Company enrichment in Google Sheets means an add-on fills firmographic columns (industry, size, revenue, location) from a company name or domain column. You keep the list where it already lives, and the empty cells fill themselves. In this guide, I’ll show you the routes that don’t need an add-on first, then the walkthrough I use for real lists.
I’m going to be honest with you. I once “enriched” 1,200 CRM accounts with two interns and a week of copy-paste. It technically worked. It also ruined every report we built on top of it. I’ll tell you exactly how in a minute.
Let’s get into it.
📌 TL;DR: Three ways to enrich company data in a spreadsheet: (1) research each company by hand (honest but 5-10 minutes per row); (2) VLOOKUP against a dataset you already own (real, fast, and only as good as that dataset); (3) run a company enrichment add-on: input column of names or domains, output columns of industry, size, revenue and more, row range like 2-1200, one run.
What Is Company Enrichment?
Company enrichment adds the missing fields (industry, size, revenue, location, socials) to company records you already have. You bring a bare list of names or domains. Enrichment turns each row into a profile.
What fields are we talking about? The usual set looks like this:
- Industry and category
- Employee count
- Annual revenue
- HQ location and country
- Website and LinkedIn URL
- Phone number
- Founded year and tech stack
Together, those fields are called firmographic data: demographics, but for companies. It’s the company-side twin of contact enrichment, and it’s what turns “a list of names” into something you can segment, score, and route.
What do you actually DO with those fields? Three things, mostly. You segment: “software companies, 50-500 people, DACH region” becomes a filter instead of a guess. You prioritize: size and revenue decide which accounts deserve a human touch. And you route: territory and industry rules only work when every row carries the same labels.
And why do this in a spreadsheet? Simple. That’s where the list already lives. Every event export, every scraped directory, every “can you check these accounts?” request arrives as rows and columns. Company enrichment in Google Sheets writes the answers into those same rows: no exporting, no re-importing, no tab-juggling.
But maybe you don’t need a tool at all. Let’s be fair to the alternatives first.
How Can You Enrich Company Data Without an Add-On?
Three real options: manual research, VLOOKUP against a dataset you own, or an AI-and-scraper workflow. Each works. Each has a ceiling worth knowing before you commit a week to it.
Manual Research
Open each company’s site and LinkedIn page, read, type what you find. It’s honest work and the data is usually right, on the day you type it. But do the math with me: 5-10 minutes per row, times 1,200 rows. That’s the intern-week from my confession. And here’s what nobody warns you about: two people typing industries by hand will produce “SaaS”, “Software”, “Tech”, and “software!” for the SAME industry. Your columns fill up. Your segments fall apart.
📌 Example: My 2023 cleanup: 1,200 accounts, ~35 intern-hours, four different spellings of "Software" in the industry column. The filters looked fine. The segment counts were fiction. One enrichment run later, every row used one taxonomy, and the reports finally agreed with each other.
VLOOKUP Against a Dataset You Own
If you already have a clean reference table (say, last quarter’s enriched export), VLOOKUP can pull its fields into your new list by matching on domain or name. That’s real enrichment, and it costs nothing. Two honest limits, though. VLOOKUP can’t CREATE data; it only moves what you already have. And the reference table ages: companies grow, move, and rebrand while your snapshot stands still.
AI and Scraper Workflows
The other thing you’ll find on this topic is automation templates: chains that scrape a website or ask an AI model to fill the industry column, sometimes via IMPORTXML-style scraping. They’re flexible, and tinkering is fun. But be honest about the costs: setup time, constant maintenance when sites change, and the big one: hallucinated fields. An AI-guessed “Employees: 250” looks EXACTLY like a verified one. There’s no error message for confidently wrong. If you go this route, keep AI-filled columns clearly labeled and spot-check relentlessly.
So: manual for 30 rows, VLOOKUP when you own good reference data, AI workflows if you enjoy maintenance. For everything else, here’s the boring, repeatable way.
How Do You Enrich Company Data in Google Sheets With the CUFinder Add-On?
Install the add-on, add your API key, pick the Company Enrichment service, map your columns, and run your rows. That’s the whole loop. Step by step:
- Install the add-on. Grab the CUFinder add-on from the Google Workspace Marketplace. Google’s add-ons help page explains where it appears after install.
- 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 service. Open the add-on from the Google Sheets menu. It opens as a right panel listing all the enrichment services. For full profiles, pick Company Enrichment, which takes a company name, domain, or LinkedIn URL as input and returns the firmographic fields.
- Map columns, set the range, run. Set the input column (names or domains), the output column(s) for the fields you want, and the row range (rows 2-1200, say, to skip the header and cover the list). Then run it.
One decision worth two sentences: which input column? If you have both names and domains, feed it the domains: a domain points at exactly one company, while “Marlow” could be four. Names work fine; domains work better.
And two honest expectations. Some rows come back empty: no database covers every company on earth, and a blank cell is better than a guess. Also: only pull the fields you’ll actually use. Every extra column costs credits and attention.
💡 Pro Tip: Enrich only the fields you'll use this quarter. Industry, size, and country power most segmentation: start there, run rows 2-6 as a test batch, and add more columns only when a real campaign needs them.
