Source: http://marketing-koeln.de/de/research/publications/werner-reinartz/
Timestamp: 2019-04-26 12:48:45+00:00

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Ptok, Annette, Rupinder Jindal, and Werner Reinartz (2018), "Selling, General, and Administrative Expense (SGA)-Based Metrics in Marketing: Conceptual and Measurement Challenges", Journal of the Academy in Marketing Science, 46(6), 987 1011.
Lobschat, Lara, Ernst C. Osinga, Werner Reinartz (2017). What Happens Online Stays Online? – Segment-Specific Online and Offline Effects of Banner Advertisements. Journal of Marketing Research, 54(6), 901-913. Click here for the abstract.
Reddy, Srinivas and Werner Reinartz (2017), "Digital Transformation and Value Creation", Marketing Intelligence Review, Vol 9 (1), 11-17. Click here for the abstract.
Digital transformation is taking place all around us and there is hardly a single aspect of life that has not been affected. All economic systems and market interactions result in costs for information exchange, coordination, safeguarding, enforcing, etc. Digitalization will lower these costs and therefore unleash value; the more exchanges, the higher the potential benefits. The structure of information exchange will change considerably. A key challenge is to analyze and interpret patterns in these large data volumes and to gain insights for actionable decisions. The digital transformation is pervading and transforming our daily lives fundamentally. Moreover, the developments so far are irreversible. How to survive ongoing digital transformation: 1. Don't just scratch the surface. 2. Innovate - first your mindset, then your actions. 3. Speed up.
Reinartz, Werner and Monika Imschloß (2017), "From Point-of-Sale to Point-of-Need: How Digital Technology Transforms Retailing," Marketing Intelligence Review, 9 (1), 43-47. Click here for the abstract.
Today, ever more consumers are acting very differently: To purchase certain products they do not even go near a brickand-mortar store, and if they do enter a store they are often so well informed that a clerk has little service to add. Store-based retailers are reacting by starting to "digitalize" their point of sale. . Instead of asking how the traditional point of transaction in a physical store can be just digitally augmented, retailers should rather ask how digitalization can be used to bring new value to their consumers along the entire consumption process. In our digital age, need occurrence, shopping and consumption are moving much closer in time and space and becoming more and more naturally integrated into daily routines. Digitalization offers the opportunity to have an impact on consumers' decisions much earlier - right when a need occurs. Brands have to be there when consumers like to interact. Recent trends are instant purchasing, subscription-based purchasing, and automated purchasing.
Worm, Stefan, Sundar G. Bharadawaj, Wolfgang Ulaga, and Werner Reinartz (2017), "When and Why do Customer Solutions Pay off in Business Markets?" Journal of the Academy of Marketing Science, 45 (4), 490-512. Click here for the abstract.
Kannan, P. K., Reinartz, W., & Verhoef, P. C. (2016). The path to purchase and attribution modeling: Introduction to special section. International Journal of Research in Marketing, 33(3), 449-456. Click here for the abstract.
Käuferle, M., & Reinartz, W. (2015). Distributing through multiple channels in industrial wholesaling: how many and how much?. Journal of the Academy of Marketing Science, 43(6), 746-767. Click here for abstract.
Reinartz, W. (2011). Feeling good or feeling right?-Discussion of quantitative and qualitative rankings of scholars. Schmalenbach Business Review, 63(1), 109. Click here for the abstract.
Any writing that attempts to describe how to measure researcher quality or how to improve such measures should be lauded; it is not an easy turf to proceed along. The difficulty of measuring and evaluating academic research quality stems from two aspects: the heterogeneity in viewpoints across individuals and institutions of what constitutes "good research"; and due to the underlying promotion process, the personal involvement of virtually every academic in the course of his or her career. In their article, "Quantitative and Qualitative Rankings of Scholars" Rost and Frey (R&F) point to the shortcomings of using count measures of publications and citations (which they call quantitative measures) to evaluate research in general and the research produced by young scholars up for promotion and tenure in particular. At the heart of R&F's article is the question of how to (correctly) measure an academic's impact, or in R&F's words, an academic's quality.
Reinartz, W., Dellaert, B., Krafft, M., Kumar, V., & Varadarajan, R. (2011). Retailing innovations in a globalizing retail market environment. Journal of Retailing, 87, S53-S66. Click here for the abstract.
In recent years, the combination of economic growth and population growth in emerging markets and less developed markets has accelerated the progression of globalization of retailing and globalization by retailers. The challenges faced by global and globalizing retailers (retailers who currently have or intend to establish a market presence in mature markets, emerging markets and less developed markets) can be more daunting compared to those faced by firms in other industries such as automobiles, steel, and computers. Retailing innovations that are responsive to the characteristics of distinctive national markets and broader aggregations of markets such as mature, emerging and less developed markets are critical to the success of global and globalizing retailers. Against this backdrop, this paper focuses on retailing innovations in the context of a globalizing retailing environment. It attempts to shed insights into the characteristics of retailing innovations conducive to superior performance in distinctive national markets and across broader aggregations of markets. Towards this end, we first examine the environmental conditions of markets in different development stages, namely mature, emerging and less developed markets, and explore consumer based, industry based, and legal/regulatory based challenges faced by globalizing retailers in these markets. Second, we show how these challenges can be transformed into opportunities with retailing innovations. We conclude with a roadmap for future research and present propositions on future development with respect to retailing innovations in these markets.
Ulaga, W., & Reinartz, W. J. (2011). Hybrid offerings: how manufacturing firms combine goods and services successfully. Journal of Marketing, 75(6), 5-23. Click here for the abstract.
