Capturing people’s attention today is a huge challenge. Eye tracking technology is a way to implicitly measure what makes people give more attention to certain product packs, Advertisements, billboards and many other forms of product marketing. Considering its importance in helping capture customers’ attention and figuring out what is happening in the subconscious (95%) Eye tracking holds a lot of promise.
But has it really reached its potential?
We at Karna AI believe that the potential for eye tracking is not fully explored. With this blog, we make a case that how AI will lead to better eye tracking analysis technology thereby increasing its adoption to its potential (which we believe is much higher than its current penetration).
Humans use a lot of non-verbal cues, such as eye gaze, facial expressions, gesture, body language and tone of voice, to communicate their emotions.
AI is capable of detecting these gestures just the way humans do, from multiple channels that will provide richer insight into the human expression of emotion and opinion.
Challenges with Eye Tracking Technology Today
Eye-tracking technology — which can determine where in a visual scene people are directing their gaze — can be widely used in psychological experiments and marketing research, but a lot of complexities involved in the process of eye tracking has kept it from finding consumer applications on a large scale. With the advent of Artificial Intelligence, we can bridge this gap between research and real-world applications.
In today’s scenario, market researchers who are using eye-tracking technology to conduct market research don’t have a smooth path to the required results. First, they have to partner with manufacturers to get eye tracking hardware for the experiment. Second, they have to license software to analyse all the respondent videos through manual coding which in itself is a challenge. Last but not least, is the budget constraint as the cost associated with the aforementioned tasks is exorbitant. Cost is one of the major factors why most companies shy away from this methodology of market research.
With AI most of these obstacles can be overcome. Since using AI will make our research more flexible, we will be able to use cheap hardware for our experiment. AI will code/tag all the videos automatically to save crucial time and labour for the companies. Finally, AI will considerably reduce the cost of the data analysis.
AI Powered Coding for Retail and Mobile Gaze Videos
AI Powered Eye Tracking Technology
“Eye-tracking technology tells where the attention is, but not whether it is good or bad”
By employing the power of AI to Eye Tracking Technology, We can provide detailed analysis and dynamic data visualizations that tell you if your content is seen and earning (and retaining) a user’s attention. With the help of such consumers’ visual engagement and emotion analytics data, the companies will be empowered to make informed decisions that increase their ROI on advertisements, conversion rates and optimize engagement strategy.
Eye Tracking Technology has been successfully deployed in mobile devices and webcams to enhance user experience and give companies real-time insights into consumer reactions to their products. One such example is the RoboGaze. It is an AI-powered solution by Karna AI that allows researchers to highlight and predict Gaze maps for creative ads and images. It helps a brand to identify gaze patterns from multiple respondents for their products. The insights into gaze and fixation patterns can assuage companies to come out with comprehensive products.
Customer requirements are constantly changing and technologies have no option but to keep advancing. The integration of Eye Tracking with AI will take the capabilities of Eye tracking to the next level. It will be highly beneficial for improving the sales and customer service departments of companies. Brands that will able to effectively incorporate this new blend of AI and Eye Tracking into their market research trend will become the front-runners in this race to technological excellence.
In near future, the advantages of employing eye-tracking technology will increase many folds because of constant advancements in the field of AI. Machines will be equipped with the technology to tell you exactly “where and what you are looking at”. The turnaround time for the final analysis of the recorded video will be minimised.
And farther into the future, it “could” lead to eye tracking hardware becoming obsolete and researchers will be able to employ AI capabilities to analyse videos from almost any source irrespective of its format and quality for market research, without any compatibility constraints.
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