Attain Higher Sales via Machine Learning Based Recommendation System

Get predictive analysis of historical sales pattern on your eCommerce website, based on consumer search and market trends, with the help of recommendation system.

Read how GSPANN helped a Cincinnati, US-based premier retailer, having over 700 departmental stores and 150 specialty stores, in replacing their existing manual, rule-based product recommendation technique with an automated machine learning-based recommendation system to achieve higher sales.

What can you learn from this case study?

  • Accurate product recommendation process: The manual, rule-based process for product recommendation was replaced with Machine Learning-based trained model to make the recommendation system automated, based on the historical sales pattern.
  • Automated product ranking system: Simplified the product ranking by automating the process of extracting historical data from multiple databases.
  • Achieve higher sales: The Machine Learning-based trained model was dynamic and 18% more accurate as compared to rule-based approach in predicting product sequence, which resulted in higher sales.

Product Sequencing Case Study Download

Recommendation system helps in analyzing sales pattern to achieve higher sales