u/Spirited-Alps6604

We're a small in-house performance team. we don't have a trading desk, DV 360 or TTD, so self-serve is the only option at the moment. we've shortlisted MNTN, Tatari, tvScientific.
On the demos, they sound identocal with their premium inventory, performance focus, real attribution and their provision to go live in minutes.
however, what I wont figure from a sales call is what will continue to hold up once our budget goes live. my main concerns are how honest the attribution is when tested against a geo holdout, whether the reporting is something defensible to our CFO or if its just dressed up numbers reported by the platform, how the inventory quality drops when scaled and what will only show up after I've signed.
if you've run any one of these past the trial, would you say the reality past the demo held up to what they gave you?

I want to know more of which you WOULD NOT recommend of the above and any other suggestions besides the above if you've got some.

I’m working on a growing SaaS/product business where we’ve had some early traction from referrals, founder-led sales, and a few small paid tests.

Most channels only work at a tiny scale. A LinkedIn campaign gets a few leads, Google search works until the obvious keywords get expensive, and paid social brings traffic but not always buyers. And when trying to scale, anytime we try to increase budget, CAC climbs fast and quality drops.

For people who’ve actually scaled performance marketing beyond experiments: which channels kept working as spend increased? Also curious what changed when the channel started scaling: creative volume, landing pages, offer, audience targeting, sales follow-up, attribution, or just better unit economics?

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?