as customers meet or exit the criteria.
Business Challenge
Solution
Synerise Segmentation Engine supports both rule-based and AI-assisted segment creation. Marketers define segments using a visual builder with conditions on events, attributes, aggregates, expressions, and prediction scores. Segments evaluate in real time — adding or removing customers as their data changes. Segments integrate with all activation channels including email, push, SMS, Dynamic Content, and automation flows.
This implementation leverages Synerise's Experience Hub for crafting personalized customer journeys, dynamic content, and interactive engagement experiences across all digital touchpoints and AI Hub for training, deploying, and managing machine learning models, predictions, and AI-powered recommendations. The solution delivers results through website interactions including browsing behavior, on-site engagement, and web-based content delivery and mobile app experiences including in-app messaging, push notifications, and native UI personalization.
Expected Impact
Implementing this use case delivers measurable improvements across multiple business dimensions. Organizations typically see results within the first 2-4 weeks of deployment, with compound gains as the system learns from additional data. The medium-level implementation complexity means a balanced investment of time and effort yields strong returns.
Key KPIs
- Segment precision and recall rates
- Campaign performance by segment
- Segment-level conversion rate
- Revenue per segment
- Segment growth or shrinkage trends
Data Inputs
- website — website interactions including browsing behavior, on-site engagement, and web-based content delivery
- mobile application — mobile app experiences including in-app messaging, push notifications, and native UI personalization
- Experience Hub — Experience Hub for crafting personalized customer journeys, dynamic content, and interactive engagement experiences across all digital touchpoints
- AI Hub — AI Hub for training, deploying, and managing machine learning models, predictions, and AI-powered recommendations
Implementation Steps
- 1. Define segment criteria using the visual segment builder with behavioral and attribute conditions
- 2. Test segment size and composition before activation
- 3. Connect segments to marketing channels and automation flows
- 4. Set up segment-level reporting and KPI dashboards
- 5. Monitor segment dynamics and refine criteria based on performance
- 6. Create lookalike segments for audience expansion
Technology Explanation
Synerise's segmentation engine operates on a streaming architecture that evaluates segment membership in real time as events arrive. Complex conditions including event sequences, time windows, and aggregate functions are compiled into an optimized query plan. The engine handles segments with millions of members with sub-second evaluation latency.
Platform Components
- Experience Hub — Experience Hub for crafting personalized customer journeys, dynamic content, and interactive engagement experiences across all digital touchpoints
- AI Hub — AI Hub for training, deploying, and managing machine learning models, predictions, and AI-powered recommendations
Channels
- website — website interactions including browsing behavior, on-site engagement, and web-based content delivery
- mobile application — mobile app experiences including in-app messaging, push notifications, and native UI personalization
Target Industries
- Books
- Cosmetics
- Electronics
- Fashion & Apparel
- FMCG
- Home & Furniture
- Jewelry
- Multi
- Retail
Functionality Used
- Promotions
- Segmentation — creating precise customer segments using Synerise's real-time segmentation engine that combines behavioral, transactional, and demographic data for targeted marketing
- Predictions — using Synerise's AI prediction models to forecast customer behavior such as churn risk, purchase propensity, lifetime value, and next best action
Implementation Complexity
Medium — This use case requires moderate technical knowledge and some configuration effort.
Time to Value
2-4 weeks
Documentation
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