Bernd Skiera

The Impact of New Media on Customer Relationships

Recent years have witnessed the rise of new media channels such as Facebook, YouTube, Google, and Twitter, which enable customers to take a more active role as market players and reach (and be reached by) almost everyone anywhere and anytime. These new media threaten long established business models and corporate strategies, but also provide ample opportunities for growth through new adaptive strategies. This paper introduces a new ‘‘pinball’’ framework of new media’s impact on relationships with customers and identifies key new media phenomena which companies should take into account when managing their relationships with customers in the new media universe. For each phenomenon, we identify challenges for researchers and managers which relate to (a) the understanding of consumer behavior, (b) the use of new media to successfully manage customer interactions, and (c) the effective measurement of customers’ activities and outcomes.

Seeding Strategies for Viral Marketing: An Empirical Comparison

Seeding strategies have strong influences on the success of viral marketing campaigns, but previous studies using computer simulations and analytical models have produced conflicting recommendations about the optimal seeding strategy. This study compares four seeding strategies in two complementary small-scale field experiments, as well as in one real-life viral marketing campaign involving more than 200,000 customers of a mobile phone service provider. The empirical results show that the best seeding strategies can be up to eight times more successful than other seeding strategies. Seeding to well-connected people is the most successful approach because these attractive seeding points are more likely to participate in viral marketing campaigns. This finding contradicts a common assumption in other studies. Well-connected people also actively use their greater reach but do not have more influence on their peers than do less well-connected people.

Internet-Based Virtual Stock Markets for Business Forecasting

The application of Internet-based virtual stock markets (VSMs) is an additional approach that can be used to predict short- and medium-term market developments. The basic concept involves bringing a group of participants together via the Internet and allowing them to trade shares of virtual stocks. These stocks represent a bet on the outcome of future market situations, and their value depends on the realization of these market situations. In this process, a VSM elicits and aggregates the assessments of its participants concerning future market developments. The aim of this article is to evaluate the potential use and the different design possibilities as well as the forecast accuracy and performance of VSMs compared to expert predictions for their application to business forecasting. After introducing the basic idea of using VSMs for business forecasting, we discuss the different design possibilities for such VSMs. In three real-world applications, we analyze the feasibility and forecast accuracy of VSMs, compare the performance of VSMs to expert predictions, and propose a new validity test for VSM forecasts. Finally, we draw conclusions and provide suggestions for future research.

Dashboards as a service: why, what, how, and what research is needed?

Recent years have seen the introduction of a “marketing dashboard” that brings the firm’s key marketing metrics into a single display. Service firms across industries have created such dashboards e...Recent years have seen the introduction of a “marketing dashboard” that brings the firm’s key marketing metrics into a single display. Service firms across industries have created such dashboards either by themselves or together with a dashboard service provider. This article examines the reasons for this development and explains what dashboards are, how to develop them, what drives their adoption, and which academic research is needed to fully exploit their potential. Overcoming the challenges faced in dashboard development and operation provides many opportunities for marketing to exercise a stronger influence on top management decisions. The article outlines five stages of dashboard development and discusses the relationships among demand for dashboards, supply of dashboards, and the implementation process in driving adoption and use of dashboard systems. Key topics for future research include metrics selection, relationships among metrics, and the ultimate question of whether dashboards provide sufficient benefits to justify their adoption.

Not all Fun and Games: Viral Marketing for Utilitarian Products

The success of products such as FarmVille has prompted many firms to engage in viral marketing on Facebook and other social media websites. Yet is the viral marketing approach adopted for games suitable for other, more utilitarian products? This study aims to answer questions that link product characteristics and contexts to viral marketing success: Should primarily utilitarian products rely on the same sharing mechanisms for their viral marketing campaigns as less utilitarian products? If not, why is this the case, and how should viral marketing for primarily utilitarian products differ? This empirical study analyzes the Facebook viral marketing campaigns of 751 products and reveals that the same sharing mechanism that made FarmVille so successful is the worst possible mechanism for promoting primarily utilitarian products. These findings are in line with theory from social psychology: because consumers do not visit Facebook to learn about utilitarian products, they rely on simple cues and heuristics to process viral marketing messages about these products. This study thus contributes to literature on viral marketing in general and sharing mechanisms in particular; it also offers practical, hands-on recommendations to marketing managers in charge of designing viral marketing campaigns for both more and less utilitarian products.

