Scott A. Neslin

Pursuing the Value-Conscious Consumer: Store Brands Versus National Brand Promotions

The objective of this article is to determine whether national brand promotions and store brands attract the same value-conscious consumers, which would aggravate channel conflict between manufacturers and retailers. The authors identify psychographic and demographic traits that potentially drive usage of store brands and national brand promotions. They then develop a framework and structural equation model to study the association of these traits with store brand and national brand promotion usage. The authors find that though demographics do not influence these behaviors directly, they have significant associations with psychographic characteristics and therefore are useful for market targeting. Most important, usage of store brands and usage of promotions, particularly out-of-store promotions, are associated with different psychographics. Store brand use correlates mainly with traits related to economic benefits and costs, whereas the use of out-of-store promotions is associated mainly with traits related to hedonic benefits and costs. These differences result in four well-defined and identifiable consumer segments: deal-focused consumers, store brand–focused consumers, deal and store brand users (use-all), and nonusers of both store brands and deals (use-none). Therefore, manufacturers and retailers have the opportunity to either avoid each other or compete head to head, depending on which segment they target.

Revenue Premium as an Outcome Measure of Brand Equity

The authors propose that the revenue premium a brand generates compared with that of a private label product is a simple, objective, and managerially useful product-market measure of brand equity. The authors provide the conceptual basis for the measure, compute it for brands in several packaged goods categories, and test its validity. The empirical analysis shows that the measure is reliable and reflects real changes in brand health over time. It correlates well with other equity measures, and the measures association with a brands advertising and promotion activity, price sensitivity, and perceived category risk is consistent with theory.

Challenges and Opportunities in Multichannel Customer Management

Multichannel customer management is the design, deployment, coordination, and evaluation of channels through which firms and customers interact, with the goal of enhancing customer value through effective customer acquisition, retention, and development. The authors identify five major challenges practitioners must address to manage the multichannel environment more effectively: (a) data integration, (b) understanding consumer behavior, (c) channel evaluation, (d) allocation of resources across channels, and (e) coordination of channel strategies. The authors also propose a framework that shows the linkages among these challenges and provides a means to conceptualize the field of multichannel customer management. A review of academic research reveals that this field has experienced significant research growth, but the growth has not been distributed evenly across the five major challenges. The authors discuss what has been learned to date and identify emerging generalizations as appropriate. They conclude with a summary of where the research-generated knowledge base stands on several issues pertaining to the five challenges.

Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models

This article provides a descriptive analysis of how methodological factors contribute to the accuracy of customer churn predictive models. The study is based on a tournament in which both academics and practitioners downloaded data from a publicly available Web site, estimated a model, and made predictions on two validation databases. The results suggest several important findings. First, methods do matter. The differences observed in predictive accuracy across submissions could change the profitability of a churn management campaign by hundreds of thousands of dollars. Second, models have staying power. They suffer very little decrease in performance if they are used to predict churn for a database compiled three months after the calibration data. Third, researchers use a variety of modeling “approaches,” characterized by variables such as estimation technique, variable selection procedure, number of variables included, and time allocated to steps in the model-building process. The authors find important differences in performance among these approaches and discuss implications for both researchers and practitioners.

The Role of Retail Promotion in Determining Future Brand Loyalty: Its Effect on Purchase Event Feedback

Abstract We model and estimate the role of retail promotion in determining future brand loyalty through its effect on purchase event feedback. Purchase event feedback represents the effect of current purchases on future brand preference. Our model assesses the extent to which purchases made under a retail promotion enhance or detract from the level of feedback, compared to nonpromotion purchases. We apply the model to two product categories and compare the effects of price versus nonprice retail promotions. We find that in-store price promotions are associated with negative purchase event feedback compared to nonpromotion purchases, whereas nonprice promotions such as features or sampling have no effect or in fact are associated with positive purchase event feedback, compared to purchases made off promotion.

