GLOSSARY

What is incrementality in marketing?

Incrementality is the portion of an outcome — conversions, revenue — that a marketing activity actually caused, beyond what would have happened without it. It is measured by comparing a treated group against a randomly held-out control group running at the same time. Anything short of that comparison measures correlation, not contribution.

Incrementality vs. attribution

Attribution divides credit for a conversion among the touchpoints that preceded it — last click, first touch, some weighted curve. It answers "which of our activities was nearby when this happened?" Incrementality asks the harder, more useful question: "would this have happened anyway?" A branded-search click gets full credit under most attribution models and often near-zero incrementality, because the buyer was already coming. The two numbers can disagree by an order of magnitude, and the incremental one is the one the spend decision should follow.

Revenue incrementality, done properly

For website personalization the incrementality unit that matters is dollars per visitor: revenue in treated sessions versus held-out sessions. Conversion rate alone can mislead — an experience can convert more visitors into smaller orders, lifting CVR while revenue falls — so the revenue verdict has to be measured directly and decomposed into conversion rate times order value.

The statistics need care too. Session revenue is zero-inflated and heavy-tailed: most sessions are worth nothing and rare large orders dominate the mean, which breaks the assumptions behind a t-test. AXO uses a seeded percentile bootstrap — thousands of resamples, deterministic so the same inputs always yield the same confidence interval — and only reports significance when the interval's lower bound clears zero.

QUESTIONS PEOPLE ASK

What is the difference between incrementality and attribution?

Attribution allocates credit among touchpoints that preceded a conversion; it cannot tell you whether the conversion would have happened anyway. Incrementality measures exactly that, using a randomized control group that never received the treatment. Attribution answers "what was nearby?" Incrementality answers "what did we cause?" — and they routinely disagree.

What is incremental revenue per visitor?

The difference in revenue per session between visitors who received a treatment and a randomly held-out control group, measured over the same period. It is the personalization number a finance team can act on, because it captures both conversion-rate effects and order-value effects in one dollar figure with a confidence interval.

Why measure revenue incrementality with a bootstrap instead of a t-test?

Because session revenue violates a t-test's assumptions: most sessions are $0 and rare large orders create a heavy tail. A percentile bootstrap builds the confidence interval empirically by resampling observed sessions. Seeding the bootstrap makes the result reproducible — the same data always produces the same interval, so the verdict is auditable rather than a dice roll.

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