Contributions published at Quantitative Marketing (Florian Stahl)

An increasing number of companies, headhunters, musicians, artists or other professionals use online social network services such as Facebook, LinkedIn or MySpace to increase the atten-tion on brands, products, and services. For such actors, it is therefore important to understand how networking activities and their impact on the ego-network structure affect marketing suc-cess. For example, such an understanding is beneficial for the numerous artists and music bands who promote their music and concerts on platforms such as MySpace or Facebook to attain popularity and to increase both their fan network and downloads of their songs. While recent research has identified single influential users capable of acting as multipliers for viral marketing (e.g. Iyengar, Van den Bulte, and Valente 2011) and modeled social conta-gion effects in product diffusion (e.g., Du and Kamakura 2011), we know little about how active management of friend network structures via networking activity influences the success of firms and individuals engaged in such activities. Noteworthy exceptions include Stephen and Toubia (2010) and Yoganarasimhan (2012). Stephen and Toubia (2010) show how the network structure of B2B shop can be used to predict shop performance. Yoganarasimhan (2012) analyze how the size and structure of the local network around a youtube node influence the aggregate diffusion of products seeded by it. However, Stephen and Toubia (2010) use a static framework, and both Stephen and Toubia (2010) and Yoganarasimhan (2012) do not study how marketing activities on a social network dynamically shape the network structure of the friend network and do not calibrate the short- and long-term effects of networking activities on measures of a brand's or individual's success. In this paper we empirically investigate the impact of actors networking activities and the ef-fect of the local network around a node on actor's online success (such as attention, demand or downloads). In particular, we analyze how the network activities that an actor engages in influ-ences the actor's egocentric positions within the network, and how such activities in combina-tion with these network positions impact actors online success. We use data on 440 music art-ists who actively operate profiles on an online social network and track their networking activ-ities and network positions over a period of one year. We develop a dynamic Bayesian model to analyze how such a network of music artists can drive music downloads by engaging in ac-tive communication and building of friendship activities. Personal network information is tracked monthly over a period of one year. In our Bayesian modeling approach we control for artist heterogeneity. As both network activities and network positions are potentially endoge-neous, and instrumental variables are not available readily, we use a latent instrumental variable approach to model the endogeneity of multiple network influence variables. We show that network structure has an effect on success, over and above direct effects of mar-keting activities. This implies an important long-term effect as network structures once estab-lished are self-supporting and that companies can establish profitable structures once, and reap benefits over a longer period. More specifically, our results indicate that online success is de-termined by both the social network structure and networking activities of an actor, rather than by their outside popularity. Most importantly, the drivers of online success are not limited to the size of actor’s personal friend network. Second, we derive how network structures can be developed strategically by employing specific network activities. That means we explore in which way different network activities influence sociometric network measures and we reveal successful strategies of managing friend networks by simulating the short- and long-term effects of firm's marketing activities. We discuss these and other managerial implications for re-searchers and practitioners.

The growth of online social networks and the decreasing effectiveness of traditional marketing have lead to a surge of interest in using such networks for marketing purposes. Actors embedded in such social networks are interested in understanding how to leverage the interactions and relationships among network members to increase their popularity and garner online success. In this paper we analyze how the network activities that an actor engages in influences the actor's egocentric positions within the network and how such activities in combination with these network positions eventually impact marketing success. In particular, we propose a dynamic framework and study short-term and long-term effects of networking activities on online success as well as on network positions. Our sample consists of a set of 440 music artists who actively operate profiles on multimedia online social network. Personal network information is tracked monthly over a period of one year. Our results indicate that online success is determined by both the social network structure and networking activities of the music artists rather than by unobserved factors like their outside popularity. Most importantly for marketing, acquiring new friends has a long-term impact on online success whereas communicating with friends and providing new content affect online success only in the short run. The findings of our study provide several insights into the use of personal online social networks for promoting products and services online.

