How do promotions work? New evaluation ways by linking scanning analyses and single source household panel data

Date of publication: June 15, 1995

Company: Nielsen

Author: Klaus Brüne


In the first place, traditional evaluations of trade promotions provide a weekly view of the sales volume influenced by promotion activities. The use of scanning data permits to exactly quantify the sales volume which is generated by promotion. By means of statistical methods, it is furthermore possible to forecast which sales increases can be expected when different promotion activities take place at the Point of Sale. In order to judge how additional sales were generated and which effect on the future brand success can thus be expected - particularly from a mid-term, profit-oriented point of view - the individual consumer and his behaviour have to be extracted from anonymity. Only a continuous observation of the individual purchase behaviour of single households can make consumer reactions on promotions transparent in the course of time and thus answer the following questions: Do we succeed in attracting new buyers at all - certainly the primary goal of promotion activities - or do we only reach already existing users? How do promotion purchases look like, for example, in case of significant price reductions? Do additional purchases of loyal buyers at least lead to a higher brand loyalty? Is trade able to distinguish itself and to establish a competitive advantage by means of aggressive price actions that are less and less controllable by manufacturers? Practical applications for analysing the mechanisms in a variety of markets reveal significant differences regarding the effect of promotion activities on mid-term purchase behaviour. Promotions are only one part of an integrated communication system. The isolated view of impulses which is outlined in this article is only a first step, whereas the second step consists of evaluating all impulses on the actual purchase behaviour, including the explanation of the short-term and mid-term contribution of classical advertising by using Single Source data.

Klaus Brüne


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