Market Basket Analysis
The market basket analysis screens of the application all relate to the market basket affinity rules generated by AA. The tiles and screens provide a way to view different sets of data, depending on the configurations used for your business.
Market basket rules and their associated metrics are a key insight into product demand and customer buying behaviors. Understanding which products are more likely to sell together allow your business to coordinate targeted offers and promotions for products that have strong affinities elsewhere, without having to promote those other categories. It is also possible to understand market basket differences between customer segments, allowing you to further refine your sales and promotion strategies to target specific groups of customers that will bring in the most value to your business.
There are five screens available for viewing the AA results, each containing a different subset of affinity rules with certain characteristics as described below.
Table 7-10 Market Basket
| Field Name | Description |
|---|---|
|
Class |
Displays market basket affinities between different classes, without any consideration for whether the items were on promotion or not. |
|
Subclass |
Displays market basket affinities between different subclasses, without any consideration for whether the items were on promotion or not. |
|
Promotion |
Displays market basket affinities between different subclasses when the antecedent (if) components are promoted and the consequent (then) components are not promoted. |
|
Customer Segment |
Displays market basket affinities between different subclasses when the antecedent (if) components are promoted and the consequent (then) components are not promoted, further separated by customer segments. |
|
All |
Displays a searchable list of all available affinity rules for all types. |
After you select one of the five info tiles at the top of the screen, you will be presented with additional filter prompts and a data table for displaying results.
The filters above the table allow you to limit the data displayed in the table. AA can generate a large number of rules, and usually only the most common rules supported by the largest number of sales transactions are used in analyses. Which filters are displayed will depend on the current screen being examined. The following table provides an explanation of how all the filters impact the displayed results.
Table 7-11 Market Basket Filters
| Filter Name | Description |
|---|---|
|
Top |
Selecting a different number will change how many market basket rules are displayed in the results table. |
|
All |
Selecting the check box overrides the Top filter to instead display all available market basket rules. |
|
Classes/Subclasses |
Select specific classes or subclasses for which market basket rules should be displayed. This filter will be applied as an OR condition for either the IF components or the THEN components. If there are multiple IF components, then a match is only required for one of the components. |
|
Customer Segments |
Select specific customer segments for which market basket rules should be displayed. |
|
Select Product Hierarchy |
(All Screen Only) This prompt is used to choose which level of the hierarchy you are entering search criteria for. |
|
Show only Affinities with Promotions |
(All Screen Only) This prompt allows you to choose whether the results should be limited to promoted subclass affinities. |
Once you have selected your desired filter settings, you may begin to review the market basket affinities. The main table on each screen describes the product affinities that were found when analyzing the market basket data, sorted in descending order by your chosen performance metric (the Top 10 By global prompt described earlier in this chapter). In addition to the product affinities, numerous metrics are provided to describe the market basket data that contains these products.
Table 7-12 Market Basket Affinities
| Field Name | Description |
|---|---|
|
Customer Segment |
(Customer Segment screen only) Displays the customer segment for which the product affinity was found. |
|
Promotion |
(All affinities screen only) Displays whether the rule represents IF components that were on promotion. |
|
If |
Displays the classes or subclasses containing items that were purchased in the market baskets for a given product affinity. All market baskets that contributed to a rule will contain items from these product categories. |
|
Then |
Displays the class or subclass that was found to have an affinity with the IF components of the market basket rule. Market baskets containing the IF categories were found to contain items from the THEN category enough times to establish a product affinity between the IF and THEN components. |
|
Baskets |
The number of market baskets that contain items from both the IF and THEN components of the rule. |
|
Avg Sales from If Items |
The average sales retail amount from items belonging to the IF classes or subclasses. |
|
Avg Profit from If Items |
The average sales profit from items belonging to the IF classes or subclasses. |
|
Avg Sales Quantity from If Items |
The average sales units from items belonging to the IF classes or subclasses. |
|
Avg Sales from Affinity Items |
The average sales retail amount from items belonging to the THEN class or subclass. |
|
Avg Profit from Affinity Items |
The average sales profit from items belonging to the THEN class or subclass. |
|
Avg Sales Quantity from Affinity Items |
The average sales units from items belonging to the THEN class or subclass. |
The purpose of these summary metrics is to provide a quick view of the sales and profitability of the market baskets described by each rule. Even though a market basket affinity is present in a large number of baskets, it may not generate much profit or be of particular interest to the business user at this time. The summary metrics allow the user to quickly identify market basket affinities that are worth analyzing in more detail. Once the user has selected a rule to investigate, clicking that row in the table generates additional information about it in a panel to the right side of the screen.