This article examines key success factors for designing and delivering combinations of goods and services (i.e., hybrid offerings) in business markets. Goods manufacturers, unlike pure service providers, find themselves in a unique position to grow revenues through hybrid offerings but must learn how to leverage unique resources and build distinctive capabilities. Using case studies and depth interviews with senior executives in manufacturing companies, the authors develop a resource–capability framework as a basis for research and practice. Executives identify four critical resources: (1) product usage and process data derived from the firm’s installed base of physical goods, (2) product development and manufacturing assets, (3) an experienced product sales force and distribution network, and (4) a field service organization. In leveraging these specific resources, successful firms build five critical capabilities: (1) service-related data processing and interpretation capability, (2) execution risk assessment and mitigation capability, (3) design-to service capability, (4) hybrid offering sales capability, and (5) hybrid offering deployment capability. These capabilities influence manufacturers’ positional advantage in two directions: differentiation and cost leadership. The authors propose a new typology of industrial services and discuss how resources and capabilities affect success across categories of hybrid offers.
Van Bruggen, G. H., Antia, K. D., Jap, S. D., Reinartz, W. J., & Pallas, F. (2010). Managing marketing channel multiplicity. Journal of Service Research, 13(3), 331-340. Click here for the abstract.
Advances in information technology and changing customer needs for channel service outputs have dramatically affected the routes to markets in many industries. The authors propose that these changes have led to significant alterations in how customers interact with firms and consequently to a phenomenon that we dub ‘‘channel multiplicity.’’ Channel multiplicity is characterized by the customer’s reliance on multiple sources of information from independent (and often disparate) channel organizations and increasing demand for a seamless experience throughout the buying process. The authors identify the new market operating realities driving channel multiplicity and provide an overview of the consequences for channel design and channel management: a broadened view of products and services, channel leadership challenges, alterations in channel structure, and an expanded view of distribution intensity. The authors also identify issues triggered by these developments, which calls for further research in this field.
Verhoef, P. C., Reinartz, W. J., & Krafft, M. (2010). Customer engagement as a new perspective in customer management. Journal of Service Research, 13(3), 247-252. Click here for the abstract.
Since 2000, customer management (CM) research has evolved and has had a significant impact on the marketing discipline. In an increasingly networked society where customers can interact easily with other customers and firms through social networks and other new media, the authors propose that customer engagement is an important new development in CM. Customer engagement is considered as a behavioral manifestation toward the brand or firm that goes beyond transactions. The authors propose a conceptual model of the antecedents, impediments, and firm consequences of customer engagement and relate this model to seven articles appearing in the special issue on customer engagement.
Reinartz, W., Haenlein, M., & Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. International Journal of Research in Marketing, 26(4), 332-344. Click here for the abstract.
Variance-based SEM, also known under the term partial least squares (PLS) analysis, is an approach that has gained increasing interest among marketing researchers in recent years. During the last 25 years, more than 30 articles have been published in leading marketing journals that have applied this approach instead of the more traditional alternative of covariance-based SEM (CBSEM). However, although an analysis of these previous publications shows that there seems to be at least an implicit agreement about the factors that should drive the choice between PLS analysis and CBSEM, no research has until now empirically compared the performance of these approaches given a set of different conditions. Our study addresses this open question by conducting a large-scale Monte-Carlo simulation. We show that justifying the choice of PLS due to a lack of assumptions regarding indicator distribution and measurement scale is often inappropriate, as CBSEM proves extremely robust with respect to violations of its underlying distributional assumptions. Additionally, CBSEM clearly outperforms PLS in terms of parameter consistency and is preferable in terms of parameter accuracy as long as the sample size exceeds a certain threshold (250 observations). Nevertheless, PLS analysis should be preferred when the emphasis is on prediction and theory development, as the statistical power of PLS is always larger than or equal to that of CBSEM; already, 100 observations can be sufficient to achieve acceptable levels of statistical power given a certain quality of the measurement model.
Kumar, V., Venkatesan, R., & Reinartz, W. (2008). Performance implications of adopting a customer-focused sales campaign. Journal of Marketing, 72(5), 50-68. Click here for the abstract.
Through field experiments conducted in two business-to-business firms, the authors evaluate the financial and relational consequences of adopting a customer focus in sales campaigns. In both the experiments, salespeople adopting the customer-focused sales campaign coordinated their sales calls with the objective of selling all the products that a customer was predicted to purchase only at the time the customer was expected to purchase. The authors compare this strategy with the current practice in the organization in which salespeople for each product category independently contacted the customers who were expected to purchase in that category without any guidance on the expected timing of customer purchase. The experiments show that adopting a customer-focused sales campaign can significantly increase firm profits and return on investment. The total incremental profits obtained from implementing the customer-focused sales campaign was more than $1 million. High-revenue customers were the source of improvements in the efficiency of marketing contacts, whereas low-revenue customers were the source of improvements in the effectiveness of the marketing contacts. A customer-focused sales campaign also improved the relationship quality between the customer and the firm. This research provides empirical evidence for theoretical expectations of the benefits provided by a customer-focused sales campaign. Organizations can use the field experiments illustrated in this study as a template for implementing the first step in migrating to a customer-centric organization.
Reinartz, W., Thomas, J. S., & Bascoul, G. (2008). Investigating cross‐buying and customer loyalty. Journal of Interactive Marketing, 22(1), 5-20. Click here for the abstract.
