David Ing and Andrew A. Mitchell


During the 1980s, there was a dramatic increase in the installation of systems which capture Point-of-Sale (POS) data by retailers. The increase of installations was greatest in the supermarket segment, after the adoption of an industry standard for bar coding (i.e. the Universal Product Code) by the consumer packaged goods manufacturers. The reported benefits from this adoption of standards has led to similar standards by vendors of other lines of consumer goods (e.g. apparel) carried by department stores and mass merchandisers. The initial impetus for retailers to install sophisticated POS systems was to decrease the time required to record the item purchases by customers, and to improve the accuracy of prices charged at checkout. Both manufacturers and retailers believed, however, that even greater benefits might be realized when the POS data were analysed, and applied to improve the effectiveness and efficiency of marketing activities logistics.

Prior to the general availability of POS data, marketing was usually considered to be an art. One reason for this view was that measures of market performance were available only at very aggregate levels, temporally and geographically. This made it difficult to assess the effect of a specific marketing events (e.g. price promotions), which might have occurred for a brief period of time (e.g. one week) in a particular retail chain. Consequently, successful marketing was attributed to the intuitive understanding of consumer tastes, and the creativity of media advertising. The availability of weekly POS data at the household, store, account and market level, when coupled with measures of causal variables (e.g. store displays), provides the opportunity to obtain precise measures of the effect of different marketing events. However, in order to take advantage of the availability of these data, firms must take a more scientific approach to marketing, and an appropriate commitment of resources.

The decision to commit the resources necessary to effectively use these data, however, has proven to be neither simple nor obvious for most companies. While the cost to retain POS data as an electronic byproduct of transactional systems is low, the resources required to store and analyse these data are significant. In addition, attributing improvements in bottom-line profitability to the direct application of these data has proven difficult.

The purpose of this chapter is to discuss the form and content of POS data available to marketers, how these data supplement and replace other forms of marketing data, and issues which have arisen in their effective managerial use. In the first two sections, we discuss the data as generated from transactions, and as applied in the two-stage channel structure which is common in consumer goods marketing. In the third section, a learning curve of expertise in the science of marketing is introduced. The following four sections review some leading-edge applications. The chapter concludes with an outlook on the future for POS data.


David Ing and Andrew A. Mitchell, "Point-of-Sale Data in Consumer Goods Marketing: Transforming the Art of Marketing into the Science of Marketing", The Marketing Information Revolution, Robert C. Blattberg, Rashi Glaser and John D. C. Little (editors), Harvard Business School Press, 1994.


The Marketing Information Revolution book cover

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1994/01 Point-of-Sale Data in Consumer Goods Marketing: Transforming the Art of Marketing into the Science of Marketing