Rabikar Chatterjee

A three-stage model of integrated marketing communications at the marketing-sales interface

The marketing and sales functions in many firms are often at odds despite their common goal of increasing revenue and profit. The finger pointing goes both ways: Marketing complains of poor lead follow-up by sales, and in turn, sales grumbles about the quality of leads generated by marketing. This disconnect can be damaging; high lead volumes generated through effective marketing campaigns could actually hurt downstream sales because of wasted effort on poorly qualified leads and/or delays in sales follow-up resulting from limited sales force capacity. To examine the revenue and profit implications of coordinated communications efforts at the marketing-sales interface, the authors develop a three-stage model that captures the effects of sequential marketing/sales communications on lead generation, appointment conversion, and sales closure. The results, which are based on a collaborative effort with a large home improvement retailer, suggest a complex interplay among marketing efforts (multiple media that generate leads), delays in follow-up (time lag between inquiry and sales force contact), and sales efficiencies (appointment and sales conversion). The findings underscore the impact of multimedia spending on the timing and effectiveness of subsequent communications, implying that improved internal collaboration between marketing and sales can offer significant upside potential for the firm. Finally, the authors develop a managerial decision support tool to simulate the impact of varying communications budgets, timing, and allocation on the marketing and sales planning system.

The Name-Your-Own-Price Channel in the Travel Industry: An Analytical Exploration

Name-your-own-price (NYOP) retailers, such as Priceline, offer an alternative distribution channel for service providers in the travel industry such as airlines, hotels, and car rental companies. Our research employs an analytical model to identify and understand key trade-offs driving the decision by a service provider to employ an NYOP channel, assuming that such a channel is available. This decision requires the existence of forces that counteract the adverse consequences of cannibalization of sales through traditional posted-price channels. Our analysis provides some insight into these forces. Contracting with the NYOP retailer facilitates market segmentation and price discrimination, and allows for disposal of excess capacity after meeting business travel demand. However, the cost of this flexibility is that the service provider can no longer credibly precommit to maintaining high prices when there is unsold capacity. Also, when contracting with an independent retailer, the service provider is unable to extract the entire revenue generated from NYOP consumers. A key insight from our model is that the rationale for contracting with an NYOP retailer is driven by the uncertainty in business travel demand, not the expectation of excess capacity. Indeed, all else equal, the larger the capacity, the less likely it is that contracting with an NYOP retailer is the right decision on the part of the service provider.

Strategic Pricing of New Products and Services

This chapter organizes and reviews the literature on new product pricing, with a primary focus on normative models that take a dynamic perspective. Such a perspective is essential in the new product context, given the underlying demandand supply-side dynamics and the need to take a long-term, strategic, view in setting pricing policy. Along with these dynamics, the high levels of uncertainty (for fi rms and customers alike) make the strategic new product pricing decision particularly complex and challenging. Our review of normative models yields key implications that provide (i) theoretical insights into the drivers of dynamic pricing policy for new products and services, and (ii) directional guidance for new product pricing decisions in practice. However, as abstractions of reality, these normative models are limited as practical tools for new product pricing. On the other hand, the new product pricing tools available are primarily helpful for setting specifi c (myopic) prices rather than a dynamic long-term pricing policy. Our review and discussion suggest several areas that offer opportunities for future research.

Accommodating the Effects of Brand Unfamiliarity in the Multidimensional Scaling of Preference Data

This paper presents a multidimensional scaling (MDS) methodology (vector model) for the spatial analysis of preference data that explicitly models the effects of unfamiliarity on evoked preferences. Our objective is to derive a joint space map of brand locations and consumer preference vectors that is free from potential distortion resulting from the analysis of preference data confounded with the effects of consumer-specific brand unfamiliarity. An application based on preference and familiarity ratings for ten luxury car models collected from 240 consumers who intended to buy a luxury car within a designated time frame is presented. The results are compared with those obtained from MDPREF, a popular metric vector MDS model used for the scaling of preference data. In particular, we find that the consumer preference vectors obtained from the proposed methodology are substantially different in orientation from those estimated by the MDPREF model. The implications of the methodology are discussed.

Deriving Ultrametric Tree Structures from Proximity Data Confounded by Differential Stimulus Familiarity.

This paper presents a new procedure called TREEFAM for estimating ultrametric tree structures from proximity data confounded by differential stimulus familiarity. The objective of the proposed TREEFAM procedure is to quantitatively “filter out” the effects of stimulus unfamiliarity in the estimation of an ultrametric tree. A conditional, alternating maximum likelihood procedure is formulated to simultaneously estimate an ultrametric tree, under the unobserved condition of complete stimulus familiarity, and subject-specific parameters capturing the adjustments due to differential unfamiliarity. We demonstrate the performance of the TREEFAM procedure under a variety of alternative conditions via a modest Monte Carlo experimental study. An empirical application provides evidence that the TREEFAM outperforms traditional models that ignore the effects of unfamiliarity in terms of superior tree recovery and overall goodness-of-fit.

Segmentation of Spatially Dependent Geographical Units: Model and Application

We develop and test a new methodology that assigns geographical units (such as ZIP codes) to market segments by simultaneously considering bases of segmentation, such as customer attitudes and needs, such that the resulting segments display a high level of spatial concentration. Such concentrated segments are managerially desirable because of the logistical and administrative efficiencies created by implementing spatially concentrated segment-level strategies. The suggested approach captures spatial dependence flexibly while allowing us to identify managerially actionable segments that effectively balance homogeneity and spatial concentration. An illustrative empirical application demonstrates how the results can be utilized to derive consumer insights for actionable segmentation strategies. A Monte Carlo simulation and an assessment of the quality of the segments obtained from the empirical application support the value of the proposed spatially dependent segmentation method. This paper was accepted by P...