Market Basket Analysis Task

AKA: Basket Analysis.
Context:
- It can be solved by a Market Basket Analysis System (that implements a market basket analysis algorithm).
- …
Example(s):
See: Discounts And Allowances, Cross-Selling, Up-Selling, Sales Promotion, Apriori Algorithm; Association Rule; Frequent Itemset; Frequent Pattern.

References

(Toivonen, 2017) ⇒ Toivonen H. (2017) Basket Analysis. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA
- QUOTE: The goal of basket analysis is to utilize large volumes of electronic receipts, stored at the checkout terminals of supermarkets, for better understanding of customer behavior.
  While many forms of learning and mining can be applied to market baskets, the term usually refers to some variant of association rule mining. In the basic setting, each market basket constitutes an example essentially defined by the set of purchased products. Association rules then identify sets of items that tend to be bought together. A classical, anecdotal discovery from supermarket data is that “if a basket contains diapers then it often also contains beer.” This example illustrates several potential benefits of market basket analysis by association rules: simplicity and understandability of the results, actionability of the results, and a form of nonsupervised approach where the consequent of the rule has not been fixed by the user. Association rules are often found with the Apriori algorithm, and are based on frequent itemsets.

(Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Affinity_analysis Retrieved:2017-12-1.
- .. 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]