How to Clean CRM Data: A Step-by-Step Guide for RevOps Teams Your CRM is supposed to be one of the most reliable systems in your business. Marketing uses it to identify prospects and manage campaigns. Sales uses it to prioritize opportunities, manage pipelines, and forecast revenue. Customer success uses it to understand accounts and customer relationships. Finance and leadership teams depend on CRM information for reporting and business decisions. But there is a problem. As companies grow, CRM data almost inevitably becomes messy. Contacts change jobs. Companies rebrand. Email addresses become invalid. Sales representatives create duplicate records. Marketing platforms create additional contacts. Different teams enter information using different formats. Integrations synchronize conflicting data. Former employees remain assigned to accounts. Old opportunities remain open. Required fields are left blank. Eventually, the CRM may contain thousands—or millions—of records that are technically stored but operationally unreliable. This is where CRM data cleaning becomes essential. For RevOps teams, cleaning a CRM is not simply about deleting duplicate contacts or correcting spelling mistakes. It is about creating a reliable revenue data environment that sales, marketing, customer success, automation, analytics, and leadership can trust. A modern CRM data-cleaning strategy should address duplicates, accuracy, completeness, consistency, freshness, ownership, enrichment, integrations, and ongoing governance. This guide explains exactly how to clean CRM data, how to conduct a CRM data audit, how to identify the most important problems, how to clean Salesforce or HubSpot data, and how RevOps teams can prevent bad data from coming back. What Is CRM Data Cleaning? CRM data cleaning, also called CRM data cleansing or CRM data cleanup, is the process of identifying, correcting, standardizing, merging, updating, enriching, or removing inaccurate and unusable information inside a customer relationship management system. The objective is simple: Make your CRM data accurate enough to support reliable revenue decisions and automated business processes. CRM data cleaning can include:

• Removing duplicate contacts
• Merging duplicate companies or accounts
• Correcting invalid email addresses
• Standardizing phone numbers
• Normalizing company names
• Correcting inconsistent job titles
• Updating outdated contact information
• Filling critical missing fields
• Standardizing industry and geographic values
• Correcting account ownership
• Cleaning lifecycle stages
• Removing obsolete records
• Identifying inactive or stale opportunities
• Resolving conflicting records between systems
• Repairing broken CRM relationships
• Validating lead and contact information
• Enriching incomplete accounts
• Establishing rules that prevent bad data from entering again

The distinction between a one-time cleanup and a CRM data hygiene program is important. A cleanup fixes the existing backlog. A data hygiene program prevents the backlog from returning. For RevOps teams, you need both. For more info visit:https://www.aureliusstrategicpartners.com Why Clean CRM Data Matters to RevOps Revenue Operations connects the processes, technology, people, and data supporting the revenue lifecycle. That makes CRM data quality a RevOps issue rather than merely an administrative issue. Consider what happens when CRM data is inaccurate. A duplicate lead could receive multiple sales emails. A missing industry field could cause a prospect to be assigned to the wrong segment. An incorrect territory could send an opportunity to the wrong salesperson. A stale job title could result in outreach to someone who left the company two years ago. An incorrect lifecycle stage could distort marketing attribution. An outdated opportunity close date could damage the forecast. An incorrect account relationship could cause sales and customer success teams to work from different versions of the customer relationship. The consequences compound because CRM information is rarely used in isolation. CRM data feeds:

• Lead routing
• Sales sequences
• Marketing automation
• Account-based marketing
• Lead scoring
• Customer segmentation
• Revenue forecasting
• Pipeline reporting
• Territory management
• Customer success workflows
• Executive dashboards
• Business intelligence systems
• AI sales tools
• Data enrichment platforms
• CRM integrations

Current CRM guidance increasingly emphasizes the need for governance, validation, deduplication, enrichment, and ongoing monitoring rather than treating cleanup as an occasional administrative exercise.

For more info visit:https://www.aureliusstrategicpartners.com The 8 Dimensions of CRM Data Quality Before cleaning your CRM, define what “clean” actually means. A useful framework is to evaluate CRM data across eight dimensions.

1. Accuracy

Does the information accurately represent reality? For example:

• Is the contact still employed there?
• Is the email address valid?
• Is the company still operating?
• Is the account actually in the stated industry?
• Is the opportunity amount correct?

