Interactive Metrics, What You Really Need to Know


Published on

In this informative presentation, Maria Harrison will take you through the good, the bad and the ugly of interactive metrics. Interactive marketing is a double-edged sword when it comes to metrics.

Just because everything can be counted, doesn’t mean it’s important in making business decisions that will help you have a positive impact on your interactive marketing initiatives.

Ms. Harrison will show you how simplistic interactive metrics can really be, how to set benchmarks, and develop meaningful executive dashboards that will help you make the right decisions to improve your interactive marketing efforts. She will define some basic interactive metric terms and teach you how to immediately apply those metrics to your business.

Published in: Self Improvement
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Interactive Metrics, What You Really Need to Know

  1. 1. Interactive Metrics What You Really Need to Know June 18, 2009 Presented by: Maria Harrison
  2. 2. Agenda <ul><li>Introduction </li></ul><ul><li>Tracking vs. Analytics & Analysis </li></ul><ul><li>What It Means to Be Average </li></ul><ul><li>Dashboards </li></ul><ul><li>Resources </li></ul>
  3. 3. Introduction <ul><li>Maria Harrison </li></ul><ul><ul><li>12 year Internet industry veteran </li></ul></ul><ul><ul><li>Experience in online marketing strategies, online marketing plans, online media buying plans, web site usability, email marketing, search engine marketing, web 2.0, affiliate marketing, social media and more. </li></ul></ul><ul><ul><li>Previous Roles & Accomplishments: </li></ul></ul><ul><ul><ul><li>Vice President of Marketing, The Laredo Group </li></ul></ul></ul><ul><ul><ul><li>Director of Online Marketing, Interval International, an InterActive Corp (IAC) company </li></ul></ul></ul><ul><ul><ul><li>Interactive marketing consultant for IAC’s new business opportunity unit </li></ul></ul></ul><ul><ul><ul><li>Former President, South Florida Interactive Marketing Association and founding board member </li></ul></ul></ul><ul><ul><ul><li>Founded and operated Key Promotions, Inc., a private web consulting firm for clients such as Barbizon International Modeling, the National Cancer Health Institute, Lexus and others. </li></ul></ul></ul>
  4. 4. Quote of The Day <ul><li>Everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted. </li></ul><ul><li>Albert Einstein </li></ul>
  5. 5. Tracking vs. Analytics & Analysis <ul><li>Website tracking refers to the act of archiving existing websites and tracking changes to the website over time. – </li></ul><ul><li>Web analytics is the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web usage. There are two categories of web analytics; off-site and on-site web analytics. – </li></ul>
  6. 6. Tracking vs. Analytics & Analysis <ul><ul><li>Web analytics suites do the tracking and allow you to report on the data you’re tracking. Web analytics suites give you: </li></ul></ul><ul><ul><ul><li>Ways to slice and dice the data </li></ul></ul></ul><ul><ul><ul><li>Charts and graphs </li></ul></ul></ul><ul><ul><ul><li>Reports - aggregate your log file data </li></ul></ul></ul><ul><ul><ul><li>Examples of some popular ones: </li></ul></ul></ul><ul><ul><ul><ul><li>Google Analytics (It’s FREE!)  </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Omniture </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Coremetrics </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Webtrends </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Etc. </li></ul></ul></ul></ul>
  7. 7. Tracking vs. Analytics & Analysis <ul><li>Knowing what to track and selecting the right tracking tools are NOT accomplishing ANALYSIS! </li></ul><ul><li>Analysis is hard work. Analysis is hard work. Analysis is hard work. Analysis is hard work. </li></ul>
  8. 8. Tracking vs. Analytics & Analysis <ul><li>Breaking it down </li></ul><ul><ul><li>Tracking gives you data points such as: </li></ul></ul><ul><ul><ul><li>Hits </li></ul></ul></ul><ul><ul><ul><li>Visitors to site – unique and repeat </li></ul></ul></ul><ul><ul><ul><li>Average time on site </li></ul></ul></ul><ul><ul><ul><li>Referring sites </li></ul></ul></ul><ul><ul><ul><li>Bounce rate </li></ul></ul></ul><ul><ul><ul><li>Keywords </li></ul></ul></ul><ul><ul><ul><li>Pages visited within a site </li></ul></ul></ul><ul><ul><ul><li>Clickstream data </li></ul></ul></ul>
  9. 9. <ul><ul><li>Bounce Rate </li></ul></ul><ul><ul><ul><li>Represents the percentage of initial visitors to a site who &quot;bounce&quot; away to a different site, rather than continue on to other pages within the same site. </li></ul></ul></ul><ul><ul><ul><li>Anything over 50% should scare you </li></ul></ul></ul><ul><ul><ul><li>Anything over 35% should be testing page elements to lower it </li></ul></ul></ul><ul><ul><ul><li>Anything between 25-35% is OK </li></ul></ul></ul><ul><ul><ul><li>Anything under 25% is worth doing a back-flip over! </li></ul></ul></ul>Tracking vs. Analytics & Analysis
