CRM Data Management: Best Practices to Drive Greater Business Value From Your CRM
Updated: Jul 4
Table of Content
CRM data management is critical to leveraging your CRM system's full potential. This blog post explores the importance of CRM data management. It provides valuable tips and best practices to optimize your data for driving enhanced business value.
While most organizations understand the importance of CRM Software in place and are willing to invest time and money, many also complain about poor data quality. This negatively impacts their data-driven decision-making.
When an organization is confident about its data, it helps it make faster and more informed decisions.
In today's Customer Oriented business environment, CRM is more than a Sales force automation and Customer service management tool. Modern CRMs like D365 Customer Engagement and Salesforce are designed to provide you with AI and ML-based Customer Insights which bring increased business value and boost smart decision-making capabilities.
But it all depends on the quality of the data, which in turn depends on your organization's understanding of the value of effective CRM data management practices.
What Is CRM Data Management?
CRM data management involves managing the data stored in a CRM system to ensure that it is accurate, detailed, consistent, and secure. It includes practices such as data cleaning, data validation, data standardization, and data integration.
Poor data quality can produce false insights, delay decision-making, and ultimately have negative effects on your business's success.
Therefore, it is crucial to follow the best CRM data management practices to ensure your system delivers maximum value to your organization.
CRM Data Management Tips And Best Practices
Businesses can ensure they have access to high-quality data and increase the value of their CRM system by adhering to the best practices for CRM data management.
Let us look at some of these key practices that you can follow:
1. Valuable Data Identification
Identify the data that is valuable for your business – it largely depends on your organization’s business goals. In addition, it is equally critical to collaborate with business departments directly on data identification.
2. CRM Data Design
Make sure your CRM is designed to capture the data identified in point number 1 in the right format. It should also havenecessary business rules and validations to ensure consistency and data quality.
3. Relevant Data Selection
More often, we do not pay much attention to the number of data columns and their significance.
E.G., capturing the social media LinkedIn profile detail may still be more relevant for a professional services based organization than Ecommerce.
Make sure it is relevant and easy to enter for the system user.
Quality should take precedence over quantity – software applications are designed to cater to diverse industry needs thus it becomes a neccessity to critically analyze every data field in place and filter out the non-relevant ones based on our business goals.
4. Historical Data Migration
Migration of historical data from legacy systems plays a very crucial role in the success or failure of an upcomingsoftware implementation rollout. Cleaning data at the import level becomes a highly significant exercise otherwise you carry forward the same challenges to the new system.
5. User Training and Data Entry
In order to improve user adoption, software training should be prioritized, as well as a focus on correct data entry by users of the system. This needs to be a periodic activity within the organization as new joiners or existing employees could transition to different roles.
6. Periodic Data Monitoring
Periodic monitoring of data to check for inconsistencies, as well as keeping an audit trail enabled for key data columns only in a table will help a lot in ensuring reliable data quality in the long run.
Here’s How Microsoft Dynamics 365 CRM Can Help Your Business
D365 Customer Engagement provides a very effective data management framework tha allows for easy data migration and handling of data afterwards.
There are many standard approaches and tools available to manage data migrations such as:
· D365 Data Import utility,
· Power Platform dataflows,
· Power Apps Excel add-in,
· Power Automate,
· Azure Logic Apps,
· Custom API migrations, etc.
But the selection of the right approach depends on many factors like data volume, solution complexity, and required data transformations.
Our Microsoft D365 experts at Duco Consultancy recommend carefully evaluating the value of data weighed against the volume of data. This is done by evaluating skillset availability, the time and money required to perform the data migration, and, of course, the cost of storage.
Microsoft offers many alternatives where you can