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Google Analytics for measuring website performance

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  • Plaza, Beatriz

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.

Suggested Citation

  • Plaza, Beatriz, 2011. "Google Analytics for measuring website performance," Tourism Management, Elsevier, vol. 32(3), pages 477-481.
    • Handle: RePEc:eee:touman:v:32:y:2011:i:3:p:477-481
    DOI: 10.1016/j.tourman.2010.03.015
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    1. Law, Rob & Qi, Shanshan & Buhalis, Dimitrios, 2010. "Progress in tourism management: A review of website evaluation in tourism research," Tourism Management, Elsevier, vol. 31(3), pages 297-313.
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    Cited by:

    1. Victoria Ateca Amestoy, 2013. "Demand for cultural heritage," Chapters, in: Ilde Rizzo & Anna Mignosa (ed.), Handbook on the Economics of Cultural Heritage, chapter 4, pages i-i, Edward Elgar Publishing.
    2. Mihai COSTEA & Cristian Valentin HAPENCIUC & Gabriela ARIONESEI, 2017. "THE USE OF THE NEW INFORMATION AND COMMUNICATION TECHNOLOGIES (NICTs) AT THE LEVEL OF BUSINESS IN THE TOURISM INDUSTRY FROM ROMANIA AND THE CEE-EU COUNTRIES," Revista de turism - studii si cercetari in turism / Journal of tourism - studies and research in tourism, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 24(24), pages 1-10, December.
    3. Roy, Gobinda & Sharma, Swati, 2021. "Measuring the role of factors on website effectiveness using vector autoregressive model," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    4. Miroslav Mandić & Iva Gregurec & UgljeÅ¡a Vujović, 2023. "Measuring the Effectiveness of Online Sales by Conducting A/B Testing," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 35(2), pages 223-249.
    5. Pakkala, H. & Presser, K. & Christensen, T., 2012. "Using Google Analytics to measure visitor statistics: The case of food composition websites," International Journal of Information Management, Elsevier, vol. 32(6), pages 504-512.
    6. Darko B. Vukovic & Lubov Spitsina & Ekaterina Gribanova & Vladislav Spitsin & Ivan Lyzin, 2023. "Predicting the Performance of Retail Market Firms: Regression and Machine Learning Methods," Mathematics, MDPI, vol. 11(8), pages 1-23, April.
    7. Ateca-Amestoy, Victoria & Prieto-Rodriguez, Juan, 2013. "Forecasting accuracy of behavioural models for participation in the arts," European Journal of Operational Research, Elsevier, vol. 229(1), pages 124-131.
    8. Baka, Vasiliki, 2016. "The becoming of user-generated reviews: Looking at the past to understand the future of managing reputation in the travel sector," Tourism Management, Elsevier, vol. 53(C), pages 148-162.
    9. Pan, Bing, 2015. "The power of search engine ranking for tourist destinations," Tourism Management, Elsevier, vol. 47(C), pages 79-87.
    10. Vinicius Luiz Ferraz Minatogawa & Matheus Munhoz Vieira Franco & Izabela Simon Rampasso & Rosley Anholon & Ruy Quadros & Orlando Durán & Antonio Batocchio, 2019. "Operationalizing Business Model Innovation through Big Data Analytics for Sustainable Organizations," Sustainability, MDPI, vol. 12(1), pages 1-29, December.
    11. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    12. Anna Podara & Dimitrios Giomelakis & Constantinos Nicolaou & Maria Matsiola & Rigas Kotsakis, 2021. "Digital Storytelling in Cultural Heritage: Audience Engagement in the Interactive Documentary New Life," Sustainability, MDPI, vol. 13(3), pages 1-22, January.
    13. Nantachai Kantanantha & Jiaranai Awichanirost, 2022. "Analyzing and forecasting online tour bookings using Google Analytics metrics," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(3), pages 354-365, June.
    14. Elena Not, 2021. "Mining mobile application usage data to understand travel planning for attending a large event," Information Technology & Tourism, Springer, vol. 23(3), pages 291-325, September.
    15. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
    16. Ruzza, Mirko & Tiozzo, Barbara & Mantovani, Claudio & D’Este, Fabiano & Ravarotto, Licia, 2017. "Designing the information architecture of a complex website: A strategy based on news content and faceted classification," International Journal of Information Management, Elsevier, vol. 37(3), pages 166-176.
    17. Di Fatta, Davide & Patton, Dean & Viglia, Giampaolo, 2018. "The determinants of conversion rates in SME e-commerce websites," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 161-168.
    18. Evangelos Mourelatos & Manolis Tzagarakis, 2018. "An investigation of factors affecting the visits of online crowdsourcing and labor platforms," Netnomics, Springer, vol. 19(3), pages 95-130, December.
    19. Karol Król & Dariusz Zdonek, 2020. "Aggregated Indices in Website Quality Assessment," Future Internet, MDPI, vol. 12(4), pages 1-23, April.

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