What is incrementality?

Incrementality, also called incremental lift or incremental revenue, is the measurable impact caused by a marketing activity, promotion, or incentive that would not have occurred without it. 

A campaign can generate redemptions, clicks, and purchases and still not be incremental, if those customers were already going to buy. Incrementality isolates the behavior the campaign actually caused from the behavior that was going to happen regardless.

How does incrementality work?

Incrementality is measured by comparing two groups: a test group that receives the campaign, and a control group that doesn't. The difference in behavior between them is the incremental lift.

That difference can be measured across conversions, revenue, repeat purchases, average order value, referrals, or any other outcome the campaign is meant to drive. The formula is straightforward: what happened with the incentive, minus what would have happened without it.

Incrementality vs. attribution

Attribution and incrementality answer different questions, and confusing them is expensive.

Attribution tells you which channel or touchpoint gets credit for a conversion. 

Incrementality tells you whether that conversion would have happened without the campaign at all. 

A customer can click a promo email, see a retargeting ad, and redeem a checkout coupon and still have been going to buy regardless. Attribution gives all three touchpoints credit. Incrementality asks whether any of them actually changed the outcome.

How to measure incrementality

A/B holdout testing is the gold standard. The one rule that makes or breaks it: keep the control group clean. Once your holdout starts receiving the same incentive through another channel, the measurement falls apart.

Common incrementality metrics

The right metric depends on what the incentive is supposed to do.

• Incremental conversions: extra conversions caused by the campaign
• Incremental revenue: extra revenue generated beyond the expected baseline
• Incremental lift: percentage increase in performance compared with the control group
• Incremental ROAS: return on incentive spend based only on incremental results
• Cost per incremental order: campaign cost divided by additional orders generated

A welcome discount focuses on incremental first purchases. A loyalty campaign focuses on incremental repeat orders. A referral campaign focuses on incremental new customers. Different campaign, different scoreboard.

Why incrementality matters for promotions and loyalty

Promotions are easy to launch and even easier to misread. A campaign with high redemption can still be weak if it mostly reaches customers who were already planning to buy.

Incrementality helps brands understand whether incentives are actually changing behavior. For example, it can help answer:

• Did a discount increase conversions, or just reward existing intent?
• Did loyalty points drive repeat purchases?
• Did a referral reward bring in genuinely new customers?
• Did a win-back offer reactivate dormant customers?
• Did a coupon improve revenue, or just reduce margin?

Without incrementality, teams optimize for visible activity: redemptions, clicks, purchases, signups. Useful numbers, but not proof of impact.

How Voucherify supports incrementality testing

Voucherify's incentive optimization engine lets you configure segment-level targeting and distribution rules, which is the foundation of a clean holdout test. You define who receives an offer, exclude a control group at the distribution level, and track redemption and conversion data per segment through the API. Every promotion event is logged, so the data you need to calculate incremental lift is available without custom instrumentation.