Is 3/4 of the Sales Promotion Bump Due to Brand Switching? No it is 1/3

Several researchers have decomposed sales promotion elasticities based on household scanner panel data.A key result is that the majority of the sales promotion elasticity, about 74 percent on average, is attributed to secondary demand effects (brand switching) and the remainder to primary demand effects (timing acceleration and quantity increases).We demonstrate that this result does not imply that if a brand gains 100 units in sales during a promotion the other brands in the category lose 74 units (74 percent).We offer a complementary decomposition measure based on unit sales.This measure shows the ratio of the current cross-brand unit sales loss to the current own-brand unit sales gain during promotion, and we report empirical results for this measure.We also derive analytical expressions that transform the elasticity decomposition into a decomposition of unit sales effects.These expressions show the nature of the difference between the two decompositions.To gain insight into the magnitude of the difference, we apply these expressions to previously reported elasticity decomposition results.We find that on average about one third of the unit sales increase is attributable to losses incurred by other brands in the same category (i.e., they lose 33 units).Thus, secondary demand effects account for a far smaller percent of the unit sales promotion effect than has been inferred from elasticity decomposition results.We find that the difference is due to the manner in which the two decomposition measures deal with the category expansion that occurs during a promotion.One interpretation is that the elasticity decomposition yields a gross measure of brand switching, in the sense that category sales are held constant.The unit sales decomposition yields a net measure of brand switching: it accommodates the category expansion effect that applies to both promoted and nonpromoted brands in the models.

Explaining competitive reaction effects

Changes in promotional expenditure decisions for a brand, as in other marketing decisions, should be based on the expected impact on purchase and consumption behavior as well as on the likely reactions by competitors. Purchase behavior may be predicted from estimated demand functions. Competitive reactions can be anticipated based on estimated reaction functions, which show how changes in an instrument for one brand depend on changes in one or more instruments for other brands. Economic and other arguments suggest that the parameters of such reaction functions (e.g. reaction elasticities) should exhibit systematic patterns. We consider these parameters in an economic framework that also contains two other useful measures, viz. net- and gross demand elasticities. For a defender, the net demand elasticity is the difference between the (positive) demand effect of a reaction (the competitive reaction elasticity multiplied by the corresponding own-brand demand elasticity) and the (negative) cross-brand effect (cross-brand demand elasticity). The gross demand elasticity captures just the (positive) demand effect of the reaction. Net demand-, gross demand- and reaction elasticities are useful yardsticks for managers. Our empirical results suggest that managers' competitive reactions do take into account the consumer response to cross-brand and own-brand activities. For example, the greater a cross-brand elasticity, the greater the corresponding reaction elasticity. Similarly, the greater the own-brand elasticity, the smaller the corresponding reaction elasticity. These effects are consistent with managerial behavior that aims to preserve market shares. We also find that the frequency of changes in other brands' marketing variables has a negative impact on competitive reactions. Interestingly, we do not find that average within-firm competitive reaction elasticities are smaller than for brands offered by different firms. However, we do find that for one firm, this reaction incidence is far lower for sister brands (presumably due to the use of category management), while for another firm, this incidence is higher relative to non-sister brands, consistent with expectations derived from personal interviews of all brand managers. The latter result suggests that the characteristics of reward or resource allocation systems may influence the competitive intensity between managers in the same firm. (C) 2001 Elsevier Science B.V. All rights reserved

Models for Marketing Decisions: Postcriptum

2nonenoneP. LEEFLANG; WITTINK D.RLeeflang, Pieters; Wittink, D. R