Bas Donkers

Undervalued or Overvalued Customers: Capturing Total Customer Engagement Value

Customers can interact with and create value for firms in a variety of ways. This article proposes that assessing the value of customers based solely upon their transactions with a firm may not be sufficient, and valuing this engagement correctly is crucial in avoiding undervaluation and overvaluation of customers. We propose four components of a customer’s engagement value (CEV) with a firm. The first component is customer lifetime value (the customer’s purchase behavior), the second is customer referral value (as it relates to incentivized referral of new customers), the third is customer influencer value (which includes the customer’s behavior to influence other customers, that is increasing acquisition, retention, and share of wallet through word of mouth of existing customers as well as prospects), and the fourth is customer knowledge value (the value added to the firm by feedback from the customer). CEV provides a comprehensive framework that can ultimately lead to more efficient marketing strategies that enable higher long-term contribution from the customer. Metrics to measure CEV, future research propositions regarding relationships between the four components of CEV are proposed and marketing strategies that can leverage these relationships suggested.

Estimating Risk Attitudes Using Lotteries: A Large Sample Approach

Attitudes towards risk play a major role in many economic decisions. In empirical studies it is quite often assumed that attitudes towards risk do not vary across individuals. This paper questions this assumption and analyses which factors influence an individuals risk attitude. Based on questions on lotteries in a large household survey we first semiparametrically estimate an index for risk aversion. We only make weak assumptions about the underlying decision process and our estimation method allows for generalisations of expected utility. We then estimate a structural model based on Cumulative Prospect Theory. Expected utility is strongly rejected and both the value function and the probability weighting function vary significantly with (among other things) age, income, and wealth of the individual.

Predicting customer potential value an application in the insurance industry

For effective Customer Relationship Management (CRM), it is essential to have information on the potential value of customers. Based on the interplay between potential value and realized value, managers can devise customer specific strategies. In this article, we introduce a model for predicting the potential value of a current customer. Furthermore, we discuss and apply different modeling strategies for predicting this potential value.

Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide

Discrete-choice experiments (DCEs) have become a commonly used instrument in health economics and patient-preference analysis, addressing a wide range of policy questions. An important question when setting up a DCE is the size of the sample needed to answer the research question of interest. Although theory exists as to the calculation of sample size requirements for stated choice data, it does not address the issue of minimum sample size requirements in terms of the statistical power of hypothesis tests on the estimated coefficients. The purpose of this paper is threefold: (1) to provide insight into whether and how researchers have dealt with sample size calculations for healthcare-related DCE studies; (2) to introduce and explain the required sample size for parameter estimates in DCEs; and (3) to provide a step-by-step guide for the calculation of the minimum sample size requirements for DCEs in health care.

Dynamic and Competitive Effects of Direct Mailings: A Charitable Giving Application

The authors propose a dynamic direct mailing response model with competitive effects. Purchase and promotion history are incorporated to map the dynamic competitive interactions among the firms sending the mailings. The authors investigate the impact of direct mailings on the revenues of each firm and its competitors over time. The model accounts for endogeneity of the mailing decision and for unobserved heterogeneity across households. The model is considered in a charitable giving setting, in which households often receive many direct mailings of different charities within a short period and competition is strong. The authors construct a unique database by merging the databases of three large charity organizations in the Netherlands. This results in household-level data on the direct mailings households received from and their donations to each of the three charities. The results show that a charitys own mailings are short-term substitutes; that is, an extra mailing cannibalizes the revenues of subsequent mailings. Furthermore, competitive charitable direct mailings tend to be short-term complements; that is, the direct mailings increase the total pie that is divided among the charities. In the long run, these effects die out. The results are also interpreted from a behavioral perspective.

Preferences for colorectal cancer screening strategies: a discrete choice experiment

Background:Guidelines underline the role of individual preferences in the selection of a screening test, as insufficient evidence is available to recommend one screening test over another. We conducted a study to determine the preferences of individuals and to predict uptake for colorectal cancer (CRC) screening programmes using various screening tests.Methods:A discrete choice experiment (DCE) questionnaire was distributed among naive subjects, yet to be screened, and previously screened subjects, aged 50–75 years. Subjects were asked to choose between scenarios on the basis of faecal occult blood test (FOBT), flexible sigmoidoscopy (FS), total colonoscopy (TC) with various test-specific screening intervals and mortality reductions, and no screening (opt-out).Results:In total, 489 out of 1498 (33%) screening-naïve subjects (52% male; mean age±s.d. 61±7 years) and 545 out of 769 (71%) previously screened subjects (52% male; mean age±s.d. 61±6 years) returned the questionnaire. The type of screening test, screening interval, and risk reduction of CRC-related mortality influenced subjects’ preferences (all P<0.05). Screening-naive and previously screened subjects equally preferred 5-yearly FS and 10-yearly TC (P=0.24; P=0.11), but favoured both strategies to annual FOBT screening (all P-values <0.001) if, based on the literature, realistic risk reduction of CRC-related mortality was applied. Screening-naive and previously screened subjects were willing to undergo a 10-yearly TC instead of a 5-yearly FS to obtain an additional risk reduction of CRC-related mortality of 45% (P<0.001).Conclusion:These data provide insight into the extent by which interval and risk reduction of CRC-related mortality affect preferences for CRC screening tests. Assuming realistic test characteristics, subjects in the target population preferred endoscopic screening over FOBT screening, partly, due to the more favourable risk reduction of CRC-related mortality by endoscopy screening. Increasing the knowledge of potential screenees regarding risk reduction by different screening strategies is, therefore, warranted to prevent unrealistic expectations and to optimise informed choice.

