Analyzing Digital Advertisement Effectiveness using Image Processing Model with Person’s Attentiveness

In recent days, the revenue generated by different advertising mediums is massive, in particular the revenue generated through digital advertisement is approximately 200 billion dollars worldwide in 2020. The revenue generated from these ads often depends on the watch time of the ad and/or the user involvement in the ad. Number of viewers clicking the skip button is an important statistic that helps to determine the quality of the ad. If the ad is appealing to the viewers, it grabs the user’s interest and attention in the first few seconds to increase the watch time, making the user watch the ad completely. A person is more likely to buy the product or service being advertised if he finds the advertisement interesting. An advertisement should provide an insight into the key aspects of the product which will enable the target customer to decide whether he wants to use the product or service. More viewers are taking control by skipping advertisements they don’t want to see. Hence companies must take actions to ensure that theirs reach the target audience, with the right blend of reach and relevance. Ad effectiveness offers a solution to the companies looking to understand the impact of their ads on the audiences they want to influence. Hence, the effectiveness of the advertisement is very important to sell to the target audience. To aid companies in measuring the effectiveness, a tool/application which detects and analyses people’s attentiveness to the advertisement would be of great help in making advertisements that are engaging and appealing to the general public. In this paper, an image processing model is proposed to implement eye gaze and head pose tracking system, to analyze the person’s attentiveness towards the ad. This proposed approach can be used and analyzed by the advertising industry to determine the effectiveness of their advertisement in selling their product or service to the target audience.