Diy Platform App Store Index Renewal
Renewal Propensity is a type of classification problem used to predict whether an existing user or customer will renew his/her subscription or discontinue the subscription, based on the historical data.
How to Build my first Renewal Propensity app?
To get you started immediately, we have provided a sample training data of some subscription based business, which contains 14 different attributes or features and target label namely is_renew. The value of target label is either Y or N, defining whether the customer has renewed the service or not.
To prepare your own training dataset [Visit here][TODO]
We have provided a sample data set of
- Go to the app store, build a renewal propensity app by searching for Renewal Propensity.
- You will be redirected to the app settings page where you can configure and run the app.
- Under Quick Settings,
3.1. Select an existing dataset or upload a new dataset and click Save.
3.2. Select the target field, the field that indicates whether customer has renewed the subscription or not and click Save.
- Now click on Run Now to start the app. The app may run for 5 to 20 minutes (dependending on the size of input data) and then the trained model will be saved.
- Use this model to get the renewal propensity.
5.1. Click on Build App on the model to build the inference app using that model.
5.2. Provide the input in the given fields and click on Get Results. The predicted renewal propensity class and scores will be displayed on the right side of the screen.
- [Optional] To use this model to predict more than one examples, [Visit here] [TODO]
The output of the infer app will the predicted class (renew or not) and probability score of prediction.
Go ahead and build your first Renewal Propensity App