Many organizations get fixated on metrics data, without thinking of where it comes from. But, what if your metrics indicate a problem which originates somewhere else?diagnose

Huh? What I’m asking is, “why should we believe that the place at which we measure our metrics is also the place where the problem occurs?” Perhaps the metric is simply reporting a symptom, but not the malady itself.

Take, for example, a rather common fixation on Exit Pages. These are often bumped up the organizational ladder as “oh, these pages have to be fixed! they have high Exit rates, therefore people are leaving! Let’s re-factor, or AB test, or etc.

Certainly a high Exit rate indicates something is amiss, and deserves attention. What I’m suggesting, however, is that a high Exit rate page is often not a problem with the Exit page itself at all, but rather, a manifestation of a problem much earlier in the process.

Think Globally

Do we really want to be treating symptoms, rather than the disease? You have weight loss? Eat more. You’re thirsty all the time? Drink more. Feel tired or run-down? Get a full nights sleep. Yet, all three of those symptoms are correlated with diabetes, for which eat more, drink more, sleep more are hardly the best pieces of advice. You may well cure a symptom (act locally) but have little impact on the disease (think globally).

The Exit page can also be thought of as the place where the visitor “gave up.” Something occurred on previous pages or interaction points, and the reported Exit page is simply the final divorce decree your customer is serving on you. Yes, it is much like a divorce, where the marriage has ended de facto long before it’s ended de jura.

Look Beyond The Exit Page

Many analysts get caught up in this conundrum. They are tasked with reporting metrics and (usually) making suggestions for improvement. But, unless they are looking at the bigger picture, they have a built-in incentive to treat the symptomatic problem. Don’t you fall into that.

To be sure, there are plenty of cases where the Exit page is the problem. And this is my point — the fact that a page has a high Exit rate isn’t sufficient to diagnose the problem. So, in line with taking a broader view of continuous optimization at your organization, join me in this thought experiment: what would it mean if the Exit page itself were a problem, versus the Exit page being not much more than the place where the problem is measurable? How would we expect the measurements of Exit pages in this context?

Clues To Diagnosing The Real Problem

Here’s one approach:

If we think of Exit page as “end of conversation” or “not interested,” etc. —  then you might expect that the time spent on this page to be of approximately average or even above average time spent on this page, compared to all other Exit pages. The visitor has continued down a conversational path with you, and has come to a point where, in some context, you’re no longer relevant to her. Fair enough, we can investigate the various factors on that page that may have gone awry, and fix those we are capable of fixing.

However, what about when the visitor loses her way long before the Exit page? Obviously, she hasn’t exited yet (otherwise one of the earlier pages would have been analytically reported as the Exit page for this visitor). But, from the moment of her dis-engagement, what we might expect a human to do is to flitter around a bit in an attempt to get back on track or find what she is looking for.

Visitors have goals on your site, and they will put in (at least a little) effort in getting to those goals. Maybe hit the Back button. Or go to the home page. She might even start using the Primary navigation. You may be surprised, but Primary Nav is one of the least used parts of a site among visitors who are getting what they want, and one of the most used parts of a site among visitors that are having a “disconnect” from you.

So, what might we expect to see in the metrics in this case? We should see such Exit pages as having much lower time spent on this page compared to the average Exit page. And likely, the pages just before getting to the Exit page also have lower-than-average Time Spent as she jumps around trying to rediscover the scent of her intended trail.

What else might we expect? Well, in those cases where the problem is really the Exit page (that is, “we have a problem with Exit Pages” versus “we have a problem somewhere earlier in the process“), the spread of the average metrics for this page such as Time Spent, etc., should be fairly narrow and static over time. The standard deviation of the metric will be fairly tight compared to its average.

In contrast, if you have both types of Exit page problems on your site, then you’d expect the standard deviation to be much wider, because really, you’re measuring two different populations of problems. This in itself suggests an occasional “binning” of the Exit pages in some visual way so you can diagnose if you have anything other than a bell curve distribution of Exit page problems.

Apply This Thinking To Other Metrics

Once you start thinking about your problem with Exit pages this way, you can come up with better ways to isolate Symptoms from Disease, and you’re that much further along in treating both effectively. Your Patient-Visitor will thank you because she’ll get more done at your site.

By the way, this sort of shift in your thinking will point you toward a similar approach to other problems on your site. For example, Bounce Rate.

(As an aside, I’ll make the distinction here that Exit Page is the last page the visitor was on in a session, and Bounce page is a special kind of Exit page where the visitor was only ever on that one page before leaving.)

For years, people have made a lot out of Bounce Rate — as they should — but without considering that the Bounce page, typically a landing page or home page, may not really have any problem with it at all.

Again, this doesn’t mean that all Bounce Rates are ignorable. Just the opposite, because what I’m asserting is that there is as strong a possibility that the Bounce Page is being bounced off of because of something wrong with the Ad or the referring Search Engine result, or etc., which set up an expectation that the Bounce page isn’t prepared to handle.

Perhaps someone in charge of PPC efforts has changed something in the Ad — with good intent — but if this scent isn’t followed through on the ensuing pages, it manifests as an increase to the Bounce rate when they get to the site.

This occurs far more often than you would think, because so many organizations are set up as silos. You’ve got the analysts on one side trying to measure as much of it as they can get done, people responsible for the website tweaking optimizing away, and PPC folks driving click-throughs, but possibly without interacting with the team managing the site. All of which create symptoms that there’s something wrong with the site when the disease may well be the lack of coordinated effort cross-company.

That should give us all something to think about. I’m curious, what percentage (rough estimate) would you put on the ratio of Exit Pages that have problems with the page itself versus problems that occured much earlier in the process? My experience is that it’s far closer to 50:50 than any organization would like to admit(meaning: “I can’t treat this problem until I know more!”).

Image from shutterstock used under license.

Opinions expressed in the article are those of the guest author and not necessarily Marketing Land.

Related Topics: Analytics | Analytics & Marketing Column | Channel: Analytics | Conversion Rate Optimization

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About The Author: is one of the inventors of Persuasion Architecture and regularly combats innumeracy among marketers in his popular "Math for Marketers" series. John's 2008 best-seller, "Always Be Testing", written with business partner Bryan Eisenberg, has been the standard reference for conversion optimization through testing since its release and has been used for the basis of both academic coursework as well as corporate training.



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