Brand search

Consumers frequently buy the products they find most easily. This has forced manufacturers and retailers to invest in package design, shelf layouts, and expensive advertising campaigns to facilitate findability of their products. Surprisingly, there is no research in marketing that investigates how consumers localize products, which we call brand search. This dissertation investigates the brand search process and develops a statistical model that describes the eye movements of consumers while they are searching for a specific product. The proposed model uncovers the search strategies of consumers and suggests which marketing tools manufacturers and retailers may use to influence this process.

Brand Search.

Consumers frequently buy the products they find most easily. This has forced manufacturers and retailers to invest in package design, shelf layouts, and expensive advertising campaigns to facilitate findability of their products. Surprisingly, there is no research in marketing that investigates how consumers localize products, which we call brand search. This dissertation investigates the brand search process and develops a statistical model that describes the eye movements of consumers while they are searching for a specific product. The proposed model uncovers the search strategies of consumers and suggests which marketing tools manufacturers and retailers may use to influence this process.

Viral marketing can be a safe bet

Today, from a business and marketing perspective, vast numbers of customers and potential customers interact with one another through electronic and online channels that range from emails to social media hubs such as Facebook, MySpace and Twitter

A Viral Branching Model for Predicting the Spread of Electronic Word-of-Mouth

In a viral marketing campaign an organization develops a marketing message, and stimulates customers to forward this message to their contacts. Despite its increasing popularity, there are no models yet that help marketers to predict how many customers a viral marketing campaign will reach, and how marketers can influence this process through marketing activities. This paper develops such a model using the theory of branching processes. The proposed Viral Branching Model allows customers to participate in a viral marketing campaign by 1) opening a seeding email from the organization, 2) opening a viral email from a friend, and 3) responding to other marketing activities such as banners and offline advertising. The model parameters are estimated using individual-level data that become available in large quantities already in the early stages of viral marketing campaigns. The Viral Branching Model is app

Competition for attention in online social networks: Implications for seeding strategies

Many firms try to leverage consumers’ interactions on social platforms as part of their communication strategies. However, information on online social networks only propagates if it receives consumers’ attention. This paper proposes a seeding strategy to maximize information propagation while accounting for competition for attention. The theory of exchange networks serves as the framework for identifying the optimal seeding strategy and recommends seeding people that have many friends, who, in turn, have only a few friends. There is little competition for the attention of those seeds’ friends, and these friends are therefore responsive to the messages they receive. Using a game-theoretic model, we show that it is optimal to seed people with the highest Bonacich centrality. Importantly, in contrast to previous seeding literature that assumed a fixed and non-negative connectivity parameter of the Bonacich measure, we demonstrate that this connectivity parameter is negative and needs to be estimated. Two independent empirical validations using a total of 34 social media campaigns on two different large online social networks show that the proposed seeding strategy can substantially increase a campaign’s reach. The second study uses the activity network of messages exchanged to confirm that the effects are driven by competition for attention

Cross-National Logo Evaluation Analysis: An Individual Level Approach

The universality of design perception and response is tested using data collected from ten countries: Argentina, Australia, China, Germany, Great Britain, India, the Netherlands, Russia, Singapore, and the United States. A Bayesian, finite-mixture, structural-equation model is developed that identifies latent logo clusters while accounting for heterogeneity in evaluations. The concomitant variable approach allows cluster probabilities to be country specific. Rather than a priori defined clusters, our procedure provides a posteriori cross-national logo clusters based on consumer response similarity. To compare the a posteriori cross-national logo clusters, our approach is integrated with Steenkamp and Baumgartner’s (1998) measurement invariance methodology. Our model reduces the ten countries to three cross-national clusters that respond differently to logo design dimensions: the West, Asia, and Russia. The dimensions underlying design are found to be similar across countries, suggesting that elaborateness, naturalness, and harmony are universal design dimensions. Responses (affect, shared meaning, subjective familiarity, and true and false recognition) to logo design dimensions (elaborateness, naturalness, and harmony) and elements (repetition, proportion, and parallelism) are also relatively consistent, although we find minor differences across clusters. Our results suggest that managers can implement a global logo strategy, but they also can optimize logos for specific countries if desired.adaptation;standardization;Bayesian;international marketing;design;Gibbs sampling;concomitant variable;logos;mixture models;structural equation models

Cross-National Logo Evaluation Analysis: An Individual Level Approach

The universality of design perception and response is tested using data collected from ten countries: Argentina, Australia, China, Germany, Great Britain, India, the Netherlands, Russia, Singapore, and the United States. A Bayesian, finite-mixture, structural-equation model is developed that identifies latent logo clusters while accounting for heterogeneity in evaluations. The concomitant v

Brand search

Consumers frequently buy the products they find most easily. This has forced manufacturers and retailers to invest in package design, shelf layouts, and expensive advertising campaigns to facilitate findability of their products. Surprisingly, there is no research in marketing that investigates how consumers localize products, which we call brand search. This dissertation investigates the brand search process and develops a statistical model that describes the eye movements of consumers while they are searching for a specific product. The proposed model uncovers the search strategies of consumers and suggests which marketing tools manufacturers and retailers may use to influence this process

Defining eye-fixation sequences across individuals and tasks:The binocular-individual threshold (BIT) algorithm

We propose a new fully automated velocity-based algorithm to identify fixations from eye-movement records of both eyes, with individual-specific thresholds. The algorithm is based on robust minimum determinant covariance estimators (MDC) and control chart procedures, and is conceptually simple and computationally attractive. To determine fixations, it uses velocity thresholds based on the natural within-fixation variability of both eyes. It improves over existing approaches by automatically identifying fixation thresholds that are specific to (a) both eyes, (b) x- and y- directions, (c) tasks, and (d) individuals. We applied the proposed Binocular-Individual Threshold (BIT) algorithm to two large datasets collected on eye-trackers with different sampling frequencies, and compute descriptive statistics of fixations for larger samples of individuals across a variety of tasks, including reading, scene viewing, and search on supermarket shelves. Our analysis shows that there are considerable differences in the characteristics of fixations not only between these tasks, but also between individuals

Visual competition suppression during planned purchases

Online advertising can help consumers to implement their purchase intentions on shopping websites. This research tests the hypothesis that online advertising can speed-up product search by visually suppressing competing products rather than by enhancing the target product on websites that lack a systematic visual organization. First, a survey shows that searching for products on a shopping website after having clicked on an online ad is a common experience. Second, a lay-theory experiment shows that the majority of participants incorrectly predict that online ads do not affect product search but if these ads do, product search would be independent of shopping website design. Third, three eye-tracking and two search-time experiments reveal that online ads with an image of the target product improved search speed by about 25%, for websites without a systematic visual organization of products. Improved search speed was primarily due to faster rejection of competing products, because the ads helped to perceptually suppress their color features. These results provide new insights into online advertising effects, the fundamental search processes through which these accrue, and how ads can support consumers in making their planned purchases