Out of the Blue is now Consequential

Out of the Blue is now Consequential.

We started the company because marketing measurement was surprisingly unreliable. A company could spend millions of dollars on advertising and still have several systems giving it different answers about what produced the revenue.

At first this looked like a measurement problem. If we could reconcile the data and show what was actually happening, teams could make better decisions.

That turned out to be only partly true.

Once you know what happened, someone still has to decide what to do next. Should you move budget from one campaign to another? Is performance actually falling, or did a tracking signal break? Should you change something now or wait for more data?

For most of the history of advertising software, a person made these decisions. The software produced information and the person decided what to do with it.

That boundary is starting to disappear.

Meta and Google already automate much of bidding, targeting and creative selection. More of the decisions about where money goes will eventually be made by software too.

This makes a problem that used to be annoying much more important.

When a person sees bad data, they may notice that something looks wrong. A machine does not necessarily do that. If the signal says conversions have fallen, it can respond exactly as it was designed to respond even if the real problem is that the conversion signal itself stopped working.

So as the decision layer becomes more automated, the signal layer has to become more reliable.

This is the idea behind Consequential.

The first part of the product is Revenue Intelligence. It tries to answer a simple question: are we going to hit the number? It connects what is happening in advertising and the funnel back to what is actually happening to revenue.

The second part is the Ads Control Plane. Once you understand what is happening, it helps answer the next question: where should the next dollar go?

The important part is that these two things should not be separate. A system that recommends a change should know what it expects that change to do. After the change is made, it should be possible to see whether that prediction was right.

This sounds obvious, but most marketing software does not work this way. Measurement happens in one place, decisions happen somewhere else, and a few weeks later someone tries to remember why a change was made in the first place.

We think these things will collapse into one system.

As software takes a larger role in deciding where marketing dollars go, the valuable system will not just be the one with the best dashboard. It will be the one that knows what is happening, understands what should happen next, and can tell whether the decision it made was right.

That is what we are building Consequential to become.

The name came from something simple. These decisions may look like numbers moving between campaigns, but they have real consequences for revenue.

And increasingly, the person making them may not be a person.