Gary J. Russell

Measuring Brand Value with Scanner Data

Using actual consumer choice data from a single-source scanner panel, we construct two measures of brand value which capture different aspects of brand equity. Brand Value measures perceived quality, the value assigned by consumers to the brand, after discounting for current price and recent advertising exposures. Brand Intangible Value isolates the component of brand value which cannot be directly attributed to the physical product, thus measuring the value created by such factors as brand name associations and perceptual distortions. We illustrate these measures in a study of the powder laundry detergent category and briefly relate the results to strategic variables (order of entry and cumulative advertising expenditures).

Nutrition Information in the Supermarket

Lists of nutrition information posted in supermarkets were designed to reduce the information-processing costs of comparing alternative foods. In Experiment 1, lists of vitamins and minerals increased nutrition knowledge but had no influence on actual purchases. In Experiment 2, a list of added sugar—a negative component of food—increased the market share of low-sugar breakfast cereals at the expense of high-sugar brands. We conclude that effort-reducing displays are a successful technique for increasing information use, especially for the more highly valued negative nutrients.

Analysis of cross category dependence in market basket selection

Abstract Market basket choice is a decision process in which a consumer selects items from a number of product categories on the same shopping trip. The key feature of market basket choice is the interdependence in demand relationships across the items in the final basket. This research develops a new approach to the specification of market basket models that allows a choice model for a basket of goods to be constructed using a set of “local” conditional choice models corresponding to each item in the basket. The approach yields a parsimonious market basket model that allows for any type of demand relationship across product categories (complementarity, independence, or substitution) and can be estimated using simple modifications of standard multinomial logit software. We analyze the choice of four grocery store categories that exhibit common cross-category brand names for both national brands and private labels. Results indicate that cross-category price elasticities are small. We argue that store traffic patterns may be more important than consumer-level demand interdependence in forecasting market basket choice.

Multiple-Category Decision-Making: Review and Synthesis

In many purchase environments, consumers use information from a number of product categories prior to making a decision. These purchase situations create dependencies in choice outcomes across categories. As such, these decision problems cannot be easily modeled using the single-category, single-choice paradigm commonly used by researchers in marketing. We outline a conceptual framework for categorization, and then discuss three types of cross-category dependence: cross-category consideration cross-category learning, and product bundling. We argue that the key to modeling choice dependence across categories is knowledge of the goals driving consumer behavior.

Modeling Multiple Category Brand Preference with Household Basket Data

Household basket data contain important information about the structure of brand preferences both within and across product categories. This research exploits the information in long-run basket summary data to segment consumers with respect to brand preferences. The approach provides insights into the competitive structure of brands within each product category and identifies potential synergies across product categories. The model is applied in an analysis of retailer and national brand name preferences for four paper goods categories. We discuss implications for joint promotion, product bundling and product assortment decisions.

Predicting Product Purchase from Inferred Customer Similarity: An Autologistic Model Approach

Product recommendation models are key tools in customer relationship management (CRM). This study develops a product recommendation model based on the principle that customer preference similarity stemming from prior purchase behavior is a key element in predicting current product purchase. The proposed recommendation model is dependent on two complementary methodologies: joint space mapping (placing customers and products on the same psychological map) and spatial choice modeling (allowing observed choices to be correlated across customers). Using a joint space map based on past purchase behavior, a predictive model is calibrated in which the probability of product purchase depends on the customers relative distance to other customers on the map. An empirical study demonstrates that the proposed approach provides excellent forecasts relative to benchmark models for a customer database provided by an insurance firm.

Inferring Market Structure from Customer Response to Competing and Complementary Products

We consider customer influences on market structure, arguing that market structure should explain the extent to which any given set of market offerings are substitutes or complements. We describe recent additions to the market structure analysis literature and identify promising directions for new research in market structure analysis. Impressive advances in data collection, statistical methodology and information technology provide unique opportunities for researchers to build market structure tools that can assist “real-time” marketing decision-making.

Perspectives on Multiple Category Choice

Multiple category choice is a decision process in which an individualselects a number of goods, all of which are nonsubstitutable with respect toconsumption. Choices can be made either simultaneously or sequentially. Thekey feature of multiple category choice is the treatment of the choices asinterrelated because each item in the final collection of goods contributesto the achievement of a common behavioral goal. We discuss current andpotential applications of psychology, economics and consumer choice theoryin developing models of multiple category choice.

A model of latent symmetry in cross price elasticities

This paper develops the Latent Symmetric Elasticity Structure (LSES), a market share price elasticity model which allows elasticities to be decomposed into two components: a symmetric substitution index revealing the strength of competition between brand pairs, and a brand-specific coefficient revealing the overall impact of a brand on its competitors. An application of the model to unconstrained cross price elasticities shows that brand-price competition in one market is well-represented by a LSES model in which brand substitutability and elasticity asymmetry are related to average price level.

Identifying multiple preference segments from own- and cross-price elasticities

The authors develop an approach to decompose a market-level matrix of own- and cross-price elasticities to reveal potentially overlapping preference segments. The approach is grounded on the premise that markets may be represented by a parsimonious number of relatively homogeneous segments. Market-level elasticities are expressed as functions of segment weights and within-segment market shares. These relationships permit segment weights and within-segment market shares to be estimated from the market-level elasticity matrix and patterns of brand substitutability to be analyzed. The approach is illustrated with data on the grocery coffee category.