Want to know how to bring the intelligence of predictive analysis to your Bubble app? Here’s a quick summary:
1- Export the data: Start by extracting the data you want to analyze directly from your app or database.
2- Data cleaning: Thoroughly clean the data, removing problematic entries like null or inconsistent values. This ensures the quality and accuracy of your analysis.
3- Exploratory analysis: Analyze the data to identify the variables that most influence your customers’ behavior. These predictor variables will form the basis of your model.
4- Model training: Use a machine learning tool (i.e.: R, python, etc. We used Alteryx also a no code tool) to train your model using the selected predictor variables.
5- Exporting coefficients: With the model trained, export the generated coefficients and integrate them into your Bubble app.
6- Dynamic calculation: Now, with the coefficients integrated, you can dynamically calculate the probability of your target variable within your app, enabling real-time predictions.
Want to see this in action? 
Check out my short where I present a real case study showing how predictive analysis helped a company to predict a food hamper demand.
