If you’re reading this, you probably want to get your hands on solid company data—not just another spreadsheet of random contacts. Maybe you’re tired of buying “leads” that go nowhere, or you’re trying to get more targeted with your B2B outreach. This guide will walk you through the practical steps to export company data from Coresignal, clean it up, and actually use it to reach the right people. It’s written for folks who want results, not just another sales pitch.
Why Use Coresignal for B2B Outreach?
Let’s get this out of the way: no data provider is magic. Coresignal is one of the bigger names for public company and people data scraped from sources like business profiles, employee lists, and social networks. You’re not buying a silver bullet—you’re buying a raw material. If you want to target the right companies, you still have to know what you’re looking for and do the work.
What Coresignal is good for: - Large datasets of company profiles and employee info, updated fairly often. - Decent coverage for tech, finance, and SaaS companies, especially in North America and Europe. - Filtering by things like industry, size, location, and recent activity.
What it’s not: - A magic lead list that closes deals for you. - Perfectly up-to-date or 100% accurate (nobody is—don’t let anyone tell you otherwise). - A replacement for your own research, context, or judgment.
With that in mind, let’s get into the nitty-gritty.
Step 1: Get Access (Don’t Skip the Fine Print)
First, you need access to Coresignal’s data. This isn’t a self-serve tool where you swipe your card and download a CSV in five minutes. Here’s how it usually goes:
- Contact Sales: You’ll talk to a salesperson. They’ll ask about your use case, which data you want (companies, people, jobs, etc.), and how often you need updates.
- Choose Your Dataset: For B2B outreach, focus on their “Company Data” or “Employees at Companies” datasets.
- Negotiate Pricing: Data isn’t cheap. Prices depend on the volume, refresh rate, and which countries or industries you want. Don’t be afraid to push back or ask for a sample.
- Review the Contract: Seriously, read it. Watch for limits on usage (some vendors restrict how you can contact people), data retention, and compliance issues (GDPR, CCPA, etc.).
- Set Up Delivery: Most customers get bulk data via S3 buckets, FTP, or API. Make sure you have someone technical to help if you need it.
Pro tip: If you’re just experimenting, ask for a trial or a sample export. Don’t commit big money until you’ve seen the data quality for your target market.
Step 2: Define Your Ideal Company Profile
Before you start exporting, get clear on who you actually want to reach. “All companies in the US” is useless. Instead, get specific:
- Industry: Which verticals matter to you? Tech, finance, manufacturing?
- Company Size: Headcount, revenue, or both? Small businesses need different pitches than enterprises.
- Location: Country, region, or city? Are you avoiding certain geographies?
- Growth Signals: Recent hiring, funding rounds, new offices? Some Coresignal fields cover these.
- Tech Stack: If you sell SaaS, filter by companies using certain technologies. (You’ll need to enrich data elsewhere for this.)
Write this down. You’ll use these filters in the next step.
Step 3: Export the Data You Actually Need
Once you’ve got access and your filters, it’s time to pull the data. Here’s how it usually works:
3.1 — Bulk Download
If you’re getting a full dataset (e.g., “all US tech companies”), Coresignal will give you a big file or S3 bucket. You’ll need to filter it yourself. This is common if you want to slice and dice the data for different campaigns.
What you get: - CSV, Parquet, or JSON files with hundreds of thousands (or millions) of rows. - Fields like: company name, URL, industry, size, HQ location, employee count, founding year, and sometimes employee profiles.
What to watch out for: - Files can be massive—hundreds of MBs or even a few GBs. Don’t try to open them in Excel unless you like crashing your computer. - Not every field is filled for every company. Expect gaps.
3.2 — API Access
If you only need a subset (e.g., “all SaaS companies in Germany with 50-200 employees”), ask about API access. You can set your filters upfront and only pull what you want.
Pros: - Less data wrangling up front. - Easier to automate regular updates if you run campaigns often.
Cons: - You’ll need someone who can script against their API (usually REST or GraphQL). - Still expect to do some cleaning—no API gives you perfect data.
