As current advertising technologies such as cookies and unique device identifiers (UDIDs) lose their effectiveness and are being scrutinised for their consumer privacy compliance, digital marketers are looking for alternatives. Here James Lamberti, General Manager and Vice President at AdTruth, discusses the issues facing targeting capabilities and breaks down their solution.

Can you provide some insight into the background of AdTruth as a business?

AdTruth is the digital media division of global device recognition leader 41st Parameter. Our focus is to provide marketers with universal device recognition across the entire digital media ecosystem so they can recognise and reach their audiences in an increasingly device-dependent world.

How and why did you make the move from financial fraud detection to mobile/ad tech?

Our parent company, 41st Parameter, continues to focus on detecting and preventing fraud in the financial services, e-commerce and travel industries. In 2011 the company realised it could leverage its eight years of research and development in device recognition to solve a new and growing problem: how to recognise users for targeted marketing.

In the world of digital advertising, audience recognition and effective targeting are core requirements. For better or worse, existing approaches – primarily cookies – just don’t perform as well as marketers demand. There are a number of reasons for this: consumers may block or delete cookies, regulators and privacy advocates look at them warily and on mobile devices – which are so critical today – they simply don’t work.

We started AdTruth because the 41st Parameter device recognition technology was ideally suited to solve the audience recognition problem.

Can you outline how the technology works?

There are hundreds of parameters that combine to differentiate between consumer devices. Things like the device type, operating system, language, and timezone – the list goes on and on – are used to create a device ID (it’s important to note that none of the information used contains any personally identifiable information).

Once these parameters have been analysed, an anonymous hash is generated. This is stored on the client side server. No residue is left on the device. When someone visits a Web site, a hash is generated and checked against the ones stored on the server. If there’s a match, an advertiser can deliver targeted impressions based on the behaviors and demographic data associated with the stored hash.

How is the technology currently being deployed? What are the use cases?

AdTruth is being used across the digital media industry to recognise audiences on any internet-connected device. This enables effective targeting and tracking to provide a more relevant and consumer-friendly advertising experience. The device recognition technology works across all devices including desktops, smartphones, tablets and more. The greatest interest is coming from the mobile industry, where there is a lack of technology available for effective audience recognition. Companies like BlueKai, for example, need to be able to identify audiences for its customers across mobile. Another use case is performance tracking, where InMobi - the largest independent mobile ad network - uses AdTruth to provide an identification layer. Adtruth helps them increase their CPM by doing three things. One, helping them recognise previously unseen audiences. Two, helping them build a much stronger behavioral targeting capability and, lastly, as a strategic partner for research and development for device recognition.

Is there an opportunity for large publishers/advertisers that have multi-screen relationships with users, to be able to map their users’ registration details and identify them across different screens/devices?

What you’re describing is ‘householding’ and it is becoming a Holy Grail for digital marketers. Unfortunately, solving this problem is a real challenge, since most approaches infringe on consumer privacy, as they need to link the devices to a piece of personal information. In some ways though, the industry has even more fundamental problems it needs to solve.

For example, there’s no way for most advertisers to know whether someone they’re targeting via the mobile, web or an app is the same person. It’s a huge problem. In fact, in some cases our customers have reported a 90% overlap. That means they’ve been targeting and delivering impressions at rates far higher than they intended or consumers want. It means they might display an ad for an app that someone already has installed on their phone or tablet. It’s irritating, wasteful and something we can solve for them.

How could an advertiser or publisher buy this mapped device ID in real time through various exchanges? Can the decisioning be executed in the same way as a bid request is decisioned against a cookie?

Absolutely. Our anonymous hashes, Device IDs, function in much the same way as cookies – only more broadly, more effectively and with greater respect for consumer privacy. The deployment of AdTruth is a foundational layer across the ecosystem creating a universal device recognition approach.

Is this a privacy-friendly solution? How does this differ from technologies labeled as 'fingerprinting'?

Our technology is absolutely privacy-friendly. Early on we met with lawyers and regulators in the US and EU to show them how our technology works and to make sure we were within the letter and spirit of relevant rules and regulations. In every case the answer was “yes”.

Our approach is unique in a number of ways. First, as mentioned earlier, we don’t collect any personally identifiable information. Things like UDID or GUID are attached forever to a specific device. If an individual is associated with that device then they are associated with the UDID or GUID – and that means their identity can be known as those identifies are tracked by marketers. Not OK.

We’re also different from device fingerprinting. That approach leaves residue on a user’s device. People don’t want things installed on their devices without their knowledge. We don’t do it now and we won’t in the future. You don’t need to do that kind of thing to deliver valuable data to marketers.

We have an approach that works, outperforms cookies and other current technologies and is fully privacy-compliant. It’s a much better approach – especially in the mobile world.