Competitive Reactions and the Cross-Sales Effects of Advertising and Promotion

How do competitors react to each other's price-promotion and advertising actions? How do these reactions influence the net sales impact we observe? We answer these questions by performing a large-scale empirical study of the short-run and long-run reactions to promotion and advertising shocks in over 400 consumer product categories, over a four-year time span. Competitive reaction can be passive, accommodating or retaliatory. We first develop a series of expectations on the type and intensity of reaction behavior, and on the moderators of this behavior. These expectations are assessed in two ways. First, vector-autoregressive models quantify the short-run and long-run effect of a promotion or advertising action on competitive sales and on competitive reactions. By cataloging the numerical results, we are able to formulate empirical generalizations of reaction behavior ("how do they react?"). Second, we estimate structural models of reaction intensity, in function of various market and competitive characteristics ("what are the drivers of reaction?"). Finally, by comparing our findings on reaction behavior with those on promotion and advertising effectiveness, we are able to evaluate competitive reaction behavior ("are they reacting as they should?"). A major finding is that competitive reaction is predominantly passive. When it is present, it is usually retaliatory in the same instrument, but accommodating or retaliatory in a different instrument. There are very few long-run consequences of any type of reaction behavior. We also report on several moderating effects that are in line with expectations, and that support the presence of a certain amount of rationality in competitive reaction behavior. The net impact of the over-time effects of advertising and price-promotion attacks, competitive reactions and the sales effectiveness of each, is that competitors' sales are generally not affected, and especially not in the long run. We weigh the evidence that this sales neutrality is "natural" (i.e., due to the nature of consumer response) versus "managed" (i.e., due to the vigilance and effectiveness of competitors), and conclude in favor of the former.advertising;competitive reactions;impulse response functions;price promotions

Measuring Short- and Long-run Promotional Effectiveness on Scanner Data Using Persistence Modeling

The use of price promotions to stimulate brand and firm performance is increasing. We discuss how (i) the availability of longer scanner data time series, and (ii) persistence modeling, have lead to greater insights into the dynamic effects of price promotions, as one can now quantify their immediate, short-run, and long-run effectiveness. We review recent methodological developments, and illustrate how the analysis of numerous brands and product categories has resulted in various empirical generalizations. Finally, we argue that persistence modeling should not only be applied to traditional performance metrics such as sales, but also to metrics such as firm value and customer equity.time-series analysis;scanner data;promotional effectiveness;persistence

Measuring Short- and Long-run Promotional Effectiveness on Scanner Data Using Persistence Modeling

The use of price promotions to stimulate brand and firm performance is increasing. We discuss how (i) the availability of longer scanner data time series, and (ii) persistence modeling, have lead to greater insights into the dynamic effects of price promotions, as one can now quantify their immediate, short-run, and long-run effectiveness. We review recent methodological developments, and illustrate how the analysis of numerous brands and product categories has resulted in various empirical generalizations. Finally, we argue that persistence modeling should not only be applied to traditional performance metrics such as sales, but also to metrics such as firm value and customer equity

Competitive Reactions and the Cross-Sales Effects of Advertising and Promotion

How do competitors react to each other's price-promotion and advertising actions? How do these reactions influence the net sales impact we observe? We answer these questions by performing a large-scale empirical study of the short-run and long-run reactions to promotion and advertising shocks in over 400 consumer product categories, over a four-year time span. Competitive reaction can be passive, accommodating or retaliatory. We first develop a series of expectations on the type and intensity of reaction behavior, and on the moderators of this behavior. These expectations are assessed in two ways. First, vector-autoregressive models quantify the short-run and long-run effect of a promotion or advertising action on competitive sales and on competitive reactions. By cataloging the numerical results, we are able to formulate empirical generalizations of reaction behavior ("how do they react?"). Second, we estimate structural models of reaction intensity, in function of various market and competitive characteristics ("what are the drivers of reaction?"). Finally, by comparing our findings on reaction behavior with those on promotion and advertising effectiveness, we are able to evaluate competitive reaction behavior ("are they reacting as they should?"). A major finding is that competitive reaction is predominantly passive. When it is present, it is usually retaliatory in the same instrument, but accommodating or retaliatory in a different instrument. There are very few long-run consequences of any type of reaction behavior. We also report on several moderating effects that are in line with expectations, and that support the presence of a certain amount of rationality in competitive reaction behavior. The net impact of the over-time effects of advertising and price-promotion attacks, competitive reactions and the sales effectiveness of each, is that competitors' sales are generally not affected, and especially not in the long run. We weigh the evidence that this sales neutrality is "natural" (i.e., due to the nature of consumer response) versus "managed" (i.e., due to the vigilance and effectiveness of competitors), and conclude in favor of the former

Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented