Track Visitor Engagement using Google Analytics!

One of the major complaints about my work on measures of Visitor and Audience Engagement is that unless you have Visual Site (= Omniture on Premise), Unica, Coremetrics, SAS, or a custom data warehouse solution you’re somewhat limited in your ability to make the calculation. Now, thanks to the recent upgrade to Google Analytics and the availability of session-level segmentation everyone can use my calculation to explore engagement patterns on their site.

Yep, free measures of Visitor Engagement from Analytics Demystified and Google Analytics!

It was a post from Alec Cochrane about engagement that got me thinking about the application of my calculation using Google’s segmentation features, thanks Alec! Heck, had I been paying more attention to his blog I would have noticed that even Avinask Kaushik (who persists in his dogmatic assertion that “engagement cannot be measured”) refers to GA’s ability to make the calculation.

Keep in mind, what I’m describing in this post is not a full-blown measure of Visitor Engagement for a lot of reasons. Still, as I’m kicking it around it appears to be a pretty good start and per my entire approach towards measures of engagement, I’d rather have all of you banging on the idea than work in a vacuum.

So how does it work?

Step 1: Gather Your Threshold Values

The first step is to determine what thresholds you want to set for your Click-Depth, Duration, Recency, and Loyalty indices.  You can get the first two from GA’s Visitors > Overview report (shown at right) while Recency and Loyalty come from Visitors > Visitor Loyalty > Recency and Visitors > Visitor Loyalty > Loyalty respectively.

Depending on your site you may need to be creative in how you set the Loyalty and Recency thresholds, especially since GA’s reporting on these measures is not super robust. Fortunately, since the segmentation tool is pretty flexible you can play with the threshold values once you’ve set them.

Step 2: Create Your Engaged Visitors Segment

The next step is to create a segment that lets you identify “engaged” visitors on your site. I’ll first describe the basic calculation, which is essentially the same as Audience Engagement only applied to click-stream data, and then expand in a follow-up post on the idea leveraging the Interaction Index, the Brand Index, and the Feedback Index.

Start by “creating a new custom segment” and adding the visitor dimension “Page Depth” (Google Analytics’s measure of Click-Depth during the session) setting the condition to “Greater than or equal to” the Click-Depth threshold value you discovered in Step 1:

Make sure to test the segment and confirm that things are working. In the example above you can see that about 25% of the sessions to my site last May were of at least three page views. Next you’re going to add the Duration Index by adding an “and” statement and dragging in the visitor dimension for “Visit Duration” and setting the condition to “Greater than or equal to” the time on site threshold determined in step 1:

Because you’re using an “and” statement we are getting the number of sessions that were both at least three page views and at least three minutes in duration; while this is imperfect compared to the visitor by session scoring strategy we described in the longer white paper the use of “and” ensures that we’re identifying visitors who are paying Attention as measured by clicks and session duration.

The next step is to roll in the Loyalty and Recency indices using the visitor dimensions “Count of Visits” and “Days Since Last Visit”.  As I mentioned above you may need to play with the thresholds here, perhaps creating a visitor segment of goal converters (purchases, leads, etc.) and examining the return visit behavior for that segment.  Also, when you set “Days Since Last Visit” be sure to use the condition “Less than or equal to” to capture visitors who have been to the site recently:

If your site is like mine you’ll see a noticeable drop in the number of matching visits when you add “Count of Visits” or “Days Since Last Visit” because of the use of the “and” operator.  But this is good and to be expected since if everyone coming to your site was truly engaged then you wouldn’t be reading this post, you would just be rolling in money.

All you have to do now is name and save the segment and you’re in business!  I called my segment “Engaged Visitors” which is not technically correct — really what I’m tracking is “Engaged Visits” — but when you see the final application of the segment below you’ll understand why.

Step 3: Mine Google Analytics for Engaged Visitors

Once you’ve created your “Engaged Visitors” segment you can start to apply it to the various reports in Google Analytics.  I recommend comparing the engagement segment against “All Visits” to get context — and GA does something nice here in calculating the percentage of segment members (= sessions where all four engagement criteria are met) for you.  Here you can see how this comparison looks in the Visitors > Map Overlay report:

While I’m only drawing a moderately engaged audience from Australia I am feeling the love from Spain! Probably since my good friend Rene Deschamps is Spanish or perhaps since I’m talking to a web analytics consulting group in Spain about coming over for a presentation and a big Web Analytics Wednesday event this coming Spring … who knows?

Now, I am pretty delighted with how easily these segments can be applied to the various reports in Google Analytics … hell, just the fact that the segment stays applied when I navigate from report to report is nice.  And yes, there are some obvious improvements that could be made but for a first effort this is pretty nice.

The same segment can be applied to reports that are more critical to how you run you business, for example the keyword report.  When I look at three top keywords driving traffic to my site you can see a clear pattern begin to emerge (and this is without adding the Brand Index into the engagement calculation):

Here you can see an obvious difference in the level of engagement associated with external searches for my brand’s name and “Web Analytics Wednesday.”  Even searches for Judah Phillips driving traffic to my site are bringing in a highly engaged audience (Judah, since I know you’re sensitive about this, nearly 30% of the visits associated with searches for you are scoring as engaged … nice work, buddy!)

If you’re willing to keep drilling down you can learn all kinds of wonderful things.  Here is a comparison of network traffic coming from WebTrends and Omniture:

Finally, if you’re using your one user defined field to capture some type of visitor identifier (hopefully doing so in line with your privacy policy) you can actually apply the engagement segment to individuals or groups interacting with your web site and actually begin to measure true Visitor Engagement.  Here you can see my very good friends Judah and June who are highly engaged at the Analytics Demystified web site, shown in stark contrast to another very active visitor who does not appear to be paying me any Attention at all:

This has become a long post so I’ll stop here for now and leave you with the following summary points:

• Google Analytics, like any session-based system, is not perfectly suited for calculating a true measure of Visitor Engagement;
• That said, given the recent availability of segmentation in Google Analytics, I would encourage those of you running GA to explore the use of my Visitor Engagement calculation;
• My belief is that you will begin to see for yourselves that this measure will help you identify opportunities not easily uncovered using traditional measures like average time on site and bounce rate;
• But you don’t have to take my word for it, do you? Play with the ideas I put forth in this post and let me know what you discover.  I would absolutely love to hear what you learn using this segmentation strategy or learn about applications of the segment that I haven’t thought of yet!

Last but not least, keep in mind that I have always put forth my work on Visitor and Audience Engagement as a hypothesis, one that is still being evolved and subject to testing and application in a variety of business situations. The thing I love about our community more than anything is the willingness that most of us show to explore new ideas and have an open mind.

As always I welcome your comments and feedback.