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Web analytics 101: Web Metrics

The number of possible Web Metrics is large and increasing. Multiply by the number of Dimensions, and there is nearly an infinite number of things an analyst can look at. Get your basics down in Web Analytics 101 – Web Metrics.

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Web analytics 101: Web Metrics

  1. 1. Web Analytics 101 WEB METRICS Understanding basic web metrics and best practices.
  2. 2. Basic Web Metrics Examples and definitions.
  3. 3. Measures: created by direct measurement of activity.
  4. 4. Pageviews (count) Visitors (count unique)
  5. 5. Calculated Metrics: created by dividing one measure by another measure.
  6. 6. Pageviews/User or PV/Session Sessions/User
  7. 7. Derived Metrics: created by taking a metric and dimension (usually time), and creating a new derived metric.
  8. 8. Sessions (count) Frequency; Days of Use
  9. 9. Indices: created by normalizing a group of metric observations (usually to 100) and calculating an observation’s value relative to the top normalized value.
  10. 10. Measures, Metrics, Indices Everything an analyst can look at.
  11. 11. The number of possible Web Metrics is large and increasing. Multiply by the number of Dimensions, and there is nearly an infinite number of things an analyst can look at!
  12. 12. How to Cope Managing infinite web metric options.
  13. 13. Prioritize Make sure your business leaders have designated their top metrics (commonly called KPIs – Key Performance Indicators)
  14. 14. Build a Metrics Tree Show how all of your metrics interrelate. Connect them to revenue and profit. Focus on drivers and leading indicators.
  15. 15. Revenue is a lagging indicator. Customer satisfaction is a leading indicator. New customers is a driver.
  16. 16. De-Average Utilize the de-averages technique to create new metrics.
  17. 17. Benefits De-Average
  18. 18. There really is no “average” Internet user. Small numbers of users can drive a lot of traffic. Break down your important metrics into deciles to gain new levels of insight.
  19. 19. Threshold metrics add a “mix” focus to business goals, which can have major impact on growth.
  20. 20. The Law of De-Averages Be suspicious of averages – taking them at face value can sometimes lead to wrong conclusions.
  21. 21. Keep in Mind
  22. 22. Keep in Mind Always understand how a metric will be used, and whether an average (mean, median, or mode) is the best way to present the metric.
  23. 23. Keep in Mind Always understand how a metric will be used, and whether an average (mean, median, or mode) is the best way to present the metric. Always make an attempt to understand the shape of the distribution behind the metric’s average, and if that distribution is changing over time.
  24. 24. Keep in Mind Always understand how a metric will be used, and whether an average (mean, median, or mode) is the best way to present the metric. Always make an attempt to understand the shape of the distribution behind the metric’s average, and if that distribution is changing over time. Where possible, break a metric out into quintiles or deciles, based on frequency of observations or users. Map the deciles to usage to create a customized version of the “80/20” rule for that metric.
  25. 25. Keep in Mind Always understand how a metric will be used, and whether an average (mean, median, or mode) is the best way to present the metric. Always make an attempt to understand the shape of the distribution behind the metric’s average, and if that distribution is changing over time. Where possible, break a metric out into quintiles or deciles, based on frequency of observations or users. Map the deciles to usage to create a customized version of the “80/20” rule for that metric. If the story of the de-average is significantly different than the story of the average, ensure business owners and other action drivers are sufficiently educated.
  26. 26. Keep in Mind Always understand how a metric will be used, and whether an average (mean, median, or mode) is the best way to present the metric. Always make an attempt to understand the shape of the distribution behind the metric’s average, and if that distribution is changing over time. Where possible, break a metric out into quintiles or deciles, based on frequency of observations or users. Map the deciles to usage to create a customized version of the “80/20” rule for that metric. If the story of the de-average is significantly different than the story of the average, ensure business owners and other action drivers are sufficiently educated. Where needed, set primary or secondary business goals on threshold metrics and specific segments, to further drive desired performance improvements.
  27. 27. Presented by SOCIETY CONSULTING
  28. 28. Connect With Us SOCIETY CONSULTING @SOCIETY_CONSULT SOCIETY CONSULTING SOCIETYCONSULTING.COM

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