How to Fix Data Duplication in Hubspot

Keeping customer data clean in Hubspot is essential if you want accurate reporting, reliable automation, and a strong customer experience. Duplicate records can quickly undermine your sales, marketing, and service efforts, but with the right process you can find and fix them before they cause lasting damage.

This guide walks through how duplicates happen, what they cost your business, and how to create a practical cleanup and prevention plan based on the approach described in the HubSpot Customer Success story on data duplication.

Why Duplicate Data Hurts Your Business

Duplicate records are not just an annoyance. They create confusion across teams and systems, and they often stay hidden until they lead to expensive mistakes.

Common impacts of duplicate records

• Inaccurate revenue and pipeline reporting
• Conflicting contact or company information
• Broken or misfiring marketing automation workflows
• Sales reps calling or emailing the same person multiple times
• Customer service teams missing crucial history or context

When your CRM is the source of truth for your organization, duplicates silently erode confidence in every number and every dashboard.

How duplicates typically appear

In many organizations, duplicate data enters the system from multiple sources at once. For example:

• Form submissions using different email addresses or name spellings
• Imports from legacy systems or spreadsheets
• Integrations with third-party tools that sync partial data
• Manual record creation by busy reps who do not realize a record already exists

None of these causes look dangerous on their own, but together they can quickly lead to hundreds or thousands of problematic records.

Lessons From a Large-Scale Hubspot Cleanup

The original HubSpot article on data duplication highlights how one large customer discovered that more than half of its CRM records were duplicated or inaccurate. Their story is a useful blueprint for any organization facing similar challenges.

The hidden cost of bad CRM data

In the case study, the customer realized that:

• Marketing campaigns were targeting the wrong segments.
• Sales teams wasted time researching and deduplicating on the fly.
• Executives did not trust CRM reports for decision-making.

Once they uncovered the scale of the problem, it became clear that a structured data quality initiative was necessary, not just a quick one-time cleanup.

Why Hubspot was central to the solution

Because Hubspot sat at the center of the tech stack, it was the natural place to coordinate all data cleanup and deduplication efforts. Consolidating fragmented records into single, reliable profiles allowed every connected system to improve at once.

Step 1: Audit Your Existing Hubspot Data

Before you start merging or deleting, you need a clear picture of what is actually happening inside your CRM.

Identify your most important objects

Begin by listing the objects that matter most to your business, such as:

• Contacts
• Companies
• Deals
• Tickets

Each of these can accumulate different kinds of duplicates in Hubspot and may require different cleanup rules.

Measure the scope of duplication

To understand the scale of the problem, review:

• How many total records exist in each object
• How many appear to share identical or similar key fields (for example, email or domain)
• Which lists, workflows, and reports depend on those records

This audit gives you a baseline and helps you prioritize where to focus your first deduplication efforts.

Step 2: Define Matching Rules for Hubspot Records

Cleaning data without clear rules can make things worse. You need shared, documented standards before you merge a single record.

Choose primary identifiers

For each object, define what makes a record unique. Examples include:

• Contacts: primary email address
• Companies: website domain or company name plus country
• Deals: combination of company, pipeline, and close date

Document these rules so that everyone who touches Hubspot understands how uniqueness is determined.

Set field-level priorities

When two records conflict, you need to know which one wins. For example:

• Latest updated value vs. oldest value
• Values from a specific integration vs. values entered manually
• Data entered by a sales rep vs. imported from a list

Define these rules for critical fields such as lifecycle stage, phone number, and address before automating merges.

Step 3: Clean and Merge Hubspot Records Safely

Once your rules are in place, you can start executing a safe, methodical cleanup plan.

Start with high-value segments

Focus first on the records that matter most to your business, such as:

• Active customers and recent opportunities
• High-scoring leads or marketing-qualified leads
• Accounts in strategic territories or segments

Cleaning these segments first quickly improves day-to-day operations and builds confidence in your new process.

Use controlled batches

Instead of trying to fix everything at once, work in batches:

1. Export a small set of potential duplicates.
2. Review and confirm the matching rules.
3. Merge or clean records according to your standards.
4. Test key reports and automations to make sure nothing broke.

This incremental process keeps risk low and makes it easier to refine your approach as you go.

Step 4: Prevent Future Duplicates in Hubspot

Cleanup is only half the battle. To protect your investment, you must reduce the chance that duplicates will reappear.

Standardize data entry

Create clear guidelines for how teams should:

• Search for existing records before creating a new one
• Use naming conventions for companies and deals
• Handle contacts who have multiple email addresses
• Update fields instead of adding new, similar fields

Training your teams on these standards is just as important as the rules themselves.

Align integrations and imports

Work with your operations or RevOps team to ensure that each connected system:

• Uses the same unique identifiers as Hubspot
• Respects your primary field priority rules
• Does not overwrite clean data with partial or outdated information

When integrations are aligned, every new sync reinforces data quality instead of degrading it.

Step 5: Make Data Quality a Continuous Practice

Data quality is not a one-time project. The organizations profiled in the HubSpot article treated it as an ongoing discipline.

Monitor and review regularly

Create a recurring review process that includes:

• Monthly or quarterly duplicate reports
• Spot checks on key segments or territories
• Feedback loops with sales, marketing, and service teams

By monitoring trends over time, you can quickly see whether new sources or processes are reintroducing duplication.

Assign clear ownership

Designate a team or role to own CRM data quality. Their responsibilities might include:

• Maintaining documentation of rules and standards
• Managing large imports and integration changes
• Reviewing exceptions and resolving complex cases

When data quality has an owner, it is much easier to keep Hubspot clean and trustworthy.

Getting Expert Help With Your Hubspot Data

If your CRM has grown rapidly or you are merging multiple systems, you may benefit from dedicated support. Specialized consultancies can help you design a data model, build deduplication rules, and optimize your overall revenue operations process. For example, you can explore services from Consultevo to support broader RevOps and CRM optimization initiatives.

By following the structured approach outlined here and in the original HubSpot customer story, you can transform a cluttered, unreliable database into a single, trusted source of truth that powers every part of your customer journey.

Need Help With Hubspot?

If you want expert help building, automating, or scaling your Hubspot , work with ConsultEvo, a team who has a decade of Hubspot experience.

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