What is Identity Resolution?

Identity resolution plays a crucial role in developing unique customer profiles by analysing and associating data collected through various touchpoints, channels, and systems. Utilising both deterministic and probabilistic matching techniques, it leverages multiple identifiers from different devices to create a comprehensive view.

To support this process, CDP APIs can route identifiers from each channel to the identity resolution engine, then make the unified profile available to connected tools.

This process is fundamental for refining marketing strategies, supporting data governance, and delivering a personalised customer experience.

This unification process can be achieved through software, particularly Customer Data Platforms (CDPs). These platforms integrate information from multiple devices and channels, enabling businesses to create single, unified profiles for each consumer.

👉🏼 In this article, we define what identity resolution is and explain why it is essential for your marketing strategy.

The foundation of identity resolution relies on the ability to identify and associate different identifiers corresponding to a single person, such as their email, cookie ID, and device identifier, among others. This process supports the matching of customer identities across multiple devices and channels, enhancing both business insights and user experiences.

One key aspect of identity resolution is the use of an identity graph, which represents the relationships connecting a customer's profile to all known identifiers such as physical addresses, email addresses, phone numbers, and device IDs. This graph enables a more coherent view of the known consumer journey, facilitating enhanced analytics and personalised marketing.

Identity resolution enables the creation of a 360-degree view of a consumer from available information (also known as Customer 360), which can be utilised in connected systems and marketing campaigns. This holistic customer profile is crucial for effective marketing and business strategies, allowing marketers to work on detailed profiles and comprehensive data.

Successfully communicating with customers is not easy:

Despite this, consumers are increasingly demanding, seeking an effective and transparent omnichannel relationship and greater personalisation. Identity resolution helps in creating a consistent user experience across various touchpoints and channels, helping teams personalise interactions across the channels they can connect.

Identity resolution aids in achieving data onboarding, which involves transferring offline data to an online environment to create a comprehensive customer profile and facilitate personalised marketing efforts. This helps in matching offline identifiers with online user profiles, ensuring a unified view of the consumer across all channels.

The ability to generate such a 360-degree view is essential for effectively segmenting the audience, refining targeting, and personalising communication approaches while ensuring consistency across all channels. Indeed, identity resolution is crucial for enabling deeper product insights and accurate understanding of user journeys, which are essential for delivering personalised experiences and ensuring better customer engagement. It allows marketers to create accurate, individualised profiles of customers. For example, a fictional retailer can link an in-store purchase and a web account through a loyalty number to suppress an inappropriate reminder. The purchase must also reach the tool that triggers the campaign.

Access to a comprehensive representation of customers enhances the understanding of their behaviour, satisfaction level, loyalty, and added value. This becomes a powerful lever to refine marketing strategies, accurately evaluate return on investment, identify growth opportunities, and anticipate potential risks. Proper data management and analytics are key to this process.

With cross-channel tracking, identity resolution allows for the analysis of the known stages of the customer journey, highlighting their motivations, potential hesitations, and obstacles encountered. This broad perspective enables the orchestration of a smooth and transparent user experience, finely adjusted at each engagement stage, from awareness to loyalty.

Furthermore, a robust identity resolution solution can equalise offline and online experiences. This is highly beneficial for businesses that operate both physical stores and online storefronts, allowing them to send personalised offers across channels like email, push notifications, and even physical coupons to drive purchases.

Besides creating these comprehensive profiles, having an effective identity resolution solution is invaluable for data governance and privacy compliance. With stricter regulations such as GDPR and CCPA, marketers must ensure data is consolidated and managed correctly to avoid privacy breaches and compliance issues.

Identity resolution does not, by itself, ensure security or regulatory compliance. Purposes, lawful bases, communication preferences and retention periods require explicit handling. In an environment of restrictions on advertising tracking, it can draw on first-party data collected from consumers, helping connect known interactions while preserving the relevance and effectiveness of marketing campaigns. Privacy remains a fundamental concern in this process.

Identity resolution helps build a coherent set of customer data from available sources, reflecting the consumer journey. This dataset is useful for building a learning base for machine learning and artificial intelligence algorithms. Analytics and better customer knowledge lead to better detection of behavioural and transactional patterns, potentially improving predictions (such as lookalikes, churn risk, additional expected CLV, etc.).

There are two types of identity resolution: deterministic matching and probabilistic matching.

✅ Deterministic identity resolution applies explicit rules to identifiers or combinations of attributes. These establish a match between an identifier and a customer (e.g., email, phone number, social media account, etc.).

The advantage? A decision that can be explained through the rule applied. This approach is well-suited when your users willingly log in or register on your different online channels.

That login can also provide a matching point for identity stitching, allowing earlier anonymous interactions to be associated with the customer’s journey.

However, when you lack first-party data to identify a person, you miss out on certain information and may only have a partial view of their customer journey. A shared family email, a reassigned phone number or a typing error can still connect two different people: deterministic does not mean infallible.

🎲 Probabilistic resolution relies on complex statistical algorithms to assess the likelihood that a specific identifier belongs to a particular consumer. This may include a cookie ID, device identifier, IP address, or fingerprinting techniques, where their use is permitted.

This method increases the chances of accurate entity matching across multiple digital touchpoints and channels. It also enables broader coverage of customers, including people who have never logged in, where usable signals are available.

However, there is always a risk of misidentifying the individual. This type of matching relies on sophisticated data modelling techniques. It can be considered when exact identifiers are missing, with confidence requirements suited to the use case and checks for false matches.

Of course, identity resolution is not black and white. It is possible to combine deterministic and probabilistic approaches to be as comprehensive and accurate as possible in recognising your consumers. Validate the acceptance threshold against known cases and the intended campaign. A score of 0.8 does not automatically mean 80% correct matches: that interpretation requires calibration. These hybrid models help businesses achieve a higher resolution in customer profile matching.

Often, Customer Data Platforms (CDPs) are used to centralise, transform, and aggregate data from all sources to orchestrate this process. They also allow the implementation of marketing use cases that stem from a Customer 360 view, using the relationships and interactions available. Check three things: match rate against a defined population, false matches in a validated sample, and the freshness of information reaching destinations. A higher rate alone does not demonstrate better quality.

To see how these principles work in a tool, this demonstration introduces deduplication and data matching with DinMo Identity.

Identity resolution proves to be crucial for digital marketing, helping build a more coherent view of each consumer. It opens the door to advanced analysis, informs data-driven decision-making, connects known stages of the customer journey, and addresses security and compliance challenges head-on. The integration of multiple data sources into a single platform is key to achieving this.

For businesses ready to embrace identity resolution within their digital marketing strategy, Customer Data Platforms (CDPs) greatly facilitate the process. DinMo Identity supports this work through normalisation, deduplication and reconciliation. Teams can use the consolidated information for audiences and exclusions, after checking the matching rules and source quality.

🌟 If you want to learn more about our identity resolution methods and how our modular CDP approach can help you, feel free to contact us.