Case Study: Leading US Retail Chain boosts cross-sales from 10% to 12% with Happiest Minds' Product Recommendation Solution

Product Recommendation for leading US Retail Chain

A leading US retail chain faced low recommendation coverage across 25,000+ products for kiosks and online channels: their existing model couldn’t recommend new items or categories and ignored contextual signals such as store demographics, weather and location.

Happiest Minds implemented a big‑data recommendation platform that clusters stores by demographic, weather and location data and uses machine learning (clustering, product association and collaborative filtering) to find similar products and generate cross‑sell/up‑sell suggestions for new items. The solution raised cross‑sales from 10% to 12% and delivers recommendations consistently across web, mobile and in‑store kiosks.