Cross-category Effects Research Articles

Healthy foods, healthy sales? Cross-category effects of a loyalty program promoting sales of fruit and vegetables

Globally, consumption of Fruit and Vegetables (F&V) remains below nutritional guidelines. With retailers accounting for a large portion of F&V sales, marketing can be key to increase F&V consumption at household level. However, a key challenge is the design of strategies that benefit retailers, e.g., improving loyalty, whilst promoting societal goals. This study evaluates a points-plus-cash loyalty program where participants received points by purchasing selected F&V, redeemable against a reward (plush toys in the shape of F&V). We estimate the impact of the program by comparing expenditures in several categories before, during, and after the promotional period, across two different years, and comparing consumers who redeemed a reward and those who did not. We use loyalty card data from a Croatian retailer, containing food expenditure in five categories for 268,359 consumers, over 27 weeks for 2 years. We find that the loyalty program increased F&V expenditures at the focal retailer during the promotional period. However, the increase was only for reward-redeemers, for whom the program increased expenditures in F&V as well as in other food categories. This effect persisted – at a declining rate – after the program stopped. Exposure only had a limited effect during the campaign, leading to a reduction in expenditure after the promotional period. Results indicate that a loyalty program promoting sales of F&V can create win-win benefits to both society and the retailer: it increases expenditures on healthy foods (F&V), while improving overall loyalty (i.e., expenditures) to the retailer amongst motivated consumers.

Recommendations for Investigating the Cross-Category Effect Among Hispanic and Latino Populations

Individuals who are Hispanic or Latino make up a substantial portion of the U.S. and world population yet are vastly underrepresented as both participants and stimuli in the face-perception literature. Perceiving and recognizing faces are critical components of everyday social interactions, but cross-category effects (difficulty recognizing faces from other races or ethnicities) can hinder social interactions. Cross-category effects are the most commonly studied face-perception topic with these ethnic groups, but this empirical knowledge should be expanded via culturally relevant considerations. In this article, I describe (a) errors individuals display when categorizing target faces, (b) how social status influences identity and cross-category effects, (c) the potential impact of flexible and heterogeneous social identities on face processing, (d) a critical need for more developmental research, and (e) methodological expansions and generalizability concerns. Thus, I propose important directions for future studies to address these issues and advance knowledge in the field.

Brand Network Analysis for Identifying Co-Branding and Extension Opportunities

The use of co-branding and brand extension strategies, as a way to gain access to new markets and improve overall brand salience, has grown tremendously in the past few decades. Despite the continued success of alliances between brands belonging to diverse categories, there is surprisingly little research on identifying broader cross-category effects using current digital approaches. In our work, we introduce a new, scalable approach for inferring cross-category branding insights using implicit brand networks on social media. Unlike traditional social networks that involve explicit interaction between the entities, links within a brand network are implicit and arise due to common followership between brands on Twitter. Asymmetry among brand pairs is taken into account to calculate the transcendence of brands onto new categories. Transcendence of a brand along any given category is defined as the extent to which its followers overlap with other brands from that category. Asymmetry is also leveraged to show which brands will benefit more from a cobranding alliance. Overall, the analysis is conducted at different time periods to track shifts in brand transcendence and investigate its impact on co-branding opportunities. All findings are validated against external survey ratings and extensive robustness checks are conducted.

Boundaries of Differentiated Product Markets and Retailer Pricing

This paper studies the effects of misspecified boundaries of competition on optimal retail pricing using store-level supermarket scanner data. We focus on two types of misspecification: (i) misspecification of the demand estimation problem, which can arise from either defining the product market to be too narrow or specifying an overly restrictive model of demand; (ii) misspecification of the retailer's decision problem, which can arise from the retailer separately optimizing prices in each category but failing to account for, and thus internalize, cross-category effects. Both sources of misspecification are relevant in differentiated product markets where goods are broadly related but in ways that may not be immediately a priori. Quantifying the costs associated with either form of misspecification is challenging because it requires a flexible yet valid demand system. To this end, we take a nonparametric approach to estimating a multi-category demand system that imposes minimal restrictions on the sign/magnitude of cross-price effects and also satisfies key properties required by economic theory. Our first set of empirical results is descriptive. We use data across nine diverse product groups to show that cross-category effects exists and are often nuanced in their sign and magnitude. That is, many categories are neither obvious substitutes' nor obvious We then zoom in on refrigerated juices and estimate demand nonparametrically across five juice categories where we find empirical support for a flexible model that can accommodate both substitutes and complements. We solve for optimal prices under both sources of misspecification and estimate profit losses to be in the 5-15% range.

