How do you authenticate with out-of-home measurement endpoints?

You generate a secure bearer token from your developer console to authenticate your requests. Most platforms require you to pass this token in the authorization header of every call. You rotate these credentials regularly to maintain security across your automated trading infrastructure and reporting pipelines.

What formats do these data feeds support?

Vendors typically deliver their metrics through standard JSON payloads over REST interfaces. You parse these structured responses to extract specific fields like dwell time and demographic breakdowns. Some providers also offer WebSockets for continuous data streaming directly into your live campaign monitoring dashboards.

Can you integrate attention metrics into custom reporting tools?

You can pipe the raw data directly into your preferred business intelligence software or data warehouse. This setup allows you to merge physical engagement signals with online conversion metrics. You build unified dashboards that give your clients a complete view of their omnichannel marketing performance.

Do endpoints provide historical campaign benchmarks?

Many systems allow you to query past performance records to establish baselines for your upcoming media buys. You retrieve aggregated metrics from previous quarters to understand seasonal trends in pedestrian behavior. You use this context to set realistic engagement targets for your new creative assets.

How frequently do the servers update the engagement figures?

The refresh rates vary based on the specific vendor and the hardware deployed at the venue. Some networks push updates in near real time as the sensors process the environment. Other platforms batch the information and deliver daily summaries to your connected applications.

Is there an API for out-of-home attention data?

Sneh Dhruv · Updated October 25, 2026

Yes, you can access APIs that deliver both predictive attention scores and in-flight measurement data for your out-of-home campaigns. Trillboards lets you build on the OpenAPI reference at https://api.trillboards.com/docs to automate your media buying and pull insights from 4,059,145 ad plays with a per-play audience record.

The numbers

Measure	Figure	Sample	Data window
Screens counting nearby phones by radio	6,828	6,828 screens	Jul 13 – Oct 10, 2026
Screens sensing by camera or radio	7,289	7,289 screens	Jul 13 – Oct 10, 2026
Billboard passes measured from moving vehicles	23,518,207	23,518,207 passes	Jul 13 – Oct 10, 2026
Median exposure interval at a board	5.9	9,928,376 exposure intervals	Jun 28 – Sep 25, 2026

Integrating attention measurement into your media buys

You can connect your demand-side platform directly to attention measurement providers using RESTful APIs. These connections deliver both pre-campaign predictive scores and in-flight metrics straight into your trading desk. As programmatic digital out-of-home scales to a projected $1.25 billion market, buyers need to evaluate their inventory using concrete signals. You pull these data feeds to execute attention-guaranteed programmatic deals through platforms like Vistar Media and AdQuick. To execute this, you generate secure API keys from your measurement partner and input them into your buying platform to ingest data payloads in real time.

When you buy media for a software company, you need to prove the creative captures the target demographic of developers and IT decision-makers. Traditionally, the industry relied on traffic counts and mobile panels to generate modeled impressions. Those legacy currencies show you how many devices passed a location during a specific hour. Today, you integrate sensor APIs to see exactly who looked at the screen. If your software client wants to reach developers during their morning commute, you set up automated rules to increase bids on transit shelter screens only when the API confirms high visual engagement. You feed real-world out-of-home signals into your reporting tools to justify your media spend and adjust your bidding strategy mid-flight. You use these endpoints to build custom dashboards in visualization tools like Tableau or Looker that merge out-of-home performance with your broader omnichannel analytics. By mapping these attention metrics against website traffic spikes, you can show your client exactly which physical placements drive digital conversions.

Predictive models and real-time computer vision

Multiple vendors offer different approaches to attention data through their APIs. Platforms like Amplified deliver active and passive attention data, while Lumen Research provides predicted attention duration via its LAMP platform. Adelaide integrates with computer vision platforms like Vertical Impression to feed real-world signals into its Attention Unit API. Quividi offers sensor APIs to measure real-time screen-level dwell time. You layer these tools to create a comprehensive strategy by pulling baseline predictions from Lumen Research to filter out low-performing inventory before submitting a bid.

For creative pre-testing, platforms like Dragonfly AI and expoze.io provide predictive design APIs. You use these tools to generate visual saliency heatmaps for your layouts before the campaign launches. You upload your draft creative to the expoze.io interface to see if the core brand message falls into the highest attention zones. If the heatmap shows viewers focusing on background elements instead of your call to action, you instruct your design team to increase the text contrast and retest the asset. To unify these different measurement methods, Geopath and the Out of Home Advertising Association of America partnered with Ipsos to pilot a modernized, interoperable audience measurement framework. You can calibrate your own models against real-world data, evaluating 2,989 attention forecasts graded against the camera in 7 days. You achieve this by setting up a test campaign where you run predictive models simultaneously with physical camera sensors. You then export the logs from both systems into a spreadsheet to calculate the variance. This alignment ensures your programmatic bids reflect the true value of the physical placement.

