Product to Predict who is likely to shop next day week/month

Products are design by basic consideration of below points

1. Data Wrangling (creating previous/next datasets and calculate purchase day differences)
2. Factor impacting the likelihood of customers.
3. Selecting a Machine Learning Model (Spot checking for Regression Algo, Linear and Non Linear)
4. AOC Curvy performance metric for binary classification
5. Confusion Metrix for Accuracy of Model with two or more classes.

Factor impacting the likelihood of customers.

For developed product , we have selected our feature candidates like below:
1. RFM (recency, frequency, and monetary value) scores & clusters
2. Days between the last three purchases
3. Mean & standard deviation of the difference between purchases in days

1. RFM : Understand your customer through RFM,

1. Recency: How recently a customer has made a purchase
2. Frequency: How often a customer makes a purchase
3. Monetary Value: How much money a customer spends on purchases