u/Spirited-Alps6604

I'm part of the growth team for a mid-market b2b company and I'm trying to get more immersed in incrementality without pretending we have Fortune 500 data density.

We’re spending across paid social, search, programmatic/CTV, and retargeting. The problem is that every channel can make a plausible case for impact, but once you strip out last-touch bias, branded search capture, retargeting overlap, and sales-assisted motion, the “incrementality” gets very blurry.

We can’t just pause major channels without creating real pipeline risk, and full MMM feels expensive/slow relative to how often we need to make budget decisions. Geo holdouts are also possible, but our market coverage and sales territories make clean reads hard.

For growth / demand gen / programmatic folks operating in the $5M-20M budget range, what does incrementality testing actually look like?

Most of the MCP conversation feels very developer-focused right now, but I think there’s a marketing use case that’s being underrated.

If ad platforms and analytics tools expose campaign data through MCP connectors, marketers could use ChatGPT or Claude to query performance directly instead of manually pulling reports.

That could matter a lot for channels like CTV, where reporting is often fragmented and harder to interpret.

The interesting question is: would marketers trust an AI agent to help analyze campaign performance, or would they still want everything inside the platform dashboard?