Moving past legacy traffic counts

The fundamental shift to API-driven attention data requires a clear understanding of what the sensors capture. Out-of-home advertising historically depended on modeled impressions based on broad traffic counts and historical surveys. You now have access to 5,456 screens whose camera measured the audience. These cameras record estimated age ranges, genders, dwell times, and the time spent looking at the screen. They compute face-identity templates to recognize the same person across different days and locations, linking these individuals to the device keys of the phones seen with them.

This hardware captures precise engagement metrics. You can analyze 811,776 ad plays measured by camera to see exactly how your campaign performs in the physical world. You download the ad play logs and sort them by time of day to identify when audience gaze peaks. If the data reveals that afternoon audiences look at your ad for three seconds longer than morning audiences, you can manually adjust your dayparting settings in your demand-side platform to weight your budget toward the afternoon. For roadside inventory, you can review vehicle-based measurement to understand passenger behavior. The data shows that 28.1% of camera-judged legible passes had a passenger facing the board for at least one second. You use these precise figures to optimize your creative rotation based on actual human attention. Knowing passengers have more time to read than drivers, you traffic text-heavy creatives specifically to screens with high passenger engagement scores. You base your buying decisions entirely on verified observations.

Activating data feeds for campaign optimization

API pricing structures typically involve enterprise software-as-a-service subscription tiers or programmatic CPM-based activation fees. You request a quote from the vendor to access their endpoints and integrate their data dictionaries. The U.S. out-of-home market reached a record $9.46 billion in annual revenue, driving major investments in data infrastructure. You tap into this infrastructure to build automated optimization workflows that pause underperforming creatives and reallocate budget to high-attention screens. To set this up, you write a script or use a platform rule that checks the API every hour. If the attention score drops below your defined benchmark, the system automatically halts the spend on that specific screen and shifts the funds to a placement exceeding the benchmark.

You pull these metrics into your business intelligence dashboards to show clients the exact return on their investment. The sensors send Bluetooth, Wi-Fi, and local-network identifiers broadcast by nearby phones, linking physical exposure to mobile advertising IDs. You can export these mobile advertising IDs and upload them into your social media or search buying platforms to launch highly targeted retargeting campaigns. This allows you to serve a mobile display ad to a user who just looked at your billboard. You retain access to 400 days of history kept on the sources the data products are built from. This valuable historical data lets you build accurate year-over-year comparisons and refine your audience targeting for future campaigns. For example, you can query last year's holiday campaign data to see which specific street corners generated the longest dwell times and reserve those exact screens for the upcoming season. You build a proprietary measurement advantage by combining these third-party feeds with your own first-party conversion data.

Sources

Related on Trillboards

Plan this on Trillboards

Developers build on the OpenAPI reference, and advertisers sign up here. Attention, dwell and exposure are measured and published with their sample sizes and data windows. Plan it on live inventory to see the screens, weekly views and effective CPM for the audience you pick.

Frequently asked questions

How do you authenticate with out-of-home measurement endpoints?: You generate a secure bearer token from your developer console to authenticate your requests. Most platforms require you to pass this token in the authorization header of every call. You rotate these credentials regularly to maintain security across your automated trading infrastructure and reporting pipelines.
What formats do these data feeds support?: Vendors typically deliver their metrics through standard JSON payloads over REST interfaces. You parse these structured responses to extract specific fields like dwell time and demographic breakdowns. Some providers also offer WebSockets for continuous data streaming directly into your live campaign monitoring dashboards.
Can you integrate attention metrics into custom reporting tools?: You can pipe the raw data directly into your preferred business intelligence software or data warehouse. This setup allows you to merge physical engagement signals with online conversion metrics. You build unified dashboards that give your clients a complete view of their omnichannel marketing performance.
Do endpoints provide historical campaign benchmarks?: Many systems allow you to query past performance records to establish baselines for your upcoming media buys. You retrieve aggregated metrics from previous quarters to understand seasonal trends in pedestrian behavior. You use this context to set realistic engagement targets for your new creative assets.
How frequently do the servers update the engagement figures?: The refresh rates vary based on the specific vendor and the hardware deployed at the venue. Some networks push updates in near real time as the sensors process the environment. Other platforms batch the information and deliver daily summaries to your connected applications.

Plan it

Open the planner in the planner to see the screens, the weekly views and the price before you book, or browse the audience catalogue.