Top 5

Top 5 Lookalike Audience Tools for B2B

You have a list of companies that almost bought. They fit well enough to reach your pipeline, and now you want more companies just like them. These five tools take a seed list of accounts and return lookalikes. They differ most in one thing: how deep they look before they call two companies similar.

Updated

1. CompanyEnrich 2. DiscoLike 3. Ocean.io 4. GraphIQ.ai 5. Clay

Why Lookalike Lists Go Wrong

Building a lookalike list sounds simple: give a tool your best-fit accounts, get back more like them. The trouble is what "like them" means. Many tools compare a short company description, an industry tag and an employee count. On those fields, a payroll startup and a payments infrastructure company can look like twins.

The fit that actually predicts a deal is usually more specific. It's the capability the company sells, the data it consumes, the stack it runs on. So when you compare tools, ask what they match on before you ask how big their database is. The table below puts that first.

Quick Comparison

Tool Matches on Seed input Pricing API / agents
1. CompanyEnrich Business model, industry, tech stack, market context Domain, company name or CompanyEnrich ID Credits, deducted only when matches come back REST API
2. DiscoLike Website text, ICP description, homepage phrases, technographics Lookalike domains or a plain-English ICP Self-serve app from $99/month; bulk datasets sold separately API, Python SDK, CLI, MCP
3. Ocean.io Contextual fit against segments learned from your CRM CRM data (Salesforce, HubSpot) or a seed list Premium, the highest of the five Clay, no-code workflows, AI agents
4. GraphIQ.ai Digital fingerprint, with capabilities you can toggle on and off Best customers or a seed account list Per entity under watch; unlimited seats, no credit expiry MCP server, native HubSpot
5. Clay Industry, headcount, funding stage, tech stack, hiring activity Company LinkedIn URLs or a list of seed companies Lookalike search included; enrichment uses Clay credits Clay tables and integrations

Details are taken from each vendor's own product pages as of October 8, 2026. Pricing changes often, so check the vendor's site before you commit.

1. CompanyEnrich

Best API for building your own pipeline

Matches on: Business model, industry, tech stack, market context

CompanyEnrich's Similar Companies API takes one company and returns its closest lookalikes from a database of over 33 million companies. It matches on business model, market context and core offerings, so it suits teams who want lookalikes inside their own scripts, CRM jobs or product rather than in another app.

What it does

  • Returns the top 10 matches by default (adjustable with a limit), each with a 0 to 1 similarity score
  • Every match comes with a full company profile of 60+ data points, so there's no second enrichment pass
  • Filter results by geography, company size, NAICS codes and keywords
  • Set a minScore threshold to drop weak matches before they reach your list
  • Also used for competitor discovery, TAM sizing and in-app "similar companies" widgets

Watch out for

  • It's an API first, so someone has to write the loop that runs each closed-lost account through it
  • One seed company per call: you merge and dedupe the results across your list yourself

Best for

Teams with a developer or an automation tool who want lookalikes scored and enriched in one call.

Visit CompanyEnrich →

2. DiscoLike

Best for matching on what a company actually says

Matches on: Website text, ICP description, homepage phrases, technographics

DiscoLike builds its own index instead of reselling scraped feeds. It crawls over 1 billion business web pages a month, covering more than 82 million companies in 55 languages. Because matching runs on website content, it can catch the specific capabilities that a one-line industry tag misses.

What it does

  • Search by lookalike domain, a natural-language ICP, exact homepage phrases, or tech stack
  • Finds and verifies contact emails from the open web for the companies it returns
  • Works from coding and sales agents through its API, Python SDK, CLI and MCP server
  • Nine flat-file datasets (firmographics, site text, SSL certificate history and more) delivered as JSON, CSV or S3
  • Built for TAM mapping, list validation and segment expansion

Watch out for

  • Website-based matching is only as good as the seed companies' websites; thin or vague sites give weak signals
  • Bulk datasets are a separate purchase from the $99 self-serve app

Best for

Niche B2B markets where the real fit lives in what a company sells, not in its industry code.

Visit DiscoLike →

3. Ocean.io

Most thorough, priced like it

Matches on: Contextual fit against segments learned from your CRM

Ocean.io learns your ideal customer profile from the deals already in your CRM, then finds and ranks lookalike accounts against it. It's the most complete option here for teams that want the tool to do the segmentation work, and it sits at the top of the price range.

What it does

  • Connects to Salesforce or HubSpot and analyzes win rates, deal sizes and close times to find your strongest segments
  • Scores every lookalike account against that segment so reps work the best matches first
  • Researches target websites to answer specific questions, such as tech stack, compliance, funding or leadership changes
  • Shows which roles were involved in past deals, so you know who to contact at each lookalike
  • Pushes ranked lists into Salesforce, HubSpot, Clay and agent workflows; GDPR compliant and SOC 2 Type II certified

Watch out for

  • The CRM learning is built around closed-won deals, so a closed-lost seed list needs to be uploaded and framed deliberately
  • Expensive next to the other four; hard to justify for a one-off list

Best for

Revenue teams with real CRM history and the budget for an ongoing account-scoring program.