Table 7-13 Market Basket Affinity Details
| Field Name | Description |
|---|---|
|
Support |
The percent of market baskets that contain items from the IF and THEN components of the rule. Written as a formula: Rule Transaction Count/Total Transaction Count |
|
Confidence |
The ratio of the number of transactions where the entire rule is present, compared to all transactions containing IF items. Written as a formula: Rule Transaction Count/Total IF Transaction Count |
|
Reverse Confidence |
The ratio of the number of transactions where the entire rule is present, compared to all transactions containing THEN items. If a rule has a higher Reverse Confidence than its own Confidence value, then it indicates that the rule is better represented by the reversal of the IF and THEN components. Written as a formula: Rule Transaction Count / Total THEN Transaction Count |
|
Lift |
A statistical measure of how strong the product affinity is, as compared to random chance for the rule (higher is better). Written as a formula: Rule Transaction Count * Total Transaction Count / Total IF Transaction Count/Total THEN Transaction Count |
|
Sales Amt Pct Of Total |
The percent of total sales retail amount that the rule represents. Written as a formula: Rule Sales Amount/Average Weekly Total Sales |
|
Avg Rule Sales Amt |
The average weekly sales retail amount across all transactions containing the rule. |
|
Avg Rule Sales Profit Amt |
The average weekly sales profit across all transactions containing the rule. |
|
Avg Rule Sales Qty |
The average weekly sales units across all transactions containing the rule. |
|
Avg Total Sales Amt |
The average weekly sales retail amount across all transactions. |
|
Avg Tot Sales Profit Amt |
The average weekly sales profit across all transactions. |
|
Avg Tot Sales Qty |
The average weekly sales units across all transactions. |
|
Avg Tot Txn Cnt |
The average weekly transaction count across all transactions. |
The detailed metrics for a rule provide more ways to evaluate if the rule is going to be useful for your business purpose. For example, a rule that has both high support and high confidence represents a strong product affinity that is purchased by many of your customers. Any action taken on the categories in such a rule, such as promoting a subclass on the IF side of the rule, can have significant benefits for the THEN components of the rule. Another way to use these metrics is to consider the average sales or profit that a rule brings in relative to total sales over the same period. Rules that represent a significant profit amount may be a more valuable target for your efforts than rules with lower profitability.
Another way to view the market basket affinities is to click the button found to the left of each row in the data table. This button displays a pop-up window with all of the product affinities that have been found for the IF components of the rule. This can be especially useful when your goal is to find any relationships with a specific product category, rather than seeing all of the relationships between different products.
Figure 7-9 Targeted Product Affinities Pop-Up
Description of "Figure 7-9 Targeted Product Affinities Pop-Up"
This screen is split into two main sections: the top section displays summary metrics for all rules associated with the IF components, and the bottom section displays all of the product affinities found for the IF components and a selection of detailed metrics for them.
Table 7-14 Targeted Product Affinities Summary Metrics
| Field Name | Description |
|---|---|
|
Avg Number of Baskets |
The average number of baskets found on a rule containing the IF items. |
|
Avg Sales from IF Items |
The average sales retail amount for the IF items in the rules. |
|
Avg Profit from IF Items |
The average sales profit for the IF items in the rules. |
|
Avg Sales from Affinity Item |
The average sales retail amount for the THEN items in the rules. |
|
Avg Profit from Affinity Item |
The average sales profit for the THEN items in the rules. |
Table 7-15 Targeted Product Affinities Detail Metrics
| Field Name | Description |
|---|---|
|
Then |
Displays the class or subclass that was found to have an affinity with the IF components of the market basket rule. |
|
Avg Sales |
The average weekly sales retail amount for the IF and THEN items in the rules. |
|
Avg Profit |
The average weekly sales profit for the IF and THEN items in the rules. |
|
Avg Quantity |
The average weekly sales units for the IF and THEN items in the rules. |
|
Baskets |
The number of market baskets that contain items from the IF and THEN components of the rule. |
|
Support |
The percent of market baskets that contain items from the IF and THEN components of the rule. |
|
Confidence |
The ratio of the number of transactions where the entire rule is present, compared to all transactions containing IF items. |
|
Affinity Reverse Confidence |
The ratio of the number of transactions where the entire rule is present, compared to all transactions containing THEN items. |
|
Lift |
A statistical measure of how strong the product affinity is, as compared to random chance for the rule (higher is better). |
|
% MB Sales |
The percent of total sales retail amount that the rule represents. |
|
Target Sales Value |
The average weekly total sales retail amount across all transactions in the selected periods. |
|
Target Profit |
The average weekly total sales profit across all transactions in the selected periods. |
|
Target Sales Quantity |
The average weekly total sales units across all transactions in the selected periods. |
This view of market basket affinities provides powerful insight into the relationships between different product categories, as it may expose affinities even between seemingly unrelated categories that your customers tend to purchase together. This screen allows you to see how actions taken on the target (IF) products will impact other areas within your business. For example, any action taken to increase the sales of an IF category can lift the sales of all other products with a strong affinity to those items. Conversely, if you have a category that is performing poorly on the THEN side of a rule, you may be able to take action on the IF products to boost that category's sales indirectly.