David Schmittlein on Marketing

At the request of Customer Needs and Solutions, David Schmittlein, a marketing professor and the John C. Head III Dean of the MIT Sloan School of Management, reflects on a few wide-ranging issues raised by the Journal’s editorial board members. The interview was conducted by Catherine Tucker, a marketing professor at MIT Sloan School of Management and a member of the editorial board, on behalf of the Journal on Dec. 5, 2013. Excerpts of this interview are printed here, and the full videotaped interview is available in the public domain

Assessing Validity and Test-Retest Reliability for “Pick of ” Data

A mixed binomial error model is proposed which permits the evaluation of validity and test-retest reliability when individuals are asked to pick of objects. The approach explicitly incorporates the effect of guessing as well as the respondent's true discrimination ability, and recognizes that that ability will vary across respondents. So, given the choices made by a set of individuals, we are interested in estimating the distribution of true ability over the population. To evaluate the criterion-related validity each person's choices (of objects) are compared to an objective standard—the “correct” choices. For the primary model considered here these data can be summarized by the distribution, over individuals, of the number of “matches” or agreements between a person's choices and the objective criterion. A similar procedure is used for evaluating test-retest reliability. The distribution for the number of matches is again used; but here the matches will refer to agreement between the individual's choices on this occasion, and the choices made by that individual on a previous occasion. The use of these reliability and validity results to address specific marketing questions, such as the segmentability of a market or the effect of advertising on perception and attitudes, is also discussed.pick of data, correcting for guessing, criterion-related validity, test-retest reliability

Some characterizations of stockpiling behavior under uncertainty

The objective of this note is to gain new theoretical insights into stockpiling phenomena. The model used to derive our results envisions consumers as responding optimally to uncertainties in the promotion environment. We show that, all else being equal, consumers will stockpile a promoted product more intensely: (i) the lower the availability of deal opportunities, (ii) the smaller the expected deal discount, and (iii) the lower the uncertainty about the deal/regular price, provided that dealing occurs with high/low frequency. © 1992 Kluwer Academic Publishers

Analyzing Duration Times in Marketing: Evidence for the Effectiveness of Hazard Rate Models

Some statistical methods developed recently in the biometrics and econometrics literature show great promise for improving the analysis of duration times in marketing. They incorporate the right censoring that is prevalent in duration times data, and can be used to make a wide variety of useful predictions. Both of these features make these methods preferable to the regression, logit, and discriminant analyses that marketers have typically used in analyzing durations. This paper is intended to fulfill three objectives. First, we demonstrate how decision situations that involve durations differ from other marketing phenomena. Second, we show how standard modeling approaches to handle duration times can break down because of the peculiarities inherent in durations. It has been suggested in recent marketing articles that an alternative to these conventional procedures, i.e., hazard rate models and proportional hazard regression, can more effectively handle duration type data. Third, to investigate whether these proposed benefits are in fact delivered for marketing durations data, we estimate and validate both conventional and hazard rate models for household interpurchase times of saltine crackers. Our findings indicate the superiority of proportional hazard regression methods vis-à-vis common procedures in terms of stability and face validity of the estimates and in predictive accuracy.econometric modeling, estimation and other statistical techniques, pricing research, promotion, regression and other statistical techniques

A live baby or your money back: The marketing of in vitro fertilization procedures .Management Science

Abstract A large number of clinics that offer in vitro fertilization (IVF) have begun to aggressively market the following options to couples seeking to have a genetically related baby: (1) an a la carte program where the couple pays $7,500 per attempt regardless of the outcome; or (2) a money-back-guarantee program where the couple pays a$15,000 up-front fee that covers up to three attempts -however, if after three cycles there is no live birth delivery, then the full $15,000 is refunded. If the couple contemplating these two choices knew the success probability for each attempt, then a simple analysis would show whether the a la carte or money-backguarantee program is better. Unfortunately, it is difficult for couples to gather the relevant data and even more daunting to adjust the aggregate data to their own situation. In this article we assemble the most recent available data and develop a model that allows patients, clinics, and public policy advocates to assess the a la carte vs. moneyback-guarantee programs. The most surprising result of our analysis is that the moneyback-guarantee program appears (for the patients) to be "too good to be true." That is, with reasonable projections from the most recent data, the money-back guarantee yields a substantial negative expected profit per couple for the clinics. More importantly from the patients' perspective, the money-back-guarantee turns out to be the better option for all couples with less than 0.5 success probability per cycle. (The breakeven probability is even higher if risk aversion is considered.) Virtually all traditional IVF patients can be considered to have per-cycle success probabilities well below 0.5. Can it be that clinics are offering money-back-guarantees that both lose money for the clinics and give the patients a deal that is far better for them than the traditional a la carte payment method? After a detailed analysis of the key variables -i.e., success rate per attempt, heterogeneity of couples' base rates of success, individual couples' "learning" on successive attempts, and cost to the clinic per attempt -nothing makes these money-backguarantees profitable for the clinics. Since presumably clinics are not in business to lose money, the analysis must be missing something major. Based on the kind of aggressive marketing (e.g., mass media) for the money-back guarantees, we believe it is bringing in younger and less infertile patients than those who were in IVF clinics prior to 1996. In other words, the marketing of money-back guarantees may be inducing couples who would previously have used -successfully -other less invasive procedures with fewer potential side effects and less risk of multiple births to decide, "Why wait: let's jump to IVF now and we'll get our money back if it doesn't work." We show that under this scenario the money-back-guarantees can be profitable for the clinics. The implications of earlier use of IVF are then considered for patients, clinic managers, and from an overall public policy point of view. Although the clinics that make profits and the couples who either receive a baby or their money-back are unlikely to complain, there are some significant downsides to the marketing of IVF money-backguarantees that need to be understood. Just as mothers everywhere tell their children, "When something looks too good to be true, then it is too good to be true!"

