Predictive model in eCommmerce
Building a predictive model to identify potential buyers who are more likely to use coupons on their purchase journey.
The client wanted to predict the behavior of a user who during his visit (session) on the website will leave and go get a coupon from an affiliate. The client will hence assign an affiliate id to the session.
As a solution, we built a Prediction model leveraging Machine Learning and other data technologies that predicts whether the user is going to look for the coupons or not. By this, we identify the users who come to the e-commerce website and then leave to find coupons on an affiliate website.
Machine Learning Algorithms, Data Visualization, Data Cleaning, and Predictive Analysis.
We used 6 months of historical data from an e-commerce website for the project. The data was derived from Google Analytics.
Our predictive model could identify buyers most likely to use coupons with 97% accuracy.
Soulpage is a Hyderabad, India based data science technology company with deep authority over AI, Machine Learning and NLP, etc. We provide end-to-end services from strategy consulting to software development. We work with innovation-driven enterprises, idea-driven entrepreneurs and new-age startups partner to make sense from their data, get actionable insights and gain competitive advantage. We follow complete adherence to data regulations like HIPAA, Data Protection 2018, etc.