Visit Ocean.io →

4. GraphIQ.ai

Best for curating the match by hand

Matches on: Digital fingerprint, with capabilities you can toggle on and off

GraphIQ is a B2B identity graph: companies, people, corporate hierarchies, technographics and market signals stored as relationships rather than rows. Its lookalike search uses digital fingerprint matching, and you can select or deselect specific capabilities to steer which accounts come back.

What it does

  • Covers 287 million organizations, 393 million employees and over 2 billion news and operational events
  • Maps parent and subsidiary relationships, so a lookalike isn't just another branch of a company you already lost
  • Unifies and dedupes fragmented CRM records before you build on them
  • AI agents such as Claude or ChatGPT can query the graph directly through its MCP server
  • Native HubSpot integration; a Salesforce connector is in development

Watch out for

  • No Salesforce connector yet, so Salesforce shops will be exporting and importing for now
  • Per-entity pricing rewards a focused watch list, not a huge one-time pull

Best for

HubSpot teams who want to say exactly which capabilities make a company a match.

Visit GraphIQ.ai →

5. Clay

Best free starting point

Matches on: Industry, headcount, funding stage, tech stack, hiring activity

Clay's Find Companies search has a built-in lookalike field. Paste in your closed-lost companies, preview the matches, refine, then pull them into a Clay table where the rest of your enrichment already runs. It's the quickest way to see whether a lookalike list is worth paying for.

What it does

  • Lookalike field at the top of Find Companies: add seed companies, preview, refine, import
  • Matches land in a Clay table, ready for email finding and other enrichment columns
  • An Ocean.io integration is available inside Clay for finer filters on industry, size, technologies, geography and revenue
  • Waterfall enrichment to find a verified contact at each matched company

Watch out for

  • The default lookalike leans on firmographics, so it can miss the nuanced fit a website-based tool catches
  • Free to search, but the enrichment you'll want afterwards spends credits

Best for

Anyone who already lives in Clay, or wants a free first pass before buying a dedicated tool.

Visit Clay →

Also Worth a Look

  • Apollo.io: strong company search, though exporting at volume is harder than searching.
  • Leadsforge: AI lead generation from an ICP description.
  • Tomba.io: email finding once you have the lookalike domains.

Which One Should You Pick?

  • You want to test the idea for free: Clay. Paste in your closed-lost companies and judge the matches before you spend anything.
  • The matches keep coming back too generic: DiscoLike, which matches on website content, or GraphIQ, where you switch specific capabilities on and off.
  • You want lookalikes inside your own code or product: the CompanyEnrich Similar Companies API, with scores and full profiles in one call.
  • You want an ongoing, CRM-driven account-scoring program: Ocean.io, if the budget is there.

Whichever you choose, clean the seed list first. Keep the deals you lost on price, timing or a competitor, drop the ones lost to a reorg or a budget freeze, and split the rest by segment. A tight seed list matters more than the tool.

Got your lookalike list in a spreadsheet? SuperEnrich fills in company details, LinkedIn profiles and verified emails for every row, right inside Google Sheets, using your own API keys. To size up who each lookalike competes with, see Find Company Competitors in Google Sheets.

Frequently Asked Questions

Why build a lookalike list from closed-lost companies? ▾
A closed-lost company got far enough into your pipeline to be a real opportunity. It had the problem, the budget conversation happened, and a rep thought it was worth the time. That makes your lost deals a cleaner fit signal than a cold ICP guess. A lookalike list built from them finds more companies in that same shape, which you can then work with a sharper pitch than the one that lost.
Why are so many lookalike results a poor match? ▾
Most lookalike tools compare short company descriptions, industry codes and headcount. Two 200-person SaaS companies can look identical on those fields and buy completely differently. The fit usually lives in specifics: what the product actually does, the data it consumes, the tools it runs. Tools that read website content (DiscoLike) or let you toggle capabilities (GraphIQ) get closer to that than firmographic-only matching.
How many seed companies do I need? ▾
Enough to show a pattern. Ten to twenty closed-lost accounts that share a segment usually beats a hundred mixed ones, because a mixed seed list averages out to a generic match. If your lost deals span several segments, split them and run a lookalike search per segment.
Should I filter the closed-lost list first? ▾
Yes. Drop deals lost for reasons that say nothing about fit, like a champion leaving or a budget freeze, and keep the ones that were a good fit but lost on price, timing or a competitor. Also remove the lost companies themselves from the output, along with their subsidiaries, so you aren't re-prospecting accounts that already said no.
Which tool should I try first? ▾
If you already use Clay, start with its free lookalike search and see whether the matches look right. If they come back too generic, move to DiscoLike or GraphIQ for capability-level matching. If you want lookalikes inside your own code or product, use the CompanyEnrich API. Ocean.io is the pick when you want a full account-scoring program and have the budget.

Need Help Building the List?

Tell us what your closed-lost accounts have in common. We'll help you turn them into an enriched target list.

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