Unlock DOOH advertising budgets with audience analytics
The DOOH ad network dilemma
Digital-out-of-home (DOOH) networks let advertisers reach audiences in outdoor venues and retail spaces. The networks use a combination of digital signage screens, LED billboards, and other types of digital displays to inform, entertain and engage the advertiser’s target audience.
The big issue for advertisers isn’t about how to push content out to viewers, but rather understanding how the content is being received. This knowledge ensures ad budgets are always spent wisely.
- Is the audience noticing the ads?
- Are the ads relevant to the physical space where they are shown?
- Are viewers engaging with the content in a meaningful way?
- Is the ad having the desired impact on sales?
Before the advent of audience analytics, advertisers and brand owners had a difficult time evaluating ad performance. They couldn’t really tell if viewers were engaged or if ads were reaching the right audience. Without this valuable information, stakeholders were left in the dark, making it more difficult to justify new ad spending.
DOOH ad networks rise to the challenge
To respond to this challenge, DOOH ad networks began investing in technologies that can deliver measurable and reliable performance data. Technologies like computer vision and AI-based audience analytics let advertisers validate each content’s performance by tracking viewer activity and demographics. The resulting information is used to create insightful metrics that advertisers and brand owners can leverage to improve their content and fine-tune their message.
DOOH advertising is powered by data
Thanks to new audience analytics tools developed specifically for Digital-out-of-home, advertising stakeholders are better informed than ever before. This has led to a steady growth in DOOH ad spending. With access to real-time audience analytics, advertisers and brand owners can tap into better and more reliable data. This helps them deliver the right content to the right audience at the right time.
Computer vision-powered audience analytics delivers valuable insights about:
- Footfall data: How many people have visited a site or looked at an advertisement shown on a digital signage screen?
- Attention span: How long did each person engage with the advertisement?
- Demographic data: What was the sex and age range of the person looking at the content?
This data can be linked with other information to deliver a more complete picture of audience behavior, helping advertising and brand managers make better decisions:
- Ad impressions are recorded each time an advertisement is shown on screen.
- Online activities such as tracking app downloads, website visits, or other similar actions are triggered by scanning a QR code that appears on the screen, or by typing a URL in a web browser.
These conversion metrics reflect the audience’s interest and engagement. Using audience data, stakeholders can match ad impressions to the number of people who scanned a QR code to determine how well your content is performing. This could lead to a change of strategy, like redesigning your content or reassessing your target audience.
The goal is to gather all available information, analyze it and present the results in an easily accessible way through a user-friendly web interface.
Measuring audience data
Access to meaningful performance data is the key to the advertiser’s success. It helps guide ad spend and affect creative choices. This is where audience analytics comes into play.
Track the customer’s journey
Using computer vision, audience analytics tools can track each customer as they make their way across a store or within public spaces. This information is extremely useful for store managers, store planners, brand managers, and advertisers.
- Visualize store traffic patterns in real-time. See which areas are “hot” and which are “cold”.
- Discover where shoppers are least engaged and optimize your digital signage screen locations accordingly.
- See which areas are understaffed so you can act quickly to improve the customer experience.
Improve your advertising content
Audience analytics can highlight how each ad performs in real time. By validating your ad content on a small sample of your target audience, you can experiment with fewer risks. This is an inexpensive way to try out different artwork designs or brand messaging.
For example, you can test how different demographic groups react to your content and adjust it along the way. You can show different versions to multiple audiences and see what works best. Changes can be implemented quickly and efficiently before releasing a final version to a wider audience.
Once your content is out there, you can rely on audience analytics to monitor its appeal and if necessary, tweak the message further to improve your results.
Improve your digital signage programming
Computer vision-powered audience analytics can help you do much more than track ad performance. It lets you segment your audience so you can deliver highly focused messaging. AI-enhanced audience analytics can take over your digital signage programming and make changes based on who’s looking at the display.
Your screens can show different ads to men or women, or switch content based on different age groups. There is no need for manual intervention as all changes are made in real time.
Improve the audience’s experience
Advertising and brand managers can use audience analytics to improve audience engagement by determining how many times viewers have been exposed to content before they lose interest. Having the ability to switch content and deliver a more organic viewing experience helps keep the programming more interesting, which helps drive engagement throughout your campaign.
Get a clearer picture of your advertising ROI
Making insight-driven decisions is key to advertising success. Here are some scenarios that illustrate how audience analytics is at the core of every ad campaign’s success.
Cameras installed on or near LED billboards rely on computer vision software to scan a nearby street to detect and count the type of vehicles and traffic volume over the course of each day. This data is analyzed and processed to generate valuable metrics for advertisers.
- The number of vehicles that drove by the sign daily with breakdown by hour/period.
- The type of vehicle detected (automobile, truck/bus, motorcycle, etc…)
This information lets analysts determine the number of potential passengers per vehicle based on its type. This helps determine the total number of people who were potentially exposed to the content shown on screen.
QSR Restaurant Advertising
Digital menu boards are used for presenting more than menu choices. Restaurant operators often leverage their screen networks to advertise their products, and in some cases may also display some ads from other businesses.
Restaurant displays come in many shapes and sizes making them particularly attractive for high-impact content. Think of an advertisement that takes over multiple screens or shows content that moves from one screen to the next. The goal is to capture the guest’s attention and increase conversion rates.
Cameras mounted in strategic locations can scan guests as they place their food orders to present ads based on their sex or age. In some cases, audience analytics software can also detect returning customers and base recommendations on their frequency of visits.
Bus Shelter and Street Furniture Advertising
Digital signage screens are used in bus shelters and other street furniture components to provide useful information and advertising for commuters. Screens display a mix of content that let transit users know when the next bus or commuter train is coming. The same screens can also promote a local play, a new brand of laundry soap, or display the latest winning lottery numbers.
Cameras embedded in the street furniture can scan the people who are looking at the screens to ensure the content is appropriate to the audience’s demographics. Audience data can be with city staff to provide useful information for planning and maintenance purposes.