The growth of online social networks and the decreasing effectiveness of traditional marketing have lead to a surge of interest in using such networks for marketing purposes. Actors embedded in such social networks are interested in understanding how to leverage the interactions and relationships among network members to increase their popularity and garner online success. In this paper we analyze how the network activities that an actor engages in influences the actor's egocentric positions within the network and how such activities in combination with these network positions eventually impact marketing success. In particular, we propose a dynamic framework and study short-term and long-term effects of networking activities on online success as well as on network positions. Our sample consists of a set of 440 music artists who actively operate profiles on multimedia online social network. Personal network information is tracked monthly over a period of one year. Our results indicate that online success is determined by both the social network structure and networking activities of the music artists rather than by unobserved factors like their outside popularity. Most importantly for marketing, acquiring new friends has a long-term impact on online success whereas communicating with friends and providing new content affect online success only in the short run. The findings of our study provide several insights into the use of personal online social networks for promoting products and services online.

The growth of social media and the decreasing effectiveness of traditional marketing have lead to a surge of interest in using corporate weblogs for marketing purposes. Despite the potential of corporate social media to increase the visibility of brands, products and services without spending millions of dollars in advertising, companies still struggle in finding an effective and traffic generating communication strategy for corporate weblogs. In this paper we analyse the impact of user-generated comments and online conversations between firms and (potential) customers on the attractiveness of corporate weblogs. In particular, we quantitatively analyze the formal as well as content-related characteristics of feedback triggered weblog conversations and their effects on weblog readership measured in the number of visitors and page views. Using a unique cross-sectional sample of corporate blogs of twelve Global Fortune 500 companies, we derive empirical insights about the impact of conversational activity on weblog traffic. The findings of our study provide several insights how micro-conversations on corporate social media such as weblogs can lead to an engagement with current as well as potential customers.

The number of product recalls increased dramatically in the last years and become a relevant research topic. In this paper, we analyse the impact of recalls on customer acquisition and customer retention in the automobile industry. Using actual purchase data of more than 700 car models in 22 different categories sold in the US between 1999 and 2008 we derive customer acquisition and customer retention rates from first-order Markov car model-switching matrices. Our results indicate that recalls influence customer acquisition and retention in opposed directions that implies that affected customers and drivers of other car models react in different way.

This paper examines the relationship between brand equity and customer acquisition, retention, and profit margin, the key components of customer lifetime value (CLV). We examine a unique database from the U.S. automobile market that combines 10 years of acquisition rate, retention rate, and customer profitability data with measures of brand equity from Young & Rubicam’s Brand Asset Valuator (BAV) over the same time period. We hypothesize and find that BAV brand equity is significantly associated with the components of CLV in expected and meaningful ways. For example, customer Knowledge of a brand has an especially strong positive relationship with all three components of CLV. Interestingly, however, Differentiation is a double-edged sword. While it is associated with higher customer profitability, it is also associated with lower acquisition and retention rates. We also find that marketing efforts exert indirect impacts on CLV through brand equity. Simulations show that changes in marketing, or exogenous changes in brand equity, can exert important effects on CLV. Overall, the findings suggest the “soft” and “hard” sides of marketing need to be managed in a coordinated fashion. We discuss these and other implications for researchers and practitioners.

The great potential offered by online social networks to attract consumer attention to brands and extend customer relationships has captured the marketer’s imagination. Consumers will join specific brand communities on online social networks and publically associate themselves with a brand, because they possess a preconceived perception of the underlying brand. We illustrate the impact of brand perception on the formation of online brand communities from a social-network perspective using individual-level network data. We show that brand perception – namely, differentiation, relevance, esteem, and knowledge – not only attracts the initial brand community, but also has an impact on the brand community’s evolution. Moreover, the network characteristics of the initial brand community are crucial for the long-term success of the brand community.

This paper studies profit-maximizing sampling and pricing of paid content for online news publishers. The key feature of the model is the twofold role of free samples which allows publishers to generate advertising revenues and simultaneously disclose editorial quality to potential subscribers. Taking customers' prior beliefs about article qualities into account and employing Bayesian updating, we derive the subscription demand and characterize the optimal number of articles offered for free as well as the subscription price for the content behind the paywall. Considering two cases where free sampling aims to persuade either all consumers to subscribe or only those with the highest willingness-to-pay, we find that is optimal for the publisher to offer a larger number of free samples when consumers underestimate product quality.