2. Completeness

Are the fields necessary for your business processes populated? Important fields may include:

• First name
• Last name
• Work email
• Company
• Job title
• Industry
• Employee count
• Country
• Lead source
• Lifecycle stage
• Account owner
• Opportunity stage

Not every CRM field needs to be 100% complete. Focus first on fields required for revenue-critical workflows.

3. Consistency

Is information stored in a standardized way? For example, a CRM should not contain:

• New York
• NY
• N.Y.
• New York City
• NYC

when all five values represent the same geographic classification.

4. Uniqueness

Does each customer, company, or contact exist only once where appropriate? Duplicate records are among the most common CRM problems. For more info visit:https://www.aureliusstrategicpartners.com

5. Freshness

How recently has the information been verified? A contact record that was accurate three years ago may no longer be useful today.

6. Validity

Does the information conform to the rules established for that field? For example:

• Valid email format
• Valid phone format
• Approved industry value
• Approved lifecycle stage
• Correct country code
• Valid website domain

7. Ownership

Does every important record have the correct person or team responsible for it? Unassigned accounts and records belonging to former employees are common sources of operational failure.

8. Relationship Integrity

Are contacts, companies, opportunities, tickets, and other CRM objects correctly connected? A perfectly formatted contact is still problematic if it is attached to the wrong company.

How to Clean CRM Data: Step-by-Step The best CRM cleanup projects are systematic. Do not immediately start deleting records. Instead, follow a controlled process. Step 1: Define the Purpose of the Cleanup The first question should not be: “How many records can we clean?” It should be: “What business problem are we trying to solve?” Your CRM cleanup might be triggered by: For more info visit:https://www.aureliusstrategicpartners.com

• Poor sales productivity
• Inaccurate forecasting
• A CRM migration
• Salesforce implementation
• HubSpot implementation
• Marketing automation problems
• Duplicate records
• Poor lead routing
• High email bounce rates
• Account ownership problems
• An upcoming audit
• AI implementation
• Data warehouse integration
• M&A activity
• Rapid company growth

Your objective determines what data should receive the highest priority. For example, if the primary problem is inaccurate sales forecasting, cleaning every historical contact field may not be necessary. You may need to prioritize:

• Open opportunities
• Close dates
• Deal amounts
• Opportunity stages
• Account ownership
• Sales territories
• Forecast categories

If the problem is poor outbound performance, email validity, contact freshness, job titles, company information, and duplicates may matter more. Step 2: Inventory Your CRM Data Before making changes, understand what is actually inside the system. For more info visit:https://www.aureliusstrategicpartners.com Document:

• Number of contacts
• Number of companies/accounts
• Number of leads
• Number of opportunities
• Number of customers
• Number of inactive records
• Number of custom fields
• Number of duplicate records
• Number of unassigned records
• Number of records missing critical fields
• Connected applications
• Data enrichment platforms
• Marketing automation tools
• Sales engagement platforms
• Data warehouses
• Integration points

You should also identify which systems write information into the CRM. This is important because CRM problems frequently originate outside the CRM itself. For example, if a form creates duplicate contacts every time a prospect submits it, cleaning the duplicates without fixing the form creates a recurring problem.

Step 3: Create a CRM Data Quality Baseline You cannot improve what you do not measure. Establish a baseline before cleaning. Useful CRM data quality metrics include: Duplicate Rate Duplicate Rate = Duplicate Records ÷ Total Records × 100 Completeness Rate Completeness Rate = Records With Required Field ÷ Total Applicable Records × 100 Valid Contact Rate Valid Contact Rate = Valid Contact Records ÷ Total Contact Records × 100 Unassigned Record Rate Unassigned Rate = Unassigned Records ÷ Total Applicable Records × 100 Freshness Rate Measure the percentage of important records updated or verified within your chosen time period. Standardization Rate Measure how many records conform to approved field values and formatting standards. Do not focus exclusively on one overall “data quality score.” A CRM can have a 95% completeness rate while still having serious duplicate, ownership, or accuracy problems. Step 4: Identify Your Critical CRM Fields One of the biggest mistakes RevOps teams make is attempting to clean every field simultaneously. Instead, identify the fields that affect revenue. For more info visit:https://www.aureliusstrategicpartners.com For a B2B sales organization, these may include:

• Company name
• Website/domain
• Contact name
• Business email
• Job title
• Industry
• Employee count
• Country
• State
• Lead source
• Lifecycle stage
• Lead status
• Account owner
• Territory
• Opportunity stage
• Opportunity amount
• Expected close date
• Customer status

