Minakshi Trivedi

Using variety-seeking-based segmentation to study promotional response

The link between variety seeking and promotional response has been of interest to marketing researchers for quite some time. By segmenting consumers according to their variety-seeking needs, researchers have established some interesting results regarding the variation in promotional response across segments. However, the sole basis for segmentation thus far has been unidimensional (e.g., high-and low-variety seekers). This research discusses a unique way to segment consumers based not only on the usual extent (or mean) of variety seeking but also on the intensity (or consistency) of variety-seeking behavior, a new segmentation criterion. The authors conduct an empirical study to test the two-dimensional segmentation scheme and investigate differences in response to a variety of promotions across the segments. The inclusion of the intensity aspect of variety seeking as an additional basis for segmentation has a significant impact on promotional response and offers substantially richer managerial interpretation.

Promotional evaluation and response among variety seeking segments

Research conducted over the last decade, on the influence of brand inertia or variety seeking on promotional response, has yielded mixed results. Variety seekers have been found to be more price‐sensitive by one set of researchers, while another stream of work finds them to be less sensitive. Reconciling the two findings, the current study empirically addresses the proposition that variety seekers use price promotions strategically, as a way to experiment with different brands over time. Although consumers evaluate price promotions differently according to whether the promoted brand is more or less intrinsically favored than a reference brand, high and low variety seekers respond to brand comparisons differently, leading to differences in evaluation and responsiveness to price promotion offers. The empirical results confirm that high variety seekers are less sensitive to the preference order of considered brands, but only within a limited range of intrinsic brand favorability. Once differences in brand favorability are accounted for, moreover, finds that high variety seekers are more sensitive to promotional effort. This is compatible with the notion that, within an acceptable set of brands, variety seekers use price promotions as a low‐cost strategy for experiencing different brands over time. This understanding of the relationship among promotional offers, specific brands and consumer segments, provides valuable insights to brand managers as they consider their strategic promotional options, and design an effective promotional strategy.

Investigating the Drivers of Consumer Cross-Category Learning for New Products Using Multiple Data Sets

Consumer new product adoption and preference evolution or learning may be influenced by intrinsic or internal factors (e.g., usage experiences, personal characteristics), external influences (e.g., social effects, media), and marketing activities of the firm. Moreover, the preference evolution in a certain category can spill over to other categories; i.e., consumers can exhibit cross-category learning. In this paper, we develop a multicategory framework to analyze the role of the above elements in the formation and evolution of consumer preferences across categories. We analyze these elements by employing multiple data sets, i.e., by combining revealed preference data (from scanner panel), stated data (from surveys measuring consumer lifestyle variables and demographics), and external influences (e.g., media mentions) in a completely heterogeneous framework while considering other facets of the learning process. By jointly estimating the model for organic purchases in six distinct food categories, we also explore the role of category differences. Results show that consumer new product adoption and learning is indeed impacted significantly and to various degrees by the aforementioned factors. We show how, by selectively encouraging purchases under various scenarios, firms can accelerate the learning process, not only for the focal category but also for other categories, thereby realizing considerable incremental profits. These results can be used by both manufacturers and retailers for more efficient allocation of marketing budgets across (new) products.

Brand‐specific heterogeneity and market‐level brand switching

Provides a new way to look at competitive brand strategy through analysis of switching, where the only data required are market‐level brand‐switching matrices. The parameters indicate, for each brand, the degree to which it insulates itself from competition. Shows empirically that this insulation is characteristic of both market leaders and market nichers. Compares results across eight data sets which range from consumer packaged goods to services to durables. Suggests that, by applying this method to panel or survey data, managers can better map out long‐term marketing strategies such as product design, segment targeting and advertising campaigns, and gives some examples of how this can be carried out.

