Data Hygiene: Checklist & Best Practices For a Clean CRM

Maintaining data hygiene is vital for accurate go-to-market planning, forecasting, segmentation and ABM strategies.

Yet, many organisations struggle with outdated, inconsistent, or duplicate records. Data is often siloed across teams, leading to significant inaccuracies -70% of revenue leaders lack confidence in their CRM data.

In this guide, we’ll discuss actionable data hygiene best practices for effective B2B data management that drives revenue growth. 

What is data hygiene?

Data hygiene refers to the processes and practices used to ensure that data is clean, accurate, consistent, and up-to-date. It involves identifying and correcting errors, removing duplicates, filling in missing information, and maintaining uniformity across data entries.

What’s the difference between data quality and data hygiene?

Data quality and data hygiene are closely related concepts, but they focus on different aspects of data management and maintenance.

Data quality

Refers to the overall condition of data and its ability to meet the requirements for intended use. It’s a broad, high-level concept that encompasses various attributes of data.

Data hygiene

Refers to the practices and processes used to maintain and improve data quality over time. It’s a subset of data quality management focused on cleaning, maintaining, and updating data to keep it valuable and error-free.

Why do you need good database hygiene in B2B? 

For enterprise revenue organisations, B2B data hygiene is a strategic requirement.

When customer, prospect, and account data becomes outdated, duplicated, or incomplete, it creates commercial drag across the revenue organisation. 

The scale of this issue is significant. In Validity’s State of CRM Data Management in 2024 report, 24% of CRM admins said less than half of their CRM data is accurate and complete. The most common data quality issues included incomplete data, missing data, incorrect data and duplicate records. These are the same issues that weaken segmentation, routing, forecasting and customer engagement across revenue teams.

The commercial impact is also measurable. Validity found that 31% of CRM admins reported that bad data costs them at least 20% of annual revenue. Gartner has also estimated that poor data quality costs organisations an average of $12.9 million per year. 

The goal of the data hygiene process is to improve the quality and reliability of data so it can be used effectively for planning, decision-making, analysis and execution. Clean, compliant and current data gives revenue teams a more accurate view of accounts, contacts, territories and market coverage. It also supports better segmentation, forecasting, routing, ABM and AI-driven workflows.

Here are the key benefits of CRM data hygiene:

1. Strengthens segmentation and market prioritisation 

Clean data enables more complete customer and account profiles. This helps sales and marketing teams refine customer segments, understand market coverage and prioritise the accounts with the strongest fit.

For organisations operating across multiple regions, this is particularly important. Strong customer data hygiene reduces wasted effort caused by outdated records, incorrect territories or incomplete account information. It gives GTM teams a clearer view of where to focus and why.

2. Improves how you define your ICP

Clean and enriched data is essential for defining and refining your ideal customer profile.

Accurate firmographic, demographic and technographic data helps revenue teams understand which accounts are most likely to convert, expand or retain. It also reveals patterns in customer needs, buying behaviour and market opportunity.

This creates a stronger foundation for targeting, personalisation and account selection.

3. Improves lead and account scoring

Data cleanliness improves the reliability of lead and account scoring by removing noise from your CRM and engagement data.

Accurate records help RevOps and revenue leaders identify high-potential accounts through predictive grading and scoring models. This allows teams to focus on quality opportunities and make better decisions about prioritisation, resourcing and next-best actions.

As AI-driven scoring becomes more common, B2B data quality becomes even more important. Poor data can distort model outputs and direct teams towards the wrong accounts.

4. Supports accurate routing and consistent execution 

With accurate, up-to-date data, organisations can route leads and accounts based on criteria such as company size, location, industry, territory, or ownership.

This improves response times and reduces operational friction between sales, marketing and RevOps. It also ensures the right teams engage the right accounts with the right context.

For enterprise organisations, this supports more consistent execution across markets and teams.

5. Improves customer success and expansion planning 

Good data practices, such as routinely cleaning your data, help customer success teams identify risks, expansion potential, and product adoption opportunities.

