Skip to content

Using Recommendation Systems as a business intelligence tool

This is part 1 of a 5 part series on Recommendation Systems.

If you have purchased anything online in the past 15 years, you have been exposed to a recommendation system. It takes the form of recommending products to you that “People like you” buy or are “Frequently Bought Together”, attempting to get you to buy products you might not have considered.

Recommendation systems have come a long way in those 15 years and today are becoming the primary user experience for many companies with a large number of products. Netflix streams so many movies and shows that it can overwhelm a typical user, so the primary user experience of Netflix is from recommendations about which videos you are likely to enjoy based on your viewing history.

However, recommendation systems also exist behind the scenes to predict user behavior and what product changes may or may not make you happy. At its core, a recommendation system is predicting which products you as a consumer are likely to enjoy. That is invaluable information for making business decisions.

This week we’ll cover how recommendation systems work and how they can help you make better decisions.

Tomorrow we’ll get started by reviewing the simplest kind of recommendation system, the kind Netflix might use to recommend movies to you.

Quote of the Day: “One can’t prescribe books, even the best books, to people unless one knows a good deal about each individual person.” ― Rudyard Kipling