The aim of this paper is to develop a new user‐friendly in‐house tracking methodology for academics to analyse the effectiveness of visits (return visit behaviour and length of sessions) depending on their traffic source: direct visits, referring site entries and search engine visits. In other words, how deep do visitors navigate into the web site? Which is their internal performance depending on their traffic source?
This paper addresses these questions by time series analysis of Google Analytics data. Some statistical matters with regard to the use of Google Analytics data in combination with time series methodology are fine‐tuned.
Return visits are the main engine for nurturing session length, but which type of traffic source nurtures these return visits? In order to answer this question, an important distinction must be made between “total return visits” and “marginal return visits”. Site entries stay longer to the extent their “marginal return effectiveness” is higher. For our particular web site direct visits are the most effective ones, followed by search engine visits and only thirdly link‐entries.
This methodology is critical for an effective web site traffic source monitoring and benchmarking that may lead to better web site strategies.
The importance of this paper is not the particular web site but the new methodology tested to arrive at these results, an experiment that could be repeated with different web sites.
Plaza, B. (2009), "Monitoring web traffic source effectiveness with Google Analytics: An experiment with time series", Aslib Proceedings, Vol. 61 No. 5, pp. 474-482. https://doi.org/10.1108/00012530910989625Download as .RIS
Emerald Group Publishing Limited
Copyright © 2009, Emerald Group Publishing Limited