Web Metrics vs Web Behavioral Analytics and Why You Need to Know the Difference

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An overview of the web analytics ecosystem and uncover how web behavior analytics can free you from the status quo of just counting page views. More importantly, you will discover what you need to do to truly leverage the data that is available to you from the website.

Ultimately, you will walk away with:

• An understanding of the differences between available tools
• Insight on what data to collect on your site
• Tips to help get your manager to embrace web behavior analytics
• Checklist of next steps

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Web Metrics vs Web Behavioral Analytics and Why You Need to Know the Difference

  1. 1. Analyzing the Website A l i th W b it The difference between metrics and analytics 24June 2010 Ivan Chalif Director f P d t M k ti Di t of Product Marketing @ivanchalif ivan.chalif@alterian.com
  2. 2. EVOLVE AND GROW
  3. 3. Everything Changes
  4. 4. Everything Changes
  5. 5. Agenda 1. A Short History 2. Some Background 3. How Analytics is Changing 4. Moving the Needle in Your Organization 5. Next Steps 6. Q & A
  6. 6. A SHORT HISTORY
  7. 7. A Brief History of Web Analytics ‘90: Public ‘06: Visual Internet & Sciences buys ‘97: Javascript HTTP WebSide Story broadly used for data collection ‘07: Omniture ‘93: WA is buys Visual born via log Sciences analysis ‘09: Adobe buys Omniture ‘05: Google ‘10: Alterian ‘91: 1st web buys Urchin WebJourney server ‘95: 95: Javascript released ‘05: Google ‘10: IBM buys releases GA Coremetrics 1990 1995 2000 2005 2010
  8. 8. SOME BACKGROUND
  9. 9. Definitions • Data: a measure of an action that can be tracked – a click – a page view – a download – a purchase
  10. 10. Definitions • Metric: a sum or ratio of data – click rate
  11. 11. Definitions • Metric: a sum or ratio of data – click rate – ratio of new/returning visitors
  12. 12. Definitions • Metric: a sum or ratio of data – click rate – ratio of new/returning visitors – page views this hour/day/ week/month/quarter/year
  13. 13. Definitions • Analytics: understanding what drives the behavior – Is the content useful?
  14. 14. Definitions • Analytics: understanding what drives the behavior – Is the content useful? – Does this layout work better for this segment?
  15. 15. Definitions • Analytics: understanding what drives the behavior – Is the content useful? – Does this layout work better for this segment? – Does some combination of trackable elements affect behavior?
  16. 16. Definitions • Analytics: understanding what drives the behavior – Is the content useful? – Does this layout work better for this segment? – Does some combination of trackable elements affect behavior? – Is this the right image to use?
  17. 17. HOW ANALYTICS ARE CHANGING
  18. 18. Google Changed the Game Number of organizations tracking what’s happening on their website Before Google Analytics After Google Analytics
  19. 19. Looking At the Past or Toward the Future
  20. 20. Looking At the Past • The metrics of traditional web analytics are used to report on what has already happened – How many? – Where did they go? – How long did they stay? – Did they complete the desired process (sign-up, download, purchase, purchase etc)? Aberdeen: Retail E-Commerce Analytics: Cornerstone of the Complete Customer Profile
  21. 21. Looking Toward the Future • Web behavioral analytics are used to steer the future – How are the visitors alike – Are there patterns in the traffic or behavior on a page – Which content resonates with visitors – What else can I determine about the visitor to improve the relationship Aberdeen: Retail E-Commerce Analytics: Cornerstone of the Complete Customer Profile
  22. 22. Marketers Need More Than Just Web Analytics… “First and second‐generation analytic First vendors are good at what they do, but mining for correlation and causation within massive, di ti ithi i disparate t online and offline data sets is simply not what they do.” – Eric T. Peterson y
  23. 23. Differences in Analytics Tools Web A l ti W b Analytics Web B h i A l ti W b Behavior Analytics • Focus on source • Dashboards • Focus on the individual • Track page flow on • Search term(s) • Capture non-click site behavior • Environmental data • Aggregate data • Track creative assets • Standard reports • Report on metrics p • Additional data overlay y broadly within an • Custom reports (corp., demo., profile) organization • 1:1 data
  24. 24. How to use Behavioral Data • Find out what happens between the clicks – Scrolling – Hovering – Copy/paste
  25. 25. How to use Behavioral Data • Understand how visitors are interacting with the dynamic content on the website
  26. 26. How to use Behavioral Data • Combine web behavioral data with other data for deeper analysis, segmentation and content delivery
  27. 27. How to use Behavioral Data • Link to individual profiles when visitor identifies themselves
  28. 28. How to use Behavioral Data • Link to individual profiles when visitor identifies themselves
  29. 29. How to use Behavioral Data Understand h t it i it U d t d what site visitors DO rather than just where they GO
  30. 30. MOVING THE NEEDLE
  31. 31. Identify Your Goals and Data Needs • Before embarking on any web behavioral analytics project, consider the following: – Why are you collecting the data? – What will you do with the data? – What Wh t questions do you need t ti d d to answer? – What data is needed to make informed decisions? – Who is going to utilize the data?
  32. 32. Taking it to Your Manager • Determine how web behavior analytics can benefit them • Determine how analytics can benefit the larger organization • Build a story ( y (with case studies) ) • Map out costs and benefits and indentify ROI • Design a phased deployment
  33. 33. Next Steps for Your Program 1. Look at where you are and where you want to be 2. If it’s not already part of your strategy, include behavioral analytics 3. If you already have a web analytics tool, evaluate y , some behavioral ones 4. Identify integration points
  34. 34. RECAP
  35. 35. What We’ve Covered • A bit about where we came from • A bit about how things are changing • A bit about how you can start making a plan to move the needle
  36. 36. Resources • Books – Web Analytics Demystified by Eric T. Peterson – Web Analytics 2.0 by Avinash Kaushik – Actionable Web Analytics by Jason Burby and Shane Atchison • Web – http://www.occamsrazor.com/ htt // / – http://www.webanalyticsdemystified.com/ – http://www.webanalyticsassociation.org/ – http://www.alterian.com/products/web-behavior-analytics/
  37. 37. Q&A
  38. 38. Alterian WebJourney http://www.alterian.com/
  39. 39. Analyzing the Website A l i th W b it The difference between metrics and analytics 24June 2010 Ivan Chalif Director f P d t M k ti Di t of Product Marketing @ivanchalif ivan.chalif@alterian.com

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