What Is An Identity Graph and Why Do You Need One?

Reading time: 5 minutes

We are in the information age, and the internet has become a part of us. The average person spends 8 hours and 30 minutes every day on the internet. That’s a third of our lives. 

And while years ago, people owned a few gadgets and a single browsing device was usually the norm, we now use multiple devices to access the internet.

That can be very frustrating to businesses with an online presence—and in particular, businesses in the programmatic advertising[1] space.

When you’re shopping on Amazon on your desktop using your work IP address and email, then switch to your mobile device to complete the transaction or initiate another one, it’ll be hard for businesses to monitor your online activity—and profile you for analytics and retargeting.

It’d be like chasing a rabbit.

That’s the reason why identity[3] graphs are critical.

What Is an Identity Graph?

An identity graph is a technology that gives a stable picture of an online user based on their online activities regardless of how many devices, email addresses, and IP addresses they use over a period of time.

Studies show that we own and use more devices with every passing year. A study done by Cisco predicts that there’ll be 3.6 devices per capita globally by next year, in 2023.

While three devices per consumer is already a challenge in terms of tracking online behavior, the same Cisco study projects that in the United States, the average device per capita will reach 13.6.

South Korea and Japan will follow at 12.1 and 11.1, respectively.

Asia Pacific2.13.1
Central and Eastern Europe2.54
Latin America2.23.1
Middle East and Africa1.11.5
North America8.213.4

And that’s just a sneak-peek into mobile devices. 

Consider that businesses also have many different platforms. A company will have a website with an online store and one or more apps on the side.

A good example is Nike. The American sportswear company makes 21% of its sales through its eCommerce platform. Nike’s eCommerce sales include sales earned through its two mobile apps, Nike and SNKRS apps.

Therefore, it would be a technological feat to trace and profile the online behavior of a multiple-device user who again uses different vendor platforms.

While forming a complete picture of such a user can be very difficult. But building an identity graph can help create the profile of such a consumer.

How Does Identity Graph Work?

There are four steps before a comprehensive user picture can be formed, as shown in the following table.

Step                  Description              Specific Activity
1Online Data CollectionCollecting users’ identifiers like emails through several methods, including sign-ups.
2Offline Data CollectionConsumer data like purchases are collected from sources like ad platforms, CRMs, and eCommerce sites. 
3Universal Profile CreationThe data collected in step-2 above is linked to user identifiers collected in step-1.
4Matching the profilesThis stage involves ensuring that the matching process is accurate and up-to-date.

Types of User Profiles Within the Identity Graph

There are two types of user-profiles that this technology requires as follows.

  • Authenticated Profiles: Also known as persistent profiles, these are profiles that require a user to log into a platform or a website.

    Authenticated information will require evidence of identification. Examples of authenticated profiles include email addresses or credit card numbers.
  • Non-authenticated Profiles: Non-authenticated profiles are compiled and curated from more flexible, short-lived identifiers like device IDs or website cookies.

    If a user has only one device, they may be of significant help. However, their usefulness dips as the number of user devices increases.

How Does Identity Graph Match User’s Data?

An identity graph technology will use two data matching methodologies: deterministic and probabilistic.

Deterministic Matching

Deterministic matching pairs information about a known, authenticated user across different platforms and devices.

For instance, the purchase history of xyz@gmail.com from Amazon will be matched with the purchase history of a user with the same email address on the Walmart platform.

Because the matching involves unique, personal identifiers, the information is expected to be 100% accurate.

Probabilistic Matching

Probabilistic matching uses impersonal identifiers like device ID or IP address to pair and match information.

The problem is that if I’m using the same computer with my spouse, for instance, the information matched will not reflect my behavior. For this reason, probabilistic matching is never 100% accurate.

Benefits of Identity Graph

In marketing, identity is everything. It enhances personalization, and a consumer Identity Graph will facilitate more targeted and personalized advertising.

 If you know the kind of person you’re selling to, by having a complete “graph” or picture of him, you’re likely to meet his purchasing needs better—than if you were doing it randomly.

This is particularly important since we’re getting into a space where consumers are shielding themselves because of privacy concerns.

An ID Graph also improves user analytics. If you know the profiles of your customers, you can design a marketing strategy that fits their needs.

Other than that, Identity Graph can help you better evaluate your marketing campaigns. This is because you’ll have data of your users, including their geographical locations.

With this information, you can have an accurate idea about the reach and extent of your marketing campaign[4]—and make any necessary future adjustments.

Few Things To Consider Before Onboarding an Identity Graph Vendor

Before engaging and onboarding a provider, you should ensure that the Identity Graph provides a more steady and stable solution.

To achieve this, you should opt for a solution that relies less on non-authenticated profiling and probabilistic methodologies. Instead, the Identity Graph should use authenticated profiles like email addresses.

Secondly, ensure that your Identity Graph won’t overlook some touchpoints.

How to get started with Identity Graph?

  • Step 1: Collect all identifiers and have a complete dataset from Google Analytics[2], CDP, and other platforms.
  • Step 2: Synchronize your data with that of the ID Graph provided by your partner.
  • Step 3: Your ID Graph partner should then enrich and activate your data—and the different audience segments.

If you have a problem identifying an ID Graph partner, you can consider working with LiveRamp, Zeotap, Lotame, or InfoSum.

What’s Next?

The internet has changed the advertising landscape forever.

Businesses that play catch-up may be left behind—and remain behind. 

As a result, companies that adopt enabling technologies like Identity Graphs will find themselves thriving in the new ecosystem and earning higher figures.

1. programmatic advertising. Programmatic advertising entails using machine learning and technology suites to buy and sell ad inventory with a data-driven process.
2. Google Analytics. This is Google’s traffic tracking and analytics tool that gives publishers insight into traffic origins, popular pages on their website and much more.
3. identity. The effort to recognize and understand individual audience members (including customers, prospects and other visitors) across channels and devices such that brands can interact with these individuals in ways that are relevant, meaningful and supportive of business objectives
4. campaign. A set of bidding instructions that at a minimum includes a bid price for inventory. Most campaigns also include criteria such as a specific start and end date, daily or overall budgets, frequency restrictions, and targeting based on user or inventory data.

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