Direct answer
The short version.
Attribution distributes credit among measured touchpoints. Incrementality estimates the additional outcome caused by marketing compared with a credible counterfactual. They answer different questions and should not be treated as interchangeable.
Key takeaways
Keep these three decisions.
- Credit and causation are different.
- Use experiments for causal budget questions.
- Present assumptions beside every estimate.
The operating problem
Channels close to conversion can collect credit for demand they did not create, while influential exposures with weak observability can appear unproductive. Changing the attribution model moves credit but does not by itself reveal whether total business outcomes increased.
A practical system
Use attribution for journey and operating diagnostics, then design holdouts, geographic tests, platform lift studies or other causal methods for budget-level questions. Define the counterfactual and interference risks before the experiment, and combine evidence rather than forcing every channel into one perfect model.
What to measure next
Report attributed outcomes and incremental estimates side by side with assumptions and confidence. Budget decisions should consider marginal lift, cost, scale and business constraints. Differences between methods are a reason to investigate, not to select whichever number is larger.
Primary and authoritative references
Sources used for context.
Frequently asked questions
Two useful follow-ups.
Can GA4 attribution measure incrementality?
Attribution reports describe credit across observed paths. Incrementality requires a counterfactual design such as a holdout or lift experiment.
Why can attributed conversions exceed incremental conversions?
Advertising may receive credit for actions that would have happened anyway, especially in retargeting and branded demand capture.