Accurate customer data makes it easier to understand account structures, stakeholder changes and engagement patterns. This supports faster responses to customer needs, better account planning and more relevant expansion conversations.

Over time, this can improve retention, increase customer lifetime value and strengthen the customer experience.

6. Reduces regulatory and compliance risk 

In the UK and Europe, compliance is a commercial requirement.

Regular B2B data hygiene helps ensure records remain accurate, relevant, and usable in accordance with applicable privacy and communication rules, including GDPR and PECR.

It supports stronger governance, reduces unnecessary exposure and protects brand trust.

7. Improves CRM quality and revenue predictability 

A CRM filled with duplicate, stale or incomplete records weakens alignment across sales, marketing and operations.

Sticking to CRM data hygiene best practices ensures your organisation has a trusted operating layer. It reduces gaps, inconsistencies and duplicate records, giving teams a shared view of accounts, contacts and pipeline activity.

The result is greater confidence in planning, execution and performance measurement.

8. Strengthens ABM and customer experience 

Account-based marketing depends on accurate account structures, current roles and relevant market context.

Marketing data hygiene ensures segmentation reflects the real state of each account. It reduces the risk of targeting the wrong contact, of relying on outdated job titles, or of building campaigns around inaccurate assumptions.

For enterprise teams, this improves relevance, protects credibility and supports more effective engagement across complex buying groups.

9. Creates a stronger foundation for AI-driven revenue operations 

AI workflows, predictive models and automated revenue processes are only as reliable as the data beneath them.

Poor data does not stay contained. It is amplified. Inaccurate records can distort account scoring, forecasting, routing, segmentation and next-best-action recommendations.

Clean, current and well-governed data gives AI systems the foundation they need to produce outputs revenue leaders can trust.

Looking for more insights?

Our RevOps guide will help you establish a Single Source of Truth in your RevOps function!

Data hygiene best practices

1. Define and standardise data fields

Data hygiene and validation start with knowing which data matters to your business and how it should be captured.

Enterprise revenue teams often manage data across CRMs, ERPs, spreadsheets, cloud storage, APIs and local databases. Without clear standards, these systems can quickly become inconsistent.

Company names vary. Job titles are entered differently. Phone numbers miss country codes. Regions and industries are defined in multiple ways.

The first step is to review where your data lives and how it’s structured.

During the data discovery phase, you should:

• Identify all data repositories, including CRMs, ERPs, spreadsheets, cloud storage, APIs and local databases.
• Analyse the types of data stored, such as text, numeric data, transactional data, metadata and firmographic data.
• Review which fields are essential for segmentation, routing, scoring, forecasting and compliance.
• Remove or deprioritise fields that are rarely used or poorly maintained.

Once you’ve identified the fields that matter, define clear data entry standards.

For example:

• Dates: use ISO 8601 format, such as YYYY-MM-DD.
• Phone numbers: include country codes (for example, a US country code)  and use a consistent structure  (+1-555-555-5555).  
• Addresses: follow recognised postal standards for each market.
• Job titles, industries and regions: use predefined dropdowns rather than free-text fields where possible.

This creates consistency at the point of entry and makes data easier to use across teams, systems and markets.

Sid Kumar, AVP of Revenue Operations, GTM Strategy & Planning at Databricks, said:

“It’s easy to get caught up in data for data’s sake, and more is not necessarily better in this context.”

“I think being targeted and focused about what you’re using your data for and how it’s helping you connect your go-to-market strategy with your customers is essential.”

Data often has a shelf life, and knowing when it is 70-80% accurate is usually enough to base healthy, conscious decisions on.

As Sid explained:

“You sometimes have to accept it’s never going to be perfect. There’s no such thing as ‘perfect’ data, and as soon as it becomes perfect, normally it’s outdated and stale.”

2. Adopt segmentation

With clean data, teams can create more complete customer profiles and better comprehend their audiences and customer behaviour.

Jeff Ignacio, Head of GTM Operations and Growth at Regrow Agriculture, said:

“You have to start by looking at what segments matter.”

