Price and Profit Awareness in Recommender Systems

TL;DR

This paper explores how incorporating price and profit considerations into recommender systems can align recommendations with business goals, demonstrated through literature review and numerical simulations.

Contribution

It introduces the concept of price- and profit-aware recommender systems and illustrates their potential business benefits through simulations.

Findings

Profit-aware recommendations can increase business value.

Incorporating pricing info improves recommendation relevance for providers.

Numerical simulations show potential profit gains.

Abstract

Academic research in the field of recommender systems mainly focuses on the problem of maximizing the users' utility by trying to identify the most relevant items for each user. However, such items are not necessarily the ones that maximize the utility of the service provider (e.g., an online retailer) in terms of the business value, such as profit. One approach to increasing the providers' utility is to incorporate purchase-oriented information, e.g., the price, sales probabilities, and the resulting profit, into the recommendation algorithms. In this paper we specifically focus on price- and profit-aware recommender systems. We provide a brief overview of the relevant literature and use numerical simulations to illustrate the potential business benefit of such approaches.