점포 내 쇼핑객의 동적 구매 의사결정에 의해 구매된 제품 카테고리 유형간 교차효과가 장바구니 크기에 미치는 영향

점포 내 쇼핑객의 동적 구매 의사결정에 의해 구매된 제품 카테고리 유형간 교차효과가 장바구니 크기에 미치는 영향

Pricing of demand-related products: Can ignoring cross-category effect be a smart choice?

This paper studies pricing strategies of competing retailers offering substitutable products in multiple product categories. For such retailers, in addition to accounting for within-category pricing effects, cross-category effects can also influence consumers’ purchase decisions and thereby impact the retailers’ optimal pricing strategies. We model consumers’ utility for purchasing substitutable products from the same category and from other categories as well. We then solve a game-theoretic model to identify the retailers’ optimal prices and profits. Our results show that accounting for cross-category effects largely influences the retailers’ pricing and profitability. In particular, cross-category effects influence the sensitivity of prices to within-category substitution levels. While cross-category effects have an impact on retailers’ equilibrium strategies, this effect is only relevant when within-category substitution effects are present. We also find that intentionally ignoring cross-category effects leads to lower prices for categories that are either substitutable or highly complementary, and to higher prices otherwise. When not accounting for the fact that the two categories are demand-related implies lower prices than when this information is accounted for, then at least one retailer chooses to disregard the cross-category effect at equilibrium. Finally, we find evidence for prisoner’s dilemma situations where both retailers ignore cross-category effect at equilibrium while accounting for it would yield them higher profits.

Selling Smokes or Smoking Sales: Investigating the Consequences of Ending Tobacco Sales

We measure the cross-category spillover effects of a retailer changing its assortment at the extensive margin (by dropping an entire category from its portfolio) on the outcomes for its rivals in the industry.By leveraging the quasi-experimental nature of the exit by a national pharmacy chain, hereinafter referred to as the Exiting Chain (EC) from the tobacco category, we measure the effects of this event on the revenue generated by non-tobacco products at rival pharmacy chains. We show, using Nielsen RMS data, that for each 1% increase of cigarettes sales in non-EC stores that are located near an“exiting” EC store relative to those non-EC drugstores that are not, the revenue generated by non-tobacco products grows by 0.04%. Next, using Nielsen Homescan panel data, we try to uncover the mechanism underlying this spillover by looking at how the behavior of smokers and non-smokers at EC stores is affected by the decision. We find that the frequency of trips to the exiting stores that included some tobacco product was negatively affected, suggesting that tobacco was one of the main drivers of store patronage for those trips. For non-smokers, we find that they react to EC’s action by increasing the frequency of trips to the exiting chain. However, the gains from non-smokers does not seem to outweigh losses due to smokers. To assess the generalizability of our results, we analyze the impact of a set of tobacco bans imposed by municipalities in Massachusetts and find cross-category loss patterns for drug stores in those areas that are similar to the gains to rival stores from EC’s exit.

Multiclass Vector Auto-Regressive Models for Multistore Sales Data

SummaryRetailers use the vector auto-regressive (VAR) model as a standard tool to estimate the effects of prices, promotions and sales in one product category on the sales of another product category. Besides, these price, promotion and sales data are available not just for one store, but for a whole chain of stores. We propose to study cross-category effects by using a multiclass VAR model: we jointly estimate cross-category effects for several distinct but related VAR models, one for each store. Our methodology encourages effects to be similar across stores, while still allowing for small differences between stores to account for store heterogeneity. Moreover, our estimator is sparse: unimportant effects are estimated as exactly 0, which facilitates the interpretation of the results. A simulation study shows that the multiclass estimator proposed improves estimation accuracy by borrowing strength across classes. Finally, we provide three visual tools showing clustering of stores with similar cross-category effects, networks of product categories and similarity matrices of shared cross-category effects across stores.

Multi-Category Competition and Market Power: A Model of Supermarket Pricing

In many competitive settings consumers buy multiple product categories, and some prefer to use a single firm, generating complementary cross-category price effects. To study pricing in supermarkets, an organizational form where these effects are internalized, we develop a multi-category multi-seller demand model and estimate it using UK consumer data. This class of model is used widely in theoretical analysis of retail pricing. We quantify cross-category pricing effects and find that internalizing them substantially reduces market power. We find that consumers inclined to one-stop (rather than multi-stop) shopping have a greater pro-competitive impact because they generate relatively large cross-category effects.

