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E- Tourism Performance Measurement Meeting 4

E- Tourism Performance Measurement Meeting 4. Christoph Hoffinger, MA. Agenda. Web Analytics Mesurement Techniques Data Collection & Analysis Key Performance Indicators. Web Analytics. Define your website / campaign goals clearly

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E- Tourism Performance Measurement Meeting 4

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  1. E-TourismPerformance MeasurementMeeting 4 Christoph Hoffinger, MA

  2. Agenda • Web Analytics • MesurementTechniques • Data Collection & Analysis • Key Performance Indicators

  3. Web Analytics • Define your website / campaign goals clearly • Definemeaningful indicators geared to your goals (measureable, realistic) • Definefrequencyof analysis • Benchmark with comparable websites • Use data for quality, usability andsalesenhancement of website and campaigns • Communicate data and establish aknowledge database

  4. Web Analysis

  5. Web Analysis Questions • Who haswhenwhereandhowvisited my website? • How many visitors have visited my website? • Which individual web pages have been viewed? • Which pages are the most popular pages? • How long do visitors stay on my website? • How many bookingscan I generate through my website? • How many visitors click on adverts on my website? • How good is the usabilityof my website? • Whichmarketing activities are the most successful ones? • Whichkeywordsdo users use in order to come on ourwebsite?

  6. Web Analytics • Logfile Analysis ( server) • Client-based Analysis • Tracking Pixel • Tags (e.g. Javascript)  Google Analytcis • Cookies (dataprivacyissues)

  7. Logfile Analysis • Logfiles are automatically produced by the web server • No changes to the website are required. • The data is collected on the company’s own servers (data security) • Logfiles also contain on visits from search engine spiders (not recorded by page tagging, as robots don’t execute javascript). • The web server reliably records every transaction (e.g. PDF documents)

  8. Page Tagging • Data is gathered via a "tag“ (tracking code) implemented on the page, usually written in java script • The script provides additional information on the web client or on the user, not sent in the query, such as visitors' screen sizes and the price of the goods they purchased. • Page tagging can report events that don’t involve a request to the web server • Page tagging involves the process of assigning cookies to visitors • Page tagging is currently a standard in web analytics (e.g. Google Analytics).

  9. Google Analytics Tracking Code <script type="text/javascript"> var _gaq = _gaq || []; _gaq.push(['_setAccount', 'UA-XXXXX-X']); _gaq.push(['_trackPageview']); (function() { varga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); </script>

  10. Cookies • Small string of text stored on a user's computer by a web browser • Consists of of one or more name-value pairs containing bits of information such as user preferences, shopping cart contents or other data (e.g. www.yahoo.com) • Used for maintaining specific information about users • All major web analytics applications rely mainly on cookies • Problems: • Cookie blocking: impact on calculations depending on visits, e.g. average page views / visit etc. • Cookie deletion: impact on calculations depending on unique visitors, e.g. new / returning visitor

  11. Google Analytics Cookies

  12. Data Collection • Collection and assessment of data: • Web traffic (logfiles, page tags) • Web-based transactions (payments, bookings) • Web server performance (speed, availability) • Usability studies • User submitted information

  13. Data Sources

  14. Web Analytics Goals • Monitor website and content performance • Enhance website usability & attractiveness • Gear content to user demands • Increase ROI and ROC • Optimize content work flow • CRM – segmentation and targeting • Quality control and enhancement • Product development • Savings costs for website development and content management

  15. Categoriesof Analysis

  16. Key Indicators

  17. Key Performance Indicators • Customers / Visitors • Number of Visitors and Visits: • Unique Visitors • Visits • Visitor Loyalty, Customer Retention: • New Visitors • Returning Visitors • Bounce Rate • Website Stickyness: • Pageviews • Average Pageviews / visit • Average Time on Site

  18. Key Performance Indicators • Customer Segments: • Countries of Origin (Regions, Cities) • Languages • How do Customers come to the Website? • Direct traffic • Referring Websites • Search Engines • Which Search Engines • Keywords used

  19. Key Performance Indicators • Content & Website Usability • Top Content Pages • Entry Pages • Exit Pages • Click Paths Analysis (Navigation) • Time spent on pages • Bounce Rate of pages

  20. Key Performance Indicators • E-Commerce • Number of enquiries • Number of bookings • Booking conversion • Pageviews of brochure ordering page / number of brochure order requests sent • Pageviews of enquiry form / number of enquiry forms sent • Pageviews of newsletter registration page / Newsletter registrations

  21. Key Performance Indicators • Technical Performance • Webbrowser • Operating Systems • Screen Solutions • Flash • Page Load Times

  22. Google Analytics User Interface Export Settings, Users Main Menu Trend Analysis Date Range Overview

  23. Google Analytics - Main Menu Create Individual Reports User Demographics Traffic Sources Content Analysis Conversion Tracking

  24. Thankyouforyourattention!

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