Incrementality testing has become the default answer to a problem most direct-to-consumer brands genuinely have. Platform attribution disagrees with itself; Meta and Google routinely both claim credit for the same conversion. Not to mention studies we have done reviewing one transaction at a time to find out organic search or Google Shopping transactions were being attributed to direct.
Somewhere in that noise sits the question of how to actually allocate paid media budget.
The standard pitch is that incrementality cuts through it. Run a lift study, find out which channels are creating demand versus harvesting it, and reallocate spend accordingly. Most of the content you’ll find on incrementality over the last couple of years lands somewhere in that neighborhood. That framing is incomplete, and acting on it has probably led some growth-stage brands into bad decisions. The most common one is cutting upper-funnel channels that fail standalone lift tests, only to watch total revenue drop because those channels were doing work no single-channel test could see.
The conversation needs a different anchor.
Why Incrementality Alone Doesn’t Answer The Allocation Question
Incrementality measures the causal impact of a specific channel or campaign. That is genuinely useful information, but it is not the same as understanding how marketing contributes to the business as a whole.
Consider a customer who sees a Meta ad on Monday, doesn’t click, then searches for the brand on Wednesday and converts through a paid brand search ad. Meta records a view-through. Google records a last-click conversion. A lift study on either channel in isolation might show a modest incremental contribution. The honest answer is that both ads did real work, just different work. The Meta impression created the brand consideration, while the branded search closed the demand. Cutting either one breaks the journey.
This is exactly the conclusion most brands reach when they read incrementality results without the right context. They see Meta’s lift study come in low, conclude the channel is taking credit for conversions that would have happened anyway, and reallocate the budget. Six weeks later, brand search volume drops, blended efficiency drops with it, and the team is trying to figure out what happened.
One lift study on one channel cannot tell you whether that channel deserves the budget; it can only tell you what happened inside the test, which is why allocation decisions need a metric that captures the whole business.
Marketing Efficiency Ratio (MER) Is The Metric The Conversation Is Missing
Marketing Efficiency Ratio, total revenue divided by total ad spend, is the only commonly available metric that doesn’t care which channel gets credit. It treats marketing as one investment producing one revenue stream. That is what marketing actually is at the business level, and that is the question chief financial officers and founders are actually asking when they look at…
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