Patients’ and urologists’ preferences for prostate cancer treatment: a discrete choice experiment

Background:Patients’ preferences are important for shared decision making. Therefore, we investigated patients’ and urologists’ preferences for treatment alternatives for early prostate cancer (PC).Methods:A discrete choice experiment was conducted among 150 patients who were waiting for their biopsy results, and 150 urologists. Regression analysis was used to determine patients’ and urologists’ stated preferences using scenarios based on PC treatment modality (radiotherapy, surgery, and active surveillance (AS)), and risks of urinary incontinence and erectile dysfunction.Results:The response rate was 110 out of 150 (73%) for patients and 50 out of 150 (33%) for urologists. Risk of urinary incontinence was an important determinant of both patients’ and urologists’ stated preferences for PC treatment (P<0.05). Treatment modality also influenced patients’ stated preferences (P<0.05), whereas the risk of erectile dysfunction due to radiotherapy was mainly important to urologists (P<0.05). Both patients and urologists preferred AS to radical treatment, with the exception of patients with anxious/depressed feelings who preferred radical treatment to AS.Conclusion:Although patients and urologists generally may prefer similar treatments for PC, they showed different trade-offs between various specific treatment aspects. This implies that urologists need to be aware of potential differences compared with the patient’s perspective on treatment decisions in shared decision making on PC treatment.

Men’s preferences for prostate cancer screening: a discrete choice experiment

Background:Screening for prostate cancer (PC) may save lives, but overdiagnosis and overtreatment are serious drawbacks. We aimed to determine men’s preferences for PC screening, and to elicit the trade-offs they make.Methods:A discrete choice experiment (DCE) was conducted among a population-based random sample of 1000 elderly men (55–75-years-old). Trade-offs were quantified with a panel latent class model between five PC screening aspects: risk reduction of PC-related death, screening interval, risk of unnecessary biopsies, risk of unnecessary treatments, and out-of-pocket costs.Results:The response rate was 46% (459/1000). Men were willing to trade-off 2.0% (CI: 1.6%–2.4%) or 1.8% (CI: 1.3%–2.3%) risk reduction of PC-related death to decrease their risk of unnecessary treatment or biopsy with 10%, respectively. They were willing to pay [euro ]188 per year (CI: [euro ]141–[euro ]258) to reduce their relative risk of PC-related death with 10%. Preference heterogeneity was substantial, with men with higher educational levels having a lower probability to opt for PC screening than men with lower educational levels.Conclusion:Men were willing to trade-off some risk reduction of PC-related death to be relieved of the burden of biopsies or unnecessary treatments. Increasing knowledge on overdiagnosis and overtreatment, especially for men with lower educational levels, is warranted to prevent unrealistic expectations from PC screening.

Selecting profitable customers for complex services on the internet

In contrast to books and compact discs, the number of complex services offered on the Internet is still small. The decision-making process for complex services is different because it has an additional intermediate step of “indication of interest.” The Web site is (a) visited and searched for information; subsequently, (b) a request for the service is made, which may lead to (c) a purchase. The authors acquired a unique data set from an online Dutch financial service provider, which offers services such as mortgage loans and insurance on the Internet on behalf of financial institutions. They also obtained information on whether the request for the service resulted in a purchase. The authors used the available information to predict the purchase using a latent class probit model. A direct managerial application of this model is the ability to identify and select profitable applicants, resulting in significant profit improvements for the company.

Selective Sampling for Binary Choice Models

Marketing problems sometimes pertain to the analysis of dichotomous dependent variables, such as “buy” and “not buy” or “respond” and “not respond.” One outcome can strongly outnumber the other, such as when many households do not respond (e.g., to a direct mailing). In such situations, an efficient data-collection strategy is to sample disproportionately more from the smaller group. However, subsequent statistical analysis must account for this sampling strategy. In this article, the authors put forward the econometric method that can correct for the sample selection bias, when this method does not lead to a loss in precision. The authors illustrate the method for synthetic and real-life data and document that reductions of more than 50% in sample sizes can be obtained.