02-12-2017 12:56 PM - last edited on 02-12-2017 03:50 PM by LinusH
I have built a customer engagement model using logistic regression, The approach was to take a group of customers we consider engaged, then build model to find lookalike in the customer base.
The most important variables were as you will expect, number of visits in the last 12 weeks, number of distinct product they use in the last 12 weeks etc...I have also entered variables, like visits in the last 1 week, last 4 weeks etc but the most important were only 12 weeks var.
My question is if there is any change , like price increase of products or any other events that will impact the purchase. How do I make sure in the model that it won't take 12 weeks to see how customers are getting disengaged etc..
Your help would be much appreciated.
Thank You so much
02-12-2017 06:07 PM
I would have approached it differently. Specifically, I would have identified the customers your company considers engaged, and then build a model (using both engaged and not engaged customers) and predict "engaged".
To answer your second question, as long as price increases were included in the data, you should get an indication of their effects.
Art, CEO, AnalystFinder.com