---
title: "B2B lookalike audiences (2026): ad audiences vs company lists | Openbenchmarks"
description: "B2B lookalike audiences: Meta/LinkedIn ad audiences vs lookalike company lists from your customer list. What each is for, and independently measured tools."
url: https://openbenchmarks.com/lookalikes/b2b-lookalike-audiences
---

[](https://openbenchmarks.com/) 

[← lookalike benchmark](https://openbenchmarks.com/lookalikes) 

[benchmarks](https://openbenchmarks.com/) / [lookalikes](https://openbenchmarks.com/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 — Ocean.io, Exa, Parallel, Seltz, PredictLeads, Extruct, CUFinder, Discolike, and ZoomInfo — ranked on how relevant the companies each one returns actually are, across 48 B2B seed companies.

\[01\] evidence

## 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 list Precision@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__
| Rank | Vendor | Precision@100 | Avg latency | Relevant / $1 at 100 |
| --- | --- | --- | --- | --- |
| 1 | [Seltz](https://seltz.ai "Open Seltz in a new tab") | 63.4% | 4,835 ms | 12,683 |
| 2 | [Extruct](https://www.extruct.ai "Open Extruct in a new tab") | 61.1% | 2,361 ms | 624 |
| 3 | [Ocean.io](https://www.ocean.io "Open Ocean.io in a new tab") | 59.5% | 2,444 ms | 37 |
| 4 | [Parallel](https://parallel.ai "Open Parallel in a new tab") | 56.9% | 2,680 ms | 11,383 |
| 5 | [Exa](https://exa.ai "Open Exa in a new tab") | 48.6% | 3,014 ms | 501 |
| 6 | [Discolike](https://discolike.com "Open Discolike in a new tab") | 34.6% | 1,164 ms | 66 |

short list Precision@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__
| Rank | Vendor | Precision@10 |
| --- | --- | --- |
| 1 | [PredictLeads](https://predictleads.com "Open PredictLeads in a new tab") | 89.8% |
| 2 | [Seltz](https://seltz.ai "Open Seltz in a new tab") | 84.4% |
| 3 | [Exa](https://exa.ai "Open Exa in a new tab") | 80.8% |
| 4 | [Extruct](https://www.extruct.ai "Open Extruct in a new tab") | 75.0% |
| 5 | [Ocean.io](https://www.ocean.io "Open Ocean.io in a new tab") | 74.3% |
| 6 | [Parallel](https://parallel.ai "Open Parallel in a new tab") | 69.2% |
| 7 | [ZoomInfo](https://gtm.ai "Open ZoomInfo in a new tab") | 67.1% |
| 8 | [Discolike](https://discolike.com "Open Discolike in a new tab") | 41.9% |
| 9 | [CUFinder](https://cufinder.io "Open CUFinder in a new tab") | 38.9% |

benchmarks/lookalike/lookalike-2026-q3 48 examples · 9 vendors 

audit view cell = Precision@100; the small label shows P@10 N/Avendor not yet run (or returned fewer than K results) click any scored cell to view the companies that vendor returned 

| # | Company type | [ Ocean.io ](https://www.ocean.io "Open Ocean.io in a new tab") | [ Exa ](https://exa.ai "Open Exa in a new tab") | [ Parallel ](https://parallel.ai "Open Parallel in a new tab") | [ Seltz ](https://seltz.ai "Open Seltz in a new tab") | [ PredictLeads ](https://predictleads.com "Open PredictLeads in a new tab") | [ Extruct ](https://www.extruct.ai "Open Extruct in a new tab") | [ CUFinder ](https://cufinder.io "Open CUFinder in a new tab") | [ Discolike ](https://discolike.com "Open Discolike in a new tab") | [ ZoomInfo ](https://gtm.ai "Open ZoomInfo in a new tab") |
| -- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 01 | [Cloud observability and monitoring platforms that offer any of application performance monitoring, log management, security monitoring, or synthetic monitoring Devtools seed example Datadog datadoghq.com ](https://datadoghq.com "Open Datadog in a new tab") | 68% P10 100% view | 69% P10 100% view | 93% P10 100% view | 63% P10 100% view | N/A P10 100% view | 81% P10 100% view | N/A P10 10% view | 33% P10 60% view | N/A P10 50% view |
| 02 | [Restaurant point-of-sale platforms that offer any of payments, online ordering, payroll, or inventory management Hospitality seed example Toast toasttab.com ](https://toasttab.com "Open Toast in a new tab") | 89% P10 100% view | 47% P10 60% view | 45% P10 80% view | 68% P10 100% view | N/A P10 100% view | 92% P10 100% view | N/A P10 20% view | 81% P10 50% view | N/A P10 70% view |
| 03 | [Plumbing and drain services companies that offer any of plumbing, drain cleaning, water cleanup, or home services Home Services SaaS / Chains seed example Roto-Rooter rotorooter.com ](https://rotorooter.com "Open Roto-Rooter in a new tab") | 90% P10 50% view | 86% P10 100% view | 95% P10 70% view | 91% P10 100% view | N/A P10 100% view | 90% P10 80% view | N/A P10 60% view | 86% P10 70% view | N/A P10 70% view |
| 04 | [Construction management software that offer any of project management, financials, quality, safety, or contractors B2B SaaS seed example Procore procore.com ](https://procore.com "Open Procore in a new tab") | 90% P10 100% view | 62% P10 100% view | 83% P10 90% view | 88% P10 100% view | N/A P10 100% view | 79% P10 90% view | N/A P10 60% view | 67% P10 70% view | N/A P10 90% view |
| 05 | [On-demand consumer super-apps that offer any of ride-hailing, delivery, payments, financial services, or merchant services Logistics seed example Grab grab.com ](https://grab.com "Open Grab in a new tab") | 37% P10 40% view | 47% P10 100% view | 35% P10 70% view | 19% P10 90% view | N/A P10 100% view | 71% P10 80% view | N/A P10 20% view | 33% P10 30% view | N/A P10 50% view |

Full routing by workflow, latency, cost, and methodology: [the lookalike benchmark →](https://openbenchmarks.com/lookalikes) 

\[02\] faq

## 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: Seltz currently leads on long-list relevance (Precision@100 63.4%), 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.

Openbenchmarks [← lookalike benchmark](https://openbenchmarks.com/lookalikes) [closed-won lookalike play](https://openbenchmarks.com/lookalikes/closed-won-lookalike-play) [best lookalike company finders](https://openbenchmarks.com/lookalikes/best-lookalike-company-finder-tools) [source ↗](https://github.com/openbenchmarks-labs/lookalikes) © 2026 Openbenchmarks