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Reveal is an out-of-home (OOH) measurement and attribution platform that proves the incremental causal lift of OOH campaigns across brand lift, foot traffic, in-app actions, website activity, and sales. It is built for brands, agencies, and media owners who need statistically rigorous proof of campaign impact across all OOH formats. If your priority is a defensible, causally measured read on whether OOH moved the needle—rather than just delivery metrics—Reveal is designed for that job. The main things to weigh before committing are which outcomes you need measured, whether your formats and markets are covered, and how you want to start the conversation (the site routes you through Request a Meeting or Contact Us).

What Reveal actually measures

Reveal's core claim is incremental causal lift—isolating the effect of OOH exposure rather than reporting raw exposure counts. According to the platform, it measures across all formats and all outcomes:

• Brand Lift — changes in awareness, consideration, and intent
• Foot Traffic — store visits attributed directly to OOH exposure
• Sales & Conversions — in-app actions, website activity, and purchase lift

The site presents this with a test-and-control framing. Sample figures shown on the page include exposed users (787.7K over the last 6 months), a conversion rate lift of +30.9%, and a campaign lift of +18% average at a 95% confidence interval. These are illustrative dashboard values, not guarantees for your campaign—treat them as a sense of the output format you'd receive.

Why the causal framing matters

Most OOH reporting tells you how many people could have seen an ad. Reveal's positioning is that it tells you what changed because they saw it, using test vs. control comparisons. If your stakeholders (clients, finance, brand leadership) push back on attribution claims, that distinction is the reason to consider this category of tool at all.

Who it's built for

The platform names three audiences, and your fit depends on which you are:

If you're a brand or agency running multi-format OOH and being asked to justify the budget, the measurement scope lines up. If you only need basic impression and reach counts, the incremental-lift layer may be more than you need.

Questions to settle before you commit

Because pricing, contract terms, and integration specifics aren't published on the site, these are the items to resolve directly with the team:

• Outcome coverage — Which of brand lift, foot traffic, in-app actions, website activity, and sales do you actually need? Confirm each is supported for your campaign type.
• Format coverage — Reveal states it measures impressions and reach for all OOH formats and supports omni-channel OOH strategies. Verify your specific formats (billboards, transit, place-based, etc.) are included.
• Markets — The dashboard references top DMAs and net lift by market. Confirm your target geographies are covered.
• Data integration — Ask how your first-party data (CRM, sales, web analytics) connects, and what access you need to provide.
• Reporting cadence and format — Clarify what you receive, how often, and whether it's client-ready.
• Confidence and methodology — Ask how test and control groups are constructed for your campaign, since the 95% confidence interval shown depends on study design.

How to start

The site offers two entry points: Request a Meeting and Contact Us. Both route to the sales team rather than a self-serve signup, so expect a scoping conversation. To make that conversation productive, come with:

1. Your campaign objective (which outcome you need to prove)
2. The OOH formats and markets in play
3. The data sources you can share for attribution
4. The decision the measurement is meant to inform

That framing lets the team tell you quickly whether Reveal fits—and what a study would require—before you invest further.

Reveal measures the incremental impact of out-of-home (OOH) advertising by comparing exposed users against a control group, then reporting the causal lift across brand, foot traffic, and sales outcomes. This approach applies to brands, agencies, and media owners running campaigns across any OOH format who need to prove ROI rather than just count impressions. The platform reports results with statistical confidence intervals, so the lift figures reflect measured causality rather than correlation.

The Core Mechanism: Test vs. Control

Reveal's measurement rests on a test-and-control design. Users exposed to an OOH campaign are compared against a matched control group that was not exposed. The difference between the two groups is the incremental lift — the effect attributable to the campaign itself, not to seasonality, market trends, or other media running at the same time.