3.3 — Custom Exports
Some clients ask Coresignal to run the filters for them and deliver a ready-made file. This costs extra, but it saves time if you hate dealing with raw data.
Pro tip: If your filters are complex (e.g., “companies founded after 2015, hiring for DevOps, and recently funded”), ask Coresignal if they can pre-filter. It’s usually faster than trying to do it all yourself.
Step 4: Clean and Prep the Data
Here’s where most people get stuck. Raw data is… raw. You’ll need to clean it for real-world outreach.
4.1 — Remove Duplicates and Junk
- Duplicates: Companies can show up more than once due to name variations. Deduplicate by website domain or company ID.
- Obvious Junk: Remove companies with missing names, websites, or that are clearly out of business.
4.2 — Standardize Fields
- Industry Codes: Coresignal uses their own taxonomy, not always standard NAICS/SIC. Map them to what makes sense for you.
- Locations: City and country fields are sometimes inconsistent. Standardize to avoid targeting “San Francisco” and “SF” as two different places.
4.3 — Sanity-Check Key Data
- Employee Counts: These are usually ballparks, not gospel. If you see 5,000 employees for a tiny SaaS, something’s off.
- URLs: Make sure the website field isn’t empty or just “N/A”.
4.4 — Enrich If Needed
Coresignal won’t give you everything. For example, if you want decision-maker email addresses, you’ll need to enrich the data with another tool (like Hunter, Apollo, or LinkedIn scraping). Don’t fall for “all-in-one” promises—no single source has it all.
Pro tip: Spot-check 20–30 rows manually before blasting your outreach. You’ll catch weird data issues that scripts miss.
Step 5: Segment for Outreach
Once you’ve cleaned the data, don’t send the same email to everyone. Segment your list based on what actually matters:
- By industry: Tailor your messaging. What works for fintech doesn’t work for retail.
- By size: SMBs care about saving time; enterprises want scalability.
- By recent activity: Companies with recent funding or hiring sprees are more likely to buy.
Even simple segmentation beats blasting everyone with the same pitch.
Step 6: Export to Your Tools (CRM, Email, etc.)
You’ve got a clean, targeted list. Now get it into whatever tool you use to run campaigns:
- CRM: Salesforce, HubSpot, Pipedrive, etc. If your CRM chokes on imports, break the file into batches.
- Cold Email Tools: Apollo, Outreach, Mailshake, or even good old Mail Merge.
- Spreadsheets: If you’re running manual outreach, Google Sheets works fine—just don’t share raw data with the whole team.
Watch out: Double-check your mapping. It’s easy to import the “industry” field into the “address” field by mistake.
Step 7: Respect Compliance (Seriously)
Don’t skip this. If you’re reaching out to companies in the EU or California, make sure you’re following GDPR/CCPA rules. Coresignal data is publicly sourced, but how you use it is your responsibility.
- Don’t spam. Personalize and make your outreach relevant.
- Honor opt-outs. If someone asks to be removed, do it.
- Keep your privacy policy up to date.
If you’re not sure, talk to your legal team. It’s not worth risking a fine.
What to Ignore (and What to Watch Out For)
- Hype about “real-time” data: Coresignal updates regularly, but nothing is truly real-time. Expect some lag.
- Overpromising coverage: No provider covers every company, everywhere. If you’re targeting niche industries or countries, double-check the sample.
- AI magic: Tools claiming to “auto-generate perfect leads” on top of Coresignal data are mostly fluff. Good outreach still requires judgment.
Wrapping Up: Keep It Simple, Iterate Often
Exporting company data from Coresignal isn’t rocket science, but it does take some up-front work. Don’t overcomplicate it. Start with a small, well-defined segment, test your outreach, and improve from there. The data is just a starting point—how you use it is what counts. Good luck, and don’t be afraid to get your hands dirty.
If you hit a snag, ask for help, or just take a break and come back with fresh eyes. Most of the “secret sauce” is just showing up, doing the real work, and not getting distracted by shiny tools.