CLIENT: I was looking at the analytics today!
ME: Great!
CLIENT: We have to figure out what’s wrong!
ME: Whoa, what do you mean?
CLIENT: The site is bouncing!
ME: Really? And the analytics told you that?
CLIENT: The bounce rate – it’s really high!!
ME: Oh, okay. Tell me what it is.
CLIENT: Fifty percent!
ME: Ah, well – yeah that is a bit high but not totally unheard of…
CLIENT: Oh… I see…. So, what is a bounce rate?

Hey, I just report the facts. And this is not meant to make fun of anyone, but rather use it to illustrate something that only really started happening with the appearance of Google Analytics – which is the free & easy access to analytics, and free & easy methods of misinterpreting them.

All too often website owners love to look at their stats or talk about hits and page counts and time on the site, but are often not really able to discern what it means.  And I’m not talking about just the definition of bounce rate, CPM, organic, absolute unique vs unique — the main thing is that they are missing context.

Usually after installing any analytics package the first (or maybe tenth) thing someone does is try to “test” it to see if it’s working properly.  This can be comparing to another analytics system or an internal accounting system or web logs.  Newsflash: it ain’t gonna match.  Probably not ever.  In fact, if it did match I would be more surprised.

If you set up a report tracking sales as a goal in Google Analytics and it tells you that you sold 46 hats but you know from the orders you received that you actually sold 51, then you have a problem right?  Wrong.  This is a hard pill to swallow for (especially) business people who are used to accounting reports, reporting to the IRS and those pesky Sarbanes/Oxley dudes.  It has to be exact.  But in the online analytics world it just doesn’t happen.

So we’re back to “context”.  So Google Analytics is telling us we sold 46, but last week on the same day of the week (a different sort of context) we sold 78.  Why?  And should it matter if our reports are off by a different number this time?  No.  They just might be off by more or less.  Or exactly right.  The more important thing is the trend and the disparity in those sales within the closed system of reporting that we are choosing to look at.

Again, it doesn’t mean something bad happened the week before, but some factors must have influenced the sales rate to go up the next week.  Time to dig deeper and discover more context for that uptick which is why we put up with this loosey goosey off by this much type of reporting tool.  Because it allows us to put contexts within contexts within contexts (and so on)—which systems that are only concerned with tabulating orders and shipping some stuff out are not able to do.

So, while Google Analytics is a fabulous tool, and the fact that it is available for free gives ordinary folks great insight they never had before—taking the extra step of asking “why” and not focusing on the “what” is a good start.

So back to the “bounce rate” (which, by the way, is the percentage of visitors that only view one page before leaving). Is her bounce rate bad? As it turns out there is a buy button on the homepage that sends users off to a shopping engine that is not on the same domain, thus Google Analytics determined they were “leaving” instead of moving on to buy something.  This didn’t account for all the bounces, of course, but it could explain the strangely high number.

This is a question people ask about every single stat in their analytics.  And usually the answer should be “that depends.”

Yeah, people hate that answer…