The Shopping Basket Analysis Tool The Shopping Basket Analysis tool is designed to analyze any transaction (such as tables) containing many-to-one relationships. For example, you could use this tool to analyze web pages that are visited frequently in the same browsing session, or even gene combinations that are often associated with a certain condition.

The Shopping Basket Analysis Tool The Shopping Basket Analysis tool works on transaction tables structured as Shown the following Table. In a transaction table, each data row represents an item that participates in a transaction. Because one transaction will likely include more than one item, multiple rows in a transaction table are associated with the same transaction. Each row in a transaction table contains at least two columns. One of these columns identifies the transaction that includes the current row, and the other column identifies the actual item. TRANSACTION ID ITEMS IN TRANSACTION T1 Cola Chips T2 Milk T3 T4

The Shopping Basket Analysis Tool During analysis, the tool first identifies bundles of items that appear often together in transactions (for example, products that sell together). The second part of the analysis builds a set of recommendations. A recommendation is a statement of the form, ‘‘Transactions that contain Cola will likely contain Chips’’ This statement is based on the frequent occurrence of Chips in the transactions that include Cola. Note that these recommendations are not symmetric. Even if all transactions that contain Cola also include Chips (hence a recommendation such as the earlier one), there could be many transactions in the system that include Chips and no Cola.

The Shopping Basket Analysis Tool Using the Tool

The Shopping Basket Analysis Tool Using the Tool Our goal is to find groups of products that often appear together in transactions.

The Shopping Basket Analysis Tool The Bundled Item Report The first report generated by the Shopping Basket Analysis tool describes the bundles of items that frequently appear together in the transactions The first column of the report (Bundle of items) contains the products in the group, separated with a comma. The second column (Bundle size) contains the number of products in the group (the size of the bundle). The third column (Number of sales) tells you how many transactions contain all of the products in the bundle.

The Shopping Basket Analysis Tool The Bundled Item Report The first report generated by the Shopping Basket Analysis tool describes the bundles of items that frequently appear together in the transactions The Average Value Per Sale column contains the average value of the bundle in all transactions that contain all items in the bundle. To obtain this value, the tool does the following: Traverses all transactions that contain all items in the bundle Sums the value of each product in the bundle Divides the resulting sum by the number of transactions containing the bundle

The Shopping Basket Analysis Tool The Bundled Item Report The first report generated by the Shopping Basket Analysis tool describes the bundles of items that frequently appear together in the transactions The Overall value of Bundle column is obtained in much the sameway as the average value, without the last step that computes the average Traverses all transactions that contain all items in the bundle Sums the value of each product in the bundle

The Shopping Basket Analysis Tool The Bundled Item Report If you did not make a selection for the Item Value option in the tool dialog box certain properties of the bundles cannot be computed. In this case, the tool generates a simplified report

The Shopping Basket Analysis Tool The Recommendations Report Whereas the Bundled Item report provides a descriptive view of the frequent buying patterns of your customers, the second report generated by the Shopping Basket Analysis tool, Recommendations, provides actionable items for the person performing the analysis. The recommendations on this report are based on products that were purchased together by many customers, and can be used for direct marketing such as the familiar phrase, ‘‘People who bought the items in your shopping basket also liked these other items,”

The Shopping Basket Analysis Tool The Recommendations Report The first two columns of the report contain the recommendations. The first column (Selected Item) contains the products that trigger a recommendation. The second column (Recommendation) shows the actual recommendation (the product that is frequently bought together with the selected item). The first recommendation in the Figure should be interpreted as, ‘‘The people who purchased the Mountain Tire Tube frequently also purchase the Sport-100 helmet’’

The Shopping Basket Analysis Tool The Recommendations Report The third column (Sales of Selected Items) tells you how many transactions contain the selected item. The fourth column (Linked Sales) tells how many of these transactions also contain the recommended item, the Sport-100 helmet. You can see that 749 transactions contain both the Mountain Tire Tube and the Sport-100 helmet. The fifth column (% of linked sales) expresses the same number as a percentage of Mountain Tire Tube transactions.

The Shopping Basket Analysis Tool The Recommendations Report The Overall value of Linked Sales column contains the total value of the recommended products. In the example being used here, this value contains the sum of the price for the Sport-100 helmet in all the 749 transactions that contain both the recommended product (the helmet) and the recommending product (the Mountain Tire Tube).

The Shopping Basket Analysis Tool The Recommendations Report The Average value of recommendation column shows the overall value of linked sales divided by the number of transactions that contain the recommending item (the Mountain Tire Tube). This number is the average value you will gain by recommending a Sport-100 helmet to all Mountain Tire Tube buyers.

The Shopping Basket Analysis Tool The Recommendations Report The report looks slightly different if you did not make a selection for the Item Value option in the Shopping Basket dialog box. In this case, the value columns of the report cannot be computed, and they are replaced by an Importance column with a score for each recommendation.

The Shopping Basket Analysis Tool The Recommendations Report The importance is directly related to the percentage of linked sales, but it also penalizes a recommendation that links to a very popular product. For example, In the report shown in the Figure, a very high percentage (83.1 percent) of customers who purchased a Mountain Bottle Cage also purchased a Water Bottle. However, the Water Bottle is a very popular item, and many customers are likely to buy this product. Therefore, a recommendation to buy a Water Bottle, although supported by the frequency, is not very interesting.

The Shopping Basket Analysis Tool Fine-tuning the Tool The tool is looking for the significant bundles of items, as well as for strong recommendations. Thresholds are used both for the significance of bundles and for the strength of recommendations

The Shopping Basket Analysis Tool Fine-tuning the Tool The first threshold, Minimum Support, states when a bundle of items is significant enough to be taken into account by the analysis. The significance of a bundle is directly linked to the frequency of that bundle in transactions.

The Shopping Basket Analysis Tool Fine-tuning the Tool The second threshold, Minimum Rule Probability, deals with recommendations. The Minimum Rule Probability threshold states how many Cola transactions have to include Chips before such a recommendation is considered by the tool. The default value, 40 percent, requires that at least 40 percent of the transactions containing Cola must also include Chips.