Forecasting in marketing

With the advent of advanced data collection techniques, there is an increased interest in using econometric models to support decisions in marketing. Due to the sometimes specific nature of variables in marketing, the discipline uses econometric models that are rarely, if ever, used elsewhere. This chapter deals with techniques to derive forecasts from these models. Due to the intrinsic non-linear nature of these models, these techniques draw heavliy on simulation techniques.marketing;forecasting;unobserved heterogeneity;Koyck model;attraction model;Bass model

Forecasting in marketing

With the advent of advanced data collection techniques, there is an increased interest in using econometric models to support decisions in marketing. Due to the sometimes specific nature of variables in marketing, the discipline uses econometric models that are rarely, if ever, used elsewhere. This chapter deals with techniques to derive forecasts from these models. Due to the intrinsic non-linear nature of these models, these techniques draw heavliy on simulation techniques

Do your friends make you buy this brand?: Modeling social recommendation with topics and brands

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Creating Social Contagion through Viral Product Design: A Randomized Trial of Peer Influence in Networks

We examine how firms can create word of mouth peer influence and social contagion by incorporating viral features into their products. Word of mouth is generally considered to more effectively promote peer influence and contagion when it is personalized and active. Unfortunately, econometric identification of peer influence is non-trivial. We therefore use a randomized field experiment to test the effectiveness of passive-broadcast and active-personalized viral messaging capabilities in creating peer influence and social contagion among the 1.4 million friends of 9,687 experimental users. Surprisingly, we find that passive-broadcast viral messaging generates a 246% increase in local peer influence and social contagion, while adding active-personalized viral messaging only generates an additional 98% increase in contagion. Although active-personalized messaging is more effective per message and is correlated with more user engagement and product use, it is used less often and therefore generates less total peer adoption in the network than passive-broadcast messaging

AN OFFER THEY CANNOT REFUSE: A Behavioural Approach to Stimulating Consumer Demand for Innovations in the Telecommunications Sector

Mobile advertising (m-advertising) is one of the most exciting new research areas in the marketing field. The personal, always-on and always-at-hand nature of a mobile phone, its interactive features, combined with its near universal ubiquity give the mobile device unrivalled potential as an advertising platform. In addition, mobile phone operators are uniquely positioned to further enhance its potential- their real-time access to customers’ demographic, geographic and historical data enables them not only to help retailers establish a strong electronic presence but also to allow them to customise advertising content to target specific people in specific situations. With the growing awareness of these advantages, retailers are increasingly looking to integrate m-advertising into their marketing communications. However, turning a mobile phone into an effective advertising medium poses a formidable challenge as prior consumer permission is a legal prerequisite for m-advertising practices. It is apparent that to fully embrace the potential of m-advertising, retailers need to identify the precise factors that influence consumer opt-in choice. This thesis is unique in investigating factors influencing consumer opt-in choice with the ultimate purpose of developing an effective solution to reliably stimulate opt-ins. To this end, it adopts a radical behaviourist perspective, applying a Behavioural Perspective Model (BPM) in order to explore the influence of both contextual and consumer-related factors, account for their interactive effects and, most importantly, focus on the actual opt-in choice rather than the pre-behavioural variables of “willingness” and “intention” commonly used in previous m-advertising studies. Additionally, accounting for the fact that m-advertising is a relatively new service, this thesis integrates consumer innovativeness variable into the BPM and explores its respective influence on the opt-in choice. The thesis builds upon three consecutive empirical projects, each having its own objective: Project One conducts a preliminary exploratory investigation of the opt-in phenomenon; Project Two measures the factors identified systematically; and Project Three experimentally tests the instrument developed. Overall, the results of this investigation suggest that consumer opt-in choice is largely contingency-shaped and is affected by numerous contextual variables. In particular, among the BPM components, consumers’ past experience with m-advertising and/or m-advertisers, utilitarian benefits associated with m-advertising and its content characteristics are the three most important opt-in choice determinants. Of particular significance is the consumer situation, which has been proven to greatly affect opt-in likelihood. The importance of the newly incorporated innovativeness factor is two-fold. First, it functions as one of the strongest direct predictors of the opt-in choice. Second, it serves in a moderating capacity, further amplifying the positive effects of other choice antecedents in the BPM. On this basis, it is concluded that the opt-in choice is amenable to the behaviourist explanation and that in new service contexts the innovativeness factor further contributes to the BPM’s predictive capacity