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We present a review of research studies that deal with personalization and synthesize current knowledge about these areas. We identify issues that we envision will be of interest to researchers working in the management sciences, taking an interdisciplinary approach that spans the areas of economics, marketing, information technology (IT), and operations research. We present a framework for personalization that allows us to identify key players in the personalization process as well as key stages of personalization. The framework enables us to examine the strategic role of personalization in the interactions between a firm and other key players in the firm's value system. We conceptualize the personalization process as consisting of three stages: (1) learning about consumer preferences, (2) matching offerings to customers, and (3) evaluation of the learning and matching processes. This review focuses on the learning stage, with an emphasis on utility-based approaches to estimate preference functions using data on customer interactions with a firm.

Models of advertising response implicitly assume that the entire advertising budget is spent on disseminating one message. In practice, managers use different themes of advertising (for example, price advertisements versus product advertisements) and within each theme they employ different versions of an advertisement. In this study, we evaluate the dynamic effects of different themes of advertising that have been employed in a campaign. We develop a model that jointly considers the effects of wearout as well as that of forgetting in the context of an advertising campaign that employs five different advertising themes. We quantify the differential wearout effects across the different themes of advertising and examine the interaction effects between the different themes using a Bayesian dynamic linear model (DLM). Such a response model can help managers decide on the optimal allocation of resources across the portfolio of ads as well as better manage their scheduling. We develop a model to show how our response model parameters can be used to improve the effectiveness of advertising budget allocation across different themes. We find that a reallocation of resources across different themes according to our model results in a significant improvement in demand.

We conduct a firm-level, 6-year longitudinal analysis on the impact that racial diversity in human resources has on financial performance. When considering short-term performance outcomes, we predict a curvilinear relationship between diversity and performance (i.e., firm productivity). Although we find evidence of a U-shaped relationship between racial diversity and productivity, the relationship is stronger in service-oriented relative to manufacturing-oriented industries and in more stable vs. volatile environments. For longer-term profitability, we propose and find support for more of a positive linear relationship between diversity and performance (i.e., Tobin's q) than a nonlinear one. This linear effect is stronger and more positive in munificent compared to resource-scare environments. Thus, we aid in reconciling existing, often contradictory, studies by demonstrating the potential short-term vs. long-term impact of racial diversity on performance. We offer implications for future research on diversity considering the current and projected demographic landscape.

The authors study the joint effects of creative format, message content, and targeting on the performance of digital ads over time. Specifically, they present a dynamic model to measure the effects of various sizes of static (GIF) and animated (Flash) display ad formats and consider whether different ad contents, related to the brand or a price offer, are more or less effective for different ad formats and targeted or retargeted customer segments. To this end, the authors obtain six months of data on daily impressions, clicks, targeting, and ad creative content from a major U.S. retailer, and they develop a dynamic zero-inflated count model. Given the sparse, nonlinear, and non-Gaussian nature of the data, the study designs a particle filter/Markov chain Monte Carlo scheme for estimation. Results show that carry-over rates for dynamic formats are greater than those for static formats; however, static formats can still be effective for price ads and retargeting. Most notably, results also show that retargeted ads are effective only if they offer price incentives. The study then considers the import of these results for the retailer's media schedules.

Credit card companies typically offer limited-time teaser interest rates [also known as promotional annual percentage rates (APRs)] to attract new customers. Firms hope that the promotional APRs will encourage consumers not only to open accounts, but also to transfer balances from other credit cards, revolve credit card balances, or take cash advances, each of which would lead to an increase in the firm’s profit. It is important to understand the effect of the promotional rates on customer behavior. Important research questions include: Does the lure of a low APR increase indebtedness of a customer over the short run and the long run? Between two segments—needy and opportunistic customers—which group is more likely to take advantage of the offer? A related important question for firms is whether the low APRs increase the financial risk (i.e., probability of delinquency or the probability of default of a customer) thus imposing costs of monitoring and balance recovery on the firm. Given the limited published research on these topics, we take a closer look at some of the behavioral patterns associated with the offer of promotional APRs in this study.