“Generally, how you segment could be based on demographic, firmographic or psychographic data, but data can be faulty or hard to come by. When you don’t have third-party enrichment tools that could provide you with the best in data for those segments, this can lead to some pitfalls.”

Segmentation can inform your GTM strategy, as marketing and sales teams can generate relevant, refined customer segments and optimise the customer journey.

As Sid shared:

“You need to focus on how data is helping you connect your go-to-market strategy with your customers.  

“You should start top-down and get a real perspective of your total addressable market. Then you can understand what segment of that total addressable market you feel you have the real right to win as a company.”

“You have to go and look at what data you need to understand the firmographics, demographics, technographics and everything about your prospects in that segment.”

“That way, you can understand where you’re going to orient your go-to-market motions around and get smarter about your prospects and existing customers.”

3. Enrich your data

Your organisation must balance internal and external data. Internal data highlights your company’s customers, transactions, and potential partners.

However, when it comes to prospecting, segmentation, and forecasting, these might not provide a complete and comprehensive enough view when defining your market. They can also include inaccuracies.

As Sid Kumar said:

“You tend to get more data as a company starts to become larger, but you’ve really got to find a balance between first-party and third-party data.”

“I think you’re naturally going to have a bigger mix of first-party data down in the lower end of the market, and then you’re going to have to complement that with third-party data when you start to go upmarket.”

Refreshing and enriching your data with third-party providers is crucial for maintaining data hygiene. Third-party data is more accurate and less error-prone, making it cleaner and more current.

As contact information and the marketplace change, data decays quickly. This means that sales, marketing and CS reps risk sending messages to the wrong contacts.

Data hygiene software like Cognism can provide accurate phone numbers and enrich contact data instantly to clean up historical contact records.

4. Leverage automation tools

You can automate data integration through API connectors, which link data sources to the business applications that need them. This streamlines data provision and improves the timeliness of data delivery.

Human input error is inevitable and a primary cause of bad data. You can use tools like Trustmi fraud detection to improve oversight and systems that automatically enrich, clean and validate data to ensure it is actionable and complete

Automated data hygiene can also help remove duplicates. Duplicate records cause confusion, waste storage space, and lead to inaccurate reporting.

5. Remove silos

In many organisations, sales and marketing teams use different systems and data standards, leading to inconsistent data formats. Over time, this creates conflicting views of accounts, contacts, territories and pipeline.

A strong culture of keeping your data clean helps revenue teams work from the same trusted foundation.

Integrating databases and encouraging collaboration across GTM teams improves alignment on data accuracy, ownership and usage. It also reduces the silos that weaken segmentation, reporting, routing and forecasting.

Clear governance should define:

• Which data fields matter most
• Who owns each field
• How records are created, updated and removed
• How duplicates are managed
• How enrichment is applied
• How compliance requirements are handled
• How data quality is measured over time

Data security should also be part of the hygiene process. It protects the organisation, customers and prospects from breaches, misuse and data loss.

To strengthen data security:

• Use role-based permissions to limit access to sensitive data
• Audit access logs to ensure data policies are followed
• Encrypt sensitive data in transit and at rest
• Review whether data handling complies with relevant regulations, including GDPR, PECR, HIPAA and CCPA where applicable
• Establish processes to monitor and report data breaches promptly

Implementing these data hygiene best practices helps keep B2B data accurate, actionable, compliant and aligned with commercial priorities. For enterprise revenue teams, this creates a more reliable foundation for planning, execution and growth.

For more tips on revenue operations data hygiene, take a listen to this podcast.

5-step plan to improve data hygiene

Maintaining CRM data hygiene is vital for organisations that rely on accurate B2B data for decision-making.