Linking Customer and Financial Metrics to Shareholder Value: The Leverage Effect in Customer-Based Valuation

Customers are the most important assets of most companies, such that customer equity has been used as a proxy for shareholder value. However, linking customer metrics to shareholder value without considering debt and non-operating assets ignores their effects on relative changes in customer equity and leads to biased estimates. In developing a new theoretical framework for customer-based valuation, grounded in valuation theory, this article links the value of all customers to shareholder value and introduces a new leverage effect that can translate percentage changes in customer equity into shareholder value. The average leverage effect in more than 2000 companies across ten years is 1.55, which indicates that a 10% increase in customer equity is amplified to a 15.5% increase in shareholder value. This research also compares the influence of customer and financial metrics on shareholder value. The findings challenge previous notions about the dominant effect of the retention rate and underline the importance of predicting the number of future acquired customers for a company.

Data‐driven services marketing in a connected world

Purpose – The purpose of this paper is to provide insights into the benefits of data-driven services marketing and provide a conceptual framework for how to link traditional and new sources of customer data and their metrics. Linking data and metrics to strategic and tactical business insights and integrating a variety of metrics into a forward-looking dashboard to measure marketing ROI and guide future marketing spend is explored. Design/methodology/approach – A detailed synthesis of the literature is conducted and contemporary sources of marketing data are categorized into traditional, digital and neurophysiological. The benefits and drawbacks of each data type are described and advantages of integrating different sources of data are proposed. Findings – The findings point to the importance and untapped potential of data in its ability to inform tactical and strategic marketing decisions. Future challenges, including top management support, ethical considerations and developing data and analytic capabilities, are discussed. Practical implications – The results demonstrate the need for executive service marketing dashboards that include key metrics that are service-relevant, complementary and forward-looking, with proven linkages to business outcomes. Originality/value – This paper provides a synthesis of data-driven services marketing and the value of traditional and contemporary metrics. Since the true potential of data-driven service management in a connected world is still largely unexplored, this paper also delineates fruitful avenues for future research

The Benefits of Bundling Strategies

This paper analyzes the effects of three bundling strategies — unbundling, mixed bundling, and pure bundling — on profit and sales, using a simulation study based on a model by Schmalensee (1984). The analysis shows under what conditions which strategy is the most profitable, how large the profit and sales differentials are for each strategy, and what characteristics the corresponding price structures have. Based on our results, we explain the differences observed in the study and derive a set of implications for practical price structuring.

Willingness-to-pay estimation with choice-based conjoint analysis: Addressing extreme response behavior with individually adapted designs

The increasing consideration of behavioral aspects in operations management models has prompted greater use of choice-based conjoint (CBC) studies in operations research. Such studies can elicit consumers’ willingness to pay (WTP), a core input for many optimization models. However, optimization models can yield valid results only if consumers’ WTP is estimated accurately. A simulation study and two field studies show that extreme response behavior in CBC studies, such that consumers always or never choose the no-purchase option, harms the validity of WTP estimates. Reporting the share of consumers who always and never select the no-purchase option allows for detecting extreme response behavior. This study suggests an individually adapted design that avoids extreme response behavior and thus significantly improves WTP estimation accuracy.

Prediction Markets as institutional forecasting support systems

An attractive feature of Prediction Markets (PMs) is that they provide economic incentives for informants to share unique information. It is unclear whether PMs are appropriate for applications with few knowledgeable informants as is the case for most institutional forecasting tasks. Hence, we compare the performance of small PMs with traditional judgment-based forecasting approaches. Our results show that forecasts from small PMs outperform traditional approaches in settings of high information-heterogeneity (i.e., where the amount of unique information possessed by informants is relatively high) and are no worse in settings of low information-heterogeneity.