Affinity analysis is a data analysis and data mining technique that discovers co-occurrence relationships among activities performed by (or recorded about) specific individuals or groups. In general, this can be applied to any process where agents can be uniquely identified and information about their activities can be recorded. In retail, affinity analysis is used to perform market basket analysis, in which retailers seek to understand the purchase behavior of customers. This information can then be used for purposes of cross-selling and up-selling, in addition to influencing sales promotions, loyalty programs, store design, and discount plans.[1]
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Business use of market basket analysis has significantly increased since the introduction of electronic point of sale[1]. Amazon uses affinity analysis for cross-selling when it recommends products to people based on their purchase history and the purchase history of other people who bought the same item. Family Dollar plans to use market basket analysis to help maintain sales growth while moving towards stocking more low-margin consumable goods[2]. A common urban legend highlighting the unexpected insights that can be found involves a chain (often incorrectly given as Wal-Mart) discovering that beer and diapers were often purchased together, and responding to that by moving the beer closer to the diapers to drive sales; however, while the relationship seems to have been noted, it is unclear whether any action was taken to promote selling them together[3].