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What if your method of counting visitors were flawed? What if, instead of undercounting, as was the case at the National Portrait Gallery, your data source showed far more visitors than there were. What if your data source doubled your actual visitor count?
What if that went on for years?
Imagine evaluating visitor behavior in an exhibition, but half the time you spent studying how people interacted in the space was devoted to looking at how employees behaved while installing the show.
I imagine these things would be unacceptable to many museums, but this is the sort of stuff that’s happening right now in their analytics.
Museums and other nonprofit organizations like to track the number of visitors who come to their website. They don’t often go much beyond that. They’re not studying audience behavior in relation to communications initiatives over time — they’re not often segmenting audiences and measuring results.
That makes me want to cry.
Because I often ask them about analytics right after they tell me about how they’re working so damn hard, pouring resources into social media, website content, and collateral — yet there’s no clear understanding of the return on any of the efforts or how to methodically improve on any of it.
It’s like watching someone work themselves to death digging a foundation with a shovel when they have the keys to a backhoe in their pocket.
We’re going to dig deeper into analytics, but let’s focus on those vanity metrics for now — counting visits and page views.
A default Google Analytics (GA) configuration will generate misleading information around basic website hits.
Yep — out of the box, Google Analytics can’t even count.
- 50–60% of those hits you’re tracking are bots.
- Every time someone opens a new window on their browser at work, the home page of your website launches, which accounts for those bazillion hits during the work week. (“Seems like most of our traffic is from direct visits — weird.”)
- You’ve been celebrating that you have a wonderfully low bounce rate — meanwhile, someone accidentally installed the tracking code on your site twice, so now every visit counts as two page views.
There are lots of things that can contribute to polluted data in analytics, but they can be addressed. It’s not something you want to wait on, though, because any changes you make to clean up the account won’t influence past data. Every day that passes is another day you’re operating in the dark in terms of comparing things like year over year performance.
Why don’t we pay closer attention to online behavior using analytics?
I think one contributing factor is that Google Analytics is free. We tend not to value what we get for free.
Another is an underlying assumption that people are as committed as we are.
Nonprofit employees are mission-driven. That’s fantastic — I fall in love with pretty much every nonprofit I work with for the same reason. You feel like you’re part of something bigger than yourself — it’s not just another commercial enterprise.
But that enthusiasm also makes it easy to make mistakes about your audience.
We start to take knowledge for granted. We have trouble seeing the subtle, differing motivations of the audience, and we start believing they’re all equally committed because the people in our audience we encounter most often are the ones who are more committed. (See availability heuristic.)
You start thinking things like:
“If joining or renewing online is hard, won’t people just mail in their membership checks?”
No, they won’t.
Or — yes. Some people will. But many won’t.
I’m not the only person under 40 who isn’t even sure if they own a checkbook and reaches for Xanax at the thought of stuffing an envelope. A collection of small inconveniences is enough for some people to put off even small financial decisions indefinitely. I've seen it in testing over and over again.
In short, analytics is a tool to combat these pesky, all too human tendencies.
Good data can function as a sanity check — a cool observer of your audience’s behavior that has no sympathy for your mission and is not susceptible to wishful thinking.
But the first step in using Google Analytics as a tool to support your mission is to start getting accurate data from it.
Thanks for reading,