Integration of the Sales Force: An Empirical Examination

This article develops and tests a model of integration of a marketing function, personal selling. The model, derived from transaction cost analysis as developed principally by Williamson, is formulated as a logistic function, which is estimated with data from the electronic components industry. As expected, integration is associated with increasing levels of asset specificity, difficulty of performance evaluation, and the combination of these two factors. Contrary to the transaction cost model, neither frequency of transactions nor interaction of specificity and environmental uncertainty is significantly related to integration. The transaction cost model improves significantly upon the fit of a simple model relating integration to company size alone. These results suggest that for studying transactions of this kind, it is fruitful to view the firm as a governance structure.

Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance

A maximum likelihood approach is proposed for estimating an innovation diffusion model of new product acceptance originally considered by Bass (Bass, F. M. 1969. A new product growth model for consumer durables. (January) 215–227.). The suggested approach allows: (1) computation of approximate standard errors for the diffusion model parameters, and (2) determination of the required sample size for forecasting the adoption level to any desired degree of accuracy. Using histograms from eight different product innovations, the maximum likelihood estimates are shown to outperform estimates from a model calibrated using ordinary least squares, in terms of both goodness of fit measures and one-step ahead forecasts. However, these advantages are not obtained without cost. The coefficients of innovation and imitation are easily interpreted in terms of the expected adoption pattern, but individual adoption times must be assumed to represent independent draws from this distribution. In addition, instead of using standard linear regression, another (simple) program must be employed to estimate the model. Thus, tradeoffs between the maximum likelihood and least squares approaches are also discussed.diffusion of innovations, new product forecasting, maximum likelihood

A Bayesian Cross-Validated Likelihood Method for Comparing Alternative Specifications of Quantitative Models

There are many situations in marketing in which several alternative quantitative models may be built to model a particular marketing phenomenon or system. Few methods exist for comparing the fit of such models if the models are not nested, especially if their performance on each of several criteria is important. This paper proposes a Bayesian cross-validated likelihood (BCVL) method for comparing quantitative models. It can be used when the models are either nested or nonnested, and is especially useful for nonnested models. A simulation based upon a typical marketing modeling situation shows the incremental benefit of using the BCVL method rather than existing techniques, and explores the circumstances under which BCVL works best. The applicability of the BCVL method is demonstrated using several typical marketing modeling situations.model comparison, cross-validation, marketing models

A Live Baby or Your Money Back: The Marketing of In Vitro Fertilization Procedures

Many clinics that offer in vitro fertilization (IVF) have begun to market the following options to couples: (1) an a la carte program where the couple pays $7,500 per attempt regardless of the outcome; or (2) a money-back-guarantee program where the couple pays a$15,000 fee that covers up to three attempts, however, if after three cycles there is no live-birth delivery, then the full $15,000 is refunded. We assess the a la carte versus the money-back-guarantee programs, and find the surprising result that the money-back-guarantee program appears (for the patients) to be "too good to be true." That is, the money-back guarantee yields a substantial negative expected profit per couple for the clinics. More importantly from the patients' perspective, the money-back guarantee is the better option for all couples with less than 0.5 success probability per cycle. Virtually all traditional IVF patients have had per-cycle success probabilities below 0.5. A detailed analysis of the key variables---i.e., success rate per attempt, heterogeneity of couples' rates of success, individual couples' "learning" on successive attempts, and cost to the clinic per attempt---shows that these money-back guarantees are unprofitable for the clinics. Since presumably clinics are not in business to lose money, the standard analysis must be missing something major. We suggest that the marketing of money-back guarantees is inducing couples who would previously have used---successfully---other less invasive procedures with fewer side effects and less risk of multiple births to decide to proceed directly to IVF, and that this scenario makes the money-back guarantees profitable for the clinics. The implications of earlier use of IVF are then considered from an overall public policy point of view. Just as mothers everywhere tell their children, "When something looks too good to be true, then it is too good to be true!"Marketing;, In Vitro;, Assisted Reproduction;, Health Care Marketing