Next-Best-Offer for large datasets

Association models have been the basis for next-best-offer recommendation engines for a long time. Recommendation engines are widely used for presenting customers with cross-sell offers. For example, if a customer purchases a shirt, pants, and a belt; which shoes would he also likely buy? This type of analysis is often called market-basket analysis as we are trying to understand which items customers purchase in the same basket/transaction.

Recommendations must be very granular (for example, at the product level) to be usable at the check-out register, website, and so on. For example, knowing that female customers purchase a wallet 63.9 percent of the time when they buy a purse is not directly actionable. However, knowing that customers that purchase a specific purse (for example, SKU 25343) also purchase a specific wallet (for example, SKU 98343) 51.8 percent of the time, can be the basis for future recommendations.

Product level recommendations require...