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Affinity analysis is a technique for the purpose of data mining and analysis that is meant to discover co-occurrence relationships among activities that are carried out by certain groups or individuals. As such, affinity analysis can be applied to processes where identification of agents is unique and information about activities can be recorded. In reality, affinity analysis is mainly used for market basket analysis, whereby retailers learn about the behavior of customers with regard to purchases they make. Further, such an analysis helps in up-selling and cross-selling, besides helping in loyalty programs, sales promotions, discount plans and even the designing of stores.
Affinity analysis largely involves the process of finding connections between different items based on the subject’s view of these items. Affinity analysis is used for studying patterns and behavior in customers to determine links in purchases. The most basic example of this is that of a shampoo and conditioner: while these two items are different from each other, a buyer makes a connection between them as they happen to be used at the same time.
The first step in affinity analysis is to identify the subject, which may be defined on certain conditions. The next step is to observe and then record the habits of this subject. On recording, certain patterns start to emerge, which can be used for making connections. Affinity analysis is largely used in marketing and sociology, in order to understand connections underlying between events that are connected but not directly related.