Why Data Quality Kills Revenue
Bad data doesn't just create reporting headaches — it directly impacts revenue:
Every bad record means:
- Wasted ad spend on audiences with wrong firmographics
- Missed follow-ups when contacts aren't properly routed
- Wrong reporting that leads to bad decisions
- Sales frustration with bad leads and missing info
The 6 Data Quality Problems
Every HubSpot portal has the same issues. Here's what to look for:
Duplicates
Same contact/company with multiple records. Causes split engagement history.
Inconsistent Formatting
Phone: (555) 123-4567 vs 5551234567 vs +1-555-123-4567
Invalid Emails
Bounced, typos (gnail.com), role-based (info@), disposable domains.
Missing Required Fields
No company, no lifecycle stage, no owner assignment.
Wrong Firmographics
Outdated company size, wrong industry, old job titles.
Stale Records
No activity in 12+ months, churned customers still as "Customers."
The Data Quality Checklist
Email Quality
- Run hard bounce list — exclude from all sends
- Find typo domains: gnail.com, gmial.com, outlok.com
- Flag role-based emails: info@, sales@, support@
- Check for disposable domains: mailinator, guerrillamail, tempmail
- Verify personal emails in B2B: gmail.com, yahoo.com (okay for SMB, flag for enterprise)
Duplicates
- Use HubSpot's Manage Duplicates tool (Settings → Data Management)
- Check same name, different email — common with form re-submissions
- Check same email, different name — could be typos or shared aliases
- Review company duplicates — "Acme Inc" vs "Acme, Inc." vs "ACME"
Formatting Consistency
- Phone numbers — pick one format (E.164 recommended: +15551234567)
- Names — proper case (John Smith, not JOHN SMITH or john smith)
- Countries — standardize (United States, not US, USA, U.S., America)
- Job titles — normalize (VP vs Vice President vs V.P.)
Completeness
- Contacts without companies — associate or research
- Missing lifecycle stage — every contact needs one
- No contact owner — unassigned leads slip through cracks
- Companies without industry/size — critical for segmentation
Data Quality Automation
Set up workflows to catch issues automatically:
1. Phone Number Formatter
Workflow that normalizes phone formats using Operations Hub or a custom coded action. Trigger: Phone number is known AND doesn't match your format pattern.
2. Duplicate Prevention
Use form validation to check for existing contacts before creating new ones. HubSpot's native deduplication helps, but prevention is better than cleanup.
3. Stale Record Flagging
Create a list: "Last Activity Date is more than 365 days ago." Review quarterly and either re-engage or archive.
4. Enrichment on Create
Use tools like Clearbit, ZoomInfo, or Apollo to auto-fill company data when a new contact is created. Prevents missing data from the start.
Aim for less than 1% invalid emails and less than 5% duplicates. Above that, you're losing money to bad data.
Quarterly Data Review Cadence
- Week 1: Run duplicate report, merge obvious matches
- Week 2: Email quality check, suppress bounces/invalids
- Week 3: Completeness audit, enrich missing fields
- Week 4: Stale record review, archive or re-engage