The limits of predictive eye tracking in shopper marketing

In the dynamic world of shopper marketing, understanding shopper and shopping behavior is critical. A proliferation of predictive eye tracking tools have gained traction for their ability to forecast where shoppers are likely to focus their visual attention within a design.

These tools offer valuable insights into the initial 'See' stage of the purchase funnel. However, they fall short in predicting subsequent behaviors, such as brand appeal, engagement, and ultimately, the decision to purchase.

Why real eye tracking and behavioral science audits offer superior insights 

A more comprehensive approach, integrating real eye tracking with behavioral science audits, provides deeper analysis of the entire purchase funnel:

1. See

2. Appeal

3. Engage

4. Buy

This article explores the scientific limitations of predictive eye tracking tools and argues why combining real eye tracking with psychological analysis offers superior insights for measuring in-store displays, packaging, and other shopper marketing interventions.

The science behind eye tracking 

Eye tracking technology records the movement and fixation points of the eyes, providing data on where individuals look, how long they look, and the sequence of their gaze. Real eye tracking involves the use of hardware such as
wearable eye trackers or screen-based eye trackers wearable eye trackers or screen-based eye trackers equipped with cameras that track eye movements in real-time. This method captures natural shopping behavior in realistic shopping environments. Predictive eye tracking, by contrast, relies on algorithms trained on visual data to estimate attention distribution across a design. These tools, like Tobii Pro Lab, attempt to replicate human visual attention using heatmaps and gaze plots without real-time human input. While cheaper and quicker, predictive tools sacrifice depth and accuracy for convenience.

Limitations of predictive eye tracking 

1. Attention does not equal engagement 

Capturing a shopper's gaze does not necessarily lead to interaction or purchase. Research shows that attention is a necessary but insufficient condition for action. A study by Pieters and Warlop (1999) demonstrated that attention to advertising is often incidental and does not always translate to memory retention or brand recall. Predictive models can indicate where attention might be directed but cannot assess the depth of cognitive processing or emotional engagement that follows.

2. Oversimplification of complex behavior 

Predictive eye tracking focuses solely on visual attention without measuring the emotional responses or cognitive evaluations that drive purchasing decisions. This limitation restricts the ability to understand why certain elements attract attention and how they influence shopping behavior.

A study conducted by Wedel and Pieters (2008) found that predictive eye tracking tools frequently misestimate areas of interest because they cannot account for task-specific searches or the intentional ignoring of certain stimuli, such as logos or repetitive ads. 

3. Inability to measure emotional and cognitive responses 

Predictive eye tracking focuses solely on visual attention without measuring the emotional responses or cognitive evaluations that drive purchasing decisions. This limitation restricts the ability to understand why certain elements attract attention and how they influence shopping behavior. 

Research published in the Journal of Shopper Research (Bettman et al., 1998) highlights that shopper decision-making is heavily influenced by affective responses. Predictive models that ignore these emotional components risk overestimating the effectiveness of visual stimuli. 

The superiority of real eye tracking combined with behavioral science audits 

To overcome these limitations, integrating real eye tracking data with behavioral science audits offers a more holistic understanding of shopping behavior throughout the purchase funnel.

1. Comprehensive analysis 

Real eye tracking studies capture actual visual behavior, providing insights into both where shoppers look and how they process information. When combined with behavioral science principles, this approach evaluates designs against psychological factors influencing decision-making, such as emotional resonance and cognitive load.

Behavioral science audits incorporate psychological theories to understand how shoppers perceive, interpret, and respond to marketing stimuli. This method assesses not only what shoppers see but also why they engage with certain elements and how these interactions influence purchasing decisions.

2. Actionable insights beyond attention 

While predictive tools highlight areas of attention, they do not explain the underlying reasons. Behavioral science audits delve into the psychological drivers behind shopper actions, offering recommendations to enhance visibility, appeal, engagement, and sales.

For example, a behavioral audit might reveal that a product's packaging is highly visible but fails to convert due to confusing messaging or poor emotional appeal. Real eye tracking data combined with psychological insights can inform strategic changes that improve not only visibility but also brand perception and purchase intent.

3. Enhanced predictive power for purchasing decisions 

By understanding the emotional and cognitive responses elicited by a design, marketers can better predict and influence purchasing behavior. This approach moves beyond mere attention metrics to assess how design elements contribute to brand perception and the likelihood of purchase.

Studies show that shoppers are more likely to purchase products that evoke positive emotional responses. A study by Poole and Ball (2006) found that eye tracking data, when combined with emotional metrics, provided stronger predictions of purchasing behavior than attention data alone. 

Case studies and evidence 

Case Study 1: Non-fit messaging 

A study published in Frontiers in Psychology demonstrated that non-fit messaging impacts attention, attitudes, and choice. Eye tracking evidence showed that messages incongruent with shopper expectations received attention but failed to drive engagement or purchase. This highlights the importance of aligning design elements with shopper expectations to positively influence behavior. 

Case Study 2: Limitations of predictive models 

An analysis revealed that predictive eye tracking algorithms often misestimate areas of attention because they cannot replicate cognitive processes such as concentrating on a menu for product search or ignoring a logo due to habituation. Real eye tracking provided more accurate insights into how shoppers navigate complex environments. 

Case Study 3: Behavioral science audits in action 

Adcock Solutions' behavioral science audits can integrate real eye tracking with psychological analysis to evaluate in-store displays and packaging. This approach identifies not just where shoppers look but why they make purchasing decisions, providing actionable insights that drive sales. can integrate real eye tracking with psychological analysis to evaluate in-store displays and packaging. This approach identifies not just where shoppers look but why they make purchasing decisions, providing actionable insights that drive sales. 

Conclusion 

While predictive eye tracking tools offer a cost-effective means of assessing visual attention, their inability to account for cognitive and emotional factors limits their effectiveness in driving shopper engagement and purchase decisions. 

Combining real eye tracking with behavioral science audits provides a more accurate and comprehensive analysis of the entire purchase funnel. This integrated approach not only identifies where shoppers look but also uncovers the psychological drivers behind their actions, enabling marketers to design interventions that resonate with shoppers and drive sales. 

References 

Visual attention during brand choice: The impact of time pressure and task motivation . Rik Pieters, Luk Warlop b,

Visual marketing: From attention to action. Wedel, M., & Pieters, R. (Eds.). (2008). Taylor & Francis Group/Lawrence Erlbaum Associates.

Constructive Shopper Choice Processes. James R. Bettman, Mary Frances Luce, John W. Payne

Eye Tracking in Human-Computer Interaction and Usability Research. Alex Poole and Linden J. Ball Psychology Department, Lancaster University, UK

Eye tracking evidence shows that non-fit messaging impacts attention, attitudes and choice. Ilona Fridman, Peter A Ubel, E Tory Higgins