Cross-buying (i.e., the purchase of products from multiple categories) has been associated with higher levels of customer retention, revenue generation, and loyalty. Despite these claims, debate remains as to whether cross-buying is an antecedent to such behaviors or if loyalty behaviors represent the antecedent, with cross-buying as a consequence. This research investigates the direction, strength, and nature of the relationship between customers' cross-buying behavior and associated behavioral outcomes by using a Granger-type causality modeling and two data sets. The authors determine that cross-buying is a consequence and not an antecedent of behavioral loyalty. Specifically, behavioral loyalty drives both the number of categories from which a person buys and the level of spending dispersion across those categories. These findings have significant implications for cross-selling strategies.
Jindal, R. P., Reinartz, W., Krafft, M., & Hoyer, W. D. (2007). Determinants of the variety of routes to market. International Journal of Research in Marketing, 24(1), 17-29. Click here for the abstract.
Increasingly, firms use more and different routes to market. This study investigates whether such heterogeneity in the variety of routes to market can be explained systematically. More specifically, the authors examine how (1) the type and level of a firm's customer orientation and (2) the type and degree of customer search behavior influences the firm's adoption of a variety of routes. They collect primary data on 210 firms in four consumer industries across three countries to test the hypotheses. The authors find strong evidence for a link between a firm's customer orientation and the breadth of its variety of routes but only partial evidence for a link between customer search behavior and the breadth of the variety of routes.
Echambadi, R., Arroniz, I., Reinartz, W., & Lee, J. (2006). Empirical generalizations from brand extension research: How sure are we?. International Journal of Research in Marketing, 23(3), 253-261. Click here for the abstract.
Bottomley and Holden [Bottomley, P.A., and Holden, S.J.S. (2001). Do we really know how consumers evaluate brand extensions? Empirical generalizations based on secondary analysis of eight studies. Journal of Marketing Research, 38, 494–500.] conducted a secondary analysis of Aaker and Keller's [Aaker, D.A., and Keller, K.L. (1990). Consumer evaluations of brand extensions. Journal of Marketing, 54, 27–41.] seminal brand extension study and seven other close replications, generated several empirical generalizations, and hence called for a revision of the extant understanding of brand extension evaluations. We re-examine Bottomley and Holden's conclusions. We prove analytically that the simple effects estimated by B&H are incorrect, thereby rendering some of their generalizations suspect. We re-analyze the same data using appropriate statistical techniques, and our new results clarify the understanding of how consumers indeed evaluate extensions. Specifically, we find that, although the simple effects of neither parent brand quality nor measures of fit affect evaluations of brand extensions, the interaction effects of parent brand quality with fit are important determinants of brand extension evaluations. We discuss the substantive implications of our findings and offer directions for future research.
Chandon, P., Morwitz, V. G., & Reinartz, W. J. (2005). Do intentions really predict behavior? Self-generated validity effects in survey research. Journal of Marketing, 69(2), 1-14. Click here for the abstract.
Studies of the relationship between purchase intentions and purchase behavior have ignored the possibility that the very act of measurement may inflate the association between intentions and behavior, a phenomenon called “self-generated validity.” In this research, the authors develop a latent model of the reactive effects of measurement that is applicable to intentions, attitude, or satisfaction data, and they show that this model can be estimated with a two-stage procedure. In the first stage, the authors use data from surveyed consumers to predict the presurvey latent purchase intentions of both surveyed and nonsurveyed consumers. In the second stage, they compare the strength of the association between the presurvey latent intentions and the postsurvey behavior across both groups. The authors find large and reliable self-generated validity effects across three diverse large-scale field studies. On average, the correlation between latent intentions and purchase behavior is 58% greater among surveyed consumers than it is among similar nonsurveyed consumers. One study also shows that the reactive effect of the measurement of purchase intentions is entirely mediated by self-generated validity and not by social norms, intention modification, or other measurement effects that are independent of presurvey latent intentions.
Reinartz, W., Thomas, J. S., & Kumar, V. (2005). Balancing acquisition and retention resources to maximize customer profitability. Journal of Marketing, 69(1), 63-79. Click here for the abstract.
In this research, the authors present a modeling framework for balancing resources between customer acquisition efforts and customer retention efforts. The key question that the framework addresses is, “What is the customer profitability maximizing balance?” In addition, they answer questions about how much marketing spending to allocate to customer acquisition and retention and how to distribute those allocations across communication channels.
Chandon, P., Morwitz, V. G., & Reinartz, W. J. (2004). The short-and long-term effects of measuring intent to repurchase. Journal of Consumer Research, 31(3), 566-572. Click here for the abstract.
We compare the incidence, timing, and profitability of repeated online grocery purchases made by a cohort of consumers whose purchase intentions were measured with those of similar consumers whose intentions were not measured. We find that measuring intentions increases the likelihood of repeat purchase incidence and shortens the time until the first repeat purchase but that these two mere-measurement effects decay rapidly after 3 mo. Still, we find persisting gains in customer profitability over time because the accelerated purchases of the first 3 mo. lead to faster subsequent purchases in the remainder of the period.
Reinartz, W., Krafft, M., & Hoyer, W. D. (2004). The customer relationship management process: Its measurement and impact on performance. Journal of Marketing Research, 41(3), 293-305. Click here for the abstract.
An understanding of how to manage relationships with customers effectively has become an important topic for both academicians and practitioners in recent years. However, the existing academic literature and the practical applications of customer relationship management (CRM) strategies do not provide a clear indication of what specifically constitutes CRM processes. In this study, the authors (1) conceptualize a construct of the CRM process and its dimensions, (2) operationalize and validate the construct, and (3) empirically investigate the organizational performance consequences of implementing CRM processes. Their research questions are addressed in two cross-sectional studies across four different industries and three countries. The first key outcome is a theoretically sound CRM process measure that outlines three key stages: initiation, maintenance, and termination. The second key result is that the implementation of CRM processes has a moderately positive association with both perceptual and objective company performance.
