Madvertising by AdQuick

The episode contains solid, actionable advice on measurement methodology (incrementality testing, geo-tests, MMM vs. attribution) that would be genuinely useful to a B2B marketer. However, it relies on fairly well-established frameworks in the space and lacks novel, surprising claims. The core insight - that platforms optimize for their own revenue, not advertiser outcomes - is important but not new to informed practitioners. Significant portions discuss career advice and company positioning that, while pleasant, don't deliver measurement density.

“Platforms are out there to optimize their own revenue, not advertiser outcomes”

“the best way to do that is with an explicit design experiment where you've got a treatment in one group and you've got a control in the other group”

The thinking is sound and well-articulated but largely reinforces existing orthodoxy in the measurement space: incrementality over attribution, experiments over modeling alone, skepticism of platform metrics. Covato presents these ideas clearly and connects them well, but doesn't challenge prevailing wisdom or offer contrarian frameworks. The framing of platform incentive misalignment is useful but well-established among measurement professionals.

“there isn't a way for you to understand what would happen in absence of some of those marketing channels”

“It's all kind of hocus pocus”

Covato has substantive, relevant practitioner experience: Google, Meta, Netflix, Snap, eBay - all major platforms with real measurement challenges at scale. He ran consulting work client-facing and founded a measurement consultancy. He speaks with authority about measurement methodology and has clearly worked on real problems. This is a high-caliber guest with genuine operational depth in the exact domain being discussed.

“He's been at Google Meta, Netflix, snap and eBay”

“I was always client facing for the most part”

The episode is notably light on concrete numbers, named examples, or specific case studies. Covato mentions Netflix as 'very scientific' but provides no details. He references 'a number of surprisingly large advertisers' who demand measurement capabilities but names no names. The advice on geo-testing and budget allocation is general rather than illustrated with specific results, timelines, or dollar impact. This is a significant weakness for a measurement-focused discussion.

“Netflix is very scientific, very soliciting descent”

“We've helped advertisers test into some of those AI based tactics, and they've been a mixed bag”

Host Adam Singer asks decent directional questions and shows familiarity with the space (mentioning P-Max, platform control, attribution), but the conversation lacks sharp follow-ups or productive friction. Singer rarely pushes back on claims or asks Covato to substantiate. The flow is polite but surfaces-level. When Covato offers vague statements (e.g., AI results are 'a mixed bag'), Singer doesn't probe for specifics. The career advice section feels tangential and unprobed.

“How do you explain incrementality in such a way that you can get them to actually change their behavior?”

“You'd be surprised”