Market basket analysis is a data mining technique used to discover associations and correlation relationships between items stored in transactional databases. By analyzing what items are frequently purchased together across many customers, market basket analysis can reveal important purchasing patterns and trends. Some key insights that may be discovered include:
Top Selling Item Combinations: Market basket analysis can identify the most commonly purchased combinations of items. This shows which products are strong complements to each other and are frequently bought together. Knowing the top selling item groupings allows a retailer to better merchandise and display these items near each other in store to drive additional complementary sales. It also enables targeted promotional offers and discounts for the associated products.
Impulse Purchase Relationships: The analysis can uncover items that are often impulse purchases when other items are in the basket. These additive or supplementary items may not have been on a customer’s original shopping list but get added once they see them alongside the planned purchases. Identifying these impulse relationship opens opportunities to actively promote and upsell the accompanying items to increase cart sizes and revenue per transaction.
Substitute or Cannibalization Relationships: The analysis may also find situations where one item is detracting from sales of a similar product. This occurs when customers view two things as substitutes and tend to pick one over the other. Understanding substitution relationships helps a retailer manage product assortments more strategically by potentially removing or replacing items that are cannibalizing each other’s sales.
New Product Introduction Opportunities: By analyzing existing co-purchase patterns, the market basket analysis can identify empty spaces in the data where introducing a new product may spark additional complementary sales. For example, if cookies and milk are regularly bought together, introducing cookie-flavored milk could fill a void and exploit that existing relationship. This helps guide the development and launch of new items tailored to complement current best-sellers.
Preferred Brands and Private Label Opportunities: The analysis provides visibility into which brands customers jointly select and have affinity for. It reveals the brand preferences and loyalties that drive multiple item purchases from the same manufacturer. This information helps retailers optimize brand strategies for their private label offerings, such as developing store brands designed to directly compete with identified co-purchased national brands.
Customer Segment Affinities: The analysis may uncover differences in purchasing patterns between demographic segments. For example, families with children could have distinct item groupings compared to elderly customers. Understanding these nuanced segment associations allows more targeted merchandising, assortments and promotions optimized for each customer type. It also supports the development of customized segment-specific retail experiences both online and in physical stores.
Seasonal and Geographic Tendencies: Market basket findings can expose item combinations that are especially strong during holiday or seasonal time periods. It may also uncover location-based preferences where certain regions show affinity for unique local product blends. This geographic and temporal analyses assist retailers in adjusting their assortments and marketing for optimal relevance based on time of year and community demographics served.
Supply Chain and Inventory Implications: The insights reveal dependencies between items from a demand perspective. This informs procurement, manufacturing, warehousing and store fulfillment by highlighting which products need coordinated replenishment to ensure the right complementary assortments reach shelves together. It supports supply chain optimization to fulfill complete shopping baskets and avoid lost sales from stockouts of key co-purchased items.
Market basket analysis provides a wealth of strategic business intelligence about customer shopping behaviors and the inherent links between products that drive multiple item purchases. The insights gained around top product combinations, impulse relationships, substitutes, brand preferences, seasonal tendencies and more allow retailers to profoundly improve merchandising, assortments, promotions, new product development, operations and overall customer experiences. If leveraged effectively, these findings can significantly boost sales, margins and competitive advantage.