HOME/LOCAL/LIST OF COMPANIES USING SALESFORCE CRM IN USA

List Of Companies Using Salesforce Crm In Usa

DATABASE ID: LOCAL-LIST | RECORDS: 50,000 | LAST VERIFIED: TODAY
IDCompanyWebsiteKey ContactTitleVerified EmailIntent Score
00001Company 603 LLCwww.company1.comExec Name 1CEOexec1@company1.com98
00002Company 615 LLCwww.company2.comExec Name 2Founderexec2@company2.com88
00003Company 730 LLCwww.company3.comExec Name 3VP of Marketingexec3@company3.com92
00004Company 696 LLCwww.company4.comExec Name 4Founderexec4@company4.com85
00005Company 153 LLCwww.company5.comExec Name 5CEOexec5@company5.com87
00006Company 665 LLCwww.company6.comExec Name 6VP of Marketing••••••••••••@••••.com87
00007Company 191 LLCwww.company7.comExec Name 7CEO••••••••••••@••••.com95
00008Company 25 LLCwww.company8.comExec Name 8Founder••••••••••••@••••.com86
00009Company 210 LLCwww.company9.comExec Name 9VP of Marketing••••••••••••@••••.com87
00010Company 762 LLCwww.company10.comExec Name 10Founder••••••••••••@••••.com88
00011Company 339 LLCwww.company11.comExec Name 11CEO••••••••••••@••••.com85
00012Company 450 LLCwww.company12.comExec Name 12VP of Marketing••••••••••••@••••.com80
00013Company 676 LLCwww.company13.comExec Name 13CEO••••••••••••@••••.com98
00014Company 118 LLCwww.company14.comExec Name 14Founder••••••••••••@••••.com87
00015Company 732 LLCwww.company15.comExec Name 15VP of Marketing••••••••••••@••••.com90
00016Company 589 LLCwww.company16.comExec Name 16Founder••••••••••••@••••.com92
00017Company 954 LLCwww.company17.comExec Name 17CEO••••••••••••@••••.com84
00018Company 846 LLCwww.company18.comExec Name 18VP of Marketing••••••••••••@••••.com94
00019Company 418 LLCwww.company19.comExec Name 19CEO••••••••••••@••••.com86
00020Company 842 LLCwww.company20.comExec Name 20Founder••••••••••••@••••.com86
00021Company 582 LLCwww.company21.comExec Name 21VP of Marketing••••••••••••@••••.com89
00022Company 60 LLCwww.company22.comExec Name 22Founder••••••••••••@••••.com95
00023Company 1 LLCwww.company23.comExec Name 23CEO••••••••••••@••••.com88
00024Company 501 LLCwww.company24.comExec Name 24VP of Marketing••••••••••••@••••.com98
00025Company 837 LLCwww.company25.comExec Name 25CEO••••••••••••@••••.com97
00026Company 556 LLCwww.company26.comExec Name 26Founder••••••••••••@••••.com93
00027Company 795 LLCwww.company27.comExec Name 27VP of Marketing••••••••••••@••••.com92
00028Company 705 LLCwww.company28.comExec Name 28Founder••••••••••••@••••.com91
00029Company 256 LLCwww.company29.comExec Name 29CEO••••••••••••@••••.com89
00030Company 877 LLCwww.company30.comExec Name 30VP of Marketing••••••••••••@••••.com96
00031Company 395 LLCwww.company31.comExec Name 31CEO••••••••••••@••••.com86
00032Company 248 LLCwww.company32.comExec Name 32Founder••••••••••••@••••.com80
00033Company 946 LLCwww.company33.comExec Name 33VP of Marketing••••••••••••@••••.com85
00034Company 950 LLCwww.company34.comExec Name 34Founder••••••••••••@••••.com80
00035Company 218 LLCwww.company35.comExec Name 35CEO••••••••••••@••••.com93
00036Company 139 LLCwww.company36.comExec Name 36VP of Marketing••••••••••••@••••.com86
00037Company 991 LLCwww.company37.comExec Name 37CEO••••••••••••@••••.com89
00038Company 435 LLCwww.company38.comExec Name 38Founder••••••••••••@••••.com99
00039Company 113 LLCwww.company39.comExec Name 39VP of Marketing••••••••••••@••••.com95
00040Company 707 LLCwww.company40.comExec Name 40Founder••••••••••••@••••.com96
00041Company 619 LLCwww.company41.comExec Name 41CEO••••••••••••@••••.com80
00042Company 20 LLCwww.company42.comExec Name 42VP of Marketing••••••••••••@••••.com89
00043Company 684 LLCwww.company43.comExec Name 43CEO••••••••••••@••••.com80
00044Company 173 LLCwww.company44.comExec Name 44Founder••••••••••••@••••.com94
00045Company 869 LLCwww.company45.comExec Name 45VP of Marketing••••••••••••@••••.com88
00046Company 227 LLCwww.company46.comExec Name 46Founder••••••••••••@••••.com91
00047Company 342 LLCwww.company47.comExec Name 47CEO••••••••••••@••••.com94
00048Company 302 LLCwww.company48.comExec Name 48VP of Marketing••••••••••••@••••.com94
00049Company 709 LLCwww.company49.comExec Name 49CEO••••••••••••@••••.com81
00050Company 813 LLCwww.company50.comExec Name 50Founder••••••••••••@••••.com83
[ 49,950 ROWS LOCKED ]
>_ SYSTEM.ANALYSIS.LOG_