Reinartz, W. J., & Kumar, V. (2003). The impact of customer relationship characteristics on profitable lifetime duration. Journal of Marketing, 67(1), 77-99. Click here for the abstract.
The authors develop a framework that incorporates projected profitability of customers in the computation of lifetime duration. Furthermore, the authors identify factors under a manager’s control that explain the variation in the profitable lifetime duration. They also compare other frameworks with the traditional methods such as the recency, frequency, and monetary value framework and past customer value and illustrate the superiority of the proposed framework. Finally, the authors develop several key implications that can be of value to decision makers in managing customer relationships.
Bell, D., Deighton, J., Reinartz, W. J., Rust, R. T., & Swartz, G. (2002). Seven barriers to customer equity management. Journal of Service Research, 5(1), 77-85. Click here for the abstract.
The article reviews the evolution from brand-centered marketing to customer-centered marketing and the beginnings of a focus on viewing the customer as an asset. It illustrates the practice by describing the use of a loyalty program to identify and respond to high-potential customers in the market for business-class hotels. Next, it considers seven challenges that impede wider adoption of customer equity management and concludes with a schematic model of customer-centered marketing management.
Reinartz, W. J., Echambadi, R., & Chin, W. W. (2002). Generating non-normal data for simulation of structural equation models using Mattson's method. Multivariate Behavioral Research, 37(2), 227-244. Click here for the abstract.
SEM researchers use Monte-Carlo simulations to ascertain the robustness of statistical estimators and the performance of various fit indices under varying conditions of non-normality. The efficacy of these Monte-Carlo simulations is closely related to the generation of non-normal data. Traditionally, SEM researchers have used approaches proposed by Fleishman (1978) and Vale and Maurelli (1983) to generate multivariate non-normal random numbers. However, both approaches do not provide a method to determine univariate skewness and kurtosis of the observed variables when a non-normal distribution is specified for some or all of the latent variables. Mattson (1997) proposed a method for generating data on the latent variables with controlled skewness and kurtosis of the observed variables. We empirically test the applicability of Mattson's theoretical method in a Monte-Carlo simulation. Specifically, we assess the impact of data generation, selection of transformation method, sample size and degree of skewness/kurtosis on the performance of the method. Our results suggest that Mattson's method seems to be a good approach to generate data with defined levels of skewness and kurtosis. In addition, based on the results of our analysis, we provide practicing researchers recommendations regarding their empirical implementation schemes.
Reinartz, W. J., & Kumar, V. (2000). On the profitability of long-life customers in a noncontractual setting: An empirical investigation and implications for marketing. Journal of Marketing, 64(4), 17-35. Click here for the abstract.
Relationship marketing emphasizes the need for maintaining long-term customer relationships. It is beneficial, in general, to serve customers over a longer time, especially in a contractual relationship. However, it is not clear whether some of the findings observed in a contractual setting hold good in noncontractual scenarios: relationships between a seller and a buyer that are not governed by a contract or membership. The authors offer four different propositions in this study and subsequently test each one in a noncontractual context. The four propositions relate to whether (1) there exists a strong positive customer lifetime-profitability relationship, (2) profits increase over time, (3) the costs of serving long-life customers are less, and (4) long-life customers pay higher prices. The authors develop arguments both for and against each of the propositions. The data for this study, obtained from a large catalog retailer, cover a three-year window and are recorded on a daily basis. The empirical findings observed in this study challenge all the expectations derived from the literature. Long-life customers are not necessarily profitable customers. The authors develop plausible explanations for findings that go against the available evidence in the literature and identify three indicators through discriminant analysis that can help managers focus their efforts on more profitable customers. The authors draw several marketing implications and acknowledge the limitations of the study.
Reinartz, W. J., & Kumar, V. (1999). Store-, market-, and consumer-characteristics: The drivers of store performance. Marketing Letters, 10(1), 5-23. Click here for the abstract.
Four factors have traditionally been identified in influencing store performance: store-, market-, and consumer characteristics and competition. Given partially conflicting and, in some cases, dated findings in the literature we want to re-assess the effects. In particular, past research has usually considered only two out of the four constructs at any time, which is likely to result in erroneous interpretation of results. We draw upon a unique cross-sectional sample of grocery stores with a wide array of store characteristic, store performance, trade area, and consumer demographic variables. Using structural modeling, our prime interest is to assess the differential impact of store attractiveness, market potential, and socio-economic status on two different store performance measures, while controlling for competitive effects. We find that the market potential of a store is by far the most important driver of store sales performance and sales productivity performance. With one exception, the model and the data support the hypothesized relationships about the direction and the strength of the impact of a store's attractiveness, market potential and socio-economic characteristics of the trade area on a store's performance.
Kumar, V., Hurley, M., Karande, K., & Reinartz, W. J. (1998). The impact of internal and external reference prices on brand choice: the moderating role of contextual variables. Journal of Retailing, 74(3), 401-426. Click here for the abstract.
