Incrementality (Incremental Bookings)

Incrementality measures how many bookings, or how much revenue, a marketing activity caused that would not have happened without it. An incremental booking is one that exists only because the guest saw the ad, listing or promotion. Bookings that would have been made anyway, for example by a guest who already intended to book direct, are not incremental, even if the channel receives credit for them.

Formula

Incremental Bookings = Bookings (exposed group) − Bookings (control group)

Incrementality Rate = Incremental Bookings ÷ Bookings (exposed group)

Incremental ROAS = Incremental Revenue ÷ Ad Spend

How it is measured

The standard approach is a controlled experiment: a share of the audience, or a set of regions or dates, is deliberately not exposed to the campaign (a holdout), and results are compared with the exposed group. Geo tests, on/off tests and platform lift studies are common formats.

Example

A hotel spends €10,000 on a metasearch campaign and the platform reports 200 bookings worth €50,000, a reported ROAS of 5.0. A holdout test shows that, without the campaign, the hotel would still have received 120 of those bookings through direct and organic channels. Incremental bookings are 80, incremental revenue is about €20,000 and incremental ROAS is 2.0. The channel is still profitable if margins allow, but far less so than the dashboard suggested.

Why it matters

• Exposes over-credited channels. Last-Click Attribution and branded campaigns tend to claim bookings that were already coming, a typical problem with Brand Search and Retargeting.
• Improves budget allocation. Spend moves to channels that create new demand rather than harvest existing demand.
• Informs the cost of distribution. True CPA is spend divided by incremental, not reported, bookings.
• Fits the OTA reality. Guests often research on OTAs and book direct, so the OTA contribution is partly incremental and partly a billboard effect (see Disintermediation / Billboard Effect).

Related

Incrementality complements Multi-Touch Attribution (MTA) and helps interpret the Dark Funnel. Attribution describes who gets credit; incrementality tests what truly changed.