The Problem Attribution Doesn't Solve
Why attribution metrics can't tell you if ads actually caused conversions
Attribution tells you: "These 100 users saw our ad and then converted."
But it can't tell you: "Would these users have converted anyway without seeing the ad?"
Incrementality testing is designed to answer this question by estimating causal impact. It's the difference between correlation and causation, between claiming credit for conversions and demonstrating that advertising changed outcomes.
“What would have happened if you did nothing? You should know your incremental impact and not just take credit for every post-click conversion.”— Alex Schultz, Click Here(source)This distinction matters enormously. Consider:
You target active DeFi users with ads for your new DEX. 100 of them see your ad and swap on your platform. Attribution claims success - you acquired 100 users!
You run an incrementality test. You discover that 94 of those 100 users would have found and used your DEX anyway through organic discovery, social media, or word of mouth. Your ads only caused 6 incremental conversions.
Attribution would claim 100% of conversions. Incrementality reveals you only drove 6% of them. That's a 16x difference in how you evaluate campaign performance.