The Cost of Dirty Data
Bad data costs the average company $12.9 million per year (Gartner). In CRM terms, that means:
- Sales reps calling wrong numbers
- Duplicate records causing embarrassing double-outreach
- Inaccurate pipeline forecasts misleading leadership
- Automations firing on stale or incorrect data
10 Best Practices for Clean CRM Data
1. Standardize Input at the Source
Use dropdown fields instead of free text wherever possible. "United States" vs "US" vs "USA" vs "U.S.A." — standardize it.
2. Deduplicate Monthly
Run duplicate detection at least monthly. Automo's AI auto-detects and merges duplicates based on email, phone, and company matching.
3. Validate Email on Entry
Use real-time email validation to catch typos and disposable addresses before they enter your database.
4. Require Minimum Fields
Don't make every field required — you'll get garbage data. Require only: name, email, company. Enrich the rest with AI.
5. Archive, Don't Delete
Contacts who haven't engaged in 2+ years should be archived, not deleted. You may need them for compliance or reactivation.
6. Assign Data Ownership
Every record should have an owner. Unowned records accumulate and rot.
7. Audit Custom Fields Quarterly
If a custom field has less than 20% fill rate, it's probably unnecessary. Remove it.
8. Use AI Enrichment
Let AI fill in missing data — company size, industry, social profiles, tech stack — from public sources.
9. Log Activities Automatically
Manual activity logging has a 30% compliance rate. Use email and calendar sync to capture interactions automatically.
10. Create a Data Quality Dashboard
Track: fill rate per field, duplicate rate, bounce rate, stale record percentage. Review monthly.
How Automo Helps
Automo's CRM addresses data quality at the platform level:
- AI deduplication runs continuously
- Automatic enrichment fills gaps
- Email/calendar sync captures activities without manual entry
- Standardized fields reduce garbage data
- Data quality dashboard included on all plans