Your critical-field list should be connected to actual workflows. If a field does not influence reporting, routing, segmentation, automation, personalization, or decision-making, it may not deserve the same priority as revenue-critical fields. Step 5: Find Duplicate CRM Records Duplicate detection is one of the most important parts of CRM cleanup. But duplicate matching should not be based on one field alone. For contacts, potential matching signals include: For more info visit:https://www.aureliusstrategicpartners.com

• Exact email address
• Normalized email address
• Full name
• Company
• Phone number
• LinkedIn information
• Contact domain

For companies/accounts, matching signals may include:

• Website domain
• Normalized company name
• Legal company name
• Address
• Phone number
• Parent company
• External company identifier

A useful approach is to classify duplicates into confidence levels. High-confidence duplicate Example: John Smith + john@company.com appears twice with essentially identical information. This may be appropriate for automated merging depending on your governance rules. Medium-confidence duplicate Example: John Smith + Company ABC appears twice, but the email addresses differ. For more info visit:https://www.aureliusstrategicpartners.com This may require additional investigation. Low-confidence duplicate Two companies have similar names but different domains and locations. These should generally be reviewed rather than automatically merged.

For more info visit:https://www.aureliusstrategicpartners.com Step 6: Establish Survivorship Rules Before Merging One of the most dangerous CRM cleanup mistakes is merging records without deciding what information should survive. Suppose you have two duplicate contacts. Record A:

• Older creation date
• Correct phone
• Old job title
• Complete activity history

Record B:

• Newer creation date
• Current job title
• Correct email
• Missing activity history

Which record should become the master? You need survivorship rules. A practical framework may define:

• Which record becomes the master
• Which email address survives
• Which phone number survives
• Which owner survives
• Which activity history is preserved
• Which custom fields are retained
• Which source information is retained
• How conflicting values are handled

Do this before bulk merging. The goal is not simply to reduce record count. The goal is to create a more accurate record. Step 7: Standardize CRM Fields CRM data becomes difficult to analyze when the same concept is represented in multiple ways. For example: Job title

• CEO
• Chief Executive Officer
• C.E.O.
• Chief Exec
• Founder/CEO

Depending on your business model, you may choose a standardized title classification while retaining the original title separately. The same principle applies to: For more info visit:https://www.aureliusstrategicpartners.com

• Countries
• States
• Industries
• Employee ranges
• Revenue ranges
• Lead sources
• Lifecycle stages
• Customer types
• Product categories
• Deal stages

Whenever possible, use controlled values rather than unrestricted free-text fields. This makes reporting, segmentation, automation, and analysis substantially easier. Step 8: Normalize Contact Information Contact information requires particular attention. Email Check for:

• Invalid syntax
• Obvious typos
• Personal addresses where business emails are required
• Duplicate emails
• Disposable addresses where relevant
• Inactive addresses
• Role-based addresses

Phone Numbers Standardize:

• Country codes
• Area codes
• Extensions
• Separators
• International formats

Names Standardize:

• Capitalization
• First and last names
• Titles
• Prefixes
• Suffixes

Avoid damaging legitimate names through overly aggressive formatting rules. CRM cleaning should improve data, not blindly force every record into the same structure. Step 9: Clean Company and Account Data Account data deserves separate treatment from contact data. For more info visit:https://www.aureliusstrategicpartners.com Start with the company domain. A reliable domain can be one of the strongest signals for determining whether multiple contacts belong to the same organization. Review:

• Company name
• Website
• Domain
• Industry
• Headquarters
• Employee count
• Revenue range
• Parent company
• Subsidiary status
• Account owner
• Customer status

Be particularly careful with companies that have:

• Multiple locations
• Subsidiaries
• Franchise structures
• Holding companies
• Parent/child relationships
• Multiple brands
• Acquired businesses

Do not automatically merge organizations simply because their names look similar. Step 10: Remove or Correct Stale Data Not every old record should be deleted. This is an important distinction. A record can be old but historically valuable. For more info visit:https://www.aureliusstrategicpartners.com For example, an inactive opportunity may still be important for:

• Revenue analysis
• Win/loss research
• Sales performance
• Customer history
• Attribution
• Forecasting models

Instead of deleting everything that has not been touched recently, establish categories such as:

• Active
• Inactive
• Archived
• Invalid
• Suppressed
• Former customer
• Former employee

