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Web Analytics Webinar 10June2010
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Web Analytics Webinar 10June2010



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  • We’ve seen a good deal of change in the landscape of web analytics in the past 12 months, but more than just the landscape is changing.
  • Portable computing -> laptops -> handheld devices1st cell phone, amazing at first, but over time has become more accessible to consumers and ultimately an indispensable accessoryAir travel, while not quite the luxury it once was, is considerably improved over propeller planes with limited flying distances and and comfortNow is the time for web analytics to evolve…in technology and how marketers utilize the data that can be captured
  • Lots of innovation happening in the late 90’s, but early on early half of 2000’s, it’s mostly consolidation and feature parity
  • This is the domain of current web analytics toolsBut metrics are not analytics, even though that’s what we commonly call them. Marketers need information that provides more insight into the why of visitor behavior
  • And why metrics are no longer sufficient for marketers needs
  • That’s not to say that you shouldn’t keep using whatever traditional web analytics tool you already have… just that you can gain additional benefits by using a web behavioral analytics tool
  • Let’s take a look at what you get with each type of tool--A web analytics tool, like GA or OMTR typically looks at where visitors come from and do they execute on the call to actionA web behavior analytics toolFocus on using both traditional and behavioral tools
  • This woman is reading content from the page. A web behavioral tool can provide detail on what content she saw (not just what content was served on the page); where she moved her cursor on the page, but didn’t click. Whether something on the page was interesting, so she copied it. Whether she scrolled and how much, which could indicate that the content is confusing or that there might be too much information on the page.Just knowing the metric of how many visitors saw the same page she saw is interesting, but it’s not enough. It doesn’t give marketers the information that they need to understand what is keeping her interested or not maintaining her interest
  • Provides insight on what CONTENT resonates with visitors, regardless of where they see itFor highly dynamic sites, individual creative assets or even groups of assets can appear on multiple pages and in multiple locations. Without the aid of a web behavior analytical tool, marketers won’t be able to determine which elements of their site are the best performing.
  • Talk about ALN Engine and DDV and being able to get data out of tool easilyFrom the previous slide, Courts using web behavioral data from WJ and combining it with their affinity program to provide more sophisticated targeting
  • One of the key benefits of identifying users is to be able to use that information to provide a more engaging experience. That can be on the site or via other channels.When visitors come to the site, you may not know who they are, but when there is an identifying event, the details of that visitor can be assigned to their profile.
  • What are the goals of collecting the data How can you use the behavioral data to make the website experience more engaging for visitors?What questions need to be answered Is the workflow working? Is the language clear? Can visitors find what they are looking for?What data is needed to make informed decisions Would discovering and understanding patterns in the data aid in messaging strategy What interactions will lead to better experiences on the siteWho is going to utilize the data Behavioral data can be used in a variety of ways beyond just improving the website; find out who can and wants to use the infromation


  • 1. Analyzing the Website The difference between metrics and analytics 24June 2010 Ivan Chalif Director of Product Marketing @ivanchalif
  • 3. Everything Changes
  • 4. 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. 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: Javascript released ‘05: Google ‘10: IBM buys releases GA Coremetrics 1990 1995 2000 2005 2010
  • 8. Definitions • Data: a measure of an action that can be tracked – a click – a page view – a download – a purchase
  • 9. Definitions • Metric: a sum or ratio of data – click rate – ratio of new/returning visitors – page views this hour/day/ week/month/quarter/year
  • 10. 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?
  • 12. Google Changed the Game Number of organizations tracking what’s happening on their website Before Google Analytics After Google Analytics
  • 13. Looking At the Past or Toward the Future
  • 14. 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, etc)? Aberdeen: Retail E-Commerce Analytics: Cornerstone of the Complete Customer Profile
  • 15. 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
  • 16. Marketers Need More Than Just Web Analytics… “First and second‐generation analytic vendors are good at what they do, but mining for correlation and causation within massive, disparate online and offline data sets is simply not what they do.” – Eric T. Peterson
  • 17. Differences in Analytics Tools Web Analytics Web 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 • Additional data overlay broadly within an • Custom reports (corp., demo., profile) organization • 1:1 data
  • 18. How to use Behavioral Data • Find out what happens between the clicks – Scrolling – Hovering – Copy/paste
  • 19. How to use Behavioral Data • Understand how visitors are interacting with the dynamic content on the website
  • 20. How to use Behavioral Data • Combine web behavioral data with other data for deeper analysis, segmentation and content delivery
  • 21. How to use Behavioral Data • Link to individual profiles when visitor identifies themselves
  • 22. How to use Behavioral Data Understand what site visitors DO rather than just where they GO
  • 24. 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 questions do you need to answer? – What data is needed to make informed decisions? – Who is going to utilize the data?
  • 25. Taking it to Your Manager • Determine how web behavior analytics can benefit them • Determine how analytics can benefit the larger organization • Build a story (with case studies) • Map out costs and benefits and indentify ROI • Design a phased deployment
  • 26. 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 some behavioral ones 4. Identify integration points
  • 27. RECAP
  • 28. 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
  • 29. 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 – – – –
  • 30. Q&A
  • 31. Alterian WebJourney
  • 32. Analyzing the Website The difference between metrics and analytics 24June 2010 Ivan Chalif Director of Product Marketing @ivanchalif