No abstract

The three key ad elements (brand, pictorial, and text) each have unique superiority effects on attention to advertisements, which are on par with many commonly held ideas in marketing practice. This is the main conclusion of an analysis of 1363 print advertisements tested with infrared eye-tracking methodology on more than 3600 consumers. The pictorial is superior in capturing attention, independent of its size. The text element best captures attention in direct proportion to its surface size. The brand element most effectively transfers attention to the other elements. Only increments in the text element's surface size produce a net gain in attention to the advertisement as a whole. The authors discuss how their findings can be used to render more effective decisions in advertising.

The authors provide a critical examination of marketing analytics methods by tracing their historical development, examining their applications to structured and unstructured data generated within or external to a firm, and reviewing their potential to support marketing decisions. The authors identify directions for new analytical research methods, addressing (1) analytics for optimizing marketing-mix spending in a data-rich environment, (2) analytics for personalization, and (3) analytics in the context of customers’ privacy and data security. They review the implications for organizations that intend to implement big data analytics. Finally, turning to the future, the authors identify trends that will shape marketing analytics as a discipline as well as marketing analytics education.

The number of brands in the marketplace has vastly increased in the 1980s and 1990s, and the amount of money spent on advertising has run parallel. Print advertising is a major communication instrument for advertisers, but print media have become cluttered with advertisements for brands. Therefore, it has become difficult to attract and keep consumers' attention. Advertisements that fail to gain and retain consumers' attention cannot be effective, but attention is not sufficient: Advertising needs to leave durable traces of brands in memory. Eye movements are eminent indicators of visual attention. However, what is currently missing in eye movementresearch is a serious account of the processing that takes place to store information in long-term memory. We attempt to provide such an account through the development of a formal model. We model the process by which eye fixations on print advertisements lead to memory for the advertised brands, using a hierarchical Bayesian model, but, rather than postulating such a model as a mere data-analysis tool, we derive it from substantive theory on attention and memory. The model is calibrated to eye-movement data that are collected during exposure of subjects to ads in magazines, and subsequent recognition of the brand in a perceptual memory task. During exposure to the ads we record the frequencies of fixations on three ad elements; brand, pictorial and text and, during the memory task, the accuracy and latency of memory. Thus, the available data for each subject consist of the frequency of fixations on the ad elements and the accuracy and the latency of memory. The model that we develop is grounded in attention and memory theory and describes information extraction and accumulation during ad exposure and their effect on the accuracy and latency of brand memory. In formulating it, we assume that subjects have different eye-fixation rates for the different ad elements, because of which a negative binomial model of fixation frequency arises, and we specify the influence of the size of the ad elements. It is assumed that the number of fixations, not their duration, is related to the amount of information a consumer extracts from an ad. The information chunks extracted at each fixation are assumed to be random, varying across ads and consumers, and are estimated from the observed data. The accumulation of information across multiple fixations to the ad elements in long-term memory is assumed to be additive. The total amount of accumulated information that is not directly observed but estimated using our model influences both the accuracy and latency of subsequent brand memory. Accurate memory is assumed to occur when the accumulated information exceeds a threshold that varies randomly across ads and consumers in a binary probit-type of model component. The effect of two media-planning variables, the ad's serial position in a magazine and the ad's location on the double page, on the brand memory threshold are specified. We formulate hypotheses on the effects of ad element surfac...