Video Attribution: Why First-Click and Last-Click Both Lie

Attribution models are stories we tell ourselves about which ads worked. First-click attribution tells one story. Last-click tells another. Neither story is true — but both have consequences for where budget goes and what creative gets made.

What each model hides

Last-click attribution gives 100% credit to the last ad someone clicked before converting. It systematically overvalues bottom-of-funnel advertising (search, retargeting) and undervalues everything that happened before the final click. The awareness ad that introduced the brand, the consideration ad that communicated the benefits, the social proof that built trust — these get zero credit under last-click.

The result: budget shifts toward conversion-focused advertising and away from brand-building. Short-term performance looks better. Long-term brand health declines because nobody is doing the work of creating future demand.

First-click attribution gives 100% credit to the first ad someone clicked. It systematically overvalues top-of-funnel advertising and undervalues the nurturing and conversion work that happened after the first interaction. The retargeting ad that brought someone back, the offer that closed the sale — these get zero credit under first-click.

The result: budget shifts toward awareness at the expense of conversion efficiency. Traffic increases. Conversions don't.

Multi-touch attribution: better but still flawed

Multi-touch attribution (MTA) distributes credit across multiple touchpoints. It's more fair than either single-touch model. It's also vulnerable to the same fundamental problem: it only sees trackable touchpoints. A viewer who saw your ad, didn't click, and later searched for your brand directly — their view-based conversion is invisible to MTA unless you're specifically measuring view-through conversions.

MTA also struggles with cross-device journeys. Someone sees an ad on their phone, researches on their laptop, and converts on their work desktop. MTA sees these as three different people unless you have identity resolution robust enough to connect the devices.

Incrementality: the gold standard

Incrementality testing measures what actually changed because of the ad. It compares a group that saw the ad to a group that didn't, and measures the difference in conversions between the two groups. The difference is the incremental effect of the ad — the conversions that wouldn't have happened otherwise.

Incrementality is more expensive to measure than attribution. It requires holdout groups, sufficient sample sizes, clean experimental design. It's also the only method that answers the question advertisers actually care about: did this ad cause conversions that wouldn't have happened anyway?

The practical approach: use attribution for day-to-day optimization (which channels are driving conversions?) and incrementality testing for strategic decisions (should we invest more in this channel overall?). Attribution tells you what happened. Incrementality tells you what would have happened if you'd done something different. They're different questions with different answers.