A recommendation algorithm is a computer tool commonly used to promote a product or service to a customer or prospect on a website or mobile application. These recommendations can be displayed in personalized or dedicated spaces, whether on an e-commerce site, in a newsletter, a mobile notification, or a digital advertisement, particularly for retargeting. In addition to digital media, recommendation algorithms can be used for direct mail campaigns or other marketing activities.

The main objective of a recommendation algorithm is to suggest the products most likely to be purchased and to maximize profits. To do this, these algorithms take into account a multitude of data such as purchase and return history, email and web page interactions, demographic information, stock levels, weather forecasts, margins, other customers’ purchasing habits, product reviews, and more.

For example, in a clothing subscription service, a specific algorithm can be implemented to recommend items tailored to each user’s preferences and purchasing behavior. A concrete example could illustrate how an e-commerce personalization and recommendation platform was successfully leveraged through the integration of recommendation algorithms.

Radio France also developed a podcast recommendation algorithm to offer listeners a personalized experience based on their preferences and listening history. These concrete examples demonstrate the effectiveness of recommendation algorithms in various contexts, thus providing a more relevant and enriching user experience.