Databases Reference
In-Depth Information
of a Multiple Linear Regression is the flexibility of data. Market Basket
Analysis found its first best application in retail marketing. Cash registers
in the retail environment are able to capture transaction data in granular
detail for each and every transaction. As such, transaction processing sys-
tems produce a volume and wealth of data that feed into Market Basket
Analysis. Today, the software used in manufacturing, communications,
supply chains, transportation, Web-based applications, and any other
application that can capture and log activity produce large volumes of data
used in Market Basket Analysis. The logged activity varies based on the
activity in the Itemset. One Itemset may contain one object and another
may contain one thousand objects. This variability is not found in Multi-
Linear Regression, which has a predefined set of variables, each contain-
ing one and only one value at a t ime. Regardless, the statistical nature
of Market Basket Analysis is still found in the calculations of Aἀ nity
between Objects in an Itemset.
Market Basket Analysis distinguishes itself from statistics in the goals
and methods applied during the processes of Market Basket Analysis.
Despite any altruistic claims to the contrary, the ultimate goal of Market
Basket Analysis is to make money. Either through improved marketing,
streamlined manufacturing, more eἀ cient customer interactions, or
anything else that increases revenue and/or decreases expenses, Market
Basket Analysis is expected to improve the bottom line of the enterprise.
As such, the language of Market Basket Analysis diverts from its statistical
background toward language that is more actionable within the business
operations of the enterprise. Specifically, the language of Market Basket
Analysis includes the following concepts, which may coincidentally
resemble statistics but are functional business concepts.
• Complementary—he probability of two Objects occurring in the
same Itemset is strong. The strong correlation of simultaneous occur-
rences of the Objects suggests the two objects have some connection.
That connection may be direct or indirect. For instance, in an auto
parts hardware store motor oil and an oil filter have a d irect con-
nection. The direct connection is that both are involved in an oil
change, which is the most frequent automotive maintenance. The
most famous indirect connection is that between beer and diapers. In
the “beer and diapers” anecdote of Market Basket Analysis lore, hus-
bands and fathers who go by their local store to buy diapers on their
way home from work are also susceptible to the suggestion to buy
