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What Is Cross-Device Identity Data?

Successful businesses survive by providing personalized service, right from initial contact. However, with customers cycling through different devices throughout the day and new marketing channels and media outlets opening up every day, businesses cannot consider single devices separately from their user. Cross-device identity data identifies individual users across devices with the help of IDs and cross-device graphs.

Where Does Cross-Device Identity Data Come From?

The two main ways through which cross-device tracking is conducted are deterministic and probabilistic tracking. Deterministic tracking uses personally identifiable information (known as PII) like Facebook profiles and email addresses to connect devices. Meanwhile, probabilistic tracking uses clues gleaned from millions of anonymous data points to connect devices. Examples of these anonymous data points include Wi-Fi networks, screen resolution, and operating systems.

What Types of Columns/Attributes Should I Expect When Working with This Data?

Cross-device data normally contains attributes like email, phone numbers, account usernames, and physical addresses. It also contains IP addresses, online cookies, and device IDs. Essentially, this data covers anything that can link a device to its user.

What Is This Data Used For?

Companies use cross-device identity data to recognize customers across the range of internet-connected devices that they use. The companies then combine this with behavior, preferences, demographics, and other information for marketing purposes—and not just for targeted ads. Global frequency management, for example, uses cross-device identity data to ensure that customers do not receive the same messages and ads on too many platforms as that can annoy and alienate them.

Additionally, you can use this data for sequential messaging and customer journey modeling. Or put another way, you can send different messages to a single customer through different devices, creating a targeted narrative.

How Should I Test the Quality of Cross-Device Identity Data?

First, you should collect high-quality cross-device identity data from multiple sources, as this diversity guarantees more accurate information. You should also request vendors provide sample datasets for you to test for accuracy, update frequency, and scale of information.

What Are the Most Important Factors I Should Vet When Selecting This Data?

As with many data categories, cross-device identity data comes from many different sources. This in turn makes quality assessment difficult. However, vendors that offer quality data, like the ones on our site, present the data in clear and comprehensive datasets. They should also provide previous customer referrals and sample sets for testing.

Finally, to ensure you know that the vendor uses appropriate sources and data collection methods. This is the best way to ensure you receive reliable data.

Interesting Case Studies and Blogs to Look Into

Best Practices In Cross-Device And Cross-Channel Identity Measurement
Cross-Device Identity: A Data Scientist Speaks

Tangible Examples of Impact

“Retargeting has been a breakout tactic since marketing made the shift from traditional trial and error programs to real-time programmatic campaigns. With retargeting, marketers could directly target the most promising individual consumers. It introduced a simple, practical way to put programmatic ambitions and valuable customer intent data into action, and drove clearly measurable ROI.”

IAB: A close look at retargeting and the programmatic marketer

Relevant datasets

PureB2B Demand Generation

by

PureB2B Demand Generation tracks real-time web data across devices and runs predictive analytics, powering lead and content generation

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Airnow PLC Mobile App Data

by Airnow PLC

Airnow PLC Mobile App Data consists of both a network of 400,000 app developers as well as 3.5 billion devices & more from 55 countries

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OMI Data

by

OMI Data tracks customer data across channels to improve customer care & marketing. It also helps businesses manage their data & architecture

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