“When you’re advertising a 30 second spot for $7,000, you need to sell a lot of units to get there.”

That’s how one marketing leader described the stakes.

And they had a seemingly logical way to figure out whether they were getting that return.

Take the normal baseline of Shopify and Amazon orders…

Look at what happens in the 30 minutes after the commercial airs…

And attribute anything above baseline to TV.

There was just one problem with that math.

The majority of their TV budget runs from 7pm to 10pm.

Prime shopping hours.

Which means the exact window they were using to prove TV was driving sales…

Was also the window when people were already most likely to buy.

As another marketing leader on the team explained:

“The assumption that is made is that people see the commercial and they buy it right away. And it also happens to be the prime time, shopping time.”

“That’s where it gets really a little tricky.”

Because a sale happening after your ad is not proof it happened because of your ad.

And when you're paying $7,000 for 30 seconds, that distinction gets expensive fast.

You could look at a spike in orders and conclude:

That network works.

That time slot works.

That commercial works.

Buy more.

When in reality, some of those customers may have purchased whether the commercial aired or not.

Now you're not just giving TV too much credit.

You're making your next budget decision based on sales it may never have created.

And that's where a measurement problem becomes an allocation problem.

Because every dollar you keep feeding into an expensive TV spot is a dollar that can't go somewhere else.

Maybe Google was creating more incremental revenue.

Maybe Meta had more room to scale.

Maybe TV was working, but only on certain networks.

Maybe the $7,000 spot was profitable at $5,000, but stopped making sense at $7,000.

In fact, this team already knew there were prices above which certain spots simply stopped making the return.

They just needed a better way to know which spend was actually creating the sales.

And that's the part traditional attribution makes difficult.

TV doesn't live in isolation.

While that commercial is airing, Meta is running.

Google is running.

YouTube is running.

Radio may be running.

Customers have seen previous ads.

Some were already planning to buy.

So instead of asking which channel happened to appear closest to the sale…

There’s now a way to measure the change in business results against the changes happening across your entire media mix.

That lets you ask a much more valuable question:

What actually changed because we spent the money?

Now you're not simply looking at the orders that appeared after a commercial.

You're seeing TV relative to Google, Meta and every other paid channel competing for the same budget.

And suddenly the decision isn't about who gets credit for yesterday's sale.

It's about something far more valuable:

Where should tomorrow's dollar go?

Because the $7,000 spot with the biggest sales spike afterward…

May not be the investment creating the most growth.

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