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Expert systems 435
information system and that ‘issues worthy of consideration’ can be
suggested by an advice-giving expert system. 11
A better documented, and perhaps more successful, set of expert
system developments in marketing relate to utilization of scanning data
at checkouts in supermarkets and other stores. As Brown and Goslar 12
note, consumer purchase data can now be automatically collected at
point-of-sale through scanner systems. Scanning systems allow analysis
of purchase time, place, amounts, outlet type, price and promotional
discount. Mitchell et al. 13 focus on the use of expert systems to analyze
such scanner data. As they note, the increased availability of these data
has severely tested the ability of marketing management to analyze
them. The change from bi-monthly store audit data to weekly store level
scanner data results in a 10 000-fold increase in the available data. 14 How
should these data be analyzed? One suggestion 15 is that human modes
of analysis can be replicated on an expert system. The focus is on the
automation of the more repetitive and mechanical aspects of the data
analyst’s task (such as noting differences and trends) in order to ensure
consistency in decision making and decreased analysis time. 16
As Mitchell et al. report, humans skilled in the analysis of scanner data
have several advantages, mainly in their ability to recognize change
points in time series data and construct a causal explanation of these
changes. 17 They do not advocate that expert systems should be developed
to provide complete automation of the analysis but, rather, they
assist the planner by providing a ‘first-cut’ analysis of the data, relieving
the market professional of simpler, more structured and routine data
analysis tasks. For example, one scanner-based expert system is based on
the concept that market share is inversely related to price. 18 This system
is sensitive to time periods in which the share has gone up (or down)
or the price has gone down (or up). Such relationships are summarized
and reported to the marketer.
McCann et al. 19 develop the utilization of such marketing data within
the brand management process – their Brand Manager’s Assistant (BMA)
expert system augments data analysis. For example, a data analysis
program may note that sales of ‘Munchkins’ are not as well developed
in Washington, New York and Atlanta as in all other markets. Further,
the Washington sales may be, relatively, very low. BMA would
report that ‘for Munchkins the situation in Washington required much
attention’. The brand manager may then decide to implement a trade
promotion in Washington and BMA would subsequently automatically
monitor this and, perhaps, report that, in contradiction to the brand
manager’s predictions of increased number of sales, ‘the promotion