Sensing, predicting and exploiting consumer visual attention in fast-paced marketing environments

In the attention economy, consumer attention is considered a finite, diminishing quantity acting as a currency where brands compete to attract and maintain.

Attention-Based Marketing is a relevant emerging subdiscipline of Marketing that studies consumer attention to understand and improve (visual) marketing stimuli, marketing effectiveness, and consumer behaviour by uncovering the fundamental interconnections between attention and action.

Three main challenges in this area include how to: a) efficiently measure consumer attention in fast-paced environments (e.g., in electronic marketing), b) optimise marketing stimuli for attracting consumer attention and c) democratise consumer attention data (e.g., eye-sensing data/facial expressions) for improving the experience of individual consumers, while respecting their privacy at the same time.

In-line with the above-mentioned challenges, the CONVISE project will integrate insights from the Marketing and Computer Vision disciplines to design methods for sensing, predicting, and exploiting consumer visual attention that can be used to optimise marketing effort and enhance consumer well-being, in social media advertising settings.

First, it will design video-based sensing technology for extracting reliable, market-relevant consumer visual attention maps, minimising the necessary human sensor (pre)-processing effort.

Next, it will design tools for predicting consumer attention maps from the visual advertising content, without using any sensors, to produce objective advertisement evaluation metrics that can be employed during the visual advertising content design phase.

Finally, it will experimentally evaluate the developed consumer attention prediction technology from a consumer behaviour standpoint and will develop sensing data de-identification technology, balancing between consumer privacy protection, perceived ad relevance and ad intrusiveness.