Lookalike audience targeting lets you find prospects who mirror your best customers. Instead of manually researching accounts, lookalike modeling uses data from converting customers to automatically identify similar high-fit prospects.
Here's how lookalike audiences work and how B2B teams use them to scale pipeline faster.
What Is a Lookalike Audience?
A lookalike audience is a group of prospects who share the same characteristics as your best customers. Platforms analyze traits from your existing accounts (firmographics, behaviors, demographics) and find new prospects who match those patterns.
After your marketing team creates ideal customer profiles, you feed first-party customer data into lookalike tools. The platform searches its database and returns accounts that mirror your top performers.
How Lookalike Audiences Work
Lookalike modeling starts with your seed audience: a curated list of customers with common traits (location, job title, buyer behavior). The platform's algorithm identifies patterns across that data, then finds new prospects who match those patterns.
Take these steps to find and create your lookalike audience:
Gather your first-party data through pixels, tracking, and form fills.
Analyze patterns and pinpoint recurring characteristics to form data for your seed audience.
Export your seed data set into a compressed file (and store it to use for future engagement).
Feed the seed data into a digital tool that crawls its database and spits out your lookalike audience data.
This lookalike audience data is crucial for more precise targeting in your marketing campaigns.
The process involves three components:
Seed audience: The original customer or lead list you provide
Algorithm matching: Platform analyzes traits and behaviors
Lookalike output: New prospects who share characteristics with your best customers
Building Your Seed Audience with High-Intent Segments
Not all customers make good seeds. B2B marketers need to be selective about which accounts go into their seed list.
The best seed audiences come from customers who actually fit your ICP and showed strong buying behavior. That means closed-won accounts, high-LTV customers, SQLs, and engaged prospects who converted quickly.
Start with these high-intent segments for your seed audience:
Closed-won customers from the past 12-24 months
High-LTV accounts showing expansion behavior
SQLs that converted quickly
Website visitors who requested demos or pricing
Choosing Your Lookalike Audience Size
Lookalike platforms let you control audience size, and that choice matters. Smaller audiences match your seed more closely. Larger audiences cast a wider net.
The tradeoff is precision versus reach. If you need pipeline precision, go smaller. If you need top-of-funnel reach, go larger.
Here's how to think about the size decision:
Smaller lookalike: Tighter match, higher relevance, smaller pool
Larger lookalike: Broader reach, lower precision, bigger pool
Let your campaign goal guide the choice. Pipeline campaigns need precision. Awareness campaigns need reach.
Why B2B Marketers Use Lookalike Audiences
Lookalike targeting solves the B2B targeting problem: finding qualified accounts at scale. Instead of casting wide nets or relying solely on manual research, you use customer data to automatically identify prospects most likely to convert. It's especially powerful for ABM programs that need to expand beyond known account lists.
B2B teams use lookalike audiences to:
Reach new accounts that mirror your best customers
Reduce wasted ad spend on unqualified audiences
Accelerate pipeline by targeting accounts more likely to convert
Scale ABM campaigns beyond your known account list
B2B Use Cases for Lookalike Audiences
Lookalike audiences work across the full GTM motion. Here's where B2B teams deploy them.
Common use cases include:
ABM list expansion: Find accounts that match your Tier 1 target profile
New market entry: Identify prospects in verticals where you've had early wins
Demand gen scale: Grow your targetable audience beyond known contacts
Win-back campaigns: Target prospects similar to recently churned accounts
Each use case ties back to a GTM outcome. Lookalike audience targeting helps you find the right accounts faster, whether you're expanding into adjacent verticals or scaling demand gen beyond your existing database.
Layering Intent Signals for Better Timing
Lookalike audiences tell you WHO looks like your best customers. Intent signals tell you WHEN they're actively researching. Combining both gives you the highest-priority targets:
Lookalike: Right profile (matches your ICP)
Intent: Right timing (actively researching)
Combined: Highest-priority targets (fit + in-market)
Lookalike Audiences vs. Custom Audiences vs. Retargeting
These terms confuse practitioners. Here's the difference.
Custom audiences are your known contacts. You upload lists from your CRM or collect pixel data from your website. Retargeting re-engages people who already interacted with you. Lookalikes find NEW people similar to your best performers.
Here's when to use each:
Audience Type | Source | Use Case |
|---|---|---|
Custom Audience | Your CRM, pixel, or list uploads | Target known contacts and accounts |
Retargeting | Website visitors, app users, ad engagers | Re-engage warm prospects |
Lookalike Audience | Modeled from seed audience | Find net-new prospects similar to best customers |
Best Practices for Building Effective Lookalike Audiences
Follow these practices to maximize ROI from your lookalike audiences:
Use your highest-quality seed: Closed-won accounts outperform broad website visitor lists
Refresh regularly: Stale seeds produce stale lookalikes
Set suppression lists: Exclude current customers from acquisition campaigns
Test multiple seeds: Compare lookalikes from different customer segments
Align seed to goal: Use high-LTV customers for retention campaigns, fast-closers for pipeline velocity
For more, learn how ZoomInfo data can deliver targeted ads to prospects.
Start with a Clean, ICP-Aligned Seed List
Garbage in, garbage out. Your lookalike is only as good as your seed.
Curate seeds carefully using ICP criteria (firmographics, technographics). Filter for positive outcomes like closed-won accounts, high NPS, and expansion accounts. Remove bad-fit customers who converted despite being wrong for your product.
Use this checklist for seed list hygiene:
Remove duplicates and outdated records
Filter for ICP-fit accounts only
Prioritize customers with strong outcomes (retention, expansion, referrals)
Exclude accounts that churned quickly or required heavy support
Common Lookalike Audience Mistakes (and How to Avoid Them)
Most marketers make the same mistakes with lookalike audiences. Here's what to watch for.
Common pitfalls include:
Using all website visitors as seed: Too broad. Use converters or high-intent visitors instead.
Set-and-forget mentality: Lookalikes decay as your customer base evolves. Refresh quarterly.
Audience overlap: If your lookalike overlaps heavily with retargeting, you're paying twice for the same people.
Defaulting to largest size: Bigger isn't better. Start smaller for precision, expand only if volume is the goal.
Privacy and Compliance for Lookalike Audiences
GDPR and CCPA apply to lookalike audiences. This isn't legal advice, but here's operational hygiene:
Use consented first-party data: Only upload contacts who opted in
Document data sources: Track where seed data originated
Hash identifiers: Use hashed emails where platforms support it
Maintain suppression lists: Exclude opt-outs and do-not-contact records
Establish governance: Define who can upload and maintain lists
To learn how ZoomInfo helps B2B teams build accurate, compliant audience strategies, talk to our team.