The platform reports this as:

• Exposed lift — the change measured in the exposed group
• Net lift vs. benchmark — how the campaign's lift compares to an expected baseline
• Confidence interval — typically stated at 95%, indicating the statistical reliability of the result

For example, in a sample result shown on Reveal's site, exposed users totaled 787.7K over six months, with a conversion rate lift of +30.9%. The net lift versus benchmark was reported as 30.59% vs. 25.76%, an exposed lift of +4.8 percentage points, and a campaign lift averaging +18% at a 95% confidence interval.

What Reveal Measures

Reveal covers all OOH formats and multiple outcome types, so measurement isn't limited to a single metric.

Brand Lift

Measures changes in awareness, consideration, and purchase intent among exposed users compared to the control group. This answers whether the campaign shifted how people think about the brand.

Foot Traffic

Attributes store visits directly to OOH exposure. This connects a physical ad — billboard, transit, street furniture — to real-world visits at a location.

Sales & Conversions

Tracks in-app actions, website activity, and purchase lift. This extends measurement beyond the physical world into digital behavior that follows exposure.

How the Data Is Reported

Reveal's reporting includes audience demographics broken out by age band (for example, 18–24 at 12%, 25–34 at 34%, 34–44 at 28%, 45–54 at 18%, 55+ at 8%) and net lift by market across top DMAs. This lets you see not just whether the campaign worked overall, but which audience segments and which markets drove the lift.

The combination of exposed user counts, conversion rate comparisons, and confidence intervals gives agencies and media owners figures they can present to clients as evidence of causal impact.

What This Means in Practice

If you're evaluating Reveal for a campaign, the key question is whether you need causal proof — not just reach and frequency. Reveal is built for that: it isolates the incremental effect of OOH exposure on brand metrics, visits, and sales, and reports it with statistical rigor. The platform is positioned as an industry-standard tool used by agencies and media owners, and its stated purpose is proving campaign impact through brand lift, foot traffic, and sales attribution across all formats.

For teams that need to justify OOH spend with evidence of what the campaign actually changed, this test-and-control methodology is the mechanism that makes that possible.

Reveal is an out-of-home (OOH) measurement and attribution platform that proves the incremental impact of OOH campaigns. It is built for three audiences — brands, agencies, and media owners — and measures results across all OOH formats, including brand lift, foot traffic, in-app actions, website activity, and sales. If you need to show that an OOH campaign caused a measurable change rather than just estimating exposure, Reveal is designed for that job.

What Reveal Measures

Reveal positions itself around causal lift — the incremental change attributable to OOH exposure — rather than raw exposure counts alone. Its performance measurement covers:

• Brand lift — changes in awareness, consideration, and intent
• Foot traffic — store visits attributed directly to OOH exposure
• Sales and conversions — in-app actions, website activity, and purchase lift
• Impressions and reach — measured across all OOH formats

The platform also supports omni-channel OOH strategies, so OOH results can be evaluated alongside other channels rather than in isolation.

How the Measurement Works

Reveal uses a test-and-control methodology to isolate the effect of OOH exposure. The platform reports results with confidence intervals, which lets you state how certain a result is rather than presenting a single number without context.

The sample metrics shown on Reveal's site illustrate the output format:

Results are also broken out by market (for example, top DMAs such as NYC) and by audience demographics, with age bands reported as percentages of the exposed audience.

Who It Is For

Reveal names three user groups:

• Brands — to verify that OOH spend produced measurable business outcomes
• Agencies — to bring statistically defensible results to clients
• Media owners — to demonstrate campaign value to advertisers

The platform states it is trusted by leading OOH brands worldwide and has over a decade of OOH measurement experience across thousands of campaigns.

What You Can Do With It

• Prove incremental causal lift from OOH campaigns
• Measure impressions and reach across every OOH format
• Attribute store visits, app actions, website activity, and purchases to OOH exposure
• Compare exposed and control groups with reported confidence levels
• Break results down by market and audience demographic
• Build omni-channel strategies informed by OOH measurement

Getting Started

Reveal's site offers two entry points: Request a Meeting and Contact Us. Pricing, plan tiers, and any login requirements are not stated on the page, so treat commercial terms as something to confirm directly with Reveal rather than assuming free or open access.

