CRM Cleanup Guide: 8 Automations for Better Data

Your CRM is supposed to be a revenue engine. Instead, for most businesses, it is a graveyard of duplicate records, outdated contact information, inconsistent formatting, and deals that have been "in progress" for three years. Dirty CRM data does not just waste storage space. It causes your sales team to call the wrong people, your marketing to send emails to dead addresses, and your leadership to make decisions based on metrics that are fundamentally inaccurate.

The good news is that CRM data quality is a perfect automation target. The problems are predictable, the rules are definable, and the volume makes manual cleanup impractical. Here are eight automations that transform your CRM from a data dump into a reliable business asset.

1. Duplicate Detection and Merge Alerts

Duplicates are the most common CRM data problem and the most damaging. When a single customer exists as three separate records, their purchase history is fragmented, communication is inconsistent, and your metrics are inflated.

Automate duplicate detection by running a daily or weekly scan that matches records on email address, phone number, company name with fuzzy matching, and physical address. When potential duplicates are found, automatically flag them for review and present a side-by-side comparison to the data owner. For high-confidence matches where the email address is identical, automate the merge entirely.

• Trigger: Scheduled daily scan or new record creation
• Match criteria: Email, phone, company name (fuzzy), address
• Action: Auto-merge high confidence matches; route low confidence for human review

2. Contact Information Enrichment

A CRM record with just a name and email is barely useful. Automate enrichment by connecting to data providers that append company size, industry, job title, social profiles, and revenue range. Trigger enrichment when a new contact is created or when an existing contact's company field is updated.

This automation pays for itself immediately by giving your sales team context they would otherwise spend 10-15 minutes researching per prospect. Build this with Make.com connecting your CRM to enrichment APIs like Clearbit or Apollo.

3. Field Standardization

When ten people enter data differently, you end up with "United States," "US," "USA," "U.S.," and "United States of America" all in the same country field. This makes segmentation, reporting, and filtering unreliable.

Automate field standardization with rules that normalize common fields on save: state abbreviations, country codes, phone number formatting, company name suffixes (LLC, Inc., Ltd.), and industry categories. Apply these rules both to new records and retroactively to existing data through a one-time batch process.

All eight automations work together to create a self-cleaning CRM that improves over time

4. Stale Record Detection and Decay

A lead that has not been contacted in 180 days is not really a lead. An opportunity that has been sitting in the same stage for six months is not really an opportunity. Automate a decay process that identifies stale records based on last activity date, changes their status accordingly, and archives truly dead records.

Set clear rules: contacts with no activity in 90 days get a "re-engagement needed" tag. At 180 days, they move to a dormant segment. At 365 days with no activity, they are archived. This keeps your pipeline honest and your metrics meaningful.

5. Email Validation and Bounce Processing

Every bounced email hurts your sender reputation and skews your engagement metrics. Automate email validation at two points: when a new address is entered and on a monthly batch scan of your entire database. Use validation services to check for typos, defunct domains, role-based addresses, and known spam traps.

When an email bounces from an actual send, automate the response: mark the email as invalid, notify the record owner, and remove the contact from active marketing lists. This protects your deliverability and ensures your open rates reflect actual engagement.

6. Record Owner Assignment and Reassignment

Unowned records are invisible records. Automate assignment rules based on geography, industry, deal size, or lead source. When a rep leaves the company, automate the redistribution of their records using round-robin logic or territory-based rules rather than letting hundreds of contacts sit unowned for weeks.

7. Activity Logging and Touchpoint Tracking

Manual activity logging is the bane of every sales rep's existence, which is why it rarely happens consistently. Automate the capture of email sends and opens, meeting bookings from Calendly or similar tools, phone calls from your VoIP system, and form submissions from your website. This gives you a complete customer timeline without relying on reps to log their activities, which integrates with your broader customer lifecycle automation.

8. Data Health Scoring and Reporting

You cannot improve what you do not measure. Build an automated data health score that evaluates your CRM on key dimensions: field completeness percentage, duplicate rate, email validity rate, record ownership coverage, and activity recency. Generate this report monthly and deliver it to your ops team.

A CRM that you cannot trust is worse than no CRM at all. It creates a false sense of confidence while your team makes decisions based on garbage data. Invest in the automations that keep your data clean.

Always deduplicate and standardize before enriching. The order matters.

Getting Started

Begin with deduplication and standardization since they have the highest impact and lowest risk. Run a dedup scan first to understand the scope of the problem. Most businesses are shocked to find that 15-25% of their CRM records are duplicates. Once the data is clean and standardized, enrichment and the other automations become far more effective.

If you are using data entry automation to feed your CRM from external sources, adding cleanup automations at the point of entry prevents bad data from accumulating in the first place. Prevention is always cheaper than remediation.