There’s a lot of talk in the industry about identity resolution as the next generation of marketing infrastructure.

But to us, it’s nothing new.

We’ve spent the last decade building an authentic identity graph.

Not a customer database, not a relational database—a true identity graph encompassing online and offline data, all focused around a real individual.

Our graph can confidently and accurately support omnichannel marketers, providing resolution in a matter of milliseconds. It’s also an ideal source of signal data and intelligence for KYC verification and fraud prevention.

Our identity graph powers Resolve—our real-time, privacy-centric identity resolution product.

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What is an identity graph?

At its simplest, an identity graph is a database of all the little pieces of information we know about any given person, unified into a privacy-protected, single customer view.

You can think of it like tons of contact fragments—names, hashed emails, device IDs, website visits, transactions, etc.—with connections between them. A grouping of fragments and the connections between them represent a person, formed in the graph.

If you want to get technical about it, an ID graph is actually a collection of nodes and edges. The nodes are contact fragments and the edges are the connections between them.

Visualized, an identity graph looks like this:

Abstract image of an identity graph, a photo of a man using a cell phone and laptop, and icons representing contact fragments such as names, contact information, hashed emails, device IDs, website visits, social networks, transactions, and more.

What kind of information is in an identity graph?

Identity graphs can collect billions of data points about people and their behaviors.

Common identifiers in an identity graph may include:

  • Hashed emails
  • Mobile ad IDs
  • Social identities
  • Customer and/or loyalty IDs
  • Cookies
  • Device IDs

There are often also undeclared identifiers, such as:

  • Membership in an email or subscriber list
  • Demographics
  • Purchases/transactions
  • Visits to online news sites
  • Surveys
  • Voter registration
  • Motor vehicle records
  • Other financial and digital behaviors

How does an identity graph work?

The identity graph serves as the backbone of the identity resolution process.

Identity resolution relies on the identity graph to associate pieces of information with a person, learn more about that person, and reach that person across devices and channels.

You can query the graph for specific attributes to accurately identify the individual person it belongs to (from the billions of other people in the identity graph). Once you know who this person is, the graph allows you to see all of the other pieces of information collected on that person.

Together, the identity graph and identity resolution process power a variety of use cases-from customer recognition to improve the customer journey to robust identity verification and fraud prevention.

What is FullContact's identity graph?

The relationship between brands and people should be more meaningful than a single identifier. That’s why we match and provide insights and identifiers to build a whole-person picture.

Our identity graph connects data fragments of each individual, including both personal and professional identifiers, as well as hundreds of marketing attributes about each person.

Individuals are constantly evolving—moving between locations, getting new cell phones, resetting their Mobile Ad IDs, changing their name, etc. As people evolve and customers interact with various brands, our identity graph evolves with them. It learns over time to recognize who someone is, even as their identifiers may change.

FullContact’s identity graph features:


Our identity graph powers Verify—real-time and on-site intelligence to train your verification and fraud prevention models

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Our Graph is SMARTER

With dynamic and evolving person graph from diverse data sources, simply seeing that some identity fragment is connected to a person does not alone deem it trustworthy! To account for this, we invented a confidence algorithm to efficiently and accurately measure an identity’s trustworthiness.

Our confidence scheme for ensuring accuracy and robustness is baked into the core of what actually makes up a person.

The graph platform allows for learning and logic between identities in a way traditional databases simply do not. And depending on what you want to use our identity graph for, you can tune the confidence levels to get the desired results on a request-by-request basis.

The confidences are constantly evaluated through

The confidences are constantly evaluated through different types of contact elements, the trustworthiness of the sources, and the number of connections. By leveraging FullContact’s unique Human in the Loop process, we apply human intelligence to augment our workflows and act as a differentiator to normal computer-based workflows. This helps further make logical sense of customer data connections. It also expands our capabilities to continually evaluate and test our confidences in a way no one else does.

We were honored to be named one of the Top 300 API Innovations in 2019. And we continue to receive and apply for patents, including:

  • U.S. Patent Number US10445371 – Identity Resolution
  • U.S. Patent Application US20170286565A1 – Relationship Graph

Our Graph is FASTER

Real-time results get you the information you need exactly when and where you need it to improve your customer profiles and impact your customer experience.

We’re able to service requests across billions of input identifiers as well as recompute our identity graph from hundreds of billions of observations in a matter of hours. This allows us to service customers and partners via APIs with standard JSON payloads in less than 150 milliseconds to provide the most current and accurate data available.

Our batch process can also process hundreds of millions of your records within a day, joining each record to the graph to help you understand your customers better.


Our Graph is EASIER

If you can’t easily integrate our products into your system, what’s the point?

That’s why we cater to both real-time use cases (i.e. API) and offline processing with large, flat files (hundreds of millions+) for companies whose systems prefer these. We are the backbone of supporting a multitude of integrations, where we can resolve down to the individual.

We were honored to win API World’s Best in Data APIs for 2018 as a result of having great client libraries, documentation and data.


Our Graph is SECURE

Given the nature of our work, security is paramount, and protecting data is critical. It is our duty to secure personal and sensitive information. This starts from the ground up and is embedded in our culture.

We’ve implemented processes and technologies around:

  • Data encryption
  • Controlled access to sensitive data
  • Employee training
  • Rigorous background checks

FullContact invests in and maintains the highest level of data security. We’ve created numerous security measures, activated per-account encryption to keep account-specific information locked up, and added an audit trail for decryption requests.

We’re SOC2 Type II certified, which is considered the most comprehensive certification under SOC protocols. SOC 2 Type II builds on SOC 1, while additionally requiring a third- party audit, standard operating procedures for organizational oversight, vendor management, risk management, and regulatory oversight. To earn this designation, we went through a rigorous evaluation over the course of a year and are actively maintaining its certification.

We take data privacy so seriously that we were poised and ready to comply with CCPA and GDPR requirements. We have chosen to take the stance that these guidelines apply to everyone—not just those individuals who fall under the CCPA and GDPR protections.

Why? Because it’s the right thing to do.

We had the pleasure of winning the Advisory Board of Privacy Council Award in 2018.


Our identity graph powers Enrich—our data ecosystem that lets you append multidimensional customer and prospect data.

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