The impact of internal reference price discrepancy (between actual price and internal reference price), and external reference price discrepancy (between actual price and external reference price) on brand choice is studied in two different contexts: whether the consumer faces a stockout condition at the time of purchase or not, and whether the consumer is a deal-prone consumer or not. Internal reference price is based on the past prices paid for the brand by the consumer, and external reference price is dependent upon the prices of all brands in the category at the point of purchase. Hypotheses are tested by estimating brand choice models using IRI scanner panel data for two product categories—saltine crackers and baking chips. Results indicate that, in general, the impact of the external reference price discrepancy on brand choice is greater than that of the internal price discrepancy. However, this varies depending upon the contextual conditions. For consumers facing a stockout condition at the time of purchase, and for deal-prone consumers, the impact of the external reference price discrepancy on brand choice is greater than that of the internal reference price discrepancy. However, for consumers not facing a stockout condition, and for non-deal-prone consumers, there is no difference in the impact of the internal and external reference price discrepancy on brand choice. Also, the impact of both the external and internal reference price discrepancy on brand choice is greater for consumers not facing a stockout condition at the time of purchase relative to facing a stockout condition, and for deal-prone consumers than for non-deal-prone consumers. Implications for pricing strategies are discussed for retailers, and limitations and extensions of this study are also provided.
Kumar, V., & Reinartz, W. (2012). Customer relationship management: Concept, strategy, and tools, Heidelberg: Springer. Click here for the abstract.
Customer relationship management (CRM) as a strategy and as a technology has gone through an amazing evolutionary journey. The initial technological approach was followed by many disappointing initiatives only to see the maturing of the underlying concepts and applications in recent years. Today, CRM represents a strategy, a set of tactics, and a technology that have become indispensible in the modern economy. This book presents an extensive treatment of the strategic and tactical aspects of customer relationship management as we know it today. It stresses developing an understanding of economic customer value as the guiding concept for marketing decisions. The goal of the book is to serve as a comprehensive and up-to-date learning companion for advanced undergraduate students, master's degree students, and executives who want a detailed and conceptually sound insight into the field of CRM.
•This comprehensive treatment of CRM strategy, concepts, and tools provides a unified perspective. Thus the reader sees the forest AND the trees.
•Numerous cases show direct application of concepts, thus making the material highly accessible and applicable.
•The latest developments in metrics, practices, and substantive domains (e.g. multi-channel management) provide readers with the state-of-the-art on this subject.
Reinartz, W. J. (2010). Understanding customer loyalty programs. In M. Mantrala & M. Krafft (Eds.), Retailing in the 21st Century. Current and Future Trends, Berlin: Springer, 409-427. Click here for the abstract.
Retailing in the new millennium stands as an exciting, complex, and critical sector of business in most developed as well as emerging economies. Today, the retailing industry is being buffeted by a number of forces simultaneously, e.g., increasing competition within and across retailing formats, the growth of online retailing, the advent of 'radio frequency identification' (RFID) technology, the explosion in customer-level data availability, the global expansion of major retail chains like Wal-Mart and METRO AG and so on. Making sense of it all is not easy, but of vital importance to retailing practitioners, analysts, and policymakers. With crisp and insightful contributions from many of the world's leading experts in retailing, "Retailing In The 21st Century" offers, in one book, a compendium of state-of-the-art, cutting-edge knowledge to guide successful retailing in the new millennium.
Reinartz, W. J., & Venkatesan, R. (2008). Decision models for customer relationship management (CRM). In B. Wierenga (Ed.), Handbook of marketing decision models, New York: Springer, 291-326. Click here for the abstract.
Marketing models is a core component of the marketing discipline. The recent developments in marketing models have been incredibly fast with information technology (e.g., the Internet), online marketing (e-commerce) and customer relationship management (CRM) creating radical changes in the way companies interact with their customers. This has created completely new breeds of marketing models, but major progress has also taken place in existing types of marketing models.
The HANDBOOK OF MARKETING DECISION MODELS presents the state of the art in marketing decision models, dealing with new modeling areas such as customer relationship management, customer value and online marketing, but also describes recent developments in other areas. In the category of marketing mix models, the latest models for advertising, sales promotions, sales management, and competition are dealt with. New developments are presented in consumer decision models, models for return on marketing, marketing management support systems, and in special techniques such as time series and neural nets. Not only are the most recent models discussed, but the book also pays attention to the implementation of marketing models in companies and to applications in specific industries.
Kumar, V., & Reinartz, W. (2006). Customer Relationship Management: A Databased Approach. New York: Wiley. Click here for the abstract.
"Customer Relationship Management: A Databased Approach" offers the promise of maximized profits for today's highly competitive businesses. This innovative book provides readers with the tools and techniques to effectively use CRM. It emphasizes the utilization of database marketing in order to build strong and profitable customer relationships. Kumar first describes how to implement database marketing and then looks at recent advances in CRM applications. Critical marketing issues like optimum resource allocation, purchase sequence, and the link between acquisition, retentions, and profitability are also examined on the basis of empirical findings.
CRM that puts the customer (not technology) first! All too often, today's companies focus on the technology of Customer Relationship Management (CRM), and lose sight of its primary goal--profitability. Offering a much-needed customer focus for the field, Kumar and Reinartz emphasize the strategic principles of customer-centric marketing that are at the heart of every successful CRM program. The text offers comprehensive coverage of CRM and its impact on various marketing activities, as well as clear explanations of databases and datamining with rigor and relevance.
Reinartz, W., & Saffert, P. (2013). Creativity in advertising: When It works and when it doesn't. Harvard Business Review, 91(6), 106-112. Click here for the abstract.