The growth of online social networks and the decreasing effectiveness of traditional marketing have lead to a surge of interest in using such networks for marketing purposes. Actors embedded in such social networks are interested in understanding how to leverage the interactions and relationships among network members to increase their popularity and garner online success. In this paper we analyze how the network activities that an actor engages in influences the actor's egocentric positions within the network and how such activities in combination with these network positions eventually impact marketing success. In particular, we study how a network of music artists can drive music downloads by engaging in active communication and building of friendship activities. Our sample consists of a set of 440 music artists who actively operate profiles on two independent online social network platforms at the same time. Personal network information on both platforms is tracked monthly over a period of one year. As network positions are endogeneous, and instrumental variables are not available readily, we use a latent instrumental variable approach to model the endogeneity of multiple network influence variables. Our results indicate that online success is determined by both the social network structure and networking activities of the music artists rather than by their outside popularity.

Firms are increasingly seeking to harness the potential of social networks for marketing purposes. Marketers are therefore interested in understanding the antecedents and consequences of relationship formation within networks and in predicting interactivity among users. In this paper we develop an integrated statistical framework for simultaneously modeling the connectivity structure of multiple relationships of different types on a common set of actors. Our modeling approach incorporates a number of distinct facets to capture both the determinants of relationships and the structural characteristics of multiplex and sequential networks. We develop hierarchical Bayesian methods for estimation and illustrate our model via two applications. The first application uses a sequential network of communications among managers involved in new product development activities and the second uses an online collaborative social network of musicians. Our applications demonstrate the benefits of modeling multiple relations jointly for both substantive and predictive purposes. We also illustrate how information in one relationship can be leveraged to predict connectivity in another relation.

This paper analyzes optimal sampling and pricing of paid content for publishers of news websites. Publishers offer free content samples both to disclose journalistic quality to consumers and to generate online advertising revenues. We examine sampling where the publisher sets the number of free sample articles and consumers select the articles of their choice. Consumerslearn from the free samples in a Bayesian fashion and base their subscription decisions on posterior quality expectations. We show thatsampling enhances subscription demand only if consumers have low quality expectations in relation to actual quality. Taking advertising and subscription revenues into account, we find that the publisher should employ either a paid-only or a free content strategy when consumers have high quality expectations. When consumers have low quality expectations, employing a sampling strategy may be optimal for the publisher.

The growth of online social networks and the decreasing effectiveness of traditional marketing have lead to a large interest in social networks. For an appropriate application of new marketing approaches marketers have to understand the impact of interactions and relationships among network members on their individual outcome and network popularity in order to use online social networks effectively in marketing. In this study we analyze networking behavior of music artists for promoting their music. Our sample consists of a set of 480 music artists who actively operate online social networks for personal success on two independent online social network platforms at the same time. Personal network information on both platforms is tracked monthly over a period of six months. Applying a count data approach we relate well-established egocentric network measures to online success. Our results indicate that online success is determined by the social network structure and networking activities of the music artists rather than by their outside popularity. Most importantly, the drivers of online success are not limited to the size of the of the artist’s personal network. The findings of our study provide several insights into the use of personal online social networks for marketing products and services.

One of the major impacts of the Internet has been the vast increase in the amount of information that became available "for free". The provision of free information, or more specifically how much information to give away for free as a viable business model, has puzzled many observers as well as managers. To study this problem, we address two related questions: First, what portion of the information good should be offered as a free sample? Second, how much should a firm charge for the full version? To address these questions, we develop an analytical model, in which a firm offers both a full version and a free sample, on which it earns advertising revenues. Taking into account customers' initial valuation (willingness-to-pay) and their experienced quality with the free version, we characterize the optimal sample portion that should be offered for free and the price of the paid version. For both cases where either free sampling aims to persuade all consumers to buy or only those with high willingness-to-pay, we find that is optimal for the firm to offer a larger free sample when customers underestimate product quality. Our model assumptions and results are generally consistent with an empirical analysis of actual firm data on the market for news. Next, we compare the models’ implications with managerial decisions and show that managers have a tendency to underestimate the impact of free samples when consumers will use them extensively in updating their expectations about product quality.

