You're on a tight deadline and the clock is ticking as you're searching frantically through a chaotic mishmash of spreadsheets, trying to find a specific customer's contact information. As the minutes tick by and frustration starts to creep in, you realize that an error in your database has left you digging through outdated, incomplete, and duplicate records.
Businesses rely heavily on data to fuel growth, make informed decisions, and deliver exceptional customer experiences. However, maintaining clean, consistent, and up-to-date data is a challenge that many website and operations teams face. This messy data can lead to inefficient operations, missed opportunities, and frustrated customers.
Luckily, these blockers can be avoided by implementing data hygiene practices.
In this post, we’ll explain what data hygiene is, why you need it, and how to efficiently implement it, particularly with your CRM.
What is Data Hygiene?
Data hygiene ensures the cleanliness, accuracy, and overall quality of data within a database, which helps you better organize and leverage useful data points. It involves activities such as data cleaning, deduplication, and normalization, aiming to eliminate errors, inconsistencies, and outdated information.
Why Practice Data Hygiene?
Practicing data hygiene is like keeping your house clean and organized — it just makes life easier.
Disorganized, missing, or mismatched data can lead to inaccurate decision-making that costs your business time and money. By regularly cleaning and validating your data, you ensure that you have accurate and reliable information at your fingertips. Ultimately, good data hygiene helps you make better business decisions and provide a smoother experience for your customers.
When's the last time you spent hours fixing, filling in, or reorganizing spreadsheets filled with too many data points rather than actually using the data to make quick business calls?
While some time should be dedicated to data hygiene, it will pay off and potentially save you hours later as hygienic data prevents those last-minute time-sucks you've made a normal part of your day. .
Smoother Software Implementation
Many tools that will help you visualize, graph, make decisions, or organize contacts rely on uploaded data to be clean and easy to read so a tool's automation will understand and make sense of it.
Clean data will help your team smoothly implement great tools that make the most of the information you have, while unhygienic data will lead to a bumpy experience or low adoption of a tool you've invested your hard-earned dollars into.
7 Data Hygiene Best Practices
1. Regular Data Cleaning
Once you've done an initial cleanup of your data, data hygiene maintenance should be quicker and easier. But, you shouldn't let it fall by the wayside – which could cause you another deep cleaning session later on. Instead, follow these steps:
- Conduct periodic reviews to identify and remove duplicate records, such as merging multiple entries for the same customer within your CRM system.
- Proactively validate and correct any incomplete or inaccurate data. For instance, ensure that all customer records have complete contact information, including email addresses and phone numbers.
- Regularly delete outdated or irrelevant data, such as old leads that have not shown any engagement for an extended period.
- Use automated tools or workflows to streamline the data cleaning process, saving time and maintaining consistency.
- Schedule regular data cleaning activities to keep your database clean and up to date.
2. Data Validation
Implementing data validation rules, using spreadsheet or data platform tools, will ensure that data entered is accurate and meets specific criteria. For example, you can validate email addresses to ensure they have the correct format and domain.
Below are a few examples of other validations you can try or keep in mind.
- Validate fields like phone numbers, postal codes, or credit card information to avoid errors or discrepancies in the data.
- Use real-time validation techniques to catch and prompt users about any data entry errors or inconsistencies.
- Provide meaningful error messages and guidance to users when validation rules are not met, helping them correct mistakes.
- Regularly review and update validation rules to align with changing data requirements or industry standards.
If your dashboard, database, or spreadsheet will be used by other stakeholders or connected to digital tools, you'll want formatting, writing styles, and other elements standardized, aligned, and consistent. Aside from making your data look and feel more professional, standardization can further help you connect automations, data validations, and data tools to your database.
Below are just a few best practices that can help.
- Use consistent formats and naming conventions for data entry fields. For example, standardize how dates are formatted, or ensure that job titles are consistently entered across the database.
- Normalize data by using predefined values or categories, avoiding variations or misspellings. For instance, use a standardized list of countries or industry classifications.
- Develop guidelines or templates for data entry, ensuring consistency within your organization. This helps eliminate errors and inconsistencies caused by manual entries or other teammates using your spreadsheets.
- Regularly monitor data inputs to ensure they follow standardization guidelines, providing feedback and corrections when necessary.
4. Regular Data Updates
Perform routine data audits to identify outdated records, such as contacts who have not engaged with your organization for a prolonged period. Archive or update these records accordingly.