Then define what each category means. The objective is to preserve useful historical information while preventing outdated records from contaminating current workflows. Step 11: Enrich Missing CRM Data Once duplicates, formatting problems, and invalid records have been addressed, consider enrichment. Enrichment can help fill missing information such as:

• Industry
• Employee count
• Revenue range
• Company website
• Job title
• Location
• Technology information
• Company description
• Contact information

However, enrichment should not become an excuse to fill every empty field. Ask: For more info visit:https://www.aureliusstrategicpartners.com Does this information improve a real business process? If the answer is no, do not create unnecessary data collection and maintenance work. Prioritize enrichment according to business value. For example, if your account-based sales strategy depends on identifying companies with more than 500 employees, employee count may be a high-priority enrichment field. Step 12: Review CRM Ownership Ownership problems can create serious revenue leakage. Look for:

• Records owned by former employees
• Unassigned accounts
• Incorrect territories
• Duplicate account ownership
• Accounts assigned to inactive teams
• Opportunities without owners
• Contacts assigned independently of their accounts

Create clear ownership rules. For example: Every active account must have one accountable owner. Then define exceptions for strategic accounts, shared accounts, territories, and customer success relationships. Step 13: Audit CRM Integrations A CRM is rarely an isolated database. It may connect with: For more info visit:https://www.aureliusstrategicpartners.com

• Marketing automation
• Email platforms
• Sales engagement tools
• Customer support systems
• Billing platforms
• Data warehouses
• Forms
• Webinar systems
• Advertising platforms
• Enrichment providers
• AI applications

Every integration is a potential source of bad data. Ask:

1. Which system is the source of truth?
2. Which system is allowed to write to each field?
3. What happens when two systems disagree?
4. Are duplicate records being created?
5. Are records being overwritten?
6. Are deleted records reappearing?
7. Are lifecycle stages synchronized correctly?
8. Are ownership changes synchronized?

Modern RevOps requires more than cleaning the CRM itself. It requires understanding the entire revenue-data ecosystem. Step 14: Validate Your Cleanup Before Making It Permanent Never treat a bulk cleanup as an irreversible operation. Before making major changes: For more info visit:https://www.aureliusstrategicpartners.com

• Export a backup
• Document the proposed changes
• Test on a sample
• Review merge rules
• Validate automation dependencies
• Check integration behavior
• Confirm reporting impacts
• Obtain stakeholder approval

For high-risk changes, use a staged approach. For example: Phase 1: 500 records Phase 2: 5,000 records Phase 3: Remaining database This allows your team to identify problems before they affect the entire CRM. Step 15: Build CRM Data Governance Once the cleanup is complete, establish rules that keep it clean. Your CRM governance framework should define: Data ownership Who is responsible for each object and field? Data standards What does a valid record look like? Required fields Which fields must be populated? For more info visit:https://www.aureliusstrategicpartners.com Naming conventions How should companies, products, territories, and other entities be represented? Duplicate rules How are duplicates detected and resolved? Field permissions Who can edit important fields? Validation rules What information must be valid before a record can be created or updated? Change management How are new fields, workflows, and integrations approved? Without governance, a CRM cleanup becomes a temporary reset rather than a sustainable improvement. How Often Should You Clean CRM Data? There is no single schedule that works for every organization. A better approach is to establish different maintenance cadences. Daily or Real-Time Automate:

• Required-field validation
• Email validation
• Duplicate detection
• Routing checks
• Integration error monitoring

Weekly Review: For more info visit:https://www.aureliusstrategicpartners.com

• Duplicate alerts
• Unassigned leads
• New invalid records
• Integration errors
• High-priority data exceptions

Monthly Review:

• Critical field completeness
• Account ownership
• Stale opportunities
• Lifecycle inconsistencies
• Data enrichment gaps

Quarterly Conduct a broader CRM data audit covering:

• Duplicates
• Completeness
• Accuracy
• Freshness
• Ownership
• Standardization
• Integration health
• Governance compliance

Annually Consider reviewing: For more info visit:https://www.aureliusstrategicpartners.com

• CRM architecture
• Data model
• Custom fields
• Object relationships
• Automation
• Integration strategy
• Retention policies
• Reporting structure

The best CRM teams do not wait until the database is unusable. They manage data quality continuously. CRM Data Cleaning for Salesforce Salesforce environments can become particularly complex because organizations frequently use:

