Usage stats can be deceiving. I'm sitting here drinking amaretto-flavored coffee. A secondary flavor (almonds?) is supposedly flowing through its ground and dripped essence, but the amaretto is definitely coming through strong.
I didn't ask for amaretto coffee.
I would never buy amaretto coffee.
It was a gift, probably plucked off the clearinghouse shelves of TJ Maxx, and this morning I remembered it was hiding out in the trunk of my car.
The standard supply of Colombian had run out, and a trip to the store is a future not current event.
So I brought this strange bag inside and tried it.
The Misleading Nature of Usage Stats
Thus far I have not:
- spat it out
- recoiled in horror
- said anything like, "OMG how AWFUL"
- thrown the bag away
- poured the decanter's contents down the drain and disinfected the container.
I am actually drinking the coffee.
It is not good.
It is not terrible.
It is coffee, and I wanted coffee.
The fact that this coffee has come along with amaretto and another mysterious flavor is secondary.
However—!
Let us imagine for a moment a survey company phones me up now.
"Sir!" begins the survey taker smartly. "Are you drinking an amaretto-flavored caffeinated beverage?"
And I would have to truthfully report, "Yes."
Yes, I am.
"Thank you sir, that is all I need today!" *click*
Ya-hum.
Usage Stats and Correct Measurement
Now can you see where this is going?
Our survey taker reports back to their marketing firm client.
My response is anonymously morphed into a total of many. Some of us are indeed drinking this specific flavor of beverage.
The marketing firm executive rubs their hands together with glee.
Usage stats are up!
Their efforts must be working.
And this, dear reader, is the extent to which most small and medium firms conduct their market research.
Not much depth, no correlation or causation testing, no deep inquiry into Why.
Let's look at what they did not find out.
They did not discover whether their product was actually wanted.
They did not determine if the user picked their product specifically, at random, or by default.
They did not find out if, as in my case, the user wanted something like that solution, and chose this one not because it was the best fit, or did exactly what they wanted, or provided the features they were looking for...but instead was an answer merely less painful to get than any other at the time.
And so on.
Yet the marketing departments will take the basic data they collected back to their offices, and congratulate themselves on providing precisely what the market wanted.
No...
Are you guilty of this?
How is your level of dialogue with your audience?
Do you know exactly why your target market buys from you, what they value from you?
If not, it's time to do some information interviews.
Sometimes it's not fun to hear that the most cherished feature of what you offer has, in reality, zero value and makes no difference in your customer's buying decision. But if you're willing to set that aside, and go after a deeper understanding of usage stats, you will learn priceless information.
>> Jason Kanigan is a creator of converting funnels, using high ticket copywriting and sales training skills. If you want what your products or services deliver to match exactly what your customers value and are looking for, get ahold of Jason. <<