You should also use data enrichment tools, applications for merging data from an existing database with third-party data, or external data sources like open data, paid data, shared data, and web data, to validate and update existing records with accurate information, such as updating job titles or company details.
You'll want to monitor, regularly review, and update records like contact details, product preferences, or company information with new customer interactions.
Lastly, encourage customer feedback or self-service options for users to update their own information, keeping your data up to date without you needing to step in.
5. Data Governance
When using even the smallest piece of customer or audience data, you'll want to make sure you're leveraging it in an ethical, legal, and thoughtful way that will ideally benefit those that interact with your brand. To do this, implement data governance policies.
Once you've developed, reviewed, and implemented data governance policies, designate data owners or stewards responsible for defining and enforcing data governance policies and procedures within your organization.
For example, appoint a data governance team to oversee the integrity and security of your data, or delegate existing employees to a task force that works together to ensure governance on a more part time basis, while juggling other data tasks.
A few other best practices to consider include:
- Implementing data access controls and permissions to ensure that only authorized personnel can modify or access sensitive data.
- Establishing data governance policies that outline data retention periods, privacy regulations compliance, and data sharing agreements with third parties.
- Regularly monitoring, auditing, and assessing data quality and compliance metrics to identify areas for improvement and ensure adherence to data governance standards.
6. Data Purge Processes
When and if you have way too much excess, useless, duplicate, out-of-date, or incorrect data, develop a data purge strategy to identify and remove unnecessary data from your database. For instance, delete expired leads or contacts that are no longer relevant to your business.
To do this:
- Establish clear criteria and rules for purging data, such as removing records that have not shown any activity within a specific time frame.
- Set up automated data purge workflows with appropriate approvals and safeguards to ensure the process is efficient and secure.
- Review and document the data purge process, including any legal or compliance considerations, to maintain transparency and accountability.
- Regularly evaluate and adjust your data purge strategy to align with evolving business needs and data retention policies.
7. CRM Data Hygiene
Having clean CRM data is crucial as it ensures accurate customer insights, enables effective targeted marketing campaigns, and facilitates seamless communication or engagement with prospects and clients.
Want to learn more about this? In the section below, we'll give a step-by-step guide on how to do this with tools like HubSpot’s Data Quality Software.
8. Employee Training
Once you've developed policies, processes, standardizations, and automations around your data, it's vital to teach others at your organization how to leverage, add to, or update these datasets to ensure they keep data clean and don't undo all of your hard work.
Provide comprehensive training, presentations, videos, and our educational documentation to employees that covers:
- The importance of data hygiene
- Their individual responsibilities in maintaining data quality.
- Data entry, updating, and standardization best practices, emphasizing the significance of accurate and complete information at the point of entry.
- Data validation techniques, automations, and tools used to ensure data accuracy and prevent errors.
As your teammates dig deeper into the data, continue to conduct regular workshops or seminars to keep them updated on the latest data hygiene practices, privacy regulations, and compliance requirements. By doing so, you'll foster data accountability and promote continuous learning .
How to Implement CRM Data Hygiene
1. Build a Data Model
A well-structured data model is key to achieving high data quality. Define your data model by identifying the key fields and properties that you want to track in your CRM system. This will provide a solid foundation for organizing and categorizing your data accurately.
HubSpot's data model feature provides you with a clear visualization of how your data is organized within the CRM. This consolidated view includes standard objects, properties, and associations, offering a comprehensive understanding of data relationships.
2. Assess Your Data
Conduct a thorough evaluation of your existing CRM data. Identify errors in CSV imports, ensure consistency in data entry, safeguard your CRM from spam submissions, and fix any formatting issues. This step will help ensure that you start with clean and reliable data.
3. Establish Data Standards
Define data standards and guidelines that specify how data should be entered into your CRM system. This includes mandatory fields, data formats, naming conventions, and any other rules that will maintain consistency and accuracy.
4. Regularly Monitor Data Health
Set up processes to monitor your CRM data health regularly. This includes conducting periodic data audits, running data quality reports, and using automation to identify and flag any data issues that arise.
With HubSpot’s Data Quality Software, you can identify outdated properties, uncover integration issues, and gain valuable insights—all in one location.
Get Started With Data Hygiene
Ultimately, strong, hygienic data leads to strong, accurate decision-making. And, the time taken to clean and maintain data hygiene well outweighs the time you used to spend searching through multiple tabs of messy spreadsheets.
Now that you know why you need a data hygiene process, the best practices for implementing one, and how to implement it in your CRM specifically, learn how HubSpot’s Data Quality Software can help you next.