Segmentando el mercado de internautas atendiendo a su nivel de afinidad: (I)fuerte, (II)medio y (III)débil

Esta investigación pretende confrontar el Marketing con Causa con el Marketing de Afinidad. Para ello se descompone la audiencia de una campaña de Marketing con Causa viral en segmentos de internautas con distinto nivel de afinidad: i) fuerte (con experiencia previa de marca y de causa); ii) medio (con experiencia previa o de marca o de causa); iii) débil (sin experiencia previa ni de marca ni de causa). El objetivo es justificar la utilidad de este criterio como vía para optimizar el resultado de la comunicación segmentada. Con dicho fin, se ha estudiado un caso real planteado de forma experimental midiendo las actitudes de una muestra de 276 internautas antes y después de visualizar un spot viral de una marca de alimentación animal que fomenta la adopción de mascotas. Mediante el análisis ANOVA se comprobó que existen diferencias significativas en la respuesta de los tres segmentos identificados en lo que a actitudes previas y posteriores a la campaña respecta.This research tries to compare Cause-Related Marketing with Affinity Marketing. To get this goal, the global audience of a viral Cause-Related Marketing campaign is divided in internet user segments with different affinity level: i) strong (with previous brand and cause experience); ii) intermediate (with previous brand or cause experience); iii) weak (without previous experiences with neither the brand nor the social cause). The aim is to justify the usefulness of this guideline in order to optimize the result of targeted communication. An experimental approach of a real case study is used by measuring the attitudes of a 276 internet users sample before and after the viewing of a pet food brand viral ad that promotes pet adoption. An ANOVA analysis methodology has let us to verify that significant differences exist between the three segments regarding to their previous and following attitudes to the campaign

Pioneers of Influence Propagation in Social Networks

With the growing importance of corporate viral marketing campaigns on online social networks, the interest in studies of influence propagation through networks is higher than ever. In a viral marketing campaign, a firm initially targets a small set of pioneers and hopes that they would influence a sizeable fraction of the population by diffusion of influence through the network. In general, any marketing campaign might fail to go viral in the first try. As such, it would be useful to have some guide to evaluate the effectiveness of the campaign and judge whether it is worthy of further resources, and in case the campaign has potential, how to hit upon a good pioneer who can make the campaign go viral. In this paper, we present a diffusion model developed by enriching the generalized random graph (a.k.a. configuration model) to provide insight into these questions. We offer the intuition behind the results on this model, rigorously proved in Blaszczyszyn & Gaurav(2013), and illustrate them here by taking examples of random networks having prototypical degree distributions - Poisson degree distribution, which is commonly used as a kind of benchmark, and Power Law degree distribution, which is normally used to approximate the real-world networks. On these networks, the members are assumed to have varying attitudes towards propagating the information. We analyze three cases, in particular - (1) Bernoulli transmissions, when a member influences each of its friend with probability p; (2) Node percolation, when a member influences all its friends with probability p and none with probability 1-p; (3) Coupon-collector transmissions, when a member randomly selects one of his friends K times with replacement. We assume that the configuration model is the closest approximation of a large online social network, when the information available about the network is very limited. The key insight offered by this study from a firm's perspective is regarding how to evaluate the effectiveness of a marketing campaign and do cost-benefit analysis by collecting relevant statistical data from the pioneers it selects. The campaign evaluation criterion is informed by the observation that if the parameters of the underlying network and the campaign effectiveness are such that the campaign can indeed reach a significant fraction of the population, then the set of good pioneers also forms a significant fraction of the population. Therefore, in such a case, the firms can even adopt the naive strategy of repeatedly picking and targeting some number of pioneers at random from the population. With this strategy, the probability of them picking a good pioneer will increase geometrically fast with the number of tries

Studying Paths of Participation in Viral Diffusion Process

Authors propose a conceptual model of participation in viral diffusion process composed of four stages: awareness, infection, engagement and action. To verify the model it has been applied and studied in the virtual social chat environment settings. The study investigates the behavioral paths of actions that reflect the stages of participation in the diffusion and presents shortcuts, that lead to the final action, i.e. the attendance in a virtual event. The results show that the participation in each stage of the process increases the probability of reaching the final action. Nevertheless, the majority of users involved in the virtual event did not go through each stage of the process but followed the shortcuts. That suggests that the viral diffusion process is not necessarily a linear sequence of human actions but rather a dynamic system.Comment: In proceedings of the 4th International Conference on Social Informatics, SocInfo 201

Success Factors in Mobile Viral Marketing: A Multi-Case Study Approach

A prior study showed that mobile viral marketing is an important issue of mobile marketing. Using a multicase study research approach, we introduce a typology of four standard types of mobile viral marketing and extract eight success factors for this new form of marketing. As a final step, we structure the relationship between both, showing success factors’significance in different standard types and deriving a success factor framework. We conclude with a consideration of research implications.

Digital Food Marketing to Children and Adolescents: Problematic Practices and Policy Interventions

Examines trends in digital marketing to youth that uses "immersive" techniques, social media, behavioral profiling, location targeting and mobile marketing, and neuroscience methods. Recommends principles for regulating inappropriate advertising to youth

Interactive Food and Beverage Marketing: Targeting Children and Youth in the Digital Age

Looks at the practices of food and beverage industry marketers in reaching youth via digital videos, cell phones, interactive games and social networking sites. Recommends imposing governmental regulations on marketing to children and adolescents

The Multidimensional Study of Viral Campaigns as Branching Processes

Viral campaigns on the Internet may follow variety of models, depending on the content, incentives, personal attitudes of sender and recipient to the content and other factors. Due to the fact that the knowledge of the campaign specifics is essential for the campaign managers, researchers are constantly evaluating models and real-world data. The goal of this article is to present the new knowledge obtained from studying two viral campaigns that took place in a virtual world which followed the branching process. The results show that it is possible to reduce the time needed to estimate the model parameters of the campaign and, moreover, some important aspects of time-generations relationship are presented.Comment: In proceedings of the 4th International Conference on Social Informatics, SocInfo 201