Literature DB >> 35622858

Measuring user interactions with websites: A comparison of two industry standard analytics approaches using data of 86 websites.

Bernard J Jansen1, Soon-Gyo Jung1, Joni Salminen1,2,3.   

Abstract

This research compares four standard analytics metrics from Google Analytics with SimilarWeb using one year's average monthly data for 86 websites from 26 countries and 19 industry verticals. The results show statistically significant differences between the two services for total visits, unique visitors, bounce rates, and average session duration. Using Google Analytics as the baseline, SimilarWeb average values were 19.4% lower for total visits, 38.7% lower for unique visitors, 25.2% higher for bounce rate, and 56.2% higher for session duration. The website rankings between SimilarWeb and Google Analytics for all metrics are significantly correlated, especially for total visits and unique visitors. The accuracy/inaccuracy of the metrics from both services is discussed from the vantage of the data collection methods employed. In the absence of a gold standard, combining the two services is a reasonable approach, with Google Analytics for onsite and SimilarWeb for network metrics. Finally, the differences between SimilarWeb and Google Analytics measures are systematic, so with Google Analytics metrics from a known site, one can reasonably generate the Google Analytics metrics for related sites based on the SimilarWeb values. The implications are that SimilarWeb provides conservative analytics in terms of visits and visitors relative to those of Google Analytics, and both tools can be utilized in a complementary fashion in situations where site analytics is not available for competitive intelligence and benchmarking analysis.

Entities:  

Year:  2022        PMID: 35622858      PMCID: PMC9140287          DOI: 10.1371/journal.pone.0268212

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


  4 in total

1.  The Detection of Emerging Trends Using Wikipedia Traffic Data and Context Networks.

Authors:  Mirko Kämpf; Eric Tessenow; Dror Y Kenett; Jan W Kantelhardt
Journal:  PLoS One       Date:  2015-12-31       Impact factor: 3.240

2.  How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?

Authors:  Brady T West; Joseph W Sakshaug; Guy Alain S Aurelien
Journal:  PLoS One       Date:  2016-06-29       Impact factor: 3.240

3.  Network analytical tool for monitoring global food safety highlights China.

Authors:  Tamás Nepusz; Andrea Petróczi; Declan P Naughton
Journal:  PLoS One       Date:  2009-08-18       Impact factor: 3.240

4.  Online and Social Media Data As an Imperfect Continuous Panel Survey.

Authors:  Fernando Diaz; Michael Gamon; Jake M Hofman; Emre Kıcıman; David Rothschild
Journal:  PLoS One       Date:  2016-01-05       Impact factor: 3.240

  4 in total

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