Do highly creative ads really inspire people to buy products? Studies have found that creative messages get more attention and lead to positive attitudes about the products, but there’s little evidence linking those messages to purchase behavior. To address this gap, Reinartz and Saffert developed a consumer survey approach that measures perceived creativity along five dimensions—originality, flexibility, elaboration, synthesis, and artistic value—and applied the approach in a study of 437 TV ad campaigns for 90 fast-moving consumer goods brands in Germany. The study then linked the assessments to sales figures for the products. The findings confirm that creative campaigns are, in general, more effective than other types of ads. The research also shows that the various creativity dimensions deliver different results. Elaboration, for instance, had a far more powerful effect on sales than did originality, a more commonly used dimension. Indeed, many companies focus on the wrong dimensions in their campaigns. This article reveals which product categories are best suited to creative advertising and which dimensions of creativity have the most influence on sales.
Reinartz, W., & Ulaga, W. (2008). How to sell services more profitably. Harvard Business Review, 86(5), 90. Click here for the abstract.
When products become commodities, manufacturing companies may seek to differentiate themselves with value-added services--a potentially profitable strategy. Unfortunately, companies often stumble in the effort. Reinartz and Ulaga conducted in-depth studies of 18 leading companies in a broad variety of product markets to learn what distinguished the successes from the rest. They discovered four steps to developing a profitable services capability. RECOGNIZE THAT YOU ALREADY HAVE A SERVICE COMPANY: You can identify and charge for simple services--as Merck did when it stopped quietly absorbing shipping costs. Switching services from free to fee clarifies their value for managers as well as for customers. INDUSTRIALIZE THE BACK OFFICE: To prevent delivery costs from eating up service-offering margins, build flexible service platforms, closely monitor process costs, and exploit new technologies that enable process innovations. The Swedish bearings manufacturer SKF provided off-site access to an online monitoring tool that could warn of potential failure in customers' machines. CREATE A SERVICE-SAVVY SALES FORCE: Services require longer sales cycles and, often, decisions from high up in a customer's hierarchy; what's more, product salespeople may be inimical to change. Schneider-Electric did a major overhaul of its sales organization and trained its people to switch from cost-plus pricing to value-based pricing. FOCUS ON CUSTOMERS' PROCESSES AND THE OPPORTUNITIES THEY AFFORD FOR NEW SERVICE OFFERINGS: You may need to acquire new capabilities to take advantage of those opportunities: The industrial coatings specialist PPG had to learn how painting robots function after it offered to take over Fiat's Torino paint shop. Services can both lock in customers and help acquire new accounts. They should be developed with care and attention.
Kumar, V., Venkatesan, R., & Reinartz, W. (2006). Knowing what to sell, when, and to whom. Harvard Business Review, 84(3), 131-137. Click here for the abstract.
Despite an abundance of data, most companies do a poor job of predicting the behavior of their customers. In fact, the authors' research suggests that even companies that take the greatest trouble over their predictions about whether a particular customer will buy a particular product are correct only around 55% of the time--a result that hardly justifies the costs of having a CRM system in the first place. Businesses usually conclude from studies like this that it's impossible to use the past to predict the future, so they revert to the timeworn marketing practice of inundating their customers with offers. But as the authors explain, the reason for the poor predictions is not any basic limitation of CRM systems or the predictive power of past behavior, but rather of the mathematical methods that companies use to interpret the data. The authors have developed a new way of predicting customer behavior, based on the work of the Nobel Prize-winning economist Daniel McFadden, that delivers vastly improved results. Indeed, the methodology increases the odds of successfully predicting a specific purchase by a specific customer at a specific time to about 85%, a number that will have a major impact on any company's marketing ROI. What's more, using this methodology, companies can increase revenues while reducing their frequency of customer contact-evidence that overcommunication with customers may actually damage a company's sales.
Thomas, J. S., Reinartz, W., & Kumar, V. (2003). Getting the most out of all your customers. Harvard Business Review, 82(7-8), 116-123. Click here for the abstract.
Companies spend billions of dollars on direct marketing, targeting individual customers with ever more accuracy. Yet despite the power of the myriad data-collecting and analytical tools at their disposal, they're still having trouble optimizing their direct-marketing investments. Many marketers try to minimize costs by pursuing only those customers who are cheap to find and cheap to keep. Others try to get the most customers they possibly can and keep all of them for as long as they can. But a customer need not be loyal to be highly profitable, and many loyal customers turn out to be highly unprofitable. Companies can get more out of direct marketing if they see it as a single system for generating profits than if they try to maximize performance measures at each stage of the process. This article describes a tool for doing just that. Called ARPRO (Allocating Resources for Profits), the tool is essentially a complex regression analysis that can estimate the impact of a company's direct-marketing investments on the profitability of its customer pool. With data that companies already gather, the tool can show managers how much to spend on acquisition versus retention and even what percentage of their funds they should allocate to the different direct-marketing channels. Using the model, companies can easily see that even small deviations from the optimal levels of customer profitability are expensive. Applying it to one catalog retailer showed, for instance, that a 10% reduction in marketing costs would lead to a 1.8 million dollar drop in long-term customer profits. Conversely, spending 69% less on marketing would actually increase average customer profitability at one B2B service provider by 42%. What's more, the tool can show that finding the optimal balance between investments in acquisition and retention can be more important than finding the optimum amount to invest overall.
Zeng, M., & Reinartz, W. (2003). Beyond online search: The road to profitability. California Management Review, 45(2), 107-130. Click here for the abstract.
The Internet brings three potential benefits to consumers: increased search efficiency, better product evaluation, and enhanced transaction convenience. However, actual benefits can vary a great deal across different product categories. In particular, difficulties in performing evaluation online have significantly reduced the volume of online transaction in a number of important product categories. Ignoring the differentiated impact of the Internet at different stages of the consumer decision-making process is a major reason for the failure of many previous online initiatives. The article identifies five e-business models that best utilize the inherent advantages of the Internet at different stages and matches what the Internet can offer with what customers truly value.
