Customer Churn Prediction
Quick StartCustom AI
It is important to maintain a customer from a costly perspective rather than acquiring a new customer. If you can prevent churn by knowing in advance which of your existing customers are likely to churn, the effect can be greater than acquiring new customers. You can analyze customer attributes, behavior, engagement, and external factors to help predict the most likely customers to leave and prevent churn. Customer churn prevention can optimize corporate profitability. By predicting customer churn, financial services companies can increase customer satisfaction as well as increase customer lifetime value.
Main function
1. Marketing-Customer churn prediction
- Purchasing process modification (process correction for pages with frequent customer churn)
- Establishment of marketing strategy (analysis of customer characteristics by departure point and establishment of differentiated marketing strategy)
- Establishment of PR strategy (establishing PR strategy through analysis of usage per page)
2. Data Security System
- Thorough data security through security processing
3. Providing various services
- Interlocking between apps, web and programs is possible by providing various programming languages
API Summary
| Data | Data type | Content | Use mode |
|---|---|---|---|
| Input data | CSV | Customer data(gender, age, duration of use, number of accounts, credit card holdings, credit score, salary, etc.) Customer log data(page login/out time, time to stay on page, logout one page, occurrence event, purchase or departure, customer departure) |
API |
| Output data | CSV | Customer churn prediction |
API |
Application procedure
| Payment | Subscription method | Attached file upon application |
|---|---|---|
| Prepaid charge | Online | Customer data required for model creation |
| Application procedure |
|---|
|