Case Study: Large Home Improvement and Appliance Store achieves enhanced product recommendations and multimillion-dollar annual savings with Happiest Minds

Recommendation engine development and deployment for a large home improvement and appliance store

Happiest Minds partnered with a large home improvement and appliance retailer to build a recommendation engine that could deliver product-to-product and customer-to-product recommendations. The retailer needed to aggregate and analyze structured and unstructured data from multiple channels and enable near real-time decision making.

The solution used an open-source big data stack—Hortonworks Hadoop for storage, Pig/Hive for processing, and MapReduce/Mahout collaborative filtering with Python—to process Teradata transactional and Omniture clickstream data and drive email campaigns and onsite recommendation views. The deployment delivered multimillion-dollar annual savings versus in-house and licensed alternatives, improved product recommendations, and increased revenues through a better customer experience.