The data in your CRM provides critical insight into your customers, leads, and sales. Having the ability to document your team’s communications with contacts, automate sales processes, and track leads through your pipeline is vital for implementing successful business strategies. Trying to accomplish those same goals without high-quality data may feel like working with one hand tied behind your back.
Ensuring the quality and accuracy of your CRM data is one of the most critical best practices for using your CRM system. Fortunately, you can ensure your CRM data is accurate by implementing a few helpful strategies.
Why is ensuring data quality important?
Flawed CRM data isn’t just a headache—it can derail your operations, waste valuable time, and even cost sales. The more information about your customers, prospects, and leads gets entered into your CRM incorrectly or becomes duplicated, the more time you have to spend resolving issues when you’d rather be doing more important tasks—and the more likely you are to make decisions based on faulty information.
How to maintain high-quality data in your CRM
Maintaining accurate CRM is critical, and luckily your team can implement some best practices to make the process go more smoothly. Follow these steps to ensure your CRM data is always accurate and usable:
1. Regularly review your CRM data
Data reviews look for outdated, incomplete, duplicate, or inaccurate data that could cause your team to make decisions without having all the facts. It’s essential to conduct regular data reviews to prevent dirty data and ensure you can trust what you see in your CRM.
How to review CRM data
Regular data review is much simpler if you and your team follow a few critical steps:
- Create a data review schedule: Going too long between data reviews can lead to inaccuracies, whether from user error or leads and customers changing their information. Set a data review schedule and have your team ensure all your information is current. A good practice is to review CRM data quarterly to identify errors and inconsistencies.
- Assign data review tasks to specific people: Divide data review tasks between several people so you can ensure certain tasks are completed. Consider who will be responsible for data input, generating analytics reports, and ensuring data accuracy. Assigning these tasks to specific people will help the process run more smoothly.
2. Clean your CRM data
The second step in ensuring your CRM data is high-quality is cleaning it. Data cleaning is the process of going through your data and solving any obvious issues that you see. These issues might be duplicates, inaccuracies, or obsolete information.
Datasets often include these kinds of errors, whether due to poor data input practices or data becoming outdated. During data cleaning, you examine all the data in your CRM, find any problems, and correct them to ensure your data is usable.
You may also have heard of data scrubbing, a more in-depth version of data cleaning involving an exhaustive search of your data for errors. Think of data cleaning as a casual wash and data scrubbing as an intense cleansing. Data scrubbing could be a part of your yearly data cleaning process.
How to clean CRM data
Understanding how to clean your CRM data before you begin the process is crucial. Follow these best practices for cleaning CRM data:
- Update your CRM when you receive new data: Knowing how to edit and bulk edit your CRM data is crucial for properly cleaning your data. As soon as you become aware of a change you need to make, go into your CRM and update the records. This ensures your team is always operating with updated data.
- Manually remove disengaged contacts: Keeping contacts in your CRM as long as possible may seem logical, but hanging onto bad contacts could be slowing your team down. Manually delete contacts that are no longer useful and make sure you unsubscribe contacts from your email campaigns who request to stop receiving them.
- Automate data cleaning with a data cleaning tool: While manually cleaning data has its place, you might find it helpful to automate certain aspects of data cleaning. Plenty of third-party data scrubbing tools exist for you to use with your CRM. Your CRM may also detect and merge duplicate data for you.
3. Complete data validation
After reviewing and cleaning your CRM data, you may be in a hurry to get back to utilizing your data—but don’t rush the process! The final strategy for ensuring data quality and accuracy is data validation.
Data validation is the step after data cleaning that guarantees your data is accurate and ready for use in your CRM. Validating your data’s accuracy is the most crucial step for ensuring your team has accurate and updated data for decision-making.
Data validation verifies whether the data cleaning was successful and whether the information meets your company’s and industry’s standards. Essentially, data validation is the time to perform final checks before putting your data into use!
How to validate your data
Here are a few best practices for validating your CRM data:
- Implement data validation rules: Before performing data validation, you need to set data validation rules. These criteria provide a set of standards by which you can judge your data to ensure its quality. Consider what rules might be appropriate for your company or industry, like a valid email format or specific date range.
- Check for inaccuracies and redundancies: With your data validation rules in place, it’s time to perform data validation. Set up scheduled validation checks with specific datasets to keep from overwhelming your team. During this step in the process, you check whether the data is complete, accurate, and updated according to your rules.
- Utilize automation: Depending on the tools at your disposal, you may be able to automate some steps in the data validation process. Automation can speed up the validation process and reduce the likelihood of error. Research some data validation tools that integrate with your CRM or automated data collection tools within your CRM to keep all your data organized.
- Enforce data entry standards: Ensuring data is updated and accurate before inputting it into your CRM can reduce the time needed to validate it later. During the data validation phase, determine what processes you can enforce to ensure accurate data entry and provide your team with clear guidance on how to put data into the system. Perhaps your team needs to enter data into the CRM as soon as they receive it or create custom data forms to capture required information from leads.
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Keep your CRM data clean in Nutshell
Working with clean CRM data is a must if you want your team to have access to the most relevant, current, and helpful data. By reviewing, cleaning, and validating your data regularly, you can ensure that your team has all the information they need to optimize their sales and marketing efforts.
With Nutshell, ensuring your CRM data is accurate is simple. Our CRM system gives you access to useful data collection and analysis tools that help you make sure you’re dealing with the highest-quality data. See how you can accomplish more with your CRM by signing up for a free trial of Nutshell today or contacting our team to learn more!
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