Suchergebnisse

Abstract
The adoption of new behaviors or new products is often influenced by those closest to us, but customer churn is influenced by social factors as well. An analysis of 1 million customers of a cellular company showed that customers were 79.7 % more likely to defect for each time one of their social neighbors defected. The more a customer communicated with a neighbor and the more characteristics they shared, such as age, gender or status, the more likely the customer was to follow the neighbor in canceling the service. The effect of a neighbor's defection on a focal customer's hazard of defection was strongest within the first month and decreased over time. The study shows that companies should take customers' social networks into account when attempting to predict and manage customer churn. Network-related information can substantially improve analysis of new product adoption, and the same seems true for the field of customer defection.

Although most published customer lifetime value models focus on strategic-level marketing decisions, managers also need models that enable them to make resource allocation decisions for individual customers. A common misperception among scholars and managers is that it is necessary to use individual-level customer profitability models to make such decisions. This article argues that a segment-based approach to customer profitability analysis can be a reasonable alternative to an individual model. The proposed stochastic segment-based approach retains the actionable information associated with individual-level analysis while also maintaining the simplicity of the more aggregate-level models. In this article, the authors develop such a segment-based assessment of customer profitability and then briefly describe an example of a major European retailer that successfully uses the approach to manage its customer base. Directions for future research in the area of stochastic customer equity modeling are also discussed.

Introduction -- The basic diffusion pattern of an innovation -- The whole is bigger than the sum of its (diffusion and customer lifetime value) parts -- Don't just stand there: do something! growing innovation equity through marketing actions -- Foreseeing bumps and potholes along the diffusion road -- Jumpstarting stalled adoption: getting the mainstream to take the plunge -- Survival in the presence of a rival: valuing innovations at the brand level -- Leaping ahead to valuing the next generation -- Innovation equity makes the world go round -- Making the framework "work" for you

"From drones to wearable technology to Hyperloop pods that can potentially travel more than seven hundred miles per hour, we're fascinated with new products and technologies that seem to come straight out of science fiction. But, innovations are not only fascinating, they're polarizing, as, all too quickly, skepticism regarding their commercial viability starts to creep in. And while fortunes depend on people's ability to properly assess their prospects for success, no one can really agree on how to do it, especially for truly radical new products and services. In Innovation Equity, Elie Ofek, Eitan Muller, and Barak Libai analyze how a vast array of past innovations performed in the marketplace--from their launch to the moment they became everyday products to the phase where consumers moved on to the "next big thing." They identify key patterns in how consumers adopt innovations and integrate these with marketing scholarship on how companies manage their customer base by attracting new customers, keeping current customers satisfied, and preventing customers from switching to competitors' products and services. In doing so, the authors produce concrete models that powerfully predict how the marketplace will respond to innovations, providing a much more authoritative way to estimate their potential monetary value, as well as a framework for making it possible to achieve that value."--Provided by publisher.

Affiliate programs offer affiliates referral fees in return for directing potential customers into a merchant's Web site. Affiliates are commonly paid based on the number of leads converted by the merchant into customers (pay-per-conversion) or based on the number of leads referred to the merchant (pay-per-lead). Given the prevalence of both, interesting questions for research are as follows: Why do both formats prevail? Under what conditions is one format preferred over the other? The authors find that pay-per-lead is more profitable when a merchant negotiates a separate deal with an affiliate. In this case, pay-per-conversion is not optimal for the affiliation alliance because it leads to suboptimal pricing by the merchant. In contrast, pay-per-lead is less profitable than pay-per-conversion for a merchant that works with a large number of affiliates all under the same terms because it is susceptible to bogus referrals that cannot be converted into customers.

Customer profitability models have evolved into an important strategic tool for marketers in recent years. Traditional customer profitability models implicitly assume that customers can be valued in isolation from one another and that social interactions can be ignored. The authors show that these conventional models may be inappropriate for markets involving new products or services because they fail to account for the social effects (e.g., word of mouth and imitation) that can influence future customer acquisitions. They show how the impact of a lost customer on the profitability of the firm depends on (a) whether the customer defects to a competing firm or disadopts the technology altogether and (b) when the customer disadopts the technology—distinctions often overlooked in conventional models. The results demonstrate how the value of a lost customer changes throughout the product life cycle, showing that the loss of an early adopter costs the firm much more than the loss of a later adopter.

The increasing emphasis on understanding the antecedents and consequences of customer-to-customer (C2C) interactions is one of the essential developments of customer management in recent years. This interest is driven much by new online environments that enable customers to be connected in numerous new ways and also supply researchers' access to rich C2C data. These developments present an opportunity and a challenge for firms and researchers who need to identify the aspects of C2C research on which to focus, as well as develop research methods that take advantage of these new data. The aim here is to take a broad view of C2C interactions and their effects and to highlight areas of significant research interest in this domain. The authors look at four main areas: the different dimensions of C2C interactions; social system issues related to individuals and to online communities; C2C context issues including product, channel, relational and market characteristics; and the identification, modeling, and assessment of business outcomes of C2C interactions.