Not all that long ago, the maxim used to be: "What you measure is what matters." That is, if your boss has a chart on her desk listing worker productivity and unplanned absences, what mattered to her was a workforce that showed up and did the work.
This made sense: Collecting enough data to measure something effectively is not easy (or cheap). Thus, if the boss collected it, it mattered to them. So why do more on your own independent of that?
The same idea extended to marketing. You spent a lot of money on billboards and commercials and flyers, but you had no easy way of measuring how that campaign or that channel worked. Unless you baked in some complicated scheme to collect audience data (a flyer that has a special coupon code that differs from the one the user might have seen in a magazine, for instance), you couldn't measure anything easily.
Welcome to the digital age. Because we've broken the world into ones and zeros, we can now measure every one and zero. Don't believe me? Ask your cell phone service provider exactly how many bits you uploaded and downloaded. They might not tell you, but they know.
While the ability to measure each one and zero is in almost everyone's hands, the question isn't what can we measure? It's: What should we measure?
If you know what you're doing, you can go to your web analytics software right now and find out how many people from Argentina who use Internet Explorer 8 visited your site. You can compare them to visitors from Russia who visited with an Android.
Of course, there's probably no reason in the world to know this information. The fact that we can know it doesn't actually make it valuable. Like a hoarder, just because you can own 27 VHS copies of "The Sound of Music" doesn't mean they will ever do you any good.
So instead of looking at data like it's a crystal ball and wondering what it can tell us, flip the plot and think about what you'd like to know instead. For example, here are some questions you can probably answer right now that might help you:
- Is that Facebook (or Google or Yahoo or Twitter or whatever) ad worth the money you spent on it? Sure, it gets lots of clicks, but do the people who clicking also buying?
- Do they buy on their first visit to the site or do they generally come back later to buy?
- What are they buying the most of?
- Is that what we would have expected?
- If you are advertising product X in an ad, do the people who click on that ad buy product Y?
- How long do people usually visit your site for before they buy?
- How many visits before they buy?
- What geography is our customer base from?
- How many sales are coming from mobile?
Advanced things you might want to know (very knowable, but requiring a little work and planning before they can be answered):
- Which ad campaign brought in the most traffic and the most sales?
- How many phone calls do we get from the web site?
- How many emails?
- Do people who call or email from the site more or less likely to buy?
This is just the tip of the analytics iceberg. Once you know what you want to know, you can measure for it. Ultimately, that means you can fix what's not working.
So now that you can measure almost everything, what matters to you?
James Ellis is a Chicago-area digital strategist with Google Analytics certification. That said, he still wonders if he would have made it as a hand model. You can get in touch with James at saltlab.com to tell him how many ways he's wrong.