Multi-Category Competition and Market Power: A Model of Supermarket Pricing

In many competitive settings, consumers buy multiple product categories, and some prefer to use a single firm, generating complementary cross-category price effects. To study pricing in supermarkets, an organizational form where these effects are internalized, we develop a multi-category, multi-seller demand model and estimate it using UK consumer data. This class of model is used widely in theoretical analysis of retail pricing. We quantify cross-category pricing effects and find that internalizing them substantially reduces market power. We find that consumers inclined to one-stop (rather than multi-stop) shopping have a greater pro-competitive impact because they generate relatively large cross-category effects. (JEL D12, L11, L13, L81)

Multi-Class Vector Autoregressive Models for Multi-Store Sales Data

Retailers use the Vector AutoRegressive (VAR) model as a standard tool to estimate the effects of prices, promotions and sales in one product category on the sales of another product category. Besides, these price, promotion and sales data are available for not just one store, but a whole chain of stores. We propose to study cross-category effects using a multi-class VAR model: we jointly estimate crosscategory effects for several distinct but related VAR models, one for each store. Our methodology encourages effects to be similar across stores, while still allowing for small differences between stores to account for store heterogeneity. Moreover, our estimator is sparse: unimportant effects are estimated as exactly zero, which facilitates the interpretation of the results. A simulation study shows that the proposed multi-class estimator improves estimation accuracy by borrowing strength across classes. Finally, we provide three visual tools showing (i) the clustering of stores on identical cross-category effects, (ii) the networks of product categories and (iii) the similarity matrices of shared cross-category effects across stores.

Satisfaction Spillovers Across Categories

We provide a descriptive study of the cross-category effects of satisfaction with financial services on retention behavior. Behavioral contrast and learning theories provide the bases for our understanding of these effects. Our empirical results reveal the following: (i) Across banking and investment categories, when customers have different providers, satisfaction with one lowers the retention probability in the other service. (ii) A customer who is dissatisfied with the investment service is more likely to stay with the current banking service. (iii) Significantly, we find that when the same firm is involved in both categories, dissatisfaction with the firm in the investment category spills over into the banking category thereby lowering its retention probability. We also find that: (a) among customers who are satisfied with banking (investment), more exposure to media increases retention probability; (b) although switching costs and order of acquisition affect retention, they do not show cross-category interactions with satisfaction. We then obtain implications for customer lifetime value (CLV) and show that it can increase satisfaction by leveraging both the within and across category effects. Bottom line: It is important for a company providing multiple services to measure satisfaction at the category level but to manage customers across categories. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2015.0941 .

Identifying Demand Effects in a Large Network of Product Categories

Planning marketing mix strategies requires retailers to understand within- as well as cross-category demand effects. Most retailers carry products in a large variety of categories, leading to a high number of such demand effects to be estimated. At the same time, we do not expect cross-category effects between all categories. This paper outlines a methodology to estimate a parsimonious product category network without prior constraints on its structure. To do so, sparse estimation of the Vector AutoRegressive Market Response Model is presented. We find that cross-category effects go beyond substitutes and complements, and that categories have asymmetric roles in the product category network. Destination categories are most influential for other product categories, while convenience and occasional categories are most responsive. Routine categories are moderately influential and moderately responsive.

Cross-category effects and private labels

Umbrella effects, or the ability of a brand in one category to generate sales for store brands in other categories, may explain the growth in private labels. We estimate the potential umbrella effects among private label products using a generalised multiple-discrete-continuous extreme value (GMDCEV) model. We find significant positive associations between private label sales in some categories with private label sales in other, related categories. Our results suggest that food retailers would be well-served to develop store brands across categories that are related in either use or production, ‘dairy’ and ‘meat’ private labels, for example, instead of creating uniform umbrella brands as is often the practice.

An Across-Store Analysis of Intrinsic and Extrinsic Cross-Category Effects

An important part of the rapidly growing shopper marketing practice is cross-category retail management. In managing two related product categories, retailers face some important questions: Which category should be stocked more? How close to each other should they be stocked in the store (aisle adjacency)? Which category should be promoted more often? And when should the two categories be sold as a bundle? To address these questions, we examine how purchases of related product and subproduct categories influence one another, and how the relative aisle locations of two related product categories influence their respective purchases. We consider both extrinsic (aisle location-based) and intrinsic (affinity-based) cross-category effects. Using aggregate store level data together with store descriptor and store shopper demographic data, we estimate a simultaneous system of models for two related product categories, soft drinks and salty snacks. We also estimate a system of salty snack subcategory purchase models. We find that both extrinsic and intrinsic cross-category effects are asymmetric, that is, different categories and subcategories have different effects on one another. We discuss the theoretical and managerial implications of these findings.

