Churn analytics helps companies plug the leak in their customer bucket, to borrow a common analogy. Many businesses prioritize attracting new customers over retaining existing ones and don’t notice the toll churn takes until it seriously erodes profits. By some measures, as many as 97 percent of customers who churn do so silently, without leaving feedback or clues as to why. If a company acquires new users at a loss—not uncommon for business or consumer apps that spend heavily on ads—and those users don’t evolve into paying customers, it’s tough for the company to make money. With churn analysis, the team there can quantify the value of customers, the price at which it makes sense to acquire them, and develop ideas to increase retention and customers’ lifetime value. Benefits of a customer churn analytics tool:
- Prevent revenue loss
- Lower customer acquisition costs
- Reduce marketing and sales costs
- Improve quality of customer service
- Increase opportunity for up-sell and cross-sell
The model takes a input like:
| Age | Anualincome | Calldroprate | Education | Homeowner |
|---|---|---|---|---|
| 30 | 30.000k | 0.7 | Bachelor | Yes |
And the output will be the probability of that customer to churn ranging from 0-100%, where 0% represent the customer Don't churn
the test set show an 98% accuracy score!