Home / 

Improve Reorder Sales with Machine Learning-based Intelligence

Read how GSPANN helped a US-based retailer, with 800+ stores and 25B annual sales, to increase reorder sales through personalized emails and deliver relevant information at the right time utilizing machine learning (ML) algorithms.

Key highlights:

  • The ML model learned from 2 years’ data of over 47+ million transactions.
  • Increase in average order value, open rate, and CTR for the reorder email campaigns.
  • 23% decrease in email unsubscription rate.

This case study can help you understand how machine learning algorithms can do wonders by learning from historical transactional data and then deliver a deep personalization to the customers, which leads to enhanced customer experience and loyalty.

Request the Case Study

Case Study logo

Case Study

Leverage Machine Learning for Product Sequencing to Drive eCommerce Revenue

Case Study logo

Case Study

Attain Higher Sales via Machine Learning Based Recommendation System

Blog logo

Blog

Automating Critical eCommerce Processes with Robotic Process Automation and Artificial Intelligence