Scene: A late night somewhere in America. Crickets softly chirping. A dog barks. A streetlamp flickers. Camera zooms in on a quiet neighborhood house. A light in the second story is on.

Cut to hands tapping on a keyboard. Cue in tense violin music. Camera pans up to laptop monitor displaying giant blinking words that read “Bounce Rate”

Real estate professional (off camera): [Ear splitting scream of terror].


When you don’t know what to look for in web analytics data you’re left with whatever the tool manufacturers present on the dashboard. Worse still, you might not be sure what to do with the numbers. You can be scared. You can wish it looked different. But if you don’t know what to do then you’re just spinning your wheels.

Here’s how I look at data when I’m in the reports mucking around.

I look for patterns.

That’s it.

Ok, maybe there’s a little more to it than that. But generally speaking, that’s the entirety of it.

One of the harder parts is not being too emotionally involved with the data. For me this is easy except when looking at the data for my own site. When looking at your own website’s data it’s hard not to get attached to a particular outcome: if you want to see something, you’ll see it (or if you’re a pessimist you’ll see the opposite).

It’s tempting to look at a number and think about it like a score in a baseball game or a time to beat in your next summer biathlon event. But data isn’t like that. It’s dispassionate. It isn’t about winning and losing. A great bounce rate for one business is might be a terrible bounce rate for another business.

So just look for patterns. Anything that makes you say “that’s interesting.” Then start asking questions like “I wonder why?” or “How long did that last?” and so on. Eventually you’ll come up with some insights and things you might want to do differently.

And that’s the purpose of looking at the data in the first place: to do things differently than you’re doing them right now. Hopefully, looking at the data will help you do things better than you’re doing them right now.

Here’s a step-by-step to get you started in pattern recognition (which is also the title of an awesome book, for those of you who like reading):

1. Log into your Google Analytics account.
2. On the dashboard there’s a line graph that shows visits.
3. Does that line have a regular pattern of bumps?
4. Change the date range (upper right corner) and look at the past year’s worth of data.
5. Does the line have any regular pattern of bumps now?
6. How about spikes?
7. How about dips?
8. If you saw any patterns can you remember if you were doing anything in particular for marketing during or shortly before those time periods?
9. Do the bumps, waves, spikes, dips correspond to seasons or weather patterns?
10. Go to the report that shows pageviews of the page that has your property search and compare the patterns there with the patterns you saw in traffic. Anything interesting?

And so on. Once you learn to recognize patterns and ask questions about the patterns (instead of reacting emotionally) then you can start to move towards making decisions and acting on the data. We’ll cover that in a future installment.

Meanwhile, don’t hesitate to post any questions you have or interesting patterns you find.

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