Product Affinity Analysis: Methods & Examples

Instructor: Brianna Whiting

Brianna has a masters of education in educational leadership, a DBA business management, and a BS in animal science.

Often times we buy certain items together. But why do some items go together? In this lesson, we will learn about a valuable tool stores use to boost sales and convince us to purchase more.

The Shopping Experience

Have you ever gone to the store for one item and ended up buying other items? Why did you buy those extra items? Were they related to the product you went to the store for in the first place? Were they impulse buys?

While we may not give much thought as to why we buy extra items when we go shopping, the stores we shop at certainly do. You see, stores have done research and utilize methods to tempt us to buy additional items while out shopping. In this lesson, we will learn about one of the ways stores determine what types of items are often purchased together - product affinity analysis.

Product Affinity Analysis

So how do stores get us to buy more than what we came to purchase? One way is to use product affinity analysis. Product affinity analysis studies patterns and behaviors of customers to determine links in purchases so that stores can increase their cross-selling potential. In other words, it is a way for a store to sell more items based on previous purchasing behaviors. Stores look at large amounts of transaction history and determine which items customers often buy together.


You may be wondering how stores determine what items are purchased together. Well, for starters, they often use a database. The database creates a basket in which an item is placed. Once the item is placed in the basket, the database will reveal products that a customer may purchase together with it based on transaction history. The products will be ranked in order of how likely they are to be purchased with the item in the basket.

Another way stores use product affinity analysis is to simply observe the actual shopping cart of the customer. Using what is called a market basket a store can see what caused the shopping trip in the first place. For example, did the customer purchase balloons, toys, and wrapping paper? The market basket would indicate that the correlation of the products indicate that the shopper made the trip to the store because of a party of some sort. Understanding why the shopper came to the store, can help a store determine what items might be purchased together based on the occasion of the visit.


Let's take some time to look at examples of stores increasing their sales via product affinity analysis.


Many of us have shopped at Amazon online before. Amazon is well known for the many different items available for purchase. However, have you ever noticed that towards the end of the page there are recommendations of other products? After looking over purchase history data, Amazon is able to understand what items customers often purchase together and has increased its sales by 30% because it recommends products to customers based on the products they are currently purchasing.


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