New Year HubSpot Cleanup: Start Fresh with Clean CRM Data

January is when most teams set new revenue targets, launch new campaigns, and realign their go-to-market strategy. It is also when your CRM's accumulated mess from the past twelve months is most likely to bite you. Stale contacts from last year's campaigns, deals that have been sitting in "Negotiation" since March, properties nobody uses anymore -- all of it is still there, quietly degrading your data quality and making it harder to trust what you see in reports.

A new year cleanup is not just spring cleaning for your CRM. It is the foundation for accurate reporting, effective automation, and a sales team that can actually trust the data they are working with.

Here is a practical checklist for starting the year right.

Phase 1: Contact cleanup

Identify and remove stale contacts

Start with contacts who have not engaged in the past year. Create a list with these criteria:

• Last activity date is more than 12 months ago
• Last marketing email open date is more than 12 months ago
• Not associated with any deal that closed in the last 12 months
• Not a current customer

This list represents contacts who are not engaging with your marketing, not in active sales conversations, and not generating revenue. Review the list for any exceptions (VIP contacts, strategic accounts), then either delete or archive the rest.

For marketing contacts specifically, downgrade unengaged ones to non-marketing status first. This immediately reduces your marketing contact count (and potentially your HubSpot bill) without losing the records entirely.

Fix contact data quality issues

Run through these checks on your remaining contacts:

Email validity. Filter for contacts with hard-bounced email addresses (HubSpot tracks this automatically). Remove bounced contacts from marketing status.

Missing required fields. Filter for contacts missing critical properties -- email, first name, last name, company, lifecycle stage. Decide whether to enrich these records, manually complete them, or remove them.

Inconsistent formatting. This is where a bulk search-and-replace pass pays off. Common issues include:

• Names in all caps or all lowercase (search for patterns like all-uppercase names)
• Country fields with inconsistent values ("US" vs "USA" vs "United States")
• Phone numbers in mixed formats
• Job titles with inconsistent capitalization or abbreviations

A single search-and-replace operation can standardize these across thousands of records in minutes.

Merge duplicates

Run HubSpot's built-in duplicate detection (Contacts > Actions > Manage Duplicates). The tool identifies potential duplicates based on email, name, and phone number. Review the suggestions and merge what is appropriate.

Be thorough here. Duplicate contacts cause inflated marketing contact counts, fragmented engagement history, and confusion for sales reps who might reach out to the same person from two different records.

Phase 2: Company and deal cleanup

Clean up company records

Merge duplicate companies. Like contacts, companies accumulate duplicates over time. Check for companies with similar names, matching domains, or shared contacts.

Update company information. Companies get acquired, rename themselves, and change addresses. If you have been pulling company data from a third-party enrichment tool, this may be somewhat current. If not, check your largest accounts for accuracy.

Standardize company names. This is another area where bulk find-and-replace is valuable. If "Acme" appears as "ACME," "Acme Inc.," "Acme, Inc.," "Acme Incorporated," and "Acme Inc" across different records, pick one standard and fix the rest.

Close out dead deals

Filter your deal pipeline for:

• Deals with a "Last Activity Date" more than 90 days ago that are still in an open stage
• Deals with a close date in the past that are still marked as open
• Deals with no associated contacts

For deals with no recent activity, work with your sales team to either update them (if they are still live) or move them to "Closed Lost." Stale open deals distort your pipeline metrics and make forecasting unreliable.

For deals with past close dates that are still open, the close date has obviously slipped. Either update the close date to a realistic new date or close the deal.

Update deal stages and pipeline

If your sales process changed during the year -- new stages were added, old ones became irrelevant -- now is the time to clean up. Look for deals stuck in deprecated stages and move them to current ones.

Phase 3: Property and automation cleanup

Audit your properties

Over a year, teams create new custom properties for campaigns, experiments, and one-off projects. Many of these become orphaned -- the campaign ended, but the property lives on.

Go to Settings > Properties and review your custom properties for each object type. For each property, ask:

• Is this property used in any active list, workflow, or report?
• Does this property have data in more than 5% of records?
• Does anyone on the team actively use this property?

If the answer to all three is "no," archive it. You can always restore archived properties if needed.

Review workflows

Check your active workflows for:

• Workflows that should have been turned off. Campaign-specific workflows from last year that are still enrolling records.
• Workflows with errors. Check the workflow error log for any that have been failing silently.
• Workflows with outdated conditions. If you changed property values or added new ones, some workflow triggers may no longer match correctly.
• Redundant workflows. Over time, teams build new workflows without deactivating old ones that do similar things. Consolidate where possible.

Audit your forms

Forms are a common source of bad data. Review your active forms:

• Are required fields still appropriate?
• Are dropdown options up to date?
• Are any forms still collecting data for campaigns that have ended?
• Do progressive profiling settings make sense for your current strategy?

Phase 4: Reporting baseline

After cleaning your data, take a snapshot of your key metrics. This becomes your baseline for the year.

• Total contacts (marketing and non-marketing)
• Total companies
• Open deals (count and total value)
• Pipeline coverage ratio
• Average deal size
• Contact data completeness score (percentage of contacts with all required fields filled)

Save these numbers somewhere your team can reference. When Q1 reports come in, you will be comparing against a clean baseline rather than numbers inflated by stale data.

Phase 5: Set up guardrails for the new year

Cleanup is only valuable if you prevent the same issues from recurring. Put these in place:

Validation rules on forms. Require standardized formats for phone numbers, enforce dropdown selections instead of free text where possible.

Workflow-based formatting. Use workflows to auto-capitalize names, trim whitespace, and standardize simple property values as records are created or updated.

Scheduled quarterly reviews. Put a recurring calendar event for a lighter version of this cleanup at the end of each quarter. Quarterly maintenance prevents the annual cleanup from being a massive project.

Documented naming conventions. Write down how your team should format company names, deal names, and other text properties. Share it in your team's documentation.

How long should this take?

For a typical HubSpot portal with 10,000-50,000 contacts, a thorough new year cleanup takes about one to two full working days. The breakdown is roughly:

• Contact cleanup: 3-4 hours
• Company and deal cleanup: 2-3 hours
• Property and automation audit: 2-3 hours
• Reporting baseline: 1 hour
• Setting up guardrails: 1-2 hours

Bulk operations significantly speed up the data standardization parts. What would take hours of manual editing takes minutes with a search-and-replace tool that can find and fix patterns across thousands of records at once.

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A clean CRM at the start of the year is not a luxury -- it is the foundation for everything your marketing, sales, and operations teams will build in the months ahead. The investment of a day or two in January pays off in more accurate reports, better automation performance, and a team that trusts the data they are working with.