Types of Headaches

Collecting a ton of data is great...

But only if you know what to do with it.

Every DTC operator knows how to extract data,
But few know how to actually use it.

You're three hours into your weekly performance review.
The data is all there. Every platform. Every metric.

ROAS looks fine, and spend is tracking.
The team is nodding along.

And then someone asks the question nobody wants to answer:
"So what are we changing?"

The room goes silent.
Because nothing in front of you is telling you what to do next.

Platform ROAS is green, but blended MER tells a different story.
Creative is running. Your team can't tell if it's working or just spending.
Attribution models all point somewhere different.
The team has the data. Nobody agrees on what to do with it.

Having data is important, but it doesn't solve everything.
You need to know what the data means.

That's a signals problem, and it's a harder fix.

You can have everything in front of you and still be unable to answer "What do we do next?"
You need to look at the full picture and decide what matters and what to do about it.

More dashboards don't fix that.
Better thinking close to the data does.

The brands that scale well walk out of a performance review with a clear next decision.

How do you handle data reviews as a founder?
Drop it in the comments.

If the idea of your next data review is keeping you up, feel free to DM me.
That's exactly the kind of problem we work through at Fluency.

♻️ Repost if you've been in a review where everyone had the data and nobody knew what to do with it.
And follow me, Jacob Rokeach, for more on what it takes to make decisions at scale.