Exploring the Impact of Google Discover on Users and Publishers: A Data-Driven Study
Artur Strzelecki, Mariia Rizun · Proceedings of the International Conference on Information Systems Development · 2023
The paper is dedicated to the analysis of Google Discover recommendation algorithms. The study is conducted on two online stores operating in Poland, for which the data from Google Search Console are available for 16 months. Google Discover is explored from the perspective of web users and web content publishers based on the total number of impressions and clicks and the click-through rate of the two websites. The results allow us to understand that although the users’ activity increases the website’s performance in Google Discover, its algorithms consider many more factors (like the popularity of other websites with similar content, users' location, and frequency of content updates) and may remove the website from Discover despite a relatively high number of clicks. Additionally, the literature review conducted in the paper revealed a gap in scientific research dedicated to the phenomena of this content recommendation system.