Market Response to a Major Policy Change in the Marketing Mix: Learning from Procter & Gamble’s Value Pricing Strategy

Much research has focused on how consumers and competitors respond to short-term changes in advertising and promotion. In contrast, the authors use Procter & Gambles (P&Gs) value pricing strategy as an opportunity to study consumer and competitor response to a major, sustained change in marketing-mix strategy. They compile data across 24 categories in which P&G has a significant market share, covering the period from 1990 to 1996, during which P&G instituted major cuts in deals and coupons and substantial increases in advertising. The authors estimate an econometric model to trace how consumers and competitors react to such changes. For the average brand, the authors find that deals and coupons increase market penetration and surprisingly have little impact on customer retention as measured by share-of-category requirements and category usage. For the average brand, advertising works primarily by increasing penetration, but its effect is weaker than that of promotion. The authors find that competitor response is related to how strongly the competitors market share is affected by the change in marketing mix and the competitors own response and to structural factors such as market share position and multi-market contact. The net impact of these consumer and competitor responses is a decrease in market share for the company that institutes sustained decreases in promotion coupled with increases in advertising.

The Impact of Brand Equity on Customer Acquisition, Retention, and Profit Margin

The authors investigate the relationships between brand equity and customer acquisition, retention, and profit margin, the key components of customer lifetime value (CLV). They examine a unique database from the U.S. automobile market that combines ten years of acquisition rate, retention rate, and customer profitability data with measures of brand equity from Young & Rubicams Brand Asset Valuator (BAV) over the same period. They hypothesize and find that BAV brand equity is significantly associated with the components of CLV in expected and meaningful ways. For example, customer knowledge of a brand has an especially strong positive relationship with all three components of CLV. Notably, however, differentiation is a double-edged sword. While it is associated with higher customer profitability, it is also associated with lower acquisition and retention rates. The authors also find that marketing efforts exert indirect impacts on CLV through brand equity. Simulations show that changes in marketing, or exogenous changes in brand equity, can exert important effects on CLV. Overall, the findings suggest that the “soft” and “hard” sides of marketing need to be managed in a coordinated way. The authors conclude with a discussion of these and other implications for researchers and practitioners.

Measuring the Impact of Promotions on Brand Switching When Consumers Are Forward- Looking

Logit choice models have been used extensively to study promotion response. This article examines whether brand-switching elasticities derived from these models are overestimated as a result of rational consumer adjustment of purchase timing to coincide with promotion schedules and whether a dynamic structural model can address this bias. Using simulated data, the authors first show that if the structural model is correct, brand-switching elasticities are overestimated by stand-alone logit models. A nested logit model improves the estimates, but not completely. Second, the authors estimate the models on real data. The results indicate that the structural model fits better and produces sensible coefficient estimates. The authors then observe the same pattern in switching elasticities as they do in the simulation. Third, the authors predict sales assuming a 50% increase in promotion frequency. The reduced-form models predict much higher sales levels than does the dynamic structural model. The authors conclude that reduced-form model estimates of brand-switching elasticities can be overstated and that a dynamic structural model is best for addressing the problem. Reduced-form models that include incidence can partially, though not completely, address the issue. The authors discuss the implications for researchers and managers.

Sales promotion: The long and the short of it

This article presents a framework for organizing and discussing how sales promotion affects sales and how to use this framework to delineate major generalizations and to identify issues in need of resolution. This framework consists of data used to measure the sales impact of promotions and the time frame of that impact.

The Determinants of Pre- and Postpromotion Dips in Sales of Frequently Purchased Goods

The authors empirically study the relationships between pre- and post-promotion dips in weekly store data and Universal Product Code (UPC), category, and store trading-area customer characteristics. Drawing on recent advances in econometric modeling, they estimate 39,441 pre- and postpromotion dip elasticities in 83 stores in ten product categories. They relate these elasticities to 24 characteristics, such as UPC price and market share, category budget share and storability, and store trading-area demographics. The authors find that UPC, category, and store trading-area customer characteristics all explain significant variation in the elasticities. For example, both pre- and postpromotion dips are stronger for high-priced, frequently promoted, mature, high-market-share UPCs. They find that postpromotion dips are not significantly different for private labels but are more prominent for UPCs with less predictable promotion patterns. They also find that stores with trading areas that consist of older customers who live in larger households and own cars are particularly prone to postpromotion dips. The findings potentially deepen the understanding of stockpiling and deceleration and blend two trends in promotion response research: an increased focus on pre- and postpromotion effects and a greater emphasis on examination of cross-sectional differences in promotion response.