  10. 10. Tracking vs. Analytics & Analysis <ul><li>Goals - Before you start analysis, you need to understand your goals. </li></ul><ul><li>Actionable Insights – If what you’re tracking, and what your web analytics suite is reporting on does not help you form actionable insights, you’re tracking the wrong thing OR you don’t understand how to use the data. </li></ul>
  11. 11. Tracking vs. Analytics & Analysis <ul><li>Inclusive – Being inclusive when it comes to analytics means two things: </li></ul><ul><ul><li>Not analyzing data that exists in silos </li></ul></ul><ul><ul><li>Not analyzing in silos – include your stakeholders! </li></ul></ul><ul><ul><li>Classic Example of the former: </li></ul></ul>
  12. 12. Tracking vs. Analytics & Analysis Click Data Analysis What can we learn from this data?
  13. 13. Tracking vs. Analytics & Analysis Conversion Data Analysis What can we learn from this data?
  14. 14. Tracking vs. Analytics & Analysis Click Data Conversion Data
  15. 15. What it Means to Be Average <ul><li>Why Averages Are Like Dessert </li></ul><ul><ul><li>Like a good dessert buffet, it’s very tempting to use averages when talking about your web metrics. </li></ul></ul><ul><ul><li>But averages are not always the answer. </li></ul></ul><ul><ul><li>Dive deeper, look beyond the surface. </li></ul></ul>
  16. 16. What it Means to Be Average <ul><li>A quantity, rating, or the like that represents or approximates an arithmetic mean; a typical amount, rate, degree, etc.; norm. – </li></ul><ul><li>Aggregate averages are more or less, useless, especially for high volume trafficked sites. </li></ul><ul><li>It’s lazy. </li></ul>
  17. 17. What it Means to Be Average <ul><li>So, what is one to do? Check out what every user is doing and give them each a separate path through the site to accommodate them? </li></ul><ul><li>No. Segmentation is the answer. </li></ul><ul><li>Take all that rolled-up aggregate data that you your web analytics tool spits out in it’s invariably pre-programmed, pre-defined report and segment it. </li></ul><ul><li>Dig into your analytics suite and figure out its segmentation capabilities. </li></ul>
  18. 18. What it Means to Be Average <ul><li>Segmentation Example by Channel: </li></ul>
  19. 19. What it Means to Be Average
  20. 20. What it Means to Be Average <ul><li>Hey! Now we can gain some real insights about visitors! </li></ul>
  21. 21. Dashboards <ul><li>Why Use Dashboards </li></ul><ul><ul><li>Understand business performance </li></ul></ul><ul><ul><li>Track critical business data in an easy to understand manner </li></ul></ul><ul><ul><li>Can vary by many factors: data available, seniority in institution, etc. </li></ul></ul><ul><ul><li>Excel </li></ul></ul>
  22. 22. Dashboards <ul><ul><li>General concepts that should be considered when creating your dashboard: </li></ul></ul><ul><ul><li>Benchmark & Segment </li></ul></ul><ul><ul><ul><li>Provide context for dashboard readers </li></ul></ul></ul><ul><ul><ul><ul><li>For example: previous sales, industry benchmarks, goals, etc. </li></ul></ul></ul></ul><ul><ul><li>Isolate Critical Few Metrics </li></ul></ul><ul><ul><ul><li>10 metrics or LESS </li></ul></ul></ul><ul><ul><ul><li>Each has to have context </li></ul></ul></ul><ul><ul><ul><li>Each has to be further segmented </li></ul></ul></ul>
  23. 23. Dashboards <ul><ul><li>Don’t Stop at Metrics—Include Insights </li></ul></ul><ul><ul><ul><li>Summarize </li></ul></ul></ul><ul><ul><ul><li>Recommended Next Steps </li></ul></ul></ul><ul><ul><ul><li>Opportunities/Missed Opportunities </li></ul></ul></ul><ul><ul><ul><li>Don’t make your executives think! </li></ul></ul></ul><ul><ul><li>The Power of a Single Page </li></ul></ul><ul><ul><li>Evolution (and stay relevant) </li></ul></ul><ul><ul><ul><li>Your business evolves </li></ul></ul></ul><ul><ul><ul><li>So should your dashboard </li></ul></ul></ul>*Avinash blog post, Five Rules for High Impact Dashboards, March2007
  24. 24. Dashboards <ul><li>Google Analytics Dashboard </li></ul>Needs Context and A Summary! Segmentation by Channel Segmentation by Metric
  25. 25. Dashboards Benchmark by Date
  26. 26. Resources <ul><li>Web Analytics Association </li></ul><ul><li>Great article on ClickZ about what digital analysis is: </li></ul><ul><li>Avinash’s blog, author of Web Analytics: An Hour a Day </li></ul>
  27. 27. Shameless Self Promotion: University of San Francisco Masters Certificate in Internet Marketing Integrated Online Strategies Search Engine Marketing & Usability Advanced Interactive Marketing Web Analytics & Measurement
  28. 28. <ul><li>Thank You Want a copy of this presentation? Go to </li></ul><ul><li>Stay In Touch: Twitter: @iclarity [email_address] </li></ul>