If you don’t keep your data clean, you risk the following: 

1. Poor data can lead to up to a 12% loss in revenue.
2. Data quickly becomes stale; regular updates are essential to protect ROI.
3. Data gaps hinder insights, leading to incorrect reporting and predictions.
4. Incomplete data skews understanding of customer segments and ideal customer profiles (ICPs).
5. Incorrect audience segmentation can lead to misfocused business strategies, neglecting key areas that drive conversions.
6. Poor data hampers personalised customer experiences, negatively impacting ROI, conversion rates, and satisfaction.
7. Inaccuracies in contact information (names, job titles, email addresses) can hinder outreach and waste time.
8. Misleading information leads reps to reach out to the wrong prospects, resulting in significant losses.

Here are five steps to follow to keep on top of your CRM data hygiene and avoid the above-mentioned challenges:

1. Conduct regular data audits

Over time, your CRM data can become disorganised—errors occur, duplicates pile up, and some records become outdated. Conducting regular audits allows you to identify these issues before they become significant problems.

Schedule periodic reviews of your data to identify duplicates, outdated information, or inaccuracies. You can use automated tools or do manual checks to correct errors and standardise formats.

How to do it:

• Review your database every 3-6 months.
• Look for incomplete fields, duplicate entries, and outdated records.
• Use tools like Excel, Google Sheets, or data cleansing tools like Cognism to help automate the process.

Darwinbox uses Cognism, and they’ve seen impressive results: 

“We tested 5 industry players for match rate and the percentage of enrichment occurring.” “Overall, Cognism had the most accurate contact details, and for US data alone, it was easily greater than 90% accuracy on data quality.”

Read the full case study

Siddhartha Jain
Head of Marketing Strategy and Operations @Darwinbox

2. Establish a data governance framework

Inconsistent formats for company names, job titles, and email addresses can lead to confusion within your system.

How to do it:

• Create clear policies and processes for data collection, storage, and usage.
• Assign team members responsibilities for ensuring data accuracy and compliance with regulations, such as GDPR.
• Regularly review these policies to adapt to changing business needs.

Using a B2B data enrichment provider like Cognism, you can ensure that your B2B database is standardised across your organisation.  

These tools streamline contact data management by automating formatting to ensure consistent job titles, industry classifications, and company names.

They also maintain database alignment, keeping your CRM or sales tools, such as Salesforce and HubSpot, up to date with clean data.

With easy B2B data integrations, Cognism automatically standardises incoming leads, improving workflow efficiency.

3. Remove duplicates and errors

If poor-quality data enters your system, it can lead to wasted marketing and sales efforts. Therefore, you must ensure your data is correct from the start.

According to research from Landbase, SDRs lose around 500 hours (62 working days) annually, validating and correcting contact information - that’snearly 25% of their selling capacity wasted on manual data hygiene when a tool like Cognism can automate it for them. 

If you use multiple platforms (e.g., CRM, marketing automation tools), ensure they are integrated to avoid data silos. Implement de-duplication tools to merge duplicate records and create a single source of truth for your data.

Jeff Ignacio said:

“RevOps serves as a single source of truth; it should govern your GTM motion, and your GTM notion needs to impact your revenue. Data-driven insights and decision-making underpin these three notions.”

4. Validate and update data regularly

B2B data can become outdated quickly, as people change jobs, companies expand or shrink, and contact information is updated.

Adopt effective maintenance and update procedures to keep your database accurate and up to date.

Use validation tools and processes to ensure data accuracy at the point of collection. This could include requiring mandatory fields, validating email addresses, or using dropdown menus instead of free text for critical fields like job titles or industries.

You could also consider implementing a Data as a Service (DaaS) solution to automate your business processes. DaaS is a cloud-based solution that provides organisations with real-time data by tapping into their CRM, data lakes, and databases via APIs.

The DaaS model makes data easy to integrate and access, without the burden of infrastructure. Cognism’s DaaS, for example, offers flexible delivery options to integrate B2B data in the format and frequency of your choice:

• API & Flat File delivery: Real-time enrichment or scheduled batch drops via Snowflake, S3, Google Cloud, Databricks or SFTP
• Data quality & compliance: Audit-ready metadata and consent trail are aligned with GDPR, CCPA, and PECR.
• Continuous value realisation: ROI benchmarking, usage health reviews and expansion scoping.

