Identity resolution is crucial for creating personalized customer experiences. However, building an architecture that can handle identity resolution as the business grows is difficult. It requires a clear strategy, a reliable universal identifier, and simple data processes. Understanding customers personally and treating them as unique individuals is key to being a customer-focused organization. However, as businesses expand, identifying each customer accurately becomes more challenging. This is where data teams can make a big difference by solving the problem of identity resolution. .

What is Identity Resolution?

Identity resolution is simply the ability to identify a Person from a large amount of data—determining who they are and the behavior they represent. It involves linking various personal identifiers to individuals as they engage with your business through different channels and devices. In other words, identity resolution is matching data or buying signals to the exact individuals interacting with your company. This enables businesses to create a complete 360-degree view of prospects, customers, and partners. It also forms the foundation for correctly automating the lead-to-account matching process.

What do Identity Resolution platforms do?

In sales and marketing, tracking buyer behavior and connecting those buyers to their respective companies and, ultimately, their purchasing teams is essential. Many marketing leads remain unused in systems simply because they can’t be linked to a company. These leads can only be evaluated based on behavior, making it challenging to score or assign them to the right salesperson. Identity resolution platforms solve this problem by gathering data from multiple buyer interactions, enhancing it with high-quality third-party information, and combining it with the company’s first-party data. The result is a unified buyer profile created through a set of rules, enabling sales and marketing teams to link buyers to companies and gain access to accurate, up-to-date information about them. This process allows for precise segmentation and targeting. Once buyer segments are defined, teams can engage these audiences in account-based marketing, connect them with various media platforms, and track how they respond to campaigns across different channels.

Why is Identity Resolution so important today?

In today’s fast-paced business world, time is everything—delays can cost you deals and leads. Companies with effective identity resolution platforms can take even basic details from simple web forms, enhance them with high-quality data, match them to CRM accounts, and assign them to the right system or person in just minutes. Identity resolution improves the reliability of your data and profiles, boosts customer service, streamlines operations, and makes data analytics more dependable. This efficiency is critical in staying competitive in today’s economic environment. Building detailed buyer profiles is essential for personalizing outreach and focusing on the most promising opportunities. To do this effectively, it’s crucial to accurately combine firmographics, demographics, technographic, intent signals, fit, persona, and engagement into a single, unified buyer profile. Identity resolution and accurate profiles are the foundation of revenue targeting, which, in turn, drives the success of sales and marketing efforts.

How does deterministic or probabilistic matching affect identity resolution?

The choice between first-party and third-party data is key when addressing customer identity. In consumer identity resolution, the source of data influences the type of identity resolution that can be applied. First-party data (collected directly from customers) allows for more precise identity resolution, while third-party data (anonymized data from external vendors) provides a broader, less specific view of identity.

• Deterministic identity matching: Deterministic identity matching is based on clear, known identifiers. Deduplication and device stitching are essential to gaining a complete understanding of customer journeys and campaign effectiveness. Clickstream data resolution, which links past actions to current identities, helps track user behavior and improve brand impressions.
  For example, a user visiting a website might be assigned a temporary anonymous ID. If they later create an account or make a purchase, that ID is linked to personal details like an email or phone number. If they return from a different device, such as a smartphone, a new anonymous ID is assigned. Deterministic matching allows for connecting these IDs, ensuring a reliable identity resolution process.
• Probabilistic identity matching: In contrast, probabilistic matching relies on making statistical guesses based on ambiguous data. It utilizes device co-location, IP addresses, or fuzzy matching algorithms to combine various non-deterministic data points to estimate a customer’s identity. Probabilistic matching is often powered by third-party data, which comes in large volumes, making it easier to conclude data patterns.
  While deterministic matching tends to be more precise and secure, probabilistic matching can be useful when handling anonymous or incomplete data. The choice between the two approaches depends on the balance between accuracy and potential risk. For example, deterministic matching ensures data security and precision, especially important in compliance with privacy laws, whereas probabilistic matching may offer better solutions when dealing with large-scale or anonymous data.