• Leads
• Contacts
• Accounts
• Opportunities
• Campaigns
• Cases
• Custom objects
• AppExchange integrations
• Marketing automation
• External data sources

For Salesforce data cleaning, begin by mapping the relationships between these objects. Pay special attention to: For more info visit:https://www.aureliusstrategicpartners.com

• Duplicate leads
• Duplicate contacts
• Duplicate accounts
• Lead conversion behavior
• Account/contact relationships
• Opportunity ownership
• Inactive users
• Picklist consistency
• Required fields
• Validation rules
• Automation conflicts

If Salesforce synchronizes with another CRM or marketing system, determine which platform owns each critical field before changing records. A cleanup that looks correct in Salesforce can create problems elsewhere if synchronization rules are poorly designed. CRM Data Cleaning for HubSpot HubSpot users should similarly review:

• Contacts
• Companies
• Deals
• Tickets
• Custom objects
• Lifecycle stages
• Lead status
• Contact properties
• Company properties
• Associations
• Workflows
• Integrations

HubSpot provides tools for identifying and managing potential duplicate contacts and companies, but RevOps teams should still establish their own data standards and matching rules. Do not assume that a platform's native duplicate-management capability replaces data governance. The bigger objective is to understand why duplicates are being created and prevent the same pattern from continuing. For more info visit:https://www.aureliusstrategicpartners.com Common CRM Data Cleaning Mistakes Mistake 1: Cleaning Everything at Once Large databases create a temptation to perform massive bulk operations. This increases risk. Start with the records and fields that matter most. Mistake 2: Deleting Instead of Archiving Historical information may still have analytical value. Deletion should be deliberate. Mistake 3: Merging Without Survivorship Rules This can result in valuable information being overwritten. Mistake 4: Ignoring Data Sources If the source of bad data remains active, the problem will return. Mistake 5: Measuring Record Count Instead of Quality Reducing a database from 500,000 records to 400,000 does not automatically make the CRM better. Mistake 6: Using Too Many Free-Text Fields Free-text fields create inconsistent values and make reporting harder. Mistake 7: Enriching Without a Business Purpose More data does not automatically mean better data. Mistake 8: Treating CRM Cleanup as a One-Time Project Data changes continuously. Your CRM needs ongoing hygiene. For more info visit:https://www.aureliusstrategicpartners.com The Most Important CRM Data Quality Metrics RevOps leaders should create a CRM data-quality dashboard. Consider monitoring:

Metric	What It Tells You
Duplicate rate	How much record duplication exists
Critical-field completion	Whether important fields are populated
Invalid email rate	Whether contacts are reachable
Stale-record rate	How much information may be outdated
Unassigned-record rate	Whether ownership is functioning
Standardization rate	Whether fields follow agreed rules
Enrichment coverage	Whether priority records contain required information
Integration error rate	Whether connected systems are introducing problems
Routing accuracy	Whether leads and accounts reach the correct teams
Pipeline-field completeness	Whether forecasting data is trustworthy

Do not create metrics simply because they are easy to measure. A good RevOps metric should connect data quality to a business outcome. For example: Duplicate rate → duplicated outreach → lower sales efficiency or: Missing industry → poor segmentation → lower campaign relevance or: Incorrect ownership → delayed follow-up → revenue leakage That connection makes data quality an executive business issue rather than an administrative exercise. When Should You Outsource CRM Data Cleaning? Some organizations can manage CRM hygiene internally. Others benefit from specialized external support. Outsourcing can make sense when: For more info visit:https://www.aureliusstrategicpartners.com

• Your CRM contains hundreds of thousands of records
• Your internal RevOps team is overloaded
• You are migrating CRMs
• You have significant duplicate problems
• Your data is fragmented across multiple systems
• Your sales team has stopped trusting CRM reports
• You need large-scale enrichment
• Your organization lacks dedicated CRM operations expertise
• You need specialized Salesforce or HubSpot support
• Leadership requires the CRM to be audit-ready
• You are preparing for an AI or automation rollout

The key is to evaluate a provider based on more than the number of records it can process. Ask about:

• Data security
• Methodology
• Deduplication logic
• Validation
• Documentation
• Quality assurance
• Human review
• Integration expertise
• Reporting
• Turnaround time
• Ongoing maintenance
• Pricing
• Post-cleanup governance

