HubSpot CRM Cleanup Checklist
Step-by-step checklist to clean, deduplicate, and optimize your HubSpot CRM data for better sales performance and reporting accuracy.
Audit Your Data
Export a full contact list and review field completeness
easyDownload all contacts from HubSpot and check which fields have the highest missing-data rates. Focus on email, company, job title, and phone.
Identify your duplicate contact rate
easyUse HubSpot's built-in duplicate management tool (Contacts → Actions → Manage duplicates) to see how many duplicate records exist.
Check email bounce rate across your database
easyReview HubSpot's email health dashboard to identify what percentage of contacts have hard-bounced emails that need removal.
Review lifecycle stage distribution
mediumEnsure contacts are in the correct lifecycle stages. Look for leads stuck in early stages that should have progressed or been disqualified.
Clean Contact Records
Merge all duplicate contacts
mediumUse HubSpot's merge tool to combine duplicate records. Prioritize records with the most recent activity as the primary record.
Remove hard-bounced email addresses
easyCreate a list of contacts with hard bounce status and either update their emails or remove them from active lists.
Standardize job title formatting
hardNormalize job titles (e.g., 'VP of Sales', 'Vice President Sales', 'VP Sales' should all be consistent) using bulk edit or workflows.
Clean up company name variations
hardStandardize company names (e.g., 'Google', 'Google Inc.', 'Google LLC' should be unified) to improve reporting and deduplication.
Verify and update phone number formats
mediumEnsure phone numbers follow a consistent format with country codes. Remove invalid or disconnected numbers.
Optimize Properties & Lists
Archive unused contact properties
easyReview all custom properties and archive any that are no longer used. This reduces clutter and improves form/workflow performance.
Review and clean up static lists
easyDelete outdated static lists and ensure active lists have clear naming conventions and purposes.
Set up automated data quality workflows
hardCreate workflows that automatically flag or fix common issues like missing company names, invalid email formats, or stale contacts.
Enrich & Maintain
Run bulk enrichment on contacts missing key fields
mediumUse Cleanlist to enrich contacts that are missing email, phone, company, or job title data from 15+ data providers.
Set up recurring data quality audits
mediumSchedule monthly or quarterly reviews of data quality metrics: bounce rates, duplicate rates, and field completeness.
Pro Tips
- Always back up your data before bulk changes — export a full contact list as a safety net
- Start with duplicates — they cause the most reporting and outreach issues
- Use HubSpot's 'Last Activity Date' to identify stale contacts that haven't engaged in 12+ months
- Set up a 'Data Quality' dashboard in HubSpot to monitor completeness and bounce rates over time
- Consider connecting Cleanlist for automated enrichment of new contacts as they enter your CRM
Related Cleanlist Features
Related Checklists
Frequently Asked Questions
How often should I clean my HubSpot CRM?
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Most teams benefit from a thorough cleanup quarterly, with automated workflows handling common issues on an ongoing basis. High-volume sales teams that add hundreds of contacts per week should review data quality monthly.
Will cleaning my CRM delete important data?
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Not if you follow best practices. Always export a backup before making bulk changes. Focus on merging duplicates (which preserves all data in one record) and removing only clearly invalid records like hard bounces and spam contacts.
How do I prevent my HubSpot data from getting dirty again?
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Set up automated workflows for data validation, require key fields on forms, implement duplicate detection rules, and use enrichment tools like Cleanlist to automatically fill in missing data for new contacts.
Need help implementing this checklist?
Cleanlist automates data enrichment, email verification, and CRM data quality at scale. Start free and see the difference clean data makes.