If your goal is to move from estimated OOH exposure to evidence of causal impact — and you need results you can present to clients or stakeholders with statistical backing — Reveal is built for exactly that use case.

Reveal is built for three groups that need to prove out-of-home (OOH) advertising actually moved people: brands, agencies, and media owners. If your job involves justifying OOH spend, reporting campaign results to a client, or selling OOH inventory on more than reach alone, Reveal's measurement and attribution tools are aimed at you. The platform measures incremental lift across brand lift, foot traffic, in-app actions, website activity, and sales — so the benefit depends on which of those outcomes your role is accountable for.

Brands: Proving Spend Drove Real Outcomes

For brands running OOH campaigns, the core value is turning "we ran billboards" into evidence of causal impact. Reveal measures the incremental lift of a campaign — the change attributable to OOH exposure rather than to background trends.

According to the platform, this covers:

• Brand lift — changes in awareness, consideration, and intent
• Foot traffic — store visits attributed directly to OOH exposure
• Sales & conversions — in-app actions, website activity, and purchase lift

The homepage illustrates the kind of output a brand would see: exposed users of 787.7K over the last six months, a conversion rate lift of +30.9%, and a campaign lift averaging +18% at a 95% confidence interval. It also breaks results down by market (top DMAs) and by audience demographics — for example, an age split showing 34% of the audience in the 25–34 bracket.

Choose Reveal if you need to defend OOH budget with outcome data (traffic, sales, brand metrics) rather than impressions alone. Look elsewhere if you only need raw impression counts and have no requirement to connect exposure to downstream behavior.

Agencies: Verifiable Results to Show Clients

Agencies sit between the brand and the media owner, and their problem is credibility: clients want proof, not estimates. Reveal positions itself as the platform "trusted by top agencies and media owners," and its stated purpose is to produce "statistical rigor you can take to your clients."

For an agency, the practical benefit is a measurement layer that:

• Attributes outcomes to OOH exposure using test-and-control methodology (the homepage shows a "Test / Control" comparison)
• Reports net lift against a benchmark — the example shows 30.59% net lift versus a 25.76% benchmark, with an exposed lift of +4.8 percentage points
• Covers all OOH formats, so a single agency can measure across its clients' varied media buys

Choose Reveal if you need a defensible, benchmarked number to present in a client report or QBR. The trade-off is that rigorous measurement requires a test-and-control setup, which means campaign planning has to accommodate the measurement design from the start.

Media Owners: Independent Data That Builds Advertiser Confidence

Media owners sell OOH inventory, and their recurring challenge is that advertisers discount OOH because its impact is hard to verify. Reveal addresses this by supplying measurement that media owners can offer alongside their inventory.

The homepage states Reveal is "trusted by leading OOH brands around the world" and enables omni-channel OOH strategies. For a media owner, that translates into:

• Independent, third-party-style proof of campaign impact
• Brand lift, foot traffic, and sales attribution across all formats — not just the formats you happen to sell
• A way to strengthen advertiser confidence and reduce the "how do I know it worked?" objection

Choose Reveal if your sales conversations stall on measurement and you want to hand advertisers outcome data. Consider the fit carefully if your inventory is limited to a single format or you don't have the campaign volume to support statistically meaningful test-and-control studies.

The Common Thread: All Formats, All Outcomes

Across all three groups, the deciding factor is the same. Reveal measures incremental causal lift across all OOH formats and supports omni-channel strategies — meaning the platform is designed for organizations whose OOH activity is varied and whose accountability extends beyond reach.

If your role requires connecting OOH exposure to a measurable business outcome — and you can plan campaigns with measurement built in — Reveal is designed for you. If you only need delivery metrics like impressions and reach, the platform's attribution capabilities go beyond what you require.