The fastest way to find similar companies: list your best customers in a column, run a lookalike enrichment on their names or domains, and let the matches land in the next column. That’s the whole trick. In this guide, I’ll show you the free research methods first (because they’re genuinely useful) and then the Google Sheets workflow I use when I need a full account list, not five names.
I’m going to be honest with you. In 2022 I spent three evenings googling “companies like” our twelve best customers. It did not go well. I’ll tell you exactly how it went in a minute.
Let’s get into it.
📌 TL;DR: Three ways to find similar companies: (1) free research: mine your CRM, read 10-K competition sections, filter by industry code; (2) competitor mapping: a lookalike search seeded with ONE company; (3) the bulk route, a lookalike enrichment in Google Sheets: input column of customer names or domains, output column of similar companies, one run.
What Counts as a “Similar Company”?
A similar company matches another on industry, size, market, and how it makes money. Not one of those. All four, roughly at once, because two 50-person software companies are NOT similar if one sells to hospitals and the other sells to gamers.
So when I score similarity, I look at four axes:
- What they sell: the industry and product category.
- How big they are: headcount and revenue band.
- Who they sell to: mid-market logistics buyers vs enterprise banks.
- How they make money: subscriptions, services, transactions.
Those four axes are really just firmographic data: the company-level facts like industry, size, and revenue that databases store about every business. And if you’ve ever written down an Ideal Customer Profile, you already have your similarity template. A lookalike list is your ICP with names attached.
Why does this matter for sales? Because your next best customer probably looks like your current best customer. I’ve written a full methods guide on how to find similar companies for prospecting and TAM work. This page is the hands-on spreadsheet version of that idea.
One quick disambiguation before we go on. If you want websites that look like a given site (same layout, same content type), that’s a “find similar websites” tool, and it’s a completely different job. We’re matching companies here, not web pages.
Now, do you even need a tool? Sometimes no. Let’s check the free routes first.
How Do You Find Similar Companies for Free?
Mine your own customer list, read public filings, or ask an AI, then verify everything. Each free method works. Each has a ceiling. Here’s the honest version of all three.
Start Inside Your Own CRM
Sort your won deals by revenue and retention. Then stare at the top ten and name the pattern out loud: “mid-market logistics companies in the DACH region with in-house fleets.” That sentence is your search query for everything that follows.
Interestingly, this is also what working salespeople recommend. The r/sales thread on finding similar companies, which ranks near the top of Google for this exact question, keeps coming back to the same advice: start from your existing clients, not from a blank search box.
Let Companies Tell You Who They Resemble
Here’s my favorite free trick. Public companies are required to describe their competition in their annual 10-K filings. And you can search those filings for free with EDGAR full-text search: type a company name, open the 10-K, and read the “Competition” section. The company literally hands you its own lookalike list.
For industry filtering, use NAICS codes, the U.S. industry classification system. A NAICS code turns “similar industry” from a feeling into a filter: every company in 493110 is a warehousing and storage company, full stop.
🔍 Did You Know? Public companies must describe their competitive landscape in their 10-K filings, and EDGAR's full-text search makes those sections free to mine. It's the closest thing to a company writing its own lookalike list.
Ask ChatGPT, With Your Eyes Open
Can ChatGPT find similar companies? Yes, as a brainstorm. I use it to widen my thinking: “list 20 European companies similar to Hansel Logistics.” But I’ve caught it recommending companies that shut down years ago, companies 100x the wrong size, and once (my favorite) a company that never existed at all.
So treat AI output as leads for research, never as a list for outreach. Verify every name before it earns a row in your sheet.
The free methods top out around 20-40 solid names. Useful. But before we scale that up, let’s handle the question that usually hides inside this one.
How Do You Find a Company’s Competitors?
Start from the company itself: its industry code, its filings, and the alternatives its customers evaluate. Because here’s the reframe that makes this easy: a competitor search is just a lookalike search seeded with ONE company instead of ten.
Business schools sort competitors into four types, and the list is worth keeping:
- Direct: same product, same buyer.
- Indirect: different product, same problem.
