Definition

identity resolution

Identity resolution is a data management process that links a customer's online behavior to their unique identity by gathering different datasets and identifying non-obvious relationships. People often access the same site in various ways (from a cell phone, computer, tablet, etc.), thus creating an array of different identities. Identity resolution works to link all of these separate identities to one customer. This allows marketers to recognize a specific buyer, gain an understanding of their behaviors and generate a personalized campaign for the customer.

What does it do?

The identity resolution process primarily benefits marketers who are seeking to engage with their consumer through personalized interactions. Since identity resolution ties an array of online identities to one customer, then the business can more clearly see where that person is in the buying process. If the customer had started looking at the product while on their phone and then later returned to the site on the computer to complete the purchase, then identity resolution tools will show that these two points of contact were made by the same person. The business now knows they have succeeded in turning the lead into a customer and they can focus their campaign on maintaining a relationship with this specific consumer rather than continuing their initial attempts to capture a first-time buyer.

This collection of data from different sources to create a specific set of data that points to an individual also helps a marketing company observe patterns in the buyer's behavior and link the customer to a unique customer ID that can be tied to internal company information across marketing, service and sales. This would not be possible with a scattered data set. As marketers gain a better understanding of the customer, their behaviors and journey, they can further customize their campaigns, make them more targeted and avoid personalization errors.

The ID graph

At the core of the identity resolution process is the identity graph (or ID graph). An ID graph is a database that connects a customer's profile to all the known personally identifiable information (PII) for that specific consumer. The different identities of a consumer may include:

These identities are gathered in the customer profile with other descriptive data and then linked to the customer's behavioral data (such as past purchases). All of this information is consensually given by the consumer, stored in the ID graph and used for identity resolution. The customer profiles are initially made with probabilistic matching, meaning algorithms and patterns are used to make an educated guess that links one customer to its various devices, identities or other data within the ID graph. The system then uses artificial intelligence (AI) and machine learning (ML) to improve their guesses and make better matches. When the consumer finally verifies their identity through an action, such as paying with a credit card, then the match is determined. The identity resolution process has succeeded in matching a consumer to their various online identities and marketers can progress with a personalized plan of action based on the individual's habits and behaviors.

Some marketing companies rely on third party ID graphs. However, increasing restrictions on the use of personal data continue to build the border between what a company can and cannot use from the third party source. In order to have total access to the customer's behaviors and journey, the company must create and maintain its own ID graph.

Identity resolution continues to grow in importance for marketers as consumers use an increasing array of devices and channels throughout the day. As technology evolves, it becomes progressively difficult to keep track of one customer's various identities and, therefore, nearly impossible to create a personalized campaign. Identity resolution makes this feasible once again by linking the varied information and creating a singular, clear identity for each consumer.

 

This was last updated in June 2019

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