The revenue-per-screen model

“How much does a screen earn?” has no single answer — but it has a clear model, and the model is more useful than any borrowed number. This data study lays out the revenue-per-screen formula with every lever exposed, runs a worked illustrative example, and shows which inputs move the answer most — so you can plug in your own venue’s numbers rather than trust someone else’s.

The model

A screen’s revenue is the product of a short chain. Stated as a monthly model:

gross ≈ daily reach × fill rate × effective CPM ÷ 1,000 × days × plays-per-visit-credited net = gross × your revenue-share — costs you bear

Simplified, the levers that matter are (framework; see the unit-economics guide):

Reach / foot traffic — how many people pass the screen’s exposure zone (and how the impression multiplier converts plays to audience impressions).
Fill rate — the share of available slots actually sold. Unsold = $0.
Effective CPM — what a sold thousand impressions clears, net of the deal type and the ad-tech haircut.
Your share — the slice that reaches you after the operator/ad-tech take and any venue revenue share.

A worked example — clearly illustrative

To show the mechanics, here’s a fully illustrative example with every assumption stated. These are placeholder inputs, not benchmarks — the point is the method, not the number:

Input	Illustrative value
Audience impressions / month (one screen)	30,000
Fill rate (share of slots sold)	30%
Effective net CPM (after haircut)	$8
→ Monthly gross to the network	30,000 × 30% × $8 ÷ 1,000 = $72
Venue revenue share	50%
→ Monthly net to the venue	$36

Change one input and the answer moves a lot: at 60% fill it’s $144 gross / $72 to the venue; at a $4 CPM it halves; at 60,000 impressions it doubles. That volatility is the real lesson — a per-screen number is meaningless without its inputs, which is exactly why the vendor “$75/screen/month” figures fail: they hide best-case, fully-sold, gross-flavoured assumptions.

Sensitivity: what moves the answer most

Not all levers are equal. Ranked by how much they swing a typical screen’s revenue:

Fill rate. This is the swing factor. It can range from near-zero (a new, non-tier-1 screen seeing mostly no-bids) to a healthy share on curated demand — a multiple-of-revenue difference. Installed capacity is not income; sold capacity is.
Foot traffic. A busy city-centre salon and a quiet suburban one are different inventory by a large factor — and it’s largely fixed by location.
Effective CPM. Moves with deal type (PMP > open exchange), venue quality and daypart — and there’s no beauty benchmark to anchor it, so it’s set by your floor and real demand.
Your share & the haircut. The base of the split (gross vs net) and the ad-tech take quietly determine what actually lands.

The takeaway from the ranking: chase fill and traffic first. A higher CPM on unsold slots is worth nothing; the binding constraint is selling the inventory, not pricing it.

How to use the model

The model is the tool; your inputs are the answer:

Plug in your venue’s real numbers — measured foot traffic, an honest fill expectation, a net CPM from real quotes, your actual share and its base.
Model net, not gross — back out the haircut and venue share so the figure is what lands.
Stress-test fill — run a low-fill case, because early fill is low; don’t plan on full.
Validate against an operator’s actual paid history for comparable venues — not a calculator, never a headline (the host-side version is in How much can a salon earn?).

The takeaway

One beauty DOOH screen earns whatever its foot traffic, fill, CPM and share say it earns — and the model above lets you compute that honestly for any venue. The number is volatile because the inputs are venue-specific, fill is the swing factor, and there’s no benchmark CPM to lean on. So don’t ask “what does a screen earn?” — run the model with your inputs, stress the fill rate, and check it against real paid history. The method is trustworthy; the single number never is.