Lookalike modeling analyzes the attributes of your best customers and finds new prospects that share those same characteristics. You define a seed audience (your top 100 accounts, your fastest-closing deals, your lowest-churn customers), and the model identifies companies in the broader market that look similar based on firmographic, technographic, and behavioral data.
Why It Matters
Your best customers share patterns you might not see intuitively. Maybe they're all between 150-400 employees, use Salesforce, and hired a RevOps person in the last year. Lookalike modeling surfaces these patterns and finds thousands of companies that match. Instead of guessing who to target, you're targeting companies that statistically resemble the ones already paying you.
How Lookalike Modeling Works
- Seed audience creation: Define your best customers based on LTV, deal size, retention rate, or other success metrics
- Feature extraction: Identify the attributes your seed audience shares: company size, industry, tech stack, growth rate, funding stage
- Pattern detection: Statistical models find which combinations of attributes are most predictive of customer success
- Prospect scoring: Score every company in the addressable market on how closely they resemble the seed audience
- List delivery: Deliver a ranked list of lookalike prospects with enriched contact data ready for outreach
Example
A company's 50 best customers are all B2B SaaS, 100-500 employees, using HubSpot, and growing headcount by 20%+ year-over-year. The lookalike model scans 200,000 companies and finds 3,200 that match all four criteria. The sales team starts prospecting into a list where every account already looks like a great customer.
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