Reinartz, W., & Kumar, V. (2002). The mismanagement of customer loyalty. Harvard Business Review, 80(7), 86-95. Click here for the abstract.
Who wouldn't want loyal customers? Surely they should cost less to serve, they'd be willing to pay more than other customers, and they'd actively market your company by word of mouth, right? Maybe not. Careful study of the relationship between customer loyalty and profits plumbed from 16,000 customers in four companies' databases tells a different story. The authors found no evidence to support any of these claims. What they did find was that the link between customers and profitability was more complicated because customers fall into four groups, not two. Simply put: Not all loyal customers are profitable, and not all profitable customers are loyal. Traditional tools for segmenting customers do a poor job of identifying that latter group, causing companies to chase expensively after initially profitable customers who hold little promise of future profits. The authors suggest an alternative approach, based on well-established "event-history modeling" techniques, that more accurately predicts future buying probabilities. Armed with such a tool, marketers can correctly identify which customers belong in which category and market accordingly. The challenge in managing customers who are profitable but disloyal--the "butterflies"--is to milk them for as much as you can while they're buying from you. A softly-softly approach is more appropriate for the profitable customers who are likely to stay loyal--your "true friends." As for highly loyal but not very profitable customers--the "barnacles"--you need to find out if they have the potential to spend more than they currently do. And, of course, for the "strangers"--those who generate no loyalty and no profits--the answer is simple: Identify early and don't invest anything.
Reinartz, W. J., & Krafft, M. (2001). Überprufung des Zusammenhangs von Kundenbindungsdauer und Kundenertragswert. Zeitschrift für Betriebswirtschaft, 71(11), 1263-1282. Click here for the abstract.
Gemeinhin wird unterstellt, dass ein positiver Zusammenhang zwischen Kundenbindung und Kundenertragswert besteht. Dieser Effekt ist bisher jedoch kaum empirisch bestätigt worden. Das Ziel dieser Arbeit ist, den Zusammenhang von Kundenbindung (im Sinne der Kundenlebenszeit) und Kundenertragswert empirisch zu prüfen. Die Datengrundlage für diese Arbeit stammt aus dem Versandhandelsbereich. Die Resultate zeigen, dass hochprofitable Segmente existieren, die sich aus loyalen oder transaktionalen Kunden zusammensetzen.
Es wird gezeigt, dass Kundenbeziehungen existieren, die hohe Ertragswerte, niedrige Mailing-Kosten pro Umsatz und hohe mittlere Preise je bestelltem Artikel bei kurzen Bindungsdauern aufweisen. Diese Befunde sind sowohl für die Unternehmenspraxis als auch für die Forschung von weitreichender Bedeutung. Die Befunde implizieren insbesondere, dass bei der Gestaltung kundenspezifischer Marketing-Maßnahmen die zeitliche Dimension (Kundenstatus) berücksichtigt werden muss.
Götz, O., Hoyer, W. D., Krafft, M., & Reinartz, W. J. (2006). Der Einsatz von Customer Relationship Management zur Steuerung von Kundenzufriedenheit. In C. Homburg (Ed.), Kundenzufriedenheit, 6th ed., Wiesbaden: Gabler, 409-430. Click here for the abstract.
Kundenzufriedenheit nimmt heute in den Zielsystemen vieler Unternehmen der verschiedensten Branchen eine führende Stelle ein. Beträchtliche Ressourcen werden in Programme zur Steigerung der Kundenzufriedenheit investiert. Die Autoren präsentieren praxisnah und wissenschaftlich fundiert den State of the Art zum Thema Kundenzufriedenheit: - Kundenzufriedenheit als strategischer Erfolgsfaktor - Instrumente zu Messung und Management von Kundenzufriedenheit - Total Quality Management - Beschwerdemanagement - Customer Relationship Management - Erfahrungen aus ausgewählten Branchen. Die 6. Auflage wurde umfassend überarbeitet und insbesondere um die Darstellung methodischer Herausforderungen bei der Kundenzufriedenheitsmessung erweitert. Neue, zahlreiche Praxisbeispiele aus dem produzierenden Bereich sowie dem Dienstleistungssektor veranschaulichen, wie facettenreich und spannend Kundenzufriedenheit gesteigert werden kann. "Kundenzufriedenheit" richtet sich an Führungskräfte, die Kundenzufriedenheit in ihren Unternehmen ermitteln und auch managen möchten. Dozenten und Studierende der Betriebswirtschaftslehre, insbesondere mit den Schwerpunkten Marketing und Unternehmensführung, erhalten einen umfassenden Einblick.
Götz, O., Hoyer, W. D., Krafft, M., & Reinartz, W. (2005). Determinanten einer erfolgreichen CRM-Implementierung. In A. Haas & B.S. Ivens (Eds.), Innovatives Marketing, Wiesbaden: Gabler, 213-231. Click here for the abstract.
Um national und international wettbewerbsfähig zu bleiben, müssen Unternehmen ihre Innovationsfähigkeit immer stärker unter Beweis stellen. Innovationskraft setzt voraus, dass Unternehmen permanent in der Lage sind, Trends zu erkennen und Lösungen zu entwickeln, um stets eine Länge Vorsprung zu haben. Die Autoren bieten dem Leser einen Überblick über die unterschiedlichen neuen Wege, die in den verschiedenen Teilbereichen des Marketing derzeit beschritten werden.
