Deciphering the Visibility of Higher Education Institutions: A Statistical Analysis of Google Search Console Data
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The research presented here delves into the connection between data from Google Search Console (GSC) and the Webometrics visibility score of a specific public university's web presence. The study scrutinized GSC parameters such as clicks, impressions, click-through-rate (CTR), and average position to assess their impact on the university's digital visibility. The results indicate that impressions and average position play a critical role in determining the Webometrics visibility score, underscoring the significance of search engine optimization for learning establishments. The research also pinpointed the most effective search queries that drive substantial visitor traffic to the university's website, underlining the need for precise content targeting to optimize search performance. In this study, a predictive model was developed using multiple linear regression analysis to accurately predict the Webometrics visibility score based on GSC metrics, suggesting that strategic efforts to enhance these parameters could boost a university's online prominence. Additionally, a theoretical model was proposed to clarify the dynamic relationship between impressions, positions, and clicks in shaping the overall web visibility. Although this study provides valuable insights, it is based on data from a single university, which calls for further investigation using more varied datasets. Ultimately, the study emphasizes the immense potential of leveraging GSC data to bolster a university's online footprint, suggesting that strategic enhancements of vital parameters can greatly improve a university's online visibility according to Webometrics. As the academic world becomes increasingly digital, implementing these findings to guide search engine optimization strategies is a crucial element of institutional administration.
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