Predictive model in eCommmerce
Data Science is being applied significantly in e-commerce. As data technologies gain more traction, we will see more innovative applications of AI, Machine Learning, etc., in e-commerce retail.
Coupons and promotional codes have become a key strategy for e-commerce as they help increase sales, draw traffic and customers’ attention to your products, obtain customer data, enhance brand reputation, provide maximum publicity, etc., thereby maximizing the business profits.
Our use case accurately predicts the buyers who are most likely to use coupons in their purchase journey by leveraging Machine Learning and other Data Science technologies.
Identifying buyers who are most likely to use a coupon while buying a product in an eCommerce site.
We built a Prediction model leveraging Machine Learning and other Data Science 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.
To read the complete use-case with detailed information on the data sets, technologies, approach, models and procedures followed download usecase.