Friday, 6 February 2015

Google Analytics Adds Basic Cohort Analysis (Beta)

In statistical analysis, a cohort is a group of people or subjects who all share some time-bound event, characteristic, or experience. For example, shoppers who visit an ecommerce site for the first time on January 30, 2015 could be said to be a cohort since they have a shared characteristic — they visited for the first time — and the experience was during the same time period, Friday, January 30. Cohort analysis is, perhaps, most useful when two or more cohorts are compared. This comparison lets marketers and analysts see the relationship between the two cohorts over time.


The Analytics’ cohort report can be configured around cohort type, cohort size, metric, and date range.

  • Cohort type. At the time of writing, the only available cohort type was acquisition date, thus one could look at how folks who visited the site on a particular date behaved over time.
  • Cohort size. This report attribute may be set to day, week, or month. In the email example above, each cohort was defined by folks who registered in January. It may be the case that if Google added additional cohort types, it would also expand the list of available cohort sizes to include other sorts of dimensions.
  • Metric. This is simply the thing one wants to measure. Presently, metrics include conversions per user, page views per user, sessions per user, user retention, goal completion, conversion, and more.
  • Date range. The relative date range for the data to be displayed.


The cohort analysis can also be run across segments. As an example, one could look at the average session duration for visitors on mobile devices versus visitors using desktop computers. Or cohorts could be based on new visitor acquisitions the week before Christmas 2014, the week including Christmas, and the week after.



This example shows session duration for three cohorts.

Doing this analysis, we might learn that visitors using desktop computers generally spend more time on site than do visitors on mobile devices and that this effect is even more extreme during the week before Christmas.



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