Use case · DOOH advertising

Schedule screens by when the street is busy

An hourly activity index around every screen: how many nearby venues are in their busy hours. Match hours to campaigns, and switch creatives with predicted live data.

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1:31 · Example: New York City, four screen locations. Products in the video are fictional; the data is real BestTime data.

The problem

Flat day-parts

Screens are sold at the same price all day, while the street changes every hour.

Expensive audience data

So planners guess which hours to buy, and which creative fits them.

No signal for the moment

A busy evening and a quiet one get the same schedule.

How BestTime helps

Hourly foot traffic forecasts for public venues, from anonymized mobile device signals from a sample of visitors, combined with weather, events and holidays. Busyness is a percentage of each venue’s own busiest hour.

Venue Filter

GET /api/v1/venues/filter

Every venue in an area or collection, filtered by type, day, hours and busyness, each with its hourly curve. One call, sorted the way you need.

Weekly forecast

GET /api/v1/forecasts/week

Every hour of the week for one venue, as a percentage of its own busiest hour.

Predicted live data

POST /api/v1/forecasts/live

An estimate for the current hour, from real-world signals such as weather, events and holidays: busier or quieter than usual.

What it brings

Typical teams

DOOH networks and media owners

Price and package screens by hour.

Programmatic platforms

An hourly activity signal for bidding.

Agencies and planners

Pick screens and hours per campaign.

Questions

Is this an impression count?

No. It’s an index of activity around the screen: the share of nearby venues that are in their busy hours, each measured against its own peak. Use it next to your audience measurement.

How do I build the index?

Call the Venue Filter with the screen’s coordinates, a radius and foot_traffic=day, then count per hour how many venues are at 60% or more of their own peak.

Can it react to today?

Predicted live data estimates the current hour from weather, events and holidays, so a rule can switch the creative when venues around a screen are busier than usual.

Video transcript

A digital screen in New York shows the same ad at eight in the morning and at eight at night. But the street around it is a different place.

Screens are often sold in flat day-parts. Audience data is expensive, so planners guess which hours to buy, and which creative fits them.

BestTime forecasts foot traffic for the venues around every screen: cafés, shops, restaurants and bars, hour by hour.

One Venue Filter call per screen location returns the nearby venues, each with its type and an hourly curve for the day.

Count how many of them are in their busy hours, and you get an activity index for every hour. Around Grand Central, it climbs from eight in the morning. Around Union Square, it peaks after work.

Then match venue types to the campaign: a coffee brand runs where cafés are busy in the morning, a drinks brand where bars fill up in the evening.

With predicted live data, a rule can even switch the creative when the venues around a screen are busier than usual.

It's an index of activity around the screen, not an impression count, so it works next to the audience data you already use.

Typical users are DOOH networks and media owners, programmatic platforms, and agencies planning out-of-home.

Start free, and check the area around your own screens in Radar.

Learn the tools

Tutorial 3: Venue Filter APITutorial 2: Radar: filter any city

Other use cases

Nightlife appsCity guides & travelSite selectionRetail & hospitality opsTourism & crowds

Try it on your own city

Sign up for free to see predicted live data for the current hour, based on real-world signals such as weather, events and holidays.

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