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• Date Submitted: 08/01/2011 12:31 AM
• Flesch-Kincaid Score: 44.3
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Market Basket Analysis is an algorithm that examines a long list of transactions in order to determine which items are most frequently purchased together. It takes its name from the idea of a person in a supermarket throwing all of their items into a shopping cart (a "market basket"). The results can be useful to any company that sells products, whether it's in a store, a catalog, or directly to the customer.
Market Basket Analysis is used to determine which products sell together. As such, the input to a Market Basket Analysis is normally a list of sales transactions, where each column represents a product and each row represents either a sale or a customer, depending on whether the goal of the analysis is to find which items sell together at the same time, or to the same person. The cells of the data normally contain only 1 (bought product) or 0 (did not buy product) values, though PolyAnalyst can work with other data in the cells, such as quantity or revenue.
Due to how Market Basket Analysis works, it is preferable to have all products represented equally in the data. That is, a product that is only sold 1 or 2 times in the entire data file should not be included, as the algorithm will find rules involving these products that are not statistically significant. In general, no product should be represented in the data more than 10 times as often as any other product. Representation of products can be equalized by categorizing them – combine similar, low-sales items together while splitting high-sales items into subtypes.

Purpose
Market Basket Analysis is one of the most common and useful types of data analysis for marketing. The purpose of market basket analysis is to determine what products customers purchase together; it takes its name from the idea of customers throwing all their purchases into a shopping cart (a "market basket") during grocery shopping. Knowing what products people purchase as a group can be very helpful to a...