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DOOH Audience Demographics Analysis

Analyzing the demographic of an ad audience is critical to optimizing campaign success. Online advertising on platforms such as Facebook and Google makes this process easy. However, these days the same insights can be gleaned offline.

Digital out of home demographic data has changed the way that media owners and media buyers work. With the ability to collect data that shows who is viewing a piece of content or ad space, media owners can prove network value whilst media buyers can more easily reach their target audience. 

In this guide, we run through exactly how this looks.

What is DOOH Audience Demographics analysis?

DOOH audience demographic data is a term that refers to any insights collected about a group of people interacting with ad content outside of the home. Audience demographics analysis can therefore tell media buyers and media owners information that can improve marketing content, prove value and improve in-location experiences.

Common types of online demographic data include age, gender, ethnicity, location, job type and income. However, new laws are making it more difficult to collect data whilst protecting privacy. The cookie ban, which is set to come in in 2023, is one such measure. 

Software (such as Sightcorp’s) that works to provide offline audience demographic analysis is not limited in the same way. Through anonymous and privacy-first methods of tracking, media owners and buyers can collect data about those viewing their ad space.

What are the main demographic categories to measure in DOOH media?

The main forms of audience demographic analysis in the digital out of home world pertain to age, gender and group recognition.

Age Recognition

Through software (such as DeepSight) statistical data can be gained on audience age. Through a camera affixed to a digital display, the facial landmarks of audience members in the vicinity can be analyzed. The software can then estimate with human levels of accuracy the age of those who are likely to have seen the content and those who had the opportunity to see the content, being in the view of the display. This data is measured in age buckets — from 1-10, 10-20, and 20-30 for example.

Gender Recognition

In the same anonymized way, audience demographic analysis software is able to determine the gender of individuals in view of a DOOH display based on facial landmarks.

Group Recognition

Determining whether there is a group or a singular person standing in front of a DOOH screen, AI-powered software can determine audience composition in real time. This means it can assess what the dominant age group and gender is; with programmatic advertising, content that relates to this dominant group can be triggered to be played. 

Other categories to measure in DOOH media:

The following are also insights that can be collected about audience members.

Mood Tracking

Through facial landmark analysis, the estimated mood or emotion of those in the field of display can be assessed anonymously. This allows media buyers to see whether their content is entertaining/ evoking a reaction in audience members.


Alongside audience demographic analysis, understanding how many people view an ad display or piece of content is critical to understanding its impact. Our software separates those who had the opportunity to see a piece of content from those who were likely to see it (those within a closer proximity to the display) to take this one step further.

Attention Time

Attention time provides details on which audience members are seeing content and also how many of them are engaging with it for longer than a few seconds. Through head pose technology, our software is able to assess for how long an individual is looking at a display.

Why is it important to measure DOOH Audience Demographics

By undertaking audience demographic analysis, media owners are able to accurately sell space with a value-first strategy and buyers are able to understand exactly who their target audience is and where they can find them. Sometimes media buyers may find interest where they aren’t expecting it and can then tweak their campaign in light of this demographic data. Other times they may collect data that allows them to realize that a particular bit of ad inventory isn’t getting them to the demographic they want. 

Statistical data of this kind ultimately saves ad revenue and increases ROI. With real-time insights, media buyers can optimize their campaigns and media owners can find the best match for their ad space. 

This is particularly true in examples where demographic data reveals unexpected results. As an example, imagine a football stadium that is usually filled with mostly men of a certain age, but occasionally has an event that mainly young women attend. With traditional DOOH advertising, ad content may cater towards this original target audience; however with real-time insights, the content can be tweaked to target new viewers.

How do you measure DOOH Audience Demographics?

There are a number of ways to measure audience demographics; most of these rely on third party data such as WiFi tracking or location based statistical data.

The most effective way to collect data, though, is through real-time video analytics powered by software such as Sightcorp’s. 

Through a camera and digital screen linked up to our software, a face is detected and analyzed entirely anonymously. Images are  never stored, rather they are converted into pixels and the raw data that is stored is unidentifiable (in the form of zeros and ones). The aggregated demographic data can then be displayed on a dashboard and users can view insights on an hourly, daily, weekly or monthly basis.  

The benefits of DOOH Demographic Analysis powered by Computer Vision:

The benefits of this type of audience demographic analysis are extensive. 

Not only does this type of demographic data allow you to understand audience composition in real time, it facilitates the automatic deployment of relevant content. Media owners can then send proof of play reports that keep media buyers confident that they are hitting their target audience and media buyers can collect data that allows them to target at scale. 

There are a number of industries in which this type of audience demographic analysis is particularly useful. 

Within retail, dynamic ads can influence particular groups of customers on their path to purchase. Selling to a particular demographic at point of sale has a noticeable impact on conversion rates. 

Restaurants are able to offer a more personalized service through self-service kiosks and up sells whilst casinos can alter which games they promote through demographic insights. 

To find out more about audience demographics analysis with our computer vision software and to learn how it could impact your business, click the link

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