In other words, why should we believe that the place at which we measure our metrics is also the location of the problem? 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 which may have occured much earlier in the process.
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 (globally a problem)
The Exit page can be thought of 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.
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; simply being a page with a high Exit rate isn’t sufficient in and of itself 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 those instances where the Exit page is simply the place where the problem is measured? How would we expect the metrics of Exit pages to act in this context?
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 of time spent 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. If this is that point, then she’ll finish up with this page and look around for more info or move on. Of course, she doesn’t move to another page on your site at this point (since we measured THIS page as the Exit page). 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 to having a 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 cases of the Exit pages being of only one type of problem or the other (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 std 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 of Exit page metrics to be much wider, because really you’re measuring two diff’t 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.
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 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 towards 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 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 had set up an expectation of relevancy — a contract with the visitor if you will — that the Bounce page isn’t prepared to handle. Perhaps someone in charge of PPC efforts has changed something in the Ad — all with good intent — but if this scent isn’t followed through from the Ad onto the ensuing pages it manifests as an increase to the Bounce rate when visitors get to the site.
This comes about 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 and optimizing away, and PPC folks add driving click-thrus 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 co-ordinated effort cross-company.
That should give us all something to think about, right? 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 (meaning: “it’s a coin flip!And I can’t treat this problem until I know more!”) than any organization would like to admit.
[This article is Cross-posted to my monthly column at MarketingLand, which is a great place to read all sorts of interesting content.]