#AdobeSummit 2017 Blog: Data without context and from a party with a stake in outcome can be worthless 

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Disclaimer: Adobe invited me to the Adobe Summit North America 2017. This post was not approved by them. They didn’t even get a preview. It’s my opinion and if you agree it’s yours too. ??

I was still flying to Las Vegas on Day 1 of the conference but was reading the tweets surrounding data and its importance. 

And I agree data is important and can quantify our successes and failures. But it can also be a big waste of time when we are  collecting stuff that doesn’t get used or analyzed for anything useful.

So much data is collected that it can be hard to keep track of it all or – more importantly – make sense of it.

And of course  data – big or small – can be bend into submission to tell just about any story. Unfortunately.


1) Just read some of the political commentary nowadays. Same data. Different interpretations and playbacks. <That’s enough politics.>

2) I’ve gained some weight but it’s all muscle.  Muscle weighs more than fat. That’s my story and I’m sticking to it. Ha ha.

But really:  Sometimes it’s the angles we look at something. Here’s an example:

I almost think I weighed more in the picture on the right – but that’s the lighter one.

How about  this one?

That’s not that far away from the pictures above. But the left is clearly skinnier than the right.

It all depends on perspective, angle and even even intent. The picture in the yellow shirt was specifically taken to show that I had gained some weight and that it’s visible. It’s time to lose it again. I use it as my motivator. That roll has to go.

Data is very similar. It depends how we look at it, what our angles are and which pieces of the full puzzle we decide to actually share.

So data is great in weight loss, marketing and also digital communication

Measure everything. And then have somebody who has no stake in the outcomes analyze what the data means

Hire a data analysis journalist. Yep I making up new jobs  again. Journalists are supposed to be unbiased and simply look for the true story and then put that story into context. So we a) know it happened and b) know what it means. 

The same concept really needs to be accomplished with our data analysis in marketing and communications. First we want to know what happened and then we want to know what it means. Of course, the next step is to predict what’s going to happen or to look at metrics and see what kind of pacing we are on towards a certain goal.

When I don’t want to look fatter I’ll take a picture in the morning, twist a bit, wear a looser shirt. Whatever. You get the point. 

But asking my wife or daughter to take it, they are worried about taking a photo and getting that done. As opposed to being my PR firm.

They are that unbiased person, though they might not add any context. 

So in the content marketing and creation and growth hacking worlds, you might consider this model – split the work up between:

  • The implementers 
  • The analysts 

That doesn’t mean the people implementing cannot look at the data. They should. Daily.  And if they’re not pacing to reach their goals they should adjust tactics. 

But it should be the analysts who are actually digging into the data and are telling us the stories that they found. They have no stake in the project and its outcome other than to uncover the most meaningful stories that the numbers and other data can show us.

Then we can use that data to improve our businesses, content and be the best that we can be-for lack of a better cliché.