Custom Search Look‑Alikes is an audience modeling solution that creates look‑alike segments derived from observed search behavior. Instead of relying on declared interests or demographics, the solution analyzes search queries and related behavioral signals to identify users who demonstrate intent patterns similar to a defined source group. The process begins with a set of seed criteria, such as known customers, converters, or specific search themes. Machine‑learning techniques analyze search activity and related browsing behavior to identify common signals, which are then used to find additional users with comparable intent profiles. Custom Search Look‑Alikes is designed for advertisers seeking to expand reach while maintaining relevance. It is particularly suited for prospecting and acquisition use cases where search intent is a strong indicator of future behavior. The solution operates within privacy‑compliant frameworks and does not rely on third‑party cookies.

Key Features

Search‑Based Audience Modeling

Uses observed search activity.

• Analysis of query‑level intent signals
• Identification of meaningful search patterns

Look‑Alike Expansion

Extends reach beyond known users.

• Finds users similar to seed audiences
• Maintains alignment with original intent

Intent Signal Analysis

Focuses on user motivations.

• Emphasis on active interest indicators
• More predictive than static attributes

Machine‑Learning Driven

Automated pattern recognition.

• Continuous refinement of audience logic
• Adaptive to changing search behavior

Privacy‑Compliant Identity Resolution

Designed for modern data environments.

• Functions without third‑party cookies
• No direct use of personally identifiable data

Activation‑Ready Audiences

Prepared for advertising execution.

• Structured for use across media platforms
• Consistent audience definitions

Benefits

Improves Prospecting Relevance

Targets users with demonstrated intent.

• Higher likelihood of engagement
• Reduced reliance on broad targeting

Expands Qualified Reach

Scales beyond existing audiences.

• Identifies new potential customers
• Preserves similarity to known converters

Leverages High‑Signal Data

Uses search as a strong indicator.

• Reflects active decision‑making behavior
• Supports performance‑driven campaigns

Supports Efficient Media Spend

Improves targeting precision.

• Reduced wasted impressions
• Better alignment with campaign goals

Reduces Technical Complexity

Simplifies advanced audience creation.

• No need for internal search data modeling
• Managed modeling and delivery process