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Market Basket Analysis: Examples & Data Mining

Instructor: Brianna Whiting

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

Think about the last time you went shopping. Was it a good experience? Were the items you were looking for easy to find? In this lesson we will learn about market basket analysis and how it helps enhance your shopping experience.

A First Look at Market Basket Analysis

Meet Karla! Karla owns her own business where she sells home accents. Although Karla has a loyal customer base, she has noticed some customers feeling a bit frustrated after shopping in her store. You see, the layout of her store just isn't working well, because items commonly purchased together are spread out all over the store. This makes shopping a long process that involves searching for items that often go together. For example, Karla has her lamps on one end of the store, with the lampshades on the other side. Customers wanting to buy a complete lamp are forced to walk all over the store to gather the needed pieces.

Knowing she needs to change how her store is organized, Karla decides to do some research to better understand what items are commonly purchased together, known as market basket analysis. Understanding these common combinations of products purchased together can help the layout of Karla's store.

Foundation Definitions

Let's take a minute to define some key definitions. Market basket analysis is the process of looking for combinations of items that are often purchased together in one transaction. So, if a customer buys one item, according to market basket analysis, they are more or less likely to buy another item. If we take our example from earlier, perhaps customers that buy bedding and curtains also tend to buy area rugs. This is because many of them are redecorating a bedroom.

Items are the things that the customers are purchasing. For example, each item is a product that Karla has in her store. When there is a group of items, this is called an item set.

Transactions are the groups of items that are purchased together. So, if a customer buys a candle and a pillow, all items occur together in one transaction.

The probability that a customer will purchase an item is known as support. In other words, if Karla is able to identify popular products that many or most of her customers purchase, then she would have support of that item or item set. For example, if most of her consumers buy curtains, then curtains will have great support.

Data Mining

While we now understand that market basket analysis is looking for items that are often purchased together, what we still need to know is how to identify what items are purchased together.

Data mining is the process that looks at big pieces of data to find patterns and relationships. It is a process that can help predict future outcomes. Karla could use data mining by gathering all of the transactions completed in one month, then looking for patterns of items that are commonly purchased together. These results can then be used to predict what future customers will purchase together. Ultimately, Karla can use this information to organize her store in a manner that places commonly purchased items together. This will help alleviate her customers' frustration at having to walk all over the store looking for items.

Why is Market Basket Analysis Used?

Being able to recognize items that are purchased together can be an asset to business owners. This is because they can use that information to help them make shopping a more convenient and positive experience for their customers. It can also be a great way to increase sales, because customers will have the ease of grabbing like items in one stop. The following are some common reasons why a business uses market basket analysis.

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