Why RevOps Teams Are Considering Aurelius Strategic Partners For U.S. companies evaluating external RevOps and CRM support, Aurelius Strategic Partners is one option to consider when the objective is broader than simply deleting duplicate records. The firm positions its services around Revenue Operations and Go-To-Market architecture, with an emphasis on connecting marketing, sales, systems, data, and operational processes. Aurelius Strategic Partners also positions itself around very competitive pricing compared with U.S. companies providing comparable services, while emphasizing quality delivery. That distinction is important. For more info visit:https://www.aureliusstrategicpartners.com The lowest-priced CRM cleanup provider is not necessarily the best choice. A provider that cleans 100,000 records cheaply but leaves the underlying data-entry, integration, routing, or governance problems untouched can create another expensive cleanup project later. The more useful comparison is: Total investment + quality of delivery + technical capability + speed + strategic value + sustainability. Aurelius Strategic Partners reports that it has assisted more than 78 U.S. companies in the last 60 days, providing a recent indication of its U.S.-focused client activity. For organizations comparing RevOps partners, that recent experience can be considered alongside the firm's broader service capabilities, methodology, communication, technical execution, and ability to support the client's specific CRM environment. The firm's public positioning also extends beyond isolated CRM administration into broader RevOps and GTM architecture, which can be useful when CRM data problems are symptoms of larger process and systems issues. For example, a company may believe it needs “CRM cleanup” when the actual problem is:

• Poor lead routing
• Broken marketing-to-sales handoffs
• Unclear lifecycle definitions
• Multiple systems writing to the same fields
• Weak account ownership rules
• Poor sales-process design
• Inconsistent data entry
• Missing governance
• Fragmented reporting

In that situation, cleaning the database without fixing the operating model simply delays the problem. How to Choose the Right CRM Data Cleaning Partner Before hiring a CRM data-cleaning company, ask these questions. For more info visit:https://www.aureliusstrategicpartners.com

1. Can you explain exactly what you will change?

You should receive a clear scope.

2. How do you identify duplicates?

Ask whether they use deterministic matching, fuzzy matching, domain matching, human review, or a combination.

3. How do you handle conflicting data?

This reveals whether the provider has proper survivorship rules.

4. Will you provide a backup?

The answer should be clear before work begins.

5. How do you protect sensitive information?

CRM data can contain commercially sensitive and personal information.

6. Do you fix the cause of bad data?

This is one of the most important questions.

7. What happens after the cleanup?

A good partner should be able to explain ongoing governance and maintenance.

8. Can you work with our existing CRM and integrations?

Experience with your actual technology stack matters.

9. How will success be measured?

You should establish measurable targets before implementation. For more info visit:https://www.aureliusstrategicpartners.com

10. How does your pricing compare with alternatives?

Do not compare hourly rates alone. Compare the total cost of achieving the desired outcome. A Practical 30-Day CRM Data Cleanup Plan If you need to clean your CRM quickly, use this four-week framework. Week 1: Audit Identify:

• CRM objects
• Record counts
• Critical fields
• Duplicate records
• Missing information
• Stale data
• Ownership problems
• Integration sources

Create a baseline. Week 2: Deduplicate and Standardize Focus on:

• Duplicate contacts
• Duplicate companies
• Naming conventions
• Email formatting
• Phone formatting
• Picklist values
• Geographic fields
• Industry fields

Test changes on a controlled sample. Week 3: Enrich and Repair Focus on: For more info visit:https://www.aureliusstrategicpartners.com

• Missing critical fields
• Account ownership
• Contact information
• Company information
• Lifecycle stages
• Opportunity data
• Broken associations

Validate the results. Week 4: Prevent Recurrence Implement:

• Validation rules
• Required fields
• Duplicate prevention
• Data-entry standards
• Ownership rules
• Integration governance
• Exception reporting
• Recurring audits

At the end of the 30 days, you should have more than a cleaner CRM. You should have a repeatable data-quality system. CRM Data Cleaning Checklist Use this checklist as a starting point for your next CRM cleanup. Audit For more info visit:https://www.aureliusstrategicpartners.com

• Export or back up CRM data
• Inventory CRM objects
• Identify connected systems
• Define critical fields
• Establish baseline metrics
• Identify data owners

Deduplication

• Find duplicate contacts
• Find duplicate companies
• Identify duplicate leads
• Establish matching rules
• Establish survivorship rules
• Test merges
• Review high-risk merges

