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How to Use the Google Analytics Frequency & Recency Report

anna-lewis
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The Google Analytics Frequency and Recency Report (within Audience > Behavior) is perfect for analyzing visits in order to help you plan your marketing campaigns or gain other beneficial insights about visits to your website.

frequency-and-recency-reports

Count of Visits

This data counts how many repeat visits there have been on your site. The data is based on visits to your website over time, showing how many times just one visit is tracked, then two visits on the same device, then three etc.

If a user visits the site on the same device three times, without clearing their cookies, they will be shown in Count of Visits rows 1, 2 and 3. This is why the numbers will decrease all the way down to the row in which the count of visits shows a range of counts (i.e. 9-14).

This is interesting as different websites will see different levels of visits per user. Knowing what is a typical pattern for your website and working to increase the count of visits is beneficial.

This report can be used to see how many people only visit the site once, compared to more than once; just subtract visits in the row for 2 visits from the number of visits where the count was 1.

Days Since Last Visits

This report shows the number of days between the visitors’ latest visit and the visit before that. Users who have one been to your website once will significantly skew the data as they fill the 0 days since last visit row. To get around this see the ‘Making the Data Clearer’ section below.

Applying various segments to this can help you dig down to find the types of customer you want more of, or those you need to see improvements from, once you have applied the segment you can review the behaviour patterns and plan your marketing activity around these patterns.

Making the Data Clearer

You will notice that the rows for 1 Visit and 0 days since last visit will often skew the results as they have so many visits and pageviews compared to other rows:

frequency-and-recency-skewed-data

To get around this you can pop an advanced segment on that excludes "count of visit is 1" or "days since last visit is 0".

count-of-visits-is-one

This will then show you a clearer visualisation of activity where more than one visit occurred, making it much easier to analyse results and make decisions on a valuable data set:

making-the-data-clearer

Frequency & Recency of Valuable Users

Additionally, it is very interesting to see the pattern of visits recorded. If people are coming back to the site six times, have they converted? To understand this, use the default segment for Visits with Conversions or Transactions. I like to create a segment that also shows the opposite so that you can compare activity of those who converted and those that didn’t.

And why stop at just transactions? If you have values for your goals or ecommerce tracking set up then use an advanced segment for revenue or goal value over $50 to see how your valuable users behave.

With these segments you can identify patterns to help you schedule remarketing campaigns, email marketing and other promotions.

Taking it Outside the Report

If a histogram isn’t your thing or if you want to see the data your way, using count of visits and days since last visit metrics in custom reports and dashboards can be very beneficial. I featured a pie chart showing total visits broken down by count of visits in my Social Media Dashboard which helps you see how loyal social visitors are.

social-visitor-loyalty

Including Count of Visits as a metric in a custom report can help you break down visits and conversion rates by the number of times users have visited the site. Adding it as the second dimension in the drilldown enables you to review this for a specific group of data.

This All Traffic Sources custom dashboard has visit and goal data for source /mediums and once you click one of the source / mediums you get a breakdown of the count of visit data for that traffic source.

count-of-visits-conversion-rate

Other segmentation or reports you might want to consider analyzing this data against are:

  • Mobile devices
  • Traffic sources
  • Landing pages
  • Members vs. Non-members (using custom variables)
  • Transactions
  • Order value
  • Locations

Hopefully these ideas help you get the most from this data to plan and improve results for your website. Here are three items that use this functionality, which you can apply to your Google Analytics account right now:


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