• The user data accessed from various devices, sites, or portals is streamlined and channelized into a unique uniform identity.
  • With the evolving technology and expanding pool of consumers, identity resolution proves to be the best tool for marketers.

Identity resolution is the process of converging digital data and activities from multiple sources to particular users. The identifiers over various touchpoints and devices are aligned to a single profile. The process becomes practically feasible with an aid of modern Machine Learning (ML) and Artificial Intelligence (AI) tools. It involves a data management system to link users’ online behavior to their unique identity by accessing different data sets and spotting non-obvious relationships.

Generally, users access the same site or portal from different devices, such as cell phones, computers, and tablets, generating various identities. Identity resolution helps to sync all these separate identities to one user. The process is crucial to customer-based marketing, which emphasizes offering consumers a consistent experience by tracking a single identity over several channels and devices. Marketers can identify a specific user, gain insights into their browsing patterns, and generate a customized campaign for that customer.


A profile database or identity graph containing known identifiers relevant to the user is used to resolve identity. Core functionalities of identity resolution consist of integration and amp; activation, compliance, data onboarding, identity graph, and real-time and amp; persistent matching.

  • The most updated and addressable user profiles are made available to systems heading to data activation by running campaigns.
  • By the prevalent regulations, users’ information regarding geography, industry, preferences, and time frame is accessed. This indicates that anything slightly associated with user information is subject to security compliance and privacy. Identity resolution caters to everything housed in the context of the enterprise.
  • Data onboarding brings all the available digital customer data onto a uniform system. Precise data onboarding is a function of security, accuracy, and speed.
  • An identity graph primarily works on Personally Identifiable Information (PII) from the customer profile with digital identifiers such as external channels, devices, or behavioral data. This may include a range of data such as cookies, IP addresses, device data, mobile advertising IDs, online surveys, and data from vendors or marketing partners. The result created with the data can be further conveyed to plan the advertising campaigns for the concerned user.
  • Once the data is procured on the Customer Data Platform (CDP) or identity resolution system of vendors, the later analytical operations begin. This involves eliminating the replicated and redundant data, anonymizing or hashing, and suppression. Ultimately, the outcome obtained is the unique individual profile of each user, being persistent and real-time.


Some identity specialists distinguish the probabilistic and deterministic identities. The probabilistic algorithms work on informed conjectures with the possibility of being correct. However, their function is slightly uncertain as they probably generate more elaborate identifier graphs with deviating connections. On the other hand, the deterministic approach generates less elaborate but more reliable and accurate results.

  • Probabilistic Identity Resolution

Here the profiles are matched on the assumption of statistical similarities speculating that the two identities must be of the same user. Various identifiers involved in the process are browser or OS, IP address, location, device type, browsing patterns, behavioral data, wi-fi networks, and timing. The combination of attributes in each use case creates a logic that indicates the probability of a match. Multiple vendors have made available the foundational databanks to assist probabilistic matching. If several identical records across different devices are found to share some common identifiers, it is concluded that it is probably a same user.

  • Deterministic Identity Resolution

Customer records are browsed and matched based on common observations across signed-in usernames, contact numbers, hashed emails, and other identifiers. The process becomes simpler if the first-party data is handy during the research. The data includes office address, email address, telephone number, credit card number, log-ins, etc. There is no room for uncertainty about user identification because if the person logs into any entrepreneurial site or portal first on a desktop and later through the mobile app. It can still be concluded with utmost confidence that the same user accessed via different devices at different times.


  • Smart identity resolution on enterprise levels can help leverage the marketing outcomes. Communication can be streamlined across various devices and touchpoints to reduce overlaps, mistargeting, and duplication. It becomes easy for the marketers to distinguish between the potential target customers and the ones not to approach. This saves hefty amounts for enterprises than usually what is spent on retargeting advertisements.
  • With the homogenous uniform data, all the platforms can easily deliver the right ads and messages on right portal to the right user, thus saving campaign expenditure and conversion rates.
  • The enhanced collaboration and integration between several domains such as sales, finance, customer service, and marketing can offer a single user relentlessly even after the purchase, thus, retaining the customers for a long time.
  • Identity resolution, at macro level, helps marketers to better differentiate between identical audience and even reach out to new chunk of consumers to plan the suitable advertising campaigns.
  • The performance and attribution tracking over various devices offer transparent analysis of users at an individual level.
  • It is obvious that over a period customers evolve to change their preferences and switch to some other enterprises. An intelligent identity resolution helps marketers to address these changes and remain relevant with the customers.
  • A comprehensive view of customer’s existing preferences helps the brand to say compliant with all regulatory and privacy requirements.
  • It has been evident that customer data management (CDM) with the help of identity resolution is the most promising way to gain and retain customers with lowest expense of advertisement campaigns.


  • The available information of the customer is sometimes just a number, sign-in, or a transaction. It becomes little tedious to access concrete data about his/her preferences, devices used, sites browsed, etc.
  • Synchronizing online identities of an individual becomes a hectic function due to non-persistent data, technology silos, and data loss as number of vendors are involved. Since customers engage and access over several touchpoints and channels on number of devices, it becomes challenging to recognize all the digital sources associated with customer’s identity.
  • Since campaigns are planned on estimations, the primary device can be accessed but everything else falls under assumption. Due to difficulty in identifying individual user preferences, the brands usually create generic campaigns, which cannot cover or engage the vast consumer prospects. Once the customers switch devices or platforms, all the engagement built on previous portals is susceptible to loss.


The significance of identity resolution continues to surge for brands, enterprises, and marketers as consumers prefer various channels and devices. As the number of consumers increases, it becomes challenging to track the various identities of a single customer, making it almost unfeasible to generate a customized and personalized campaign. Identity resolution makes this possible by linking the dispersed information to create a clear and unique identity for each customer.

Identity resolution in marketing is anticipated to become the competitive discipline for enterprises as data management and technology are continuously evolving. It can compile data across first, second, and third-party sources to attribute to a unique customer identity. Despite being advantageous to brands and enterprises, identity resolution poses security hazards to customers’ data. Recently, some US state legislatures implemented data laws to curb data transfer practices in private and government spheres. In a nutshell, the process should continue to expand and update but not at the stake of people’s personal information.