Sales and marketing tools are only as good as the data you feed them. If you’re using Cognism to get B2B contact info, you already know it’s fast and convenient—but “fast” doesn’t always mean “correct.” Dirty or outdated contact data wastes time, tanks deliverability, and makes your team look sloppy. If you want to get more out of Cognism (and not annoy people with dead emails or wrong job titles), you need to verify what you’re working with.
This guide is for anyone who wants to squeeze more accuracy from their Cognism leads—whether you’re running outbound campaigns, trying to clean up a CRM, or just tired of bouncing emails. Let’s cut through the fluff and talk about what actually works.
Why Bother Verifying Cognism Data?
Let’s be real: No data provider, including Cognism, is perfect. People change jobs, companies rebrand, phone numbers get reassigned. Even the best tools pull in stale or flat-out wrong info sometimes.
Here’s what’s at stake: - Lower bounce rates. Bad emails hurt your sender reputation. - Better response rates. Reach people who actually work there. - Smoother handoff to sales. No more “who is this?” confusion. - Less wasted time. Your team isn’t chasing ghosts.
A bit of up-front effort verifying data pays for itself quickly.
Step 1: Start With Cognism’s Built-In Verification
Cognism says it runs verification on its data, especially emails and phone numbers. That’s a good start, but don’t take it as gospel.
What Works
- Email verification: Cognism flags emails as “verified,” “risky,” or “unknown.” “Verified” is usually safe to use.
- Phone verification: Mobile numbers are more reliable than direct dials or generic company lines.
What Doesn’t
- Assuming “verified” means perfect: Even “verified” emails can go stale. People quit, get promoted, or switch companies.
- Ignoring warning signs: If Cognism marks something as “risky,” treat it as such—don’t send your best pitch.
Pro tip: Filter your exports to include only “verified” emails wherever possible. That cuts out a lot of obvious junk.
Step 2: Cross-Check With a Secondary Tool
If you’re serious about data quality, don’t rely on just one source. Even if Cognism is good, it’s not infallible.
How To Do It
- Use a dedicated email verifier. Tools like NeverBounce, ZeroBounce, or Hunter can bulk-verify your email list before you hit send.
- Spot-check phone numbers. Services like NumVerify or manual LinkedIn checks can help see if a number matches a person and company.
- Check LinkedIn or company websites. See if the person’s title, company, or email pattern lines up.
What to Ignore
- Overkill on every single contact. Spot-checking a sample of your Cognism data is usually enough—don’t waste hours double-checking low-priority leads.
- “Free” verification tools. Most are limited, inaccurate, or pushy about upsells.
Pro tip: Run a quick cross-check on a new Cognism list before importing into your CRM. It’s much easier to fix bad data now than after it’s spread.
Step 3: Use Data Enrichment for Context
Cognism gives you the basics, but sometimes you need more context—like recent job changes, company size, or tech stack—to make sure you’re targeting the right person.
How To Do It
- Use enrichment platforms. Tools like Clearbit, ZoomInfo, or Lusha can fill in gaps (though beware overlaps and extra costs).
- Automate enrichment via integrations. Many CRMs let you enrich contacts automatically when they’re imported.
What Works
- Catching outdated records. If someone shows up as a VP on Cognism but as “ex-Company” on LinkedIn, move on.
- Spotting missing info. Sometimes Cognism misses a phone number or company domain—enrichment tools can fill those holes.
What Doesn’t
- Assuming enrichment is always up-to-date. These tools update at different rates; always trust your own eyes over automation.
- Paying for enrichment you don’t need. If you already have good data, don’t get upsold on “extras.”
Pro tip: Always check for recent job changes on LinkedIn before reaching out—Cognism and enrichment tools can lag behind.
Step 4: Clean and Standardize Before Importing
If you’re planning to load Cognism data into your CRM or sales tools, clean it first. Messy data is a pain to fix once it’s spread.
How To Do It
- Standardize job titles and company names. Get rid of weird capitalizations or typos (e.g., “GOOGLE Inc.” vs. “Google”).
- Deduplicate contacts. Cognism can sometimes give you the same person twice, especially if you’re pulling large lists.
- Tag your source. Mark Cognism contacts so you know where they came from if there are issues later.
Tools That Help
- Excel or Google Sheets: A little manual cleanup goes a long way.
- CRM import tools: Many CRMs (like HubSpot or Salesforce) let you set rules for deduplication and standardization.
What to Ignore
- Importing raw data. Don’t just dump everything in—take five minutes to check for obvious problems.
- Manual entry for big lists. Use bulk import features and cleanup scripts for efficiency.
Pro tip: Keep an “original export” of your Cognism data somewhere safe, so you can trace issues back if something gets weird later.
Step 5: Monitor and Update Regularly
Even if your data starts clean, it goes stale fast. People move jobs, companies get acquired, and emails die quietly.
How To Do It
- Set a reminder to re-verify. Every 3–6 months, run your key lists through a verifier again.
- Watch your bounce rates. If bounces spike, it’s a sign your data’s going bad.
- Ask your team to flag issues. Sales and SDRs can mark bad contacts as they find them.
What Works
- Automated CRM workflows: Some CRMs can flag or remove contacts with bounced emails.
- Feedback loops: If your team spots a lot of duds from Cognism, raise it with your rep—they may have suggestions or credits.
What Doesn’t
- Assuming last month’s data is still good. Churn is real. Always double-check before a big send.
- Ignoring “soft” bounces. They can signal a full inbox, but repeated soft bounces often mean a dead address.
Pro tip: Make data hygiene part of your onboarding and offboarding process—don’t let it become a “someday” project.
What About Data Append and Automation?
There’s a lot of noise about fully-automated enrichment and “real-time” data tools. In practice, they’re hit or miss. They can make things easier at scale, but they don’t replace human judgment. Set them up if you’re drowning in updates, but don’t expect miracles.
Quick Checklist: Cognism Data Verification
Here’s a summary you can actually use:
- [ ] Filter for “verified” emails and mobiles in Cognism
- [ ] Cross-check a sample with a second tool (email and phone)
- [ ] Double-check job titles and companies on LinkedIn
- [ ] Clean and dedupe before import
- [ ] Tag your source for traceability
- [ ] Re-verify and monitor bounce rates every few months
Keep It Simple—and Keep Iterating
Perfect data doesn’t exist. The goal isn’t 100% accuracy, it’s “accurate enough that your team isn’t pulling their hair out.” Start with the easy wins, automate what you can, and don’t be afraid to spot-check when things feel off. A little skepticism and some up-front work will save you a lot of headaches down the line.