Find more prospects
like your best customers. Pay per profile.
Lookalike Enrich builds a statistical profile of your best existing customers — firmographic, demographic, and technographic attributes — then finds prospects in the broader universe whose enriched attributes closely match. The result is an audience you push to ad platforms for paid acquisition or hand to sales as an outbound list. Billed per matched profile. No subscription, no seat license.
Built for teams that already know who their best customers are.
The best acquisition signal you have is the customers already converting and retaining. Four ways teams turn that into a repeatable top-of-funnel input.
Scale paid acquisition beyond manually built segments.
Upload your highest-LTV customer list as the seed. Lookalike Enrich enriches each record with firmographic and technographic attributes, builds a statistical profile, and returns a ranked audience from the broader prospect pool. Push it to your ad platform and acquire at scale — without rebuilding the targeting logic from scratch each quarter.
Outbound lists that look like customers, not guesses.
Instead of buying a list filtered by job title and geography, start from who actually converts. Enrich your best customers, find prospects with matching firmographic and technographic profiles, and hand BDRs a list where every name resembles a proven buyer — not a demographic approximation.
Model quality starts with consistent enrichment.
A lookalike model is only as good as the attributes on both sides. Sparse or mismatched enrichment between the seed and the prospect pool weakens the match. Lookalike Enrich applies the same attribute set to both — so the comparison is apples to apples and the model has a fair signal to work from.
Embed lookalike expansion in your acquisition workflow.
Drop Lookalike Enrich into a pipeline that runs whenever your customer base crosses a milestone — a new vertical, a funding round, a product launch. Each time, the model retrains on the updated seed and returns a fresh audience. Acquisition targeting stays current without a manual rebuild.
Stop building lists from scratch.
Upload your seed, and your first matched audience lands in minutes. If you don't run a model for a month, you don't pay for the month. That's the entire deal.
- Charged only on a matched profile
- No seat license required
The honest answers.
If something below doesn't cover your case, ping us — we answer directly, no SDR funnel.
What does "pay per profile" actually mean?
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You're billed once per prospect profile returned in the matched audience. If a prospect can't be enriched or doesn't meet the similarity threshold, it doesn't appear in the output and you're not charged for it. No monthly floor, no minimum list size.
What attributes are used to build the lookalike model?
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Firmographic: industry, employee headcount, revenue band, funding stage, HQ location, headcount growth. Demographic: job title, seniority, department. Technographic: installed tools, platform categories, and competitive products in use. The same attribute set is applied to both the seed and the prospect pool so the comparison is consistent.
How large does my seed need to be?
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Larger seeds produce more stable models — 200 to 500 records is a solid starting point. Smaller seeds (50–100) still work but produce narrower audiences. Very small seeds (under 30) will return results but with lower confidence; we flag this in the response.
Where can I push the output audience?
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The API returns a ranked list of matched profiles with enriched attributes. You can push it directly to an ad platform via their audience API, load it into your CRM, route it to a sequencing tool, or hand it to BDRs as a prioritized outbound list. The output format is yours to route.
Why does enrichment consistency between seed and prospect pool matter?
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A lookalike model compares attribute vectors. If the seed is enriched with 40 fields but the prospect pool only has 15 populated, the model compares apples to oranges — similarity scores become unreliable. Lookalike Enrich applies the same enrichment pipeline to both sides, so the comparison is meaningful.
How is this different from Facebook or LinkedIn lookalike audiences?
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Ad platform lookalikes are black-box models trained on platform engagement signals you can't inspect or export. Lookalike Enrich is built on explicit firmographic, demographic, and technographic attributes — you see exactly what the model is matching on, the output is yours to use anywhere, and you're billed per profile rather than locked into platform ad spend.
What's the rate limit?
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100 RPS per key by default; we'll lift it on request. Lookalike runs are typically batch jobs, so throughput limits rarely apply — but large prospect-pool enrichment passes benefit from the higher ceiling.