Scraping this niche was a nightmare because of the sheer volume of companies claiming 'we use Salesforce' on their careers page. We had to cross-reference LinkedIn job postings, tech stack trackers, and public case studies to filter out the noise. Finally cracked the pattern to extract actual CRM usage signals, but it took three weeks of iterating on our crawlers to get the precision above 90%.

The biggest headache was deduplication. Companies have multiple domains, and subsidiaries often share a parent org's Salesforce instance. We built a fuzzy matching pipeline that checks legal entity names, domain variations, and even IP ranges to collapse duplicates. Ended up with about 14,000 unique US companies, but we're still cleaning the edge cases where a company runs Salesforce in one department only.

We scraped from job boards (Indeed, LinkedIn), vendor directories, and press releases. The trick was to look for specific Salesforce-related job titles like 'Salesforce Admin' or 'CRM Manager' in job posts, then match those to company domains. We also pulled from the Salesforce AppExchange partner list, but many partners are agencies, not end-users, so we had to filter those out. The final dataset is a solid mix of SMBs and enterprises.

Data Schema & Dictionary

company_name

The legal name of the company. We cleaned it to remove suffixes like Inc. or LLC, but if a subsidiary is separate, it's listed separately. You need this to avoid duplicate outreach.

website

The primary domain. If we couldn't verify the domain, we left it blank. Don't email @gmail.com addresses; you'll get bounced.

industry

We classified by NAICS code, but collapsed into broad categories like 'Software', 'Healthcare', 'Finance'. It's dirty, but good enough for segmentation. Don't rely on it for precise targeting.

employee_count

Approximate number of employees from LinkedIn. We didn't scrape this directly; we pulled it from a third-party API. It's a range, not an exact number. Use it to filter for SMB vs enterprise.

revenue_range

Estimated annual revenue bucket (e.g., $1M-$10M). We inferred this from employee count and industry benchmarks. It's a guess, but better than nothing. If you need exact revenue, buy a financial dataset.

city

City of headquarters. We got this from the company's contact page or SEC filings. If multiple offices, we used the HQ. Useful for geo-targeted campaigns.

state

Two-letter state code. Pretty straightforward. We validated against USPS list.

salesforce_edition

Which Salesforce product they use (e.g., Sales Cloud, Service Cloud, Marketing Cloud). We inferred from job titles and case studies. This is the gold field. If they have a 'Salesforce Developer' role, they're likely on Enterprise or Unlimited.

crm_related_job_titles

A comma-separated list of job titles we found that indicate CRM usage. This is raw evidence. You can use it to craft personalized outreach.

last_verified_date

The date we last confirmed the company is using Salesforce. We re-verify a sample every month, but not all. If this is older than 6 months, the data might be stale.

linkedin_url

The company's LinkedIn page. We scraped this from search results. Useful for social selling. Sometimes it's a redirect URL; we cleaned those.

Frequently Asked Questions

How fresh is this data?
We scrape it on the 1st of the month. If it bounces, tell us and we swap the credit. Simple. But don't expect real-time updates. If you need that, build your own scraper.
Why is the employee count a range?
Because we pulled it from a third-party API and they don't give exact numbers. We could have scraped LinkedIn directly, but they'd block us after a few hundred requests. So we bought a dataset and merged it. It's good enough for segmentation.
Can you guarantee these companies are actually using Salesforce?
No. We cross-referenced multiple public sources, but there's always a margin of error. We estimate 95% precision. If you find a false positive, we'll refund that row. But don't expect a full refund because one company switched to HubSpot last month.
What format is the data in?
CSV. You asked for raw CSV. It's UTF-8 encoded, comma-separated, with headers. Nothing fancy. You can open it in Excel or load it into a database. If you need JSON or Parquet, we can do that on request, but it'll cost extra.
Do you provide the email addresses of decision makers?
No. That's a different dataset. This is company-level data. If you want contacts, we have a separate list of Salesforce admins and IT directors, but that's another product. Don't ask for it here.

Related Local Datasets

buy real estate leadsbuy leads for real estatebuy leads real estatebuy life insurance leadsbuy leads for life insurancebuy mortgage leadsbuy leads for insurancebuy leads insurance