5. Train employees on data best practices

Educate your team about the importance of data hygiene and provide them with the tools and knowledge to maintain it. Encourage habits such as updating records after client interactions and verifying data accuracy before adding them to your systems.

Following these steps ensures that your B2B data is accurate, reliable, and actionable, leading to better decision-making and improved business outcomes.

Top 3 data hygiene services

The right data hygiene service should do more than clean obvious CRM errors. For enterprise revenue teams, it should improve the quality, consistency and usability of the data that supports GTM planning, segmentation, forecasting and AI-driven workflows.

Here are three data hygiene services to consider. Each can support HubSpot CRM data hygiene and Salesforce data hygiene.

1. Cognism Enrich

Cognism Enrich helps revenue teams keep CRM data accurate, complete and ready to act on with compliant, high-quality B2B data. It is particularly strong for organisations operating across Europe and the UK, where data accuracy, coverage and compliance are central to revenue execution.

With Cognism Enrich, teams can update existing CRM records, fill missing fields and improve the quality of account and contact data. Cognism supports integrations with Salesforce and HubSpot, as well as other revenue systems such as Microsoft Dynamics 365, Outreach, and Salesloft.

For Salesforce users, Cognism supports both Instant Enrich and Scheduled Enrich. Instant Enrich allows teams to update records on demand, while Scheduled Enrich refreshes existing Salesforce records on a regular cadence. This helps reduce data decay and keeps account and contact information up to date over time.

Cognism Enrich is best suited to revenue organisations that need a trusted European data foundation for CRM quality, segmentation, territory planning, account prioritisation and compliant GTM execution.

“Cognism blew ZI out of the water. Cognism’s match rate was 98% vs. 72% by ZoomInfo, and we found that Cognism returned a ton more phone numbers.” “When we called them to verify the numbers, the call connect rate was 22% with Cognism and 14% with ZoomInfo.”

Read the full case study

Amanda Newman
SDR Manager @User Evidence

2. ZoomInfo Enrich

ZoomInfo Enrich helps teams clean, complete, and update CRM and marketing automation data. It can append and refresh records using ZoomInfo’s B2B data, while applying custom parameters to maintain data quality across systems.

ZoomInfo Enrich integrates with Salesforce, HubSpot, Marketo, Eloqua and Microsoft Dynamics, making it a relevant option for organisations with complex revenue technology stacks.

It is often considered by teams seeking broad B2B enrichment across sales, marketing, and operations workflows, particularly in North American markets.

See how ZoomInfo compares to Cognism. 

3. HubSpot Breeze Intelligence

HubSpot Breeze Intelligence, which incorporates Clearbit’s enrichment capabilities, is designed to enrich contact and company records inside HubSpot’s Smart CRM. HubSpot says its data enrichment can add more than 40 data points and draws on over 200 million continuously refreshed profiles.

For HubSpot-led teams, Breeze Intelligence can help improve segmentation, reporting, lead qualification and workflows without adding a separate enrichment platform. It is particularly useful for email data hygiene and for organisations that are already standardising their revenue operations around HubSpot.

However, teams operating across multiple CRMs, data warehouses, or complex European markets may need to assess whether native CRM enrichment provides sufficient coverage, governance, and flexibility for enterprise GTM execution.

See how Cognism compares to Clearbit.

Ready to make B2B data hygiene a revenue advantage?

Clean CRM data is only valuable when it helps teams make better commercial decisions.

Cognism gives revenue organisations the trusted European B2B data they need to understand their markets, prioritise accounts with confidence, and operate across regions with greater consistency.

With Cognism’s Web App and Enrich, your teams can strengthen the data layer behind planning, segmentation, forecasting and AI-driven workflows, without adding more complexity to your GTM operations.

For organisations growing across Europe and the UK, this means fewer assumptions, stronger governance, and a clearer view of where revenue opportunities exist.

Book a demo to see how Cognism can help maintain B2B data hygiene, improve execution, and drive more predictable growth.