Ausgewiesene Experten aus Wissenschaft und Praxis berichten über aktuelle Trends, Innovationen und Veränderungen im Marketing: Grundlegende Aspekte, Konsumentenverhalten, Marketingprozesse, Marketinginstrumente, Management, Institutionen.
Reinartz, W. (2013). Gefährliche Ignoranz. Harvard Business Manager, 35(8), 106-107. Click here for the abstract.
Online-Handel ist wichtig, das haben viele Unternehmen begriffen. Doch den meisten ist es noch nicht gelungen, die unterschiedlichen Distributionskanäle effektiv und harmonisch zu verzahnen. Dabei gibt es längst Werkzeuge, die dabei helfen können.
Braun, G., & Leitl, M. (2012). Eine Symphonie der Kanäle. Harvard Business Manager, 34(3), 54. Click here for the abstract.
Expertenrunde: "Wo kaufen Sie ein - Im Internet oder im Laden?"; "Was ist das innovativste Handelskonzept?" - sieben Branchen-Insider beantworten Fragen rund um den Einzelhandel.
Kaum eine Branche wurde durch das Internet ähnlich grundlegend umgekrempelt wie der Einzelhandel. Doch wer auf gute Beratung, Fachwissen und Kundenorientierung setzt, kann auch heute noch in der realen Welt ordentliche Gewinne machen - darüber sind sich Branchen-Insider einig. Anders sieht es beim persönlichen Einkaufsverhalten und den Erwartungen an den Handel der Zukunft aus. Ein Stimmungsbild.
Reinartz, W., & Saffert, P. (2012). Bitte nicht abseitig! Harvard Business Manager, 34(10), 12. Click here for the abstract.
Kreativpreise gelten als harte Währung der Werbeindustrie. Doch sind die Trophäen ein Anhaltspunkt für die auftraggebenden Unternehmen? Eine Studie belegt, dass eine Werbung, die Agenturen lieben, nicht immer auch gut für die Kunden ist.
Kumar, V., Venkatesan, R., & Reinartz, W. (2006) Der gläserne Kunde. Harvard Business Manager, 28(10), 116-126. Click here for the abstract.
Viele Manager aus Marketing und Vertrieb setzen auf das Prinzip Gießkanne - sie überschütten ihre Kunden mit Angeboten, nur um keine Chance für ein Geschäft zu verpassen, was weder effizient noch effektiv ist. Der Grund für dieses Verhalten: Die Führungskräfte verfügen nicht über geeignete Verfahren, um anhand des Verhaltens der Kunden in der Vergangenheit abzuschätzen, wann diese erneut etwas kaufen werden, um ihnen rechtzeitig das passende Angebot zu unterbreiten. Methode: Die Autoren nutzen Erkenntnisse des Nobelpreisträgers Daniel McFadden, um Kundendaten statistisch auszuwerten. Auf diese Weise können sie zuverlässiger als bisher das Kaufverhalten der Kunden vorhersagen.
Praxistest: Die Autoren haben ihre Methode bei ausgewählten Kunden eines Hightech-Konzerns und eines Finanzdienstleister angewandt. Die Verantwortlichen dort konnten so die Marketingausgaben um bis zu 30 Prozent senken - und zugleich die Umsätze erheblich steigern.
Thomas, J., Reinartz, W., & Kumar, V. (2004) Holen Sie mehr aus Ihren Kunden heraus. Harvard Business Manager, 26(11), 79-89. Click here for the abstract.
Das Problem: Viele Marketingmanager glauben, dass diejenigen Kunden die höchste Rendite bringen, die am günstigsten zu werben und zu halten sind. Als Erfolgsmaßstäbe betrachten sie isoliert die Akquisitionsrate und die Kundenbindungsdauer. Diese Strategie bringt jedoch selten die maximale Rendite. Als Ergebnis einer gründlichen Studie zeigen die Autoren, dass es vielmehr auf den optimalen Mix aus Maßnahmen zur Kundengewinnung und zur Kundenpflege ankommt. Das Modell: Die Autoren entwickelten auf der Basis ihrer Untersuchungen ein mathematisches Modell, um individuell für ein Unternehmen die optimale Höhe der Investitionen je Kunde zu bestimmen. Die Marketingmanager müssen dabei nicht viel Geld für das Sammeln von Informationen ausgeben: Sie können sich auf die Daten stützen, die sie ohnehin erheben.
Reinartz, W. & Kumar, V. (2003) Kundenpflege – aber richtig. Harvard Business Manager, 25(1), 68-78. Click here for the abstract.
Viele Unternehmen umwerben Kunden, die ihnen Verluste bescheren, und vernachlässigen andere, die Gewinne bringen. Ein millionenschwerer Fehler, so die Autoren. Um die Vertriebsstrategie zu optimieren, haben sie ein Verfahren entwickelt, mit dem Firmen das bereits vorhandene Wissen über Kunden besser nutzen können.
Falsche Annahmen: Manager glauben oft, treue Kunden seien besonders wertvoll. Sie seien eher bereit, höhere Preise zu bezahlen, und ließen sich einfacher betreuen, weil sie mit den Geschäftsprozessen des Unternehmens vertraut sind. Auf einen großen Teil der loyalen Kunden trifft das jedoch nicht zu. Sie sind sehr anspruchsvoll, kennen ihren Wert und fordern daher regelmäßig Preisnachlässe.
Richtige Strategie: Das Management sollte die Kunden je nach Profitabilität und Loyalität in vier Gruppen einteilen. Jede einzelne sollte das Management anders behandeln, um so möglichst viele ertragsstarke Kunden an sich zu binden.

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