Why Incrementality fails for you

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🥲 Why Incrementality Programs Cut More Than They Ever Scale

Incrementality testing is supposed to answer a simple question: should this budget grow, move, or disappear? All three are legitimate outcomes, and all three can be backed by the same level of statistical rigor. 

Yet they rarely move through an organization at the same speed. The difference has little to do with the quality of the evidence and everything to do with how organizations are wired to make decisions.

Every incrementality test has three possible outcomes

On paper, each conclusion deserves the same level of confidence. In reality, they don’t receive the same level of support.

Why cuts move faster than growth

A recommendation to cut spend is relatively easy to approve. It reduces risk, protects margins, and rarely requires anyone to argue for investing more money during an uncertain period.

A recommendation to increase spend asks the organization to do the opposite. Someone has to approve additional budget, believe the results will hold at higher spend levels, and ultimately defend that decision if the following quarter underperforms for completely unrelated reasons.

Both recommendations may come from the exact same experiment.

Only one feels safe.

The organization isn’t reacting to the data. It’s reacting to the decision.

This is a well-documented pattern in decision-making. Organizations tend to treat preventing losses as more urgent than pursuing equivalent gains.

Inside an incrementality program, that shows up in subtle ways:

• Non-incremental spend gets approved for removal almost immediately.

• Budget increases trigger additional reviews and planning cycles.

• Proven winners wait for funding long after the evidence is accepted.

The data hasn’t become less convincing. The approval process has become more cautious.

The long-term consequence

Over several quarters, the program starts behaving like a one-way valve.

Waste gets identified and removed with very little friction. Confirmed growth opportunities accumulate in presentations while waiting for the next planning cycle, the next budget review, or another round of validation.

Eventually, the program develops a reputation for improving efficiency without accelerating growth, even though it has already identified where that growth should come from.

Build a fast lane for scale, not just cuts

Most organizations already have an efficient approval path for reducing spend. They need one for increasing it too.

Before the next incrementality study begins, define:

• What level of evidence automatically qualifies for additional investment.

• How much budget can be released without a full review cycle.

• Who approves that investment.

• How quickly the budget should move once the evidence is confirmed.

Without that second approval path, an incrementality program will keep finding real winners while remaining structurally better at cutting spend than funding growth.

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🚀Quick Hits

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📌 Pinterest urged brands to keep product catalogs updated with accurate pricing, richer titles, and complete details, saying better feeds improve product discovery, ad performance, and shopping campaign ROAS. 

🤖 Google Ads now uses AI to recommend conversion tracking improvements directly in the Conversion Summary dashboard, giving advertisers automated optimization suggestions labeled "Recommended by Google AI." 

👀 Microsoft Ads added Ad Preview Hub to Performance Max, letting advertisers securely preview and share AI-generated ad creatives across placements before campaigns go live for faster approvals. 

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