Benefits of identity resolution for business

With identity resolution, businesses can build a comprehensive view of their customers from every data source. Understanding your customers better is essential, but there are several practical advantages to implementing identity resolution.

• Increased data quality We often hear the saying, “Data is the new gold,” and it holds. However, data is valuable only when it’s accurate and high-quality. Identity resolution helps refine and combine customer behavior data, eliminating duplicates and improving data quality. With more reliable customer information, businesses can make informed decisions in areas such as product development, marketing, and customer support.
• Stronger compliance Poor data quality leads to challenges in compliance efforts, particularly when managing audits and fulfilling subject access requests. By consolidating data, businesses can efficiently manage and retrieve information, helping to identify anomalies and ensuring robust data governance. This supports compliance with regulations such as GDPR and other data protection laws.
• Better customer insights Identity resolution integrates disparate data points—such as anonymous user IDs—and assigns them to real individuals. This creates accurate, detailed customer profiles. These profiles grow as users interact with your business across various channels, helping build a comprehensive Customer 360.
  With this insight, businesses can better understand their customers’ behaviors, preferences, and historical interactions, allowing for more targeted and personalized marketing efforts.
• Reduced customer churn Maintaining existing customers is crucial for business growth. By analyzing user data and identifying risky behaviors, businesses can proactively engage and prevent churn by delivering personalized campaigns. This enhances customer retention and increases lifetime value.
• Enhanced omnichannel experiences Customers expect a seamless experience across all touchpoints—whether it’s on your website, mobile app, or during interactions with customer service.
  Identity resolution unifies interactions, behaviours, and preferences from different channels, providing users with a smooth, personalized experience across all platforms. This eliminates the need for repetitive data entry and ensures a consistent, convenient journey.

Getting started with identity resolution: Best practices and considerations

Identity resolution is crucial for managing personalized marketing and overcoming data challenges. Here are some best practices and considerations:

• Establishing a Universal Identifier
  • Challenge: Many tools use email or hashed email as identifiers, which aren’t universal.
  • Solution: Utilize canonical identifiers like externalIDs (e.g., user_id, device_id, anonymous_id) to merge and unify data into a single profile.
  • Benefits: Eliminates fragmented data and creates a comprehensive, privacy-compliant customer view.

• Simplifying data pipeline creation
  • Approach: Build and streamline data pipelines for identity resolution by collecting, processing, and activating data.
  • Solution: DataQuark's CDI facilitates real-time data collection and processing across web, mobile, and server platforms. Here Customers can ensure that data adheres to data collection best practices, thereby making it simple for data teams to focus on solving business use cases rather than fixing data problems.

• Implementing a Rigid Approach to Data Stitch Rules
  • Challenge: Flexible systems might lead to inconsistencies and confusion.
  • Solution: Implement a deterministic architecture based on exact matches, prioritizing first-party data for reliable profile unification.
  • Segment’s Role: Provides flexibility within a rigid structure, ensuring data consistency.

• Understand the role of the data warehouse
  • Challenge: Data warehouses are effective for storage but lack sophistication for identity resolution.
  • Solution: Avoid managing identity resolution solely within the warehouse. Use sophisticated data handling methods to unify customer profiles with a canonical identifier.

• Emphasizing Portability in Identity Resolution
  • Challenge: Managing identity resolution across multiple business applications can be complex and inefficient without proper integration.
  • Solution: Use APIs to manage and sync identity resolution across various business applications, ensuring data portability and enabling consistent, up-to-date profiles.

Conclusion:

Identity resolution is a critical component for businesses seeking to create a comprehensive and accurate understanding of their customers. By leveraging best practices, such as using true universal identifiers, simplifying data pipelines, and maintaining a deterministic approach, organizations can build reliable, privacy-compliant customer profiles. Additionally, focusing on portability through APIs allows seamless integration across various business applications, ensuring consistent and up-to-date profiles. As businesses continue to navigate evolving privacy laws and increasing data complexity, a thoughtful, strategic approach to identity resolution will be essential for driving meaningful insights and delivering personalized, omnichannel experiences.