A Multicategory Model of Consumers' Purchase Incidence, Quantity, and Brand Choice Decisions: Methodological Issues and Implications on Promotional Decisions

The authors propose a multicategory model of consumers' purchase incidence, quantity, and brand choice decisions. The model specification allows for cross-category promotion effects in both components of the primary demand (incidence and quantity decisions) and uses a flexible functional form of consumer's utility to accurately measure those cross-category effects. To demonstrate the importance of the methodology, the authors investigate two issues of relevance to retailers, namely, how retailers should (1) allocate promotional expenditures across brands in a category and (2) coordinate timing of promotions of brands across categories. The authors estimate the proposed model using consumers' purchases in pasta sauce and pasta categories. The results reveal that using restrictive functional forms of utilities or ignoring cross-category effects in incidence and quantity decisions leads to incorrect assessments on relative allocation of promotional expenditures across brands. Furthermore, retailers are better off contemporaneously promoting brands across the two categories than promoting them in different periods, and ignoring cross-category effects in quantity decisions leads to the opposite inference, namely, that retailers are better off promoting brands across the two categories in different periods.

Variable selection for market basket analysis

Results on cross category effects obtained by explanatory market basket analyses may be biased as studies typically investigate only a small fraction of the retail assortment (Chib et al. in Advances in econometrics, vol 16. Econometric models in marketing. JAI, Amsterdam, pp 57–92, 2002). We use Bayesian variable selection techniques to determine significant cross category effects in a multivariate logit model. Hence, we achieve a reduction of coefficients to be estimated which decreases computation time heavily and thus allows to consider more product categories than most previous studies. Next to the extension of numbers of categories, the second purpose of this paper is to learn about the capabilities of different variable selection algorithms in the context of market basket analysis. We present three different approaches to variable selection and find that an adaptation of a technique by Geweke (Contemporary Bayesian econometrics and statistics. Wiley, Hoboken, 2005) meets the requirements of market basket analysis best, namely high numbers of observations and cross category effects. For a real data set, we show (1) that only a moderate fraction of possible cross category effects are significantly different from zero (one third for our data), (2) that most of these effects indicate complementarity and (3) that the number of considered product categories influences significances of cross category effects.

Modeling Dependencies in Brand Choice Outcomes Across Complementary Categories

We build an econometric model of a household's contemporaneous brand choice outcomes in complementary product categories. This model explicitly captures cross-category dependencies in brand choice outcomes of a household. Such dependencies have not been modeled in existing multi-category demand models.Our model accommodates cross-category dependencies that arise on account of three component effects: (1) complementarity due to the additional utility that a household derives from the joint purchase of brands in complementary categories, (2) marketing spillovers due to the effects of brands’ prices in one category affecting the households’ latent utilities for brands in the complementary category, (3) unobserved dependencies due to correlations in households’ latent utilities for brands across categories.We estimate our proposed multi-category brand choice model using scanner panel data on cake mix and frosting categories. We find that complementarity accounts for the vast majority of the estimated cross-category effects in demand. We also find that as much as 55 percent of the total retail profit impact of price promotions arise on account of brand-level (focus of our study), as opposed to category-level (focus of previous studies), dependencies in household demand. Finally, we propose an easily interpretable visual representation – Largess and Free-Ride Plot – of cross-category price elasticities that summarizes the differential abilities of brands to influence, or be influenced by, brands in the complementary category.

Cross-category demand effects of price promotions.

Do promotions in a certain category lead to higher revenues in other categories? If so, to what degree? The answers to these questions are highly relevant for retailers that supply products in different categories. Empirical findings in studies that consider a limited number of categories indicate small promotional cross-category effects. This study develops a framework to determine the impact of price promotions on category revenues that include interdependencies among a substantial number of categories at the category demand level. The own- and cross-category demand effects are moderated by variables such as promotion intensity, category characteristics (own-category effects), and spatial distances between shelf locations (cross-category effects). The empirical results based on daily store-level scanner data show that approximately half of all price promotions expand own-category revenues, especially for categories with deeper supported discounts. There is a high probability (61%) that a price promotion affects sales of at least one other category. The number of categories affected is not greater than two. Moderate evidence supports the existence of cross-promotional effects between categories more closely located in a store.

A cross-category investigation into the effects of nine-ending pricing on brand choice

Retailers largely adopt nine-ending prices and these prices have attracted greater attention from researchers in marketing. Despite this increased interest, very few empirical studies have tried to quantify the effects of nine-ending prices on consumer actual behaviors. Those who have studied the behavioral effects of nine-ending prices have produced mixed findings. In this article, we investigated the cross-category effects of nine-ending pricing on consumer brand choice at the SKU level. We distinguished between different types of nine-ending while controlling for the rounded prices and other marketing-mix variables. We conducted our analysis on over 11,000 SKUs in 102 product categories of two (2) grocery retailers. We find that the effects of 99 ending prices on the SKU's category choice are larger in concentrated and promotional categories but smaller in expensive categories. However, their influence on purchase quantity is larger in expensive categories but smaller in concentrated categories.