Understanding Web Analytics: Measuring Value and Spotting Problems
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Understanding Web Analytics: Measuring Value and Spotting Problems

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  • 1. U NDERSTANDING W EB A NALYTICS Measuring Value & Spotting Problems presented by Kate O’Neill
  • 2. ANALYTICS PROCESS • Determine KPIs • What factors will determine success? • What’s actionable? • Establish a baseline • Where are the pain points? • What’s the range? • Prioritize • What’s most critical? • What’s easiest? • Validate • Form a hypothesis • Test • Analyze • Compare with baseline • Extrapolate to ROI source: Omniture SiteCatalyst Basic User Training Workbook
  • 3. WHAT’S MEASURABLE? • Traffic • Sources (finding methods) • Composition (visitor profile) • Engagement • Navigation • Content • Conversion
  • 4. WHAT’S MEASURABLE? • Traffic • Sources (finding methods) • Composition (visitor profile) • Engagement • Navigation • Content "Not everything that can be counted • Conversion counts, and not everything that counts can be counted." - Albert Einstein
  • 5. WHAT’S MEANINGFUL?
  • 6. WHAT’S MEANINGFUL? • “Where in the site are visitors most often deciding to leave?” • “Where do visitors most often go after using the internal search?” • “Do visitors who come in on blog posts actually visit the rest of the site?” • “What search terms are used by the people who are most likely to purchase?”
  • 7. WHAT’S MEANINGFUL? • “Where in the site are visitors most often deciding to leave?” • “Where do visitors most often go after using the internal search?” • “Do visitors who come in on blog posts actually visit the rest of the site?” • “What search terms are used by the people who are most likely to purchase?” In other words:
  • 8. WHAT’S MEANINGFUL? • “Where in the site are visitors most often deciding to leave?” • “Where do visitors most often go after using the internal search?” • “Do visitors who come in on blog posts actually visit the rest of the site?” • “What search terms are used by the people who are most likely to purchase?” In other words: start with a good question.
  • 9. PLANNING IS KEY TO ANALYSIS • Anticipate • Implement Data collection begins! • Modify Incremental data only
  • 10. QUICK QUIZ: What are the key performance indicators - the factors that determine success - for the Sitening.com website?
  • 11. CONVERSION METRICS • ConversionRate (Orders or Leads per Visit) • Orders • Revenue • Leads Completed
  • 12. MODEL THE SITE identify actions / events, content hierarchies, products (e- commerce), and potentially interesting characteristics
  • 13. TYPES OF REPORTS • Metrics Trending • Pathing • Next Page / Previous Page • Fall-out • Dashboards
  • 14. TRENDING helpful in spotting anomalies in patterns
  • 15. FUNNELS helpful with path fall-out visualization
  • 16. PAGE FLOW helpful in spotting content & navigation problems
  • 17. DASHBOARDS helpful in reviewing KPIs at a glance
  • 18. TRAFFIC: WHO’S COMING TO THE SITE?
  • 19. EXAMPLES OF TRAFFIC METRICS • Visits • Page Views • Traffic Sources • Unique Visitors Wait... what’s the difference between ‘absolute unique’ and ‘daily/weekly unique’?
  • 20. EXAMPLES OF TRAFFIC METRICS • Visits • Page Views • Traffic Sources • Unique Visitors Wait... what’s the difference between ‘absolute unique’ and ‘daily/weekly unique’?
  • 21. EXAMPLES OF TRAFFIC METRICS • Visits • Page Views • Traffic Sources • Unique Visitors Wait... what’s the difference between ‘absolute unique’ and ‘daily/weekly unique’?
  • 22. EXAMPLES OF TRAFFIC METRICS • Visits • Page Views • Traffic Sources • Unique Visitors Wait... what’s the difference between ‘absolute unique’ and ‘daily/weekly unique’?
  • 23. EXAMPLES OF TRAFFIC METRICS • Visits • Page Views • Traffic Sources • Unique Visitors Wait... what’s the difference between ‘absolute unique’ and ‘daily/weekly unique’?
  • 24. VISITORS: AREN’T WE ALL UNIQUE? Mon: Joe, Jane, Jeff Tues: John, Jack Weds: James, Jill Thurs: Jeff, Jason, Jack How many visits? at least 13 Fri: Jay, Joel, John How many visitors? 13 How many unique daily visitors? 13 How many unique weekly visitors? 10
  • 25. ENGAGEMENT: WHAT’S HAPPENING ONCE PEOPLE GET THERE?
  • 26. EXAMPLES OF ENGAGEMENT METRICS • Return Visits • Timeon Site / Time Spent per Visit • Bounce Rate Wait... where’s Bounce Rate in SiteCatalyst?
  • 27. EXAMPLES OF ENGAGEMENT METRICS • Return Visits • Timeon Site / Time Spent per Visit • Bounce Rate Wait... where’s Bounce Rate in SiteCatalyst?
  • 28. EXAMPLES OF ENGAGEMENT METRICS • Return Visits • Timeon Site / Time Spent per Visit • Bounce Rate Wait... where’s Bounce Rate in SiteCatalyst?
  • 29. EXAMPLES OF ENGAGEMENT METRICS • Return Visits • Timeon Site / Time Spent per Visit • Bounce Rate Wait... where’s Bounce Rate in SiteCatalyst?
  • 30. LIVE EXAMPLE: CREATING CALCULATED METRICS
  • 31. WHY PAY FOR ANALYTICS TOOLS? Google Omniture Analytics SiteCatalyst near real time data no, typically a day behind yes, usually available within minutes * advanced classifications no yes, with SAINT ability to customize data 1 custom variable 50 props, 50 eVars reporting native ActionScript Flash no yes tracking price free not free non-existent / support included crowd-sourced * except for data warehouse queries
  • 32. GA & SC NAVIGATION
  • 33. GA SC Visitor Profile > Map Overlay GeoSegmentation Visitor Retention > Return New vs. Returning Visits choose unique visitors by Absolute Unique Visitors period Pageviews Page Views Average Pageviews (custom calculated) Time on Site Time Spent per Visit Bounce Rate (custom calculated) n/a Path Length
  • 34. GA BENCHMARKING Compare a given site against others
  • 35. SEGMENTATION
  • 36. IN SITECATALYST: ASI SLOTS we’ll cover this more in a later session
  • 37. IN GA: ADVANCED SEGMENTS let’s look at this now
  • 38. PREVIEW OF ADVANCED SESSION • Tracking across Channels (SEO, PPC, social media) • Customizing & Modeling • Multi-domain Sites • Balancing Subjective and Objective Research • Behavioral Analysis & Targeting • Other topics?