Modern marketing relies on customer data collected from multiple channels, devices, and platforms. As customers interact with brands through websites, mobile apps, social media, email, and offline touchpoints, businesses need ways to connect and utilize this information effectively.

Two important concepts that support customer data management and targeting are Identity Resolution and Audience Matching. While both involve customer data, they serve different purposes.

Identity Resolution focuses on connecting data from multiple sources to create a unified customer profile. Audience Matching focuses on identifying and targeting specific groups of customers across platforms using shared data attributes.

Both approaches help businesses improve personalization, advertising effectiveness, and customer understanding.

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What Is Identity Resolution?

Identity Resolution is the process of connecting customer data from multiple sources, devices, and touchpoints to create a single, unified view of an individual customer.

Customers often interact with businesses using different devices, browsers, email addresses, or accounts. For example, a person may browse products on a smartphone, sign in from a laptop, and later make a purchase through a mobile app. Without Identity Resolution, these actions may appear to come from different users. Identity Resolution helps businesses recognize that all these interactions belong to the same individual.

The primary purpose of Identity Resolution is to build accurate customer profiles, improve customer understanding, and enable more personalized marketing and customer experiences.

How Identity Resolution Works

Identity Resolution focuses on unifying customer information from various sources into one complete profile.

Data Collection

Businesses gather customer information from multiple sources to understand how customers interact with the brand across different channels.

Examples include:

• Website visits – Information about pages viewed, products browsed, and actions taken on a website.
• Mobile app activity – Data collected when customers use a company’s mobile application.
• Email interactions – Information about emails opened, links clicked, and responses received.
• CRM records – Customer details stored in Customer Relationship Management systems, such as contact information and sales history.
• Purchase history – Records of products or services purchased by customers.
• Customer support interactions – Information from support tickets, chat conversations, phone calls, or help desk requests.
• Loyalty programs – Data collected through membership programs, reward points, and customer participation.

Identity Signals

Companies use identifiers, known as identity signals, to determine whether different records belong to the same person.

Examples include:

• Email addresses – A unique email address can help connect customer activities across platforms.
• Phone numbers – Phone numbers can be used to identify and match customer records.
• Customer IDs – Unique identification numbers assigned to customers by a business.
• Login credentials – Usernames and account logins that help verify customer identity.
• Device identifiers – Information associated with specific devices used by customers.

Profile Unification

Once matching records are identified, businesses merge them into a single customer profile. This process eliminates duplicate records and creates a more accurate representation of the customer.

Customer View Creation

Businesses use the unified profile to create a complete view of customer behavior, preferences, interactions, and purchasing patterns across all channels.

Personalization and Analysis

The unified profile is used to generate customer insights, create audience segments, improve analytics, and deliver personalized experiences, recommendations, and marketing messages.

Example

A customer browses products on a mobile phone, later signs in on a laptop, and then makes a purchase through a mobile app. Identity Resolution connects these interactions into one customer profile, allowing the business to understand the customer’s complete journey rather than viewing each interaction separately.

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What Is Audience Matching?

Audience Matching is the process of identifying and connecting specific customer groups across advertising platforms, marketing channels, or databases.

The goal is to find matching users so businesses can target, retarget, or personalize campaigns for relevant audiences. Instead of marketing to everyone, businesses can focus on people who are most likely to be interested in their products or services.

The primary purpose of Audience Matching is to improve audience targeting, increase marketing efficiency, and enhance campaign performance.

How Audience Matching Works

Audience Matching focuses on finding targetable customer groups and connecting them with advertising or marketing platforms.

Audience Creation

Businesses create audience lists based on specific characteristics or behaviors.

Examples include:

• Existing customers – People who have already purchased products or services from the business.
• Newsletter subscribers – Individuals who have signed up to receive email communications.
• Recent purchasers – Customers who have made purchases within a specific time period.
• High-value customers – Customers who generate significant revenue or frequently make purchases.
• Website visitors – People who have visited the company’s website but may not have completed a purchase.

Data Preparation

Customer identifiers are prepared so they can be matched with users on advertising or marketing platforms.

Examples include:

• Email addresses – Commonly used to identify users across platforms.
• Phone numbers – Used as another reliable identifier for matching purposes.
• Customer IDs – Unique identifiers assigned by the business to specific customers.

Platform Matching

Advertising or marketing platforms compare the submitted customer data with their own user databases. The platform searches for users whose information matches the provided identifiers.

Audience Identification

Once matches are found, the platform creates a targetable audience consisting of users who correspond to the submitted customer data.

Campaign Activation

Businesses use the matched audience to deliver targeted advertisements, promotional offers, personalized messages, or retargeting campaigns designed specifically for that group.

Example

A company uploads a list of customer email addresses to an advertising platform. The platform compares those email addresses with its user accounts and identifies matching users. It then creates an audience segment that the company can target with advertisements, helping the business reach existing customers or similar prospects more effectively.

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No.	Identity Resolution	Audience Matching
1	Identity resolution is the process of building a single unified profile of a user across multiple devices, channels, and touchpoints.	Audience matching is the process of finding similar or corresponding users across different platforms or datasets.
2	It focuses on “Who is this user really?” by connecting fragmented data points.	It focuses on “Where can I find this user or similar users elsewhere?”
3	Example: Linking a user’s email, mobile app activity, and website behavior into one profile.	Example: Matching your CRM email list with Facebook or Google Ads users for targeting.
4	It is identity-centric (single customer view creation).	It is platform-centric (matching audiences across systems).
5	It works across multiple identifiers like email, phone, cookies, device IDs.	It works using hashed identifiers or platform-based matching algorithms.
6	It builds a long-term customer identity graph.	It enables campaign targeting and ad delivery to known users.
7	Example: A SaaS company identifying that a user logging in on mobile and desktop is the same person.	Example: Uploading a customer list to Meta Ads to show ads to those users.
8	It is used for personalization, analytics, and lifecycle tracking.	It is used for retargeting and paid advertising campaigns.
9	It provides a unified customer profile (360° view).	It provides a reachable audience segment on external platforms.
10	It is more backend data engineering and identity graph-driven.	It is more marketing activation and ad platform-driven.
11	It requires advanced data stitching and probabilistic/deterministic matching logic.	It requires hashed data uploads or platform audience sync tools.
12	Example: Google Analytics 4 connecting user sessions across devices.	Example: Uploading email list to LinkedIn Campaign Manager for ads.
13	It improves personalization and internal data accuracy.	It improves ad targeting and campaign reach.
14	It operates mainly within your data ecosystem.	It operates across external advertising ecosystems.
15	It answers: “Who is the user across all touchpoints?”	It answers: “How do we reach this user on different platforms?”

Identity Resolution and Audience Matching are important customer data strategies, but they serve different purposes.

Identity Resolution focuses on connecting customer information from multiple touchpoints to create a complete and accurate customer profile. Audience Matching focuses on identifying and targeting customer groups across marketing and advertising platforms.

While Identity Resolution helps businesses understand who their customers are, Audience Matching helps businesses reach those customers more effectively.

In simple terms, Identity Resolution combines customer data into a single profile, while Audience Matching uses customer data to find and target the right audience.