benchmarks/lookalikes/b2b lookalike audiences
lookalike benchmark · audiences vs lists

B2B lookalike audiences

“Lookalike audience” means two different things. Ad-platform lookalike audiences(Meta, LinkedIn, Google) are built inside the ad platform and can't be independently measured from outside. A B2B lookalike company list — accounts like your best customers, for outbound and ABM — can. This is an independent benchmark of company lookalike / similar-companies APIs — Exa, Ocean.io, Parallel, PredictLeads, Extruct, CUFinder, and Discolike — ranked on how relevant the companies each one returns actually are, across 48 B2B seed companies.

Benchmark evidence and per-seed audit trail

Same seed companies, same judge panel, Precision@10 and Precision@100 where each endpoint supports that depth — plus the per-seed matrix so you can inspect how each vendor behaved on each company.

long listPrecision@100: how relevant a vendor stays a hundred companies deep. The metric for lists that feed automated sequences. 3 vendors cannot appear here: their endpoint returns fewer than 100 results.
Long-list lookalike quality: aggregate Precision@100 by company lookalike API vendor
RankVendorPrecision@100Avg latencyRelevant / $1 at 100
1Extruct61.1%2,361 ms624
2Ocean.io59.5%2,444 ms37
3Parallel56.9%2,680 ms11,383
4Exa48.6%3,014 ms501
5Discolike34.6%1,164 ms66
short listPrecision@10: how relevant the top of the list is. The metric that matters when a person works the results by hand and only the first few rows get touched. Every measured vendor appears here, and the only question asked of them is whether the companies are right.
Short-list lookalike quality: aggregate Precision@10 by company lookalike API vendor
RankVendorPrecision@10
1PredictLeads89.8%
2Exa80.8%
3Extruct75.0%
4Ocean.io74.3%
5Parallel69.2%
6ZoomInfo67.1%
7Discolike41.9%
8CUFinder38.9%
benchmarks/lookalike/lookalike-2026-q348 examples · 8 vendors
audit viewcell = Precision@100; the small label shows P@10N/Avendor not yet run (or returned fewer than K results)click any scored cell to view the companies that vendor returned
#Company typeOcean.ioExaParallelPredictLeadsExtructCUFinderDiscolikeZoomInfo
01Corporate spend management platforms for companies that offer any of corporate cards, expense management, travel booking, or bill payFintechseed exampleBrexbrex.com
02Cloud observability and monitoring platforms that offer any of application performance monitoring, log management, security monitoring, or synthetic monitoringDevtoolsseed exampleDatadogdatadoghq.com
03Global logistics and transportation companies that offer any of parcel delivery, freight, shipping, or supply-chain servicesLogisticsseed exampleFedExfedex.comN/A
04Global hospitality companies that offer any of hotel, lodging, travel, or guest loyaltyHospitalityseed exampleMarriottmarriott.com
05Commercial real estate services and investment firms that offer any of property leasing, facilities, valuation, or asset managementReal Estateseed exampleCBREcbre.com

Full routing by workflow, latency, cost, and methodology: the lookalike benchmark →

B2B lookalike audiences — common questions

What is a B2B lookalike audience?

The term means two different things. In advertising, a lookalike audience is a set of ad-platform users (Meta, LinkedIn, Google) that the platform's own model builds from a seed list, for ad targeting only. In B2B sales, a 'lookalike audience' usually means a lookalike company list — accounts that resemble your best customers, used for outbound, ABM, and territory building. Different products, different vendors, differently measurable.

What is the best tool to create a lookalike audience from a customer list?

If you mean ad audiences: upload your list to Meta or LinkedIn — the matching happens inside the ad platform and its quality isn't independently measurable from outside. If you mean a B2B lookalike company list from your customers, that is measurable, and measured: Extruct currently leads on long-list relevance (Precision@100 61.1%), PredictLeads on top-of-list precision (Precision@10 89.8%) — on identical seed companies, scored by a three-model LLM judge panel.

How do I build a lookalike audience from closed-won customers?

Pick your strongest, fastest-closing customers as seeds (a clean short list beats a large messy one), feed them to a lookalike tool, and get back ranked similar companies. For ads, upload the resulting list to the ad platform as a matched/seed audience. The step-by-step version for outbound is the closed-won lookalike play.

Can I use these lookalike lists for ad targeting?

Yes — a measured lookalike company list can be uploaded to LinkedIn (company list matched audiences) or converted to contacts for Meta. Note the split honestly: the list quality here is measured; what the ad platform's own matching does with it afterward is not.