- Replacement: a different way to make the problem go away entirely.
- Potential: adjacent players one pivot away from your market.
In a spreadsheet, competitor mapping looks like this: put the one company in cell A2, run a lookalike search on it, and then sort the output by hand into “competes with us” vs “just similar.” The sorting is judgment work. No tool does it for you, and honestly, that’s fine. The judgment is the valuable part.
And if you need the full research treatment (review mining, ad libraries, job postings), I’ve covered six methods in my guide to how to find a company’s competitors. For this page, the spreadsheet route continues.
How Do You Build a Lookalike List in Google Sheets?
Install the add-on, pick the lookalike service, point it at your customer column, and run your rows. That’s the loop. Step by step:
- Install the add-on. Grab the CUFinder add-on from the Google Workspace Marketplace. New to add-ons? Google’s help page explains how they install and where they live.
- Copy your API key. Head to your CUFinder dashboard and copy the API key from there.
- Enter the key in the add-on. Paste it once and you’re connected.
- Pick the lookalike service. Open the add-on from the Google Sheets menu. It opens as a right panel listing all the enrichment services. Choose Find Company Lookalikes, which takes a company name or domain and returns similar companies.
- Map columns, set the range, run. Set the input column (your customer names or domains), the output column (where the lookalikes should land), and the row range (rows 2-11, say, for ten seed customers). Then run it.
Now, the part nobody tells you: the seeds decide everything. Feed the tool your 5-10 BEST customers, not all of them. Average seeds produce average lookalikes, and “best” has a definition. Highest revenue, longest retention, shortest sales cycle. If a customer churned in month three, they don’t get to be a seed.
💡 Pro Tip: Run rows 2-3 as a test batch first. Check that the output looks like your ICP, confirm the columns are mapped right, THEN run the full seed list. Two test rows have saved me from enriching the wrong column more than once.
One honest expectation: what comes back is a candidate list, not a qualified list. The matches are firmographic: right industry, right size, right market. Whether they have budget this quarter is your job to find out. Score them before anyone calls them.
And the lookalike column is only step one. In the same sheet, you can then run company enrichment on the new names to pull industries and headcounts, grab their websites via a name-and-domain conversion, or find their LinkedIn pages in bulk for account research.
A Worked Example: 5 Rows, Before and After
Say your seed sheet looks like this, with best customers in column A, their domains in column B, and an empty column C waiting for lookalikes:
| A | B | C | |
|---|---|---|---|
| 1 | Customer | Domain | Lookalike Companies |
| 2 | Hansel Logistics | hansellogistics.com | |
| 3 | Bluepine Software | bluepinesoftware.com | |
| 4 | Corvid Analytics | corvidanalytics.com | |
| 5 | Marlow & Sons | marlowandsons.com | |
| 6 | Tidewater Robotics | tidewaterrobotics.com |
Then I ran the add-on: Find Company Lookalikes, input column B, output column C, rows 2 to 6. A minute later, the same sheet looked like this:
| A | B | C | |
|---|---|---|---|
| 1 | Customer | Domain | Lookalike Companies |
| 2 | Hansel Logistics | hansellogistics.com | Nordwind Freight, Cargoline Express, Vektor Haulage |
| 3 | Bluepine Software | bluepinesoftware.com | Cedarcode Systems, Graystack Labs, Fernwood Apps |
| 4 | Corvid Analytics | corvidanalytics.com | Larkfield Data, Quillmetrics, Ostrova Insights |
| 5 | Marlow & Sons | marlowandsons.com | Beckett Provisions, Harrow Trading, Ansel & Vine |
| 6 | Tidewater Robotics | tidewaterrobotics.com | Westbay Automation, Ironreef Systems, Calder Robotics |
Five seeds in, fifteen candidates out, and a real run with ten seeds returns far more per row. From there, my routine is always the same. Split the names into their own rows. Deduplicate. Score against the ICP. Then enrich.
→ 10 seed customers → one run → dozens of candidates → scored and deduped → next quarter’s account list, before lunch.