The topic of marketing accountability is of great interest to marketing researchers and professionals. In this paper, we model the impact of customer-based brand equity on customer acquisition and customer retention which can be used as the basis for calculating customer equity. Using actual purchase data of 39 automobile brands sold in the US between 1999 and 2008 we derive customer acquisition and customer retention from first-order Markov brand-switching matrices. Brand equity is defined by customer mind-set measures for all 39 brands using annual survey data provided by Young & Rubicam which contains responses from over 6,000 panel members. We consider competition by applying a market share attraction model and differentiating different degrees of loyalty. Our results indicate that customer-based brand equity is a predictor of both customer acquisition and customer retention. Furthermore, we can show that brand specific effects on acquisitions and retention can be explained by customer mind set metrics.

Firms managing products across multiple generations face the challenge of timing the introduction of new product generations. Early introductions capitalize on the current willingness-to-pay of existing customers, but may also lead to a phenomenon called leapfrogging, i.e. customers skipping a generation. In addition, early introductions cannibalize the existing product in the market and are associated with high product development costs. Based on individual replacement decisions, we develop a model to investigate the drivers of the optimal product introduction time. Our model predicts that firms which are able to reduce the effect technological progress by providing product upgrades or price reductions can significantly shift the optimal product introduction time.

Price discounts or unit premiums? Two alternative approaches to offer and design subscription tarifs. A firm can offer subscriptions of different durations with specific price discounts, the longer a customer subscribes, the lower the price per time unit. Alternatively, a firm can design and differentiate subscriptions of different periods applying the same price per time unit and offering customers of longer subscription periods a time period of free usage (premium). In this paper, we analyze, whether these two presentations are equivalent in terms of consumers’ evaluation, or, if there are any differences that have major managerial implications for firms offering subscription plans. Our results show that consumers have different expectations when talking about price discounts or unit premiums. Further, we derive implications for firms’ optimal pricing policy of subscriptions.

Models about customer lifetime value (CLV) explicitly or implicitly assume a “one-firm oneproduct” environment. We show empirically what problems occur when CLV models are used within a multi-product company. In 99.9% of the cases the summation of the product specific CLVs do not equal the directly estimated CLVs on product portfolio level. When CLVs are used to differentiate between customers, top customers on an aggregated portfolio level differ in more than 20% if estimation approaches are changed. The use of CLVs on product basis only, leads further to a systematic neglect of 30% of a firm’s true best customers.

The growth of online social networks has interested many marketing researchers. However, little research has compared multiple social networks and investigated the link between measures of network structure to commercial success. We make use of network information of online multimedia network platforms and analyze the network strategies of music artists for promoting music. Our analysis is based on 240 personal networks and relates well-established network measures to online success. Our results indicate that success is determined by the social network structure and networking activities rather than by outside popularity. The findings have implications for building successful networks for marketing purposes.

Although brand equity and customer equity are two of the most important topics to academic researchers and practitioners (Leone et al. 2006), so far little is known about the relationship between these two concepts (e.g., Berger et al. 2006; Kumar, Lemon and Parasuraman 2006). A better understanding on how customer equity is affected by changes in customer mindset is important, as it enables firms to influence key drivers of customer lifetime value and allows them to anticipate customer behavior changes before they occur. Furthermore, investments in branding could be directly linked to customer value. Such knowledge would help marketing managers to justify their marketing spending and quantify the return on marketing investment. In our paper we model the influence of customer-based brand equity on customer acquisition and retention rates following the brand equity framework of Keller (1993) and an extension of the customer valuation model of Gupta, Lehmann and Stuart (2004). We test our model empirically on a sample of ten major automobile brands in the largest European economy, Germany, and provide evidence about the multifarious impact of customer mindset on customer equity. Using customer perceptions data provided by Young & Rubicam’s Brand Asset Valuator model, the results show that high brand familiarity combined with a set of positive and unique brand associations has an effect on customer acquisition, whereas our brand attitude measure has a strong impact on customer retention. The empirical insights into the relationship between brand equity and customer equity help managers to quantify the return on marketing investment and to enhance the productivity and effectiveness of advertising campaigns. Thus, our research findings enable firms to initiate marketing actions that will help to build and maximize customer equity and thereby shareholder value.