PurposeThe authors offer a new approach to segment credit card customers by classifying customers into two unobserved (latent) segments: opportunistic and needy.Design/methodology/approachThe authors develop a finite mixture model to estimate customers’ tendency to borrow using the three alternatives available to them—promotional cash advances, regular cash advances and retail balances.FindingsThe results support the presence of at least two segments among credit card customers. The authors find that relative to opportunistic individuals, needy customers are typically more sensitive to interest rates. Additionally, the results indicate that offering promotional cash advances to current credit card customers increases their sensitivity to regular interest rates. Furthermore, the findings indicate that needy customers tend to have a higher stickiness in their debt. In the post-estimation analyses, the authors observe that needy customers generate more revenue than opportunistic customers. Interestingly, the bank does not perform well in targeting needy individuals and targets both groups with the same probability.Originality/valueThe authors argue that teaser rates attract at least two segments of borrowers—the “needy” segment, which is more likely to be cash-strapped, and the “opportunistic” segment, which looks at these teaser rates as an opportunity. However, banks do not observe segment membership. Hence, the authors offer a new approach to identifying these segments and show that understanding the behavior of these latent segments could help a bank target profitable customers more effectively.

PurposeThe current approach to valuing customers is based on the notion of discounted profit generated by the customers over the lifetime of the relationship, also known as customer lifetime value (CLV). However, in the financial services industry, the customers who contribute the most to the profitability of a firm are also the riskiest customers. If the riskiness of a customer is not considered, firms will overestimate the true value of that customer. This paper proposes a methodology to adjust CLV for different types of risk factors and creates a comprehensive measure of risk-adjusted lifetime value (RALTV).Design/methodology/approachUsing data from a major credit card company, we develop a measure of risk adjusted lifetime value (RALTV) that accounts for diverse types of customer risks. The model is estimated using Stochastic Frontier Analysis (SFA).FindingsMajor findings indicate that rewards cardholders and affinity cardholders tend to score higher within the RALTV framework than non-rewards cardholders and non-affinity cardholders, respectively. Among the four different modes of acquisition, the Internet generates the highest RALTV, followed by direct mail.Originality/valueThis paper not only controls for different types of consumer risks in the financial industry and creates a comprehensive risk-adjusted lifetime value (RALTV) model but also shows empirically the value of using RALTV over CLV for predicting future performance of a set of customers. Further, we investigate the impact of a firm’s acquisition and retention strategies on RALTV. The measure of risk-adjusted lifetime value is invaluable for managers in financial services.

Two major controversies in strategic group research have been whether strategic groups actually exist and if so what is the best methodological approach to identify them. One perspective on strategic groups suggests that a strategic group exists if and only if the performance of a firm in the group is a function of group characteristics after controlling for firm and industry characteristics. We test this theoretical position by developing and estimating a model for the airline industry using latent class regressions. Our analysis finds evidence for the existence of four distinct strategic groups of firms in the airline industry.

[Display omitted] ► A large fraction (38–46%) of customers are not aware of prices when making grocery purchases. ► ‘Price aware’ consumers respond more to deals than ‘price unaware’ customers. ► This prevents firms from announcing promotions without an accompanying price cut. ► Larger and deal-prone households are more price aware. There is evidence that consumer knowledge of prices is limited, implying that, on occasions, consumers may not be fully informed of prices when making a brand purchase. On such occasions, how do consumers make their brand choice decision? One possibility is that consumers use their expectation of prices. This raises an interesting question. To what extent is brand purchase either a function of preferences and posted prices or, of preferences and expectation of brand prices? Another important issue relates to the role of displays and features in simplifying consumer brand choice. First, do promotions cause consumers to restrict their attention to only promoted brands? Second, do promotions affect the price aware consumers more than the price unaware consumers? Our study uses scanner data on ketchup and peanut butter categories to answer the foregoing questions. We find that between 40 and 50% of the purchases are made by consumers using expectations of prices rather than posted prices. Consumers using price expectations may be thought of as being “unaware” of prices. We also find that promotions cause some consumers to focus exclusively on promoted brands, and this effect is greater on the price aware consumers than on the price unaware consumers. Our findings have an important bearing on the rationality of consumer expectation of prices, especially of the promoted brands. Price aware consumers act as a check against firms promoting without accompanying price cuts.