Have you ever looked at something and then asked “why?” Have you ever wondered “why did somebody make that decision?” I find myself doing it all time time, increasingly I’m asking myself “I wonder what type of metrics they looked at when making that decision.”
While walking down the Vegas strip Pubcon with some friends (on our way to epic dinner) who begged me not to name them in this anecdote we couldn’t help notice the guys handing out hooker cards. For the next 20 minutes we started asking questions like “How much are those guys paid?” “Do you think they work on commission?” “How do they track their conversion rates?” “what type of conversion rates do you think those cards have?” “do they use unique call tracking phone numbers?” “is this the world’s oldest affiliate network?” “Man I bet they’d be able to do an awesome panel at an affiliate marketing conference.”
Chances are that they don’t use analytics at all, but what if they did? imagine the possibilities.
The same thoughts were racing through my head about 20 minutes ago when I went to the vending machine to grab myself a Cherry Coke Zero. I looked at the stock of the vending machine and said “Why on earth would there be only 2 rows of diet coke, but 4 rows of grape soda? There’s no way a can of grape soda outsells a bottle of diet coke at an ad agency – is there?”
Then I spotted the candy vending machine and noticed that a bag of M&M’s cost twice as much as a bag of skittles, which was 12% cheaper than the bag of cheesy popcorn and 5% more expensive than gum. The pricing just didn’t make sense. Was it demand based? Item-cost based? Margin based? Or was it simply random?
Do you think vending machine operators stock based on previous demand? The fact that we’re always out of Diet Coke tells me that our contractor doesn’t, but what if he did?
It’s what you look at that matters
In both of these cases (and you though I wouldn’t be able to tie hookers and vending machines together…) there are probably metrics involved, but what metrics? I know that both the hookers and vending machine operators are looking at things like cost, revenue, margin and the other basics. They wouldn’t be able to sustain their business if they didn’t.
But those metrics can’t help them make day to day business decisions. In other words, they’re not as actionable as other metrics they could be looking at. In the vending machine example things like rate of sale, comparative demand, average price per sale, etc could obviously help them increase sales – but are they using them? (I’ll leave the hooker metrics to you as a take home exercise.)
And that’s the point. Analytics are everywhere; but it’s not just if you’re measuring it’s what you’re measuring that matters. The same applies to your SEO, Affiliate marketing, and general website strategies. The out of the box metrics like pageviews and visits over time are great, but how actionable are they? Can they really help you make decisions to improve your business?
If you’d like to learn more about making your analytics actionable, I’ll be giving a presentation with Brent Chaters at SES Accelerator in San Diego. I’ll be sharing some tips about what we measure on Ford and what decisions those metrics guide us to. Come join us. (Note: sadly, there will most likely not be any hookers at SES. There may be vending machines though.)