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How to Choose the Right Audience Analytics Solution for Your DOOH Network

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The right audience analytics solution helps to ensure the success of your digital out of home (DOOH) network. It has a big impact on your return on investment (ROI), since your analytics data affects how easily you are able to attract advertisers to your network, what type of advertisers you are able to attract, and how much you are able to charge. Now you might be wondering how it’s possible that an audience analytics solution can be so powerful? To answer this question, let’s first have a look at what exactly an audience analytics solution is and what it does.

What is an audience analytics solution in the context of DOOH?

In the context of DOOH, an audience analytics solution provides data on the people who come into contact with the screens within a network. The type of data that such a solution might gather includes demographic data such as age and gender, people count in the form of attention time and opportunity to see (OTS), and even some forms of emotional response data.

The power of audience analytics

When audience analytics technology is integrated with a CMS, it provides powerful opportunities for both network providers and advertisers to deliver highly relevant and tailored messages, which increases audience engagement and enhances the overall effectiveness of the digital signage network.

Furthermore, if you, as a network provider, are charging for advertising space based on the number of impressions, then it’s essential to know exactly how many impressions your screens are getting, and that you can prove to advertisers that your impression counts are accurate. And if you know that the profiles of the people viewing your screens closely align with the demographic profiles of your advertisers’ target audience, then you may be able to charge more per impression.

What are the options? Wi-Fi vs Bluetooth vs Face Analysis

When it comes to choosing a DOOH audience analytics solution, you have various options. These options differ in terms of accuracy and ease of implementation, and there is no single best option. You need to consider your own set of circumstances and requirements, and then decide what will work best for you. In some cases, you may even want to use a combination of solutions.

Here are some of the main choices that you have:


Wi-Fi tracking tracks people within a given area by picking up when their smartphones are searching for Wi-Fi signal. Since Wi-Fi must be turned on for this type of tracking to work,  and since not everyone carries a smartphone with them at all times, this is not the most accurate form of tracking.

It can, however, provide a good general idea of how many people are moving through a specific area, where they spend more time (dwell time), and so on. Depending on how the tracking is set up, and whether it is done in combination with free Wi-Fi access, it may be possible to collect demographic data and possibly even email addresses and device data.

Depending on the regulations in place in the relevant country, it may also be possible to send push notifications to devices in specific areas.

Drawbacks of this type of tracking include the fact that it is relatively expensive to set up, that calibration is required, that only OTS and not actual views can be tracked, and that Wi-Fi networks can easily get overloaded, which affects the accuracy of the data.


Bluetooth tracking works in a similar way to Wi-Fi tracking, and requires a smartphone’s Bluetooth to be turned on in order to be tracked. It does, however, offer a few advantages. It’s cheaper to set up than Wi-Fi tracking, and it provides more accurate location tracking. It can also be linked to Google Analytics for attribution modeling purposes. One of the differences, however, is that Bluetooth cannot be used to collect email addresses by allowing people to log in for free internet access.

Face Analysis

Face analysis is more accurate than Wi-Fi and Bluetooth tracking, since it doesn’t rely on audience devices, and is usually able to track every person who enters a predefined area. It works by placing a camera (or cameras) above a digital display and recording footage of the audience as they walk past. This footage is then analyzed in real-time by AI-powered face analysis software, after which the footage can be automatically discarded to maintain anonymity.

Another major advantage of face analysis is that it can determine whether people actually looked at an ad, or whether they merely had an opportunity to see (OTS).

It can also be affordable to set up, since there are software options available that can run on low-end hardware.

Choosing an audience analytics option

For the most accurate results, we recommend using a face analysis solution, possibly in combination with either Bluetooth and/or Wi-Fi tracking if you require the option to send push notifications to your audience when they are within a certain radius.

We know that choosing a face analysis solution can be a challenging task, and that’s why we’ve put together a list of questions you can use to make sure you’re considering all the crucial points.

Questions to ask when choosing a face analysis solution:

  • How accurate is it? Can it detect faces at extreme angles and at large enough distances?
  • What type of hardware will I need? Does the technology’s requirements match what I’m willing to invest in?
  • What platforms (operating systems) can it run on?
  • How many camera feeds can the solution support?
  • Can it give me the metrics that my advertisers want to know? For example, age, gender, people count, OTS, attention time?
  • What integrations are compatible with the solution? Will I be able to integrate it with a dashboard and/or CMS if I want to do this?
  • Do I need to develop anything myself? If yes, what skills and resources will I need?
  • What type of support is provided by the technology provider?
  • What will the initial investment be?
  • What will the impact on my data protection responsibilities be? Does the solution provide for privacy by default? And does it allow for anonymous data aggregation?

Sightcorp’s solution and what it can do for you

Sightcorp’s anonymous audience analytics solutions for DOOH work with face analysis, and are designed to run on affordable hardware. Since they are based on deep learning, they are able to deliver high levels of accuracy, even in challenging scenarios such as those that involve head poses at extreme angles.

Depending on your use case, there are two products for you to choose from: DeepSight Toolkit and DeepSight SDK.

DeepSight Toolkit is a plug-and-play solution that you can use right away, with no hard coding required. We also have ready integrations with dashboards and CMSs, to make it even more convenient for you to get up and running quickly.

DeepSight SDK, on the other hand, gives you the opportunity to integrate face analysis into your own solution using C++.

Both the Toolkit and the SDK incorporate privacy by design, and allow for anonymous data aggregation.

If you’d like to learn more about these products, how they work, and what the benefits are, you can try them out for two weeks for free.

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