Elsevier

Tourism Management

Volume 32, Issue 3, June 2011, Pages 477-481
Tourism Management

Google Analytics for measuring website performance

https://doi.org/10.1016/j.tourman.2010.03.015Get rights and content

Abstract

Performance measurement of tourism websites is becoming a critical issue for effective online marketing. The aim of this article is to analyse the effectiveness of entries (visit behaviour and length of sessions) depending on their traffic source: direct visit, in-link entries (for instance, en.wikipedia.org), and search engine visits (for example, Google). For this purpose, time series analysis of Google Analytics data is made use of. This method could be interesting for any tourism website optimizer.

Introduction

The Internet has revolutionized the business operations of the entire travel and tourism industry value chains. As the Internet has become the channel of customer relationships and sales, the performance measurement of tourism websites is becoming a strategic issue, critical for online marketing. Web analytics is on the increase.

Hundreds of thousands of tourism web owners worldwide have a web analyser program available to them. The web analyser provides plain and simple statistics concerning the website (number of visitors, the average number of page views per visitor, average page duration, most requested pages, domain classes and referrers). This article presents an experiment done with the information that Google Analytics offers for a R&D resource devoted to cultural tourism, about the number of visits on a website and the traffic source, which includes organic results in search engines, links from referral web pages or direct access. In other words, it investigates the differences between sessions started by direct connection by typing the site name, through a link on another site, or from a search engine, with regard to return visit behaviour and length of sessions. The importance of this paper is not the particular website http://www.scholars-on-bilbao.info, but the new methodology tested to arrive at these results. The case study must be presented only as a way to explain the new methodology, a method that could be interesting for a wider audience.

How deep do visitors navigate into the website? What is their internal performance depending on their traffic source? Are search engine visits more effective than referring site entries? This paper addresses these questions by time series analysis of Google Analytics data, in order to compare the performance of visits depending on their source: direct visits, referring site visits and search engine visits.

Why use Google Analytics? Firstly, and most importantly for the purpose of this study, it is used because Google Analytics provides time series data. Moreover, it is also employed because Google Analytics is a free service offered by Google that generates detailed statistics about the visits to a website, and which is a user friendly application with the guarantee of Google technology. This tracking application, external to the website, records traffic by inserting a small piece of HTML code into every page of the website. Google Analytics tells the web owner how visitors found the site and how they interact with it (see Dashboard in Fig. 1). Users will be able to compare the behaviour of visitors who were referred from search engines, from referring sites and emails, and direct visits, and thus gain insight into how to improve the site’s content and design (Plaza, 2009).

Section snippets

Literature review

Many studies have been made about tourism firms utilizing the Internet for relationship building, business transactions and information search (for a literature review on information technologies in tourism see Buhalis and Law, 2008, Law et al., 2009, Law et al., 2010).

In addition, several scientific articles have analyzed the use of Google Analytics and evaluated its usefulness as a web analytics tool. (Hasan et al., 2009, Plaza, 2009, Rodriguez-Burrel, 2009). Some statistical matters with

Website profile

In July 2006 a non-profit organization (based in Gernika, Basque Country-Spain) launched http://www.scholars-on-bilbao.info (Art4pax Foundation, 2008) in order to improve the dissemination of R&D results in the field of ‘Cultural Tourism’ scientific production, through the exchange of research work on the Guggenheim Museum Bilbao case. This locally based website encompasses academic works that analyse the ‘Guggenheim Effect’ (cultural tourism, the Guggenheim Museum Bilbao and dilemmas, creative

Results

Results from Table 1 show that the number of pages per entry grows by 0.06 out of every return visit, whereas the marginal effect of new visits is nil. That is to say that return visits are the main engine for nurturing session length for www.scholars-on-bilbao.info (see Fig. 5), and bounce less (Fig. 6). But, which type of traffic source nurtures these return visits?

According to the reading of the results in Table 2, 0.43 out of every direct entry visit returns, 0.36 out of every search engine

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