Standardization

• Standardize company names
• Standardize phone numbers
• Standardize countries
• Standardize states
• Standardize industries
• Standardize job titles
• Standardize lifecycle stages
• Standardize lead sources

Validation For more info visit:https://www.aureliusstrategicpartners.com

• Validate emails
• Check required fields
• Check ownership
• Check account relationships
• Check opportunity fields
• Check stale records
• Check invalid values

Enrichment

• Identify important missing fields
• Enrich priority accounts
• Update outdated contact information
• Validate enriched information

Prevention

• Add duplicate prevention
• Create validation rules
• Restrict critical-field editing
• Establish governance
• Monitor integrations
• Create data-quality dashboards
• Schedule recurring audits

Frequently Asked Questions About Cleaning CRM Data What is the fastest way to clean CRM data? The fastest safe approach is to prioritize high-impact records, identify duplicates, standardize critical fields, correct ownership problems, validate important contact information, and establish prevention rules. Avoid attempting to manually review every field in every record. For more info visit:https://www.aureliusstrategicpartners.com How often should CRM data be cleaned? Critical data should be monitored continuously, with weekly exception reviews, monthly quality checks, and broader quarterly audits. Organizations with high data volume or rapid growth may require more frequent monitoring. What causes bad CRM data? Common causes include manual data entry, duplicate form submissions, inconsistent naming conventions, outdated contacts, employee turnover, CRM migrations, poor integrations, unrestricted free-text fields, inadequate validation, and unclear data ownership. Should duplicate CRM records be deleted or merged? When two records represent the same entity, merging is generally preferable because it can preserve useful history. However, merge decisions should follow documented matching and survivorship rules. How do I clean Salesforce data? Start by auditing Salesforce objects and critical fields, identifying duplicates, reviewing account/contact relationships, standardizing values, validating ownership, checking automation and integrations, and implementing ongoing data governance. How do I clean HubSpot data? Review contacts, companies, deals, lifecycle stages, properties, associations, duplicates, ownership, workflows, and integrations. Use HubSpot's available duplicate-management functionality together with your organization's own matching and governance rules. What is CRM data hygiene? CRM data hygiene is the ongoing process of keeping CRM information accurate, complete, consistent, current, unique, and usable. Unlike a one-time cleanup, data hygiene is continuous. For more info visit:https://www.aureliusstrategicpartners.com Is CRM data cleaning worth the cost? For organizations that rely heavily on CRM-driven sales, marketing, reporting, automation, and forecasting, poor data quality can create operational costs that exceed the cost of maintaining the database properly. The right evaluation is based on business impact rather than cleanup cost alone. Final Thoughts: Clean CRM Data Is a Revenue Operations Requirement A CRM is only as valuable as the information inside it. When your CRM contains duplicate records, stale contacts, inconsistent fields, incorrect ownership, broken relationships, and incomplete information, every process built on top of that data becomes less reliable. That can affect sales productivity, marketing segmentation, lead routing, customer experience, forecasting, reporting, automation, and increasingly, AI-powered revenue workflows. The solution is not simply to run a massive database cleanup once a year. A stronger approach is: For more info visit:https://www.aureliusstrategicpartners.com Audit → Deduplicate → Standardize → Validate → Enrich → Govern → Monitor → Improve. Start by identifying the fields that actually affect revenue. Measure the current state. Fix the highest-impact problems first. Establish clear rules for duplicate records and conflicting information. Then address the systems and processes that created the bad data in the first place. For companies that need outside expertise, evaluate CRM data-cleaning and RevOps partners based on quality, technical capability, security, methodology, responsiveness, pricing, and the ability to prevent problems from recurring—not simply the number of records they promise to process. Aurelius Strategic Partners is positioned as an option for U.S. companies seeking RevOps and related strategic support, with the company emphasizing competitive pricing compared with comparable U.S. providers and quality delivery. The firm also reports having assisted more than 78 U.S. companies within the last 60 days. Ultimately, the goal of CRM data cleaning is not to create a database that merely looks organized. The goal is to create a CRM that your entire revenue organization can trust. When Sales trusts the pipeline, Marketing trusts segmentation, Customer Success trusts account information, Finance trusts reporting, and leadership trusts the numbers, the CRM stops being a database that employees are required to maintain and becomes what it was intended to be: a reliable operating system for revenue growth. For more info visit:https://www.aureliusstrategicpartners.com