Service intermediaries: a theoretical modeling framework with an application to travel agents

Purpose – The purpose of this paper is to study the motivations of an agent in a service industry to honestly represent the quality of a service provider.Design/methodology/approach – The paper develops a theoretical modeling and derives implications from it, which are then tested using empirical data.Findings – The main finding of the paper is that the agents propensity to overstate the service providers true quality level increases as the relative price of the service increases.Research limitations/implications – The testable implications are tested in the hotel industry. One could extend this to alternative services. It should be noted, however, that since the modeling framework is general, so too will be the implications that arise from it.Originality/value – The theoretical development in the paper from which the implications arise, gives the results a strong foundation and lends some validity to the work. This is complemented by a unique data set that supplies information from the agent as well as...

Consumer's value for informational role of agent in service industry

Purpose – The purpose of this paper is to study the informational role played by an intermediary in the service industry.Design/methodology/approach – The paper used survey and choice data collected from agents and customers, respectively, in the hotel industry.Findings – The paper shows that informational role of agents in choice varies from mere facilitation of the transaction (e.g. making reservation) to a more active role involving accurate predictions about attributes that consumers will perceive important, more realistic performance evaluation of choice options and providing information about experience attributes. The results also show how an agents role depends on customers prior knowledge about the choice options, the goal underlying service consumption (e.g. business vs vacation travel), benefits sought by the consumer and the agents perception about a long term relationship with the consumer. Finally, the results also reveal a unique pattern of differences between agents and consumers in the...

A cointegration analysis of demand: implications for pricing

The use of modeling and statistics for the design and development of pricing strategy is prevalent in academia as well as the industry. One of the more commonly used tools by researchers and managers alike for the estimation of linear demand models is the ordinary least squares (OLS) regression. Unfortunately, a majority of data sets to which such models are applied suffer from nonstationarity ‐ that is, the dependence of a variable on its prior values ‐ thereby violating the assumptions of a basic (naive) regression model. Estimates of variables under these conditions are known commonly to be inflated and inaccurate. While this problem is well‐known and can be corrected for among statisticians and econometricians, a simple and effective tool has not yet been designed for managers ‐ the actual users of such models. Studies some of the problems encountered when using a naive model and proposes a simple method to check for nonstationarity and redesign the model to account for the same. Using scanner data on soup, shows that the redesigned model predicts better, fits better and offers more meaningful results. Finally, looks at the implications of estimating such models for pricing strategies and issues. Surface response analysis shows how a manager can use such models for conducting insightful studies on price sensitivity.

Measuring the Efficiency of Category-Level Sales Response to Promotions

In this study, we focus on measuring the efficiency of category-level sales response to promotions across various categories and stores. Our heterogeneous stochastic frontier model allows us to attribute portions of this efficiency to specific characteristics of the stores and categories. Using our full PEM (promotional efficiency frontier) model, we analyze the efficiency of 20 frequently bought categories of a supermarket retailer and apply it to store-category-level data. We find that the average efficiency of category and store sales response across all categories and stores is 84.34%, with low values in categories such as spreads and fresh seafood and high values in categories such as frozen entrees and meat. We find that the variation in efficiency of this sales response can be attributed to specific store and category characteristics such as selling area of store, distance to competition, number of stock-keeping units in the category, and average interpurchase time. Unobserved heterogeneity is capt...

The Effects of Multichannel Shopping on Customer Spending, Customer Visit Frequency, and Customer Profitability

Multichannel strategy—in which firms offer their products or services using multiple outlets—gives firms an opportunity to tap into their broader customer base while also enhancing their shopping convenience. In this study, we investigate the antecedents of multichannel shoppers using both actual and stated behavioral data. Furthermore, we quantify the consequences of multichannel shopping along three dimensions: customer spending, customer visit frequency, and customer profitability. Our results suggest that customer-intrinsic factors have a significant effect on multichannel shoppers with customers’ technical expertise and internet service adoption having a positive impact, and deal sensitivity and shopping experience having a negative impact on multichannel adoption. Furthermore, multichannel shopping has significant positive effects on customer spending, customer visit frequency, and customer profitability. Our results provide a better understanding of customers’ multichannel shopping behavior along the stated dimensions that can be used for effective multichannel decision making by firms.