Exploiting the Installed Base Using Cross-Merchandising and Category Destination Programs

We investigate two ways to increase sales and customer loyalty by taking advantage of a store\u27s installed base of current customers. We propose a classification of products into two types. Products of Type 1 are products for which consumers have a loyalty to a specific retailer and, as far as possible, always shop at that retailer for these products. The other products (Type 2) are not associated with any retailer and are bought at whichever retailer consumers happen to shop when they plan or remember to buy the product. With this in mind, we test the potential of two marketing tools to help retailers increase their share of sales of the Type 2 segment. Using a category destination program we show that one can successfully transform Type 2 into Type 1 products. Using cross-merchandising promotions, we show that one can increase the sales of Type 2 products thereby gaining a larger share of discretionary purchases than what one would receive from a straight random allocation. Both series of tests yielded significant increases in sales and profits and were deemed successful by the retailers who implemented them

Recurring Goals and Learning: The Impact of Successful Reward Attainment on Purchase Behavior

People often strive for an identical goal (e.g., rewards offered in loyalty programs), what we refer to as recurring goals. Extant research has documented post-reward resetting i.e., a slowdown in the inter-purchase time between earning the first reward and making the first purchase toward the second reward. This research shows how consumers do not reset fully; the inter-purchase time increases after a successful completion, but it does not increase to its previous level. Partial post-reward resetting occurs because people learn about their own ability to reach the reward. Hence, successful completions increase subsequent engagements, purchase rates, and task completion

Shelf Management and Space Elasticity

Shelf management is a difficult task in which rules of thumb rather than good theory and hard evidence tend to guide practice. Through a series of field experiments, we measured the effectiveness of two shelf management techniques: “space-to-movement,” where we customized shelf sets based on store-specific movement patterns; and “product reorganization” where we manipulated product placement to facilitate cross-category merchandising or ease of shopping. We found modest gains (4%) in sales and profits from increased customization of shelf sets and 5–6% changes due to shelf reorganization. Using the field experiment data, we modeled the impact of shelf positioning and facing allocations on sales of individual items. We found that location had a large impact on sales, whereas changes in the number of facings allocated to a brand had much less impact as long as a minimum threshold (to avoid out-of-stocks) was maintained

Do Consumers Really Know if the Price Is Right? Direct Measures of Reference Price and Their Implications For Retailing

authors thank the HEC Foundation for its financial support, and Shantanu Sutta and Gilles Reference price research suggests that consumers memorize and recall price information when selecting brands for frequently purchased products. In this study, we show that previous priceknowledge surveys provided imperfect estimates of reference price. Further, we propose to use a combination of price recall, price recognition, and deal recognition to measure the degree to which consumers use auditory verbal, visual Arabic, or analogue magnitude representations to memorize prices. In addition we identify consumer and product characteristics that explain the variations in price knowledge. 2 There exists a large body of empirical evidence showing that, when making brand choices for packaged consumer goods, consumers compare observed prices to so-called reference prices they supposedly have in memory (cf., Winer 1986, or Kalyanaram and Winer 1995 for a review). Different models of reference price have been validated in the past and, in a comparison of the most common model formulations, Briesch et al. (1997) found that the best performing model is one that includes brand-specific reference prices, represented as a moving average of the pric

Real-Time Evaluation of E-mail Campaign Performance

We develop a testing methodology that can be used to predict the performance of e-mail marketing campaigns in real time. We propose a split-hazard model that makes use of a time transformation (a concept we call virtual time) to allow for the estimation of straightforward parametric hazard functions and generate early predictions of an individual campaign's performance (as measured by open and click propensities). We apply this pretesting methodology to 25 e-mail campaigns and find that the method is able to produce in an hour and fifteen minutes estimates that are more accurate and more reliable than those that the traditional method (doubling time) produces after 14 hours. Other benefits of our method are that we make testing independent of the time of day and we produce meaningful confidence intervals. Thus, our methodology can be used not only for testing purposes, but also for live monitoring. The testing procedure is coupled with a formal decision theoretic framework to generate a sequential testing procedure useful for the real time evaluation of campaigns.database marketing, e-mail, pretesting, advertising campaigns

Measuring the price knowledge shoppers bring to the store

Reference price research suggests that consumers memorize and recall price information when selecting brands for frequently purchased products. Previous price-knowledge surveys, however, indicate that memory for prices is lower than expected. In this study, we show that these priceknowledge surveys actually provided imperfect estimates of price knowledge because they focused only on recall and short-term memory. We propose, instead, to use a combination of price recall, price recognition, and deal recognition to measure the degree to which consumers use auditory verbal, visual Arabic, or analogue magnitude representations to memorize prices. We show how the combination of these three measures provides a much richer understanding of consumer’s knowledge of prices. Our results suggest that the price knowledge involved in reference prices may often not be accessible to recall but shows up in price recognition and deal recognition. In addition we identify consumer and product characteristics that explain the variations in price knowledge. We find, for instance, that frequent promotions increase the ability of consumers to remember regular prices and that store switchers do not possess a better price knowledge than other shoppers. Consumers have a strong interest in keeping a knowledge base of prices for products the