So you want to build a lead list that’s actually useful—not just a dump of random company names and emails. Maybe you’re tired of buying stale lists, or you want more control over who goes into your pipeline. If you’ve landed here, you’re probably considering Coresignal, or you already have access and want to get your hands dirty.
This guide is for anyone who needs high-quality B2B leads: salespeople, founders, marketers, or data folks who want to cut through the noise and build something that works. I’ll walk you through each step, highlight what matters (and what doesn’t), and give you the straight talk on using Coresignal without getting lost in the weeds.
Step 1: Get Clear on Your Real Criteria
Before you even log into Coresignal, step back and write down exactly who you want on your list. Not “decision makers at tech companies”—that’s too broad. The tighter you are here, the less time you’ll waste later.
Ask yourself: - What size companies do you want? (Revenue, employee count, funding stage?) - What industries are you targeting? (Be specific. “Tech” is vague; “SaaS for logistics” is better.) - Where do they need to be located? - What job titles or roles matter? - Are there dealbreakers? (E.g., exclude companies with less than 10 employees, or those founded before 2000.)
Pro tip: If you can’t describe your ideal lead in one or two sentences, you’re not ready to build a list. Get that nailed down first.
Step 2: Log Into Coresignal and Pick Your Dataset
Coresignal isn’t a magical “give me leads” button. It’s a big data platform. You’re working with raw, up-to-date data pulled from public sources (think company profiles, employee info, firmographics).
When you log in, you’ll see several datasets: - Company data: Info about organizations (industry, size, HQ, funding, etc.) - Employee data: Individual profiles, roles, skills, etc. - Job postings: Open positions by company. - Other datasets: Investment rounds, technologies, etc.
What works: For B2B lead lists, you’ll almost always start with company data, then layer in employee data if you want direct contacts.
What to ignore: Don’t bother with job postings unless you’re selling recruitment services or tracking growth signals.
Step 3: Set Up Your Filters—Be Ruthless
This is where most people go wrong. They set broad filters (“tech companies in the US”) and end up with a list that’s 90% junk.
Start with Company Filters
In the company dataset, use filters like: - Industry: Use Coresignal’s taxonomy—don’t just type “tech.” Pick specific NAICS/SIC codes, or select sub-industries. - Company size: Employee count or revenue. Be realistic; “1000+ employees” excludes a lot of innovative companies. - Location: Country, region, or city. If you’re US-only, say so. - Funding status: Want only VC-backed companies? Filter by last funding round or total funding.
Add Employee Filters (Optional)
If you want people, not just companies: - Title: Search for specific roles (“VP Engineering,” “Head of Marketing”). Use variations. - Seniority: Coresignal lets you filter by seniority levels. Skip “Intern” and “Student” unless you really want them. - Skills/Keywords: Useful if you’re after niche roles.
Tip: Overfiltering is as bad as underfiltering. Start specific, then loosen if your list is too small.
Step 4: Preview Your Results—And Sanity Check Them
Always preview before exporting anything. Coresignal will show you a sample of the records that match your filters.
What to look for: - Are these actually the types of companies/people you want? - Any oddballs or false positives? (E.g., companies in the wrong industry because of poor tagging.) - Are contact details present? Some records might lack emails or phone numbers.
If things look off: - Check your filters—maybe you went too narrow or too broad. - Try adjusting industry codes, company size, or title variants. - Don’t be afraid to start over if the sample’s way off. It’s quicker than cleaning a bad export.
Step 5: Export Your Data—But Don’t Grab Everything
Once you’re happy with the preview, it’s time to export. Coresignal usually lets you download CSV files with the fields you pick.
Only export what you need: - Company name, website, industry, size, HQ location. - Key contacts: name, title, email (if available), LinkedIn URL. - Funding info, tech stack, or other fields—only if you’ll actually use them.
Why be picky? More columns means more cleanup later. If you’re not going to use a field, skip it.
A note on contact data: Coresignal scrapes public info, so don’t expect every record to have a direct email or phone number. You might need to enrich these later (see Step 7).
Step 6: Clean and Organize Your List—This Is Where Most People Get Lazy
Your export will have duplicates, weird formatting, and missing fields. Don’t just dump it into your CRM.
What to do: - Deduplicate: Remove repeated companies or people. - Standardize fields: “VP of Sales” and “Vice President Sales” should be treated the same. - Fix weird characters: Sometimes you’ll get odd symbols or broken text from public data. - Validate contact info: Spot-check emails and LinkedIn URLs. Don’t assume everything is correct.
Pro tip: If you’re sending outreach, run emails through a validation tool. Nothing kills deliverability faster than a high bounce rate.
Step 7: Enrich and Fill in Gaps (Optional)
Coresignal is a solid data source, but it’s not perfect. You’ll probably have missing emails, phone numbers, or outdated info. Decide if you need to fill these gaps.
Options: - Enrichment tools: Services like Hunter.io, Apollo, or Clearbit can help fill in missing emails or social profiles. - Manual research: Painful, but sometimes you’ll need to dig for that perfect contact. - Skip it: If you only need company-level info (not personal emails), don’t waste time here.
Honest take: Don’t chase “perfect” data. A 90% lead list you actually use is better than a 100% list you never finish.
Step 8: Put Your List To Use (And Track What Works)
Now you’ve got a custom lead list. Don’t just let it sit on your hard drive.
How to make it actionable: - Import into your CRM or outreach tool. - Track which leads respond, convert, or bounce. - Note which filters or data points correlated with the best results.
Ruthless honesty: If your results stink, don’t blame the data provider. Go back to Step 1 and challenge your criteria. Garbage in, garbage out.
What To Ignore (And What To Watch Out For)
- Don’t chase “AI-powered” lead scoring in Coresignal or elsewhere. It usually just sorts by company size or recent funding—stuff you can filter anyway.
- Don’t buy giant lists blindly. More data isn’t better; more qualified data is.
- Don’t assume the freshest data wins. Sometimes the best prospects aren’t the most recently funded or fastest-growing.
- Watch for compliance: Coresignal uses public data, but if you’re emailing people, make sure you’re following GDPR, CAN-SPAM, etc.
Keep It Simple and Keep Testing
Building a great lead list isn’t about fancy tools or endless data fields. It’s about knowing who you want, using the filters that matter, and staying ruthless about quality. Don’t overthink it or chase “perfect”—the best lists are the ones you use, tweak, and learn from.
Start small, stay focused, and don’t be afraid to scrap a list that isn’t working. Coresignal is a powerful tool if you treat it like what it is: a data source, not a silver bullet.
Happy hunting.