That’s the workflow that replaced my three evenings of googling. In 2022, my manual hunt produced about 40 names, and half of them turned out to be subsidiaries, resellers, or companies 10x the wrong size. A subsidiary is a special kind of trap, by the way: it looks similar because it IS related, which is a different thing entirely. (Corporate family trees are their own job: that’s the find company subsidiaries workflow.)
📌 Example: My 2022 territory rebuild: 12 seed customers → one lookalike run → filtered to ~260 ICP-fit accounts → 9 discovery meetings booked in the next six weeks. The three evenings of googling had produced 40 names, half of them wrong.
What Mistakes Should You Avoid When Building Lookalike Lists?
The big ones: weak seeds, size-only matching, skipping the scoring pass, and prospecting your own customers. I’ve made most of these personally, so consider this a scar map.
- Seeding with every customer. Your churned accounts and bad-fit deals drag the profile toward “average.” Seed with the best 5-10 only.
- Matching on size alone. Same headcount does not mean same buyer. A 200-person agency and a 200-person manufacturer share almost nothing.
- Skipping the scoring pass. Candidates are not qualified accounts. A quick ICP scoring pass (even a 1-5 fit column you fill by hand) separates the “call Monday” accounts from the “maybe someday” pile.
- Not deduplicating against your CRM. Nothing embarrasses a sales team like “prospecting” an existing customer. Run deduplication against current accounts AND open opportunities before anyone dials.
- Treating the list as outreach-ready. A company name is not a contact. Real B2B prospecting still needs people, titles, and verified emails on top of the account list. And when you’d rather start from people than firms, lookalike prospecting runs this same seed-and-match play at the contact level.
- Never refreshing. Companies pivot, merge, and die. A lookalike list from last year describes last year’s market. Re-run it quarterly. It’s one run.
Get those six right, and the lookalike run becomes the most reliable list-building play I know. Still with me? Good. Quick answers to the questions people actually ask.
FAQ: Finding Similar Companies
How do you search for similar companies?
Start from a company you know, then match on industry, size, market, and business model. Free routes: your CRM, 10-K filings, NAICS codes. Bulk route: a lookalike enrichment run on a column of names or domains.
How do you find lookalike companies?
Feed your best customers into a similar company finder and score what comes back against your ICP. The seeds matter more than the tool: great seeds in, great lookalikes out.
Can ChatGPT find lookalike companies?
Yes, as a brainstorm, and no, not as a source of truth. It suggests plausible names but also returns defunct, wrong-size, and occasionally invented companies. Verify every suggestion against a live database before it enters your outreach list.
What is lookalike marketing?
Lookalike marketing targets new audiences that statistically resemble your existing customers. The term comes from ad platforms’ lookalike audiences. B2B lookalike lists apply the same idea at the company level: accounts that resemble your best accounts.
What are the 4 types of competitors?
Direct, indirect, replacement, and potential. Direct rivals sell the same product to the same buyer; indirect ones solve the same problem differently; replacements remove the problem; potential competitors sit one pivot away from your market.
How do you compare two companies in the same industry?
Line up their firmographics side by side: headcount, revenue band, target market, business model, and geography. Two columns in a sheet make the comparison honest. Gut feel alone tends to overweight whichever company you saw first.
Is there a free similar company finder?
Free methods exist (CRM mining, EDGAR filings, NAICS filters), and most tools, CUFinder included, offer free credits to start. At bulk scale, lookalike lookups cost money on every platform; the free routes cost time instead.
It’s Time to Fill Column C With Your Next Customers
You’ve got the whole toolkit now. Free research for depth. Competitor mapping when one company is the question. And a lookalike run in Google Sheets when you need a real account list by Friday.
Picture it: Monday morning, ten best customers pasted into column A, one run, and a quarter’s worth of accounts scoring themselves into shape while your coffee is still hot. That’s my actual Monday routine now. It can be yours.
And lookalikes are just one column of the story. The whole data enrichment in Google Sheets hub covers what to add next: websites, revenue, tech stacks, all of it. Tell me in the comments: which customer would YOU clone first?
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