A Worked Example: 5 Rows, Before and After
Say your sheet looks like this, with company names in column A and empty industry and employee columns waiting:
| A | B | C | |
|---|---|---|---|
| 1 | Company | Industry | Employees |
| 2 | Hansel Logistics | ||
| 3 | Bluepine Software | ||
| 4 | Corvid Analytics | ||
| 5 | Marlow & Sons | ||
| 6 | Tidewater Robotics |
Then I ran the add-on: Company Enrichment, input column A, output columns B and C, rows 2 to 6. About a minute later, the same sheet looked like this:
| A | B | C | |
|---|---|---|---|
| 1 | Company | Industry | Employees |
| 2 | Hansel Logistics | Logistics & Supply Chain | 240 |
| 3 | Bluepine Software | Software Development | 85 |
| 4 | Corvid Analytics | Data & Analytics | 32 |
| 5 | Marlow & Sons | Food & Beverage | 410 |
| 6 | Tidewater Robotics | Industrial Automation | 150 |
Notice what you’re NOT seeing: four spellings of “Software”. One taxonomy, every row. Happy with the test? Change the range to rows 2-1200 and run the real list.
→ 1,200 accounts → one run over coffee → consistent industry, size, and country columns → a CRM you can finally segment against your ideal customer profile.
And single fields have their own dedicated guides in this folder: find company websites when the domain column is the gap, get company names from domains when it’s the reverse, find company revenue in bulk for the money column, and a bulk tech stack lookup for the technology column.
Do You Need a Company Enrichment Template for Google Sheets?
No: a template is just column headers, and the add-on fills any layout you give it. People search hard for enrichment templates, so let me save you the download: here’s the entire “template” as a list you can type in 30 seconds:
- Company | Domain | Industry | Employees | Revenue | Country | LinkedIn | Last enriched
That last column is the one everyone skips and everyone needs. Data ages: the “Last enriched” date tells future you whether to trust the row or re-run it. If you’d rather start from a ready-made version with the formulas wired in, the firmographic data template for Google Sheets guide has one.
And that’s really the whole template conversation. Headers, a date column, consistent labels. The workflow templates you’ll find on this search (automation chains, AI sheets) are solving the ROUTE, not the layout. You already know the routes now.
What Mistakes Should You Avoid When Enriching Company Data?
The big ones: enriching duplicates, mixing name variants, trusting AI guesses, and never refreshing. My scar map, in full:
- Enriching before deduping. “Bluepine Software” and “Bluepine Software GmbH” are one company and two credits. Dedupe first: Sheets does it natively under Data → Data cleanup.
- Mixing name variants. Legal names, brand names, and typos match differently. Standardize the input column. Or better, enrich on domains, which don’t have spelling moods.
- One giant run with no test batch. Five rows first. Always. A mis-mapped output column at row 6 is a shrug; at row 1,200 it’s an afternoon.
- Treating AI-guessed fields as verified. Label the source of every filled column. Real data quality starts with knowing where each cell came from.
- Never refreshing. A quarter of my 2023 list was already stale when we “finished” it. Companies move, merge, and rebrand: use the Last-enriched column and re-run what’s old.
- Forgetting compliance. Company firmographics are generally low-risk, but the moment rows contain people, EU rules apply: GDPR wants a lawful basis for personal data, so keep company and contact columns distinct.
One more word on taxonomies, because they’re the quiet hero of this whole article. Governments solved this problem decades ago with classification systems like NAICS, the North American Industry Classification System: one code per industry, no moods, no synonyms. You don’t need to memorize codes. You just need every row in your sheet to use ONE label per industry, and enrichment gives you that for free.
🔍 Did You Know? Industry labels only work when they come from one taxonomy: classification systems like NAICS exist precisely because "Tech", "SaaS", and "Software" split one segment into three. Consistency beats precision in segmentation.
FAQ: Company Enrichment in Google Sheets
What is company enrichment?
Company enrichment adds missing firmographic fields (industry, size, revenue, location, socials) to company records you already have. Input a name or domain; get a fuller profile back.
How do you enrich data?
Three ways: research it manually, pull it from a dataset you own with VLOOKUP, or run an enrichment service over your list. For spreadsheets, the service route fills whole columns in one pass.
What is an example of data enrichment?
A row that says “Corvid Analytics” becomes “Corvid Analytics | Data & Analytics | 32 employees | Austin, TX | corvidanalytics.com”. Same record, four new usable fields: that’s B2B data enrichment in one sentence.
What is the difference between data enhancement and enrichment?
They’re near-synonyms, and vendors blur them. In practice, enrichment adds NEW external fields to a record, while enhancement often means improving what’s already there: fixing formats, deduping, standardizing.
Can VLOOKUP enrich company data?
Yes, if you already own a reference dataset to look into. VLOOKUP moves existing data between sheets; it can’t create new fields. Great for merging last quarter’s export, useless for a cold list.
What is the best company enrichment tool?
The honest answer: it depends on where your list lives and what inputs you have. If the list lives in a spreadsheet, a sheet-native add-on beats copy-paste tools because it processes whole columns. Test match rates on YOUR data, not demo data.
Can I enrich company data in Excel?
Yes: export your list as CSV, enrich it via the Sheets add-on or a platform upload, and import the results back. The company enrichment in Excel guide walks the round-trip.
It’s Time to Turn Names Into Profiles
You’ve got the full picture now. Manual research for a stray account. VLOOKUP when you own good reference data. And a company enrichment run for every list past 30 rows: deduped, mapped, test-batched, date-stamped.
Picture the next “can you check these accounts?” email. You paste the list, map three columns, run rows 2-1200, and answer with a segmented sheet before lunch. No interns harmed. That’s my actual workflow now, and the reports finally agree with each other.
Company profiles are half the story, too. When you need the PEOPLE at those companies, the email finder in Google Sheets guide picks up where this one stops, and the whole data enrichment in Google Sheets hub maps every other column. Tell me in the comments: how many bare company names are sitting in your CRM right now?
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