Upcoming LunaMetrics Seminars
Washington DC, Sep 22-26 Boston, Oct 6-10 Chicago, Oct 20-24 Seattle, Nov 3-7

"What does a good-looking recency chart look like?"

This was the question that greeted me in my email this morning. What should a good-looking recency chart look like? asked the writer. He was referring to a post I wrote about a year ago on how Google Analytics calculates recency.

Recency charts are like conversion rates — different for everyone. A recency chart for an ecommerce site won’t look like one for a content site. But best practices would always dictate that the chart is filtered by new and returning visitors; otherwise, new visitors and visitors who are addicted to your site will both end up in the zero days chart.

For example, here is the unfiltered recency chart from LunaMetrics, and next to it, the same chart filtered to include only returning visitors

Unfiltered Recency chart

Unfiltered Recency chart

Filtered Recency Chart

As you can see, by using Advanced Segments (that’s how I did this) to filter out the new visits (and only get returning visits), the charts look very different. On the left is the unfiltered recency chart. But on the right — the chart with only returning visits – shows what you might consider a “good looking” recency chart — one that has a larger 8-14 day bar than the 7 day bar, since 8-14 days is seven days of data.  That last point is an opinion only — remember, every site is different, and not all will see a bulge in the 8-14 day bucket — but most that I have seen do.

Robbin Steif

About Robbin Steif

Our owner and CEO, Robbin Steif, started LunaMetrics ten years ago. She is a graduate of Harvard College and the Harvard Business School, and has served on the Board of Directors for the Digital Analytics Association. Robbin is a recent winner of a BusinessWomen First award, as well as a Diamond Award for business leadership.

http://www.lunametrics.com/blog/2008/12/08/goodlooking-recency-chart/

9 Responses to “"What does a good-looking recency chart look like?"”

Thanks for this post! I also have a bump at 8-14 days, and I run a webcomic that publishes content on Mondays, Wednesdays and Fridays. I guess that’s alright.

cipals15@gmail.com says:

This has similar features with Google Analytics.

Bertjan says:

Thanks for this post.
What exactly do you mean with:

“since 8-14 days is seven days of data”

That a lot of visitors visit the site once a week?

Robbin says:

Bertjan — the 8-14 day bucket happens to be seven days, and that is just a coincidence that it is a week long. What I really meant was, people who last visited one day ago, and two days ago, etc, include visits that were just at a specific time that included only 24 hours (a day). Whereas the 8-14 day bucket includes 24*7 hours, so it should have a lot more visits. That’s why a lot of charts see a bump there.

Tom Sullivan says:

This is a very helpful post. Always looking for new ways to interpret my Google Analytic data and this is an interesting way to look at this type of data. Thanks!

amyolson says:

looking for a good guy to go out with

amyolson says:

do you want to chart

Mike says:

I need to try and determine what percentage of people visit my site more than once a day. Is that possible?

Robbin says:

Jim Gianoglio from Luna answered this question. He suggested this advanced segment

https://www.google.com/analytics/web/template?uid=_1ck3epiS5Kfaw-mSD4N5w

will answer that question. It includes visitor type = returning visitor AND days since last visit = 0. If you apply it to a multi-day range, along with the All Visits advanced segment, and look at the Audience Overview report, the Unique Visitors metric should tell you what you’re looking for (after a bit of simple division).