Affinity analysis

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]

Examples

• Market basket analysis might tell a retailer that customers often purchase shampoo and conditioner together, so putting both items on promotion at the same time would not create a significant increase in profit, while a promotion involving just one of the items would likely drive sales of the other.
• Market basket analysis can be used to divide customers into groups. A company could look at what other items people purchase along with eggs, and classify them as baking a cake (if they're buying eggs along with flour and sugar) or making omelets (if they're buying eggs along with bacon and cheese). This identification could then be used to drive other programs.

Business Use

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].

See Also

Association rule learning

References

1. ^ ^{a b} "Demystifying Market Basket Analysis". http://www.information-management.com/specialreports/20061031/1067598-1.html. Retrieved 3 November 2009. 
2. ^ "Family Dollar Supports Merchandising with IT". http://www.retailerdaily.com/entry/45999/family-dollar-merchandising/. Retrieved 3 November 2009. 
3. ^ "The parable of the beer and diapers". The Register. http://www.theregister.co.uk/2006/08/15/beer_diapers/. Retrieved 3 September 2009. 

Further reading

• J. Han et al., 2006, Data Mining: Concepts and Techniques ISBN 978-1-55860-901-3
• V. Kumar et al. 2005 Introduction to Data Mining ISBN 978-0-321-32136-7
• U. Fayyad et al. 1996 Advances in Knowledge Discovery and Data Mining ISBN 978-0-262-56097-9

External links

• Examples of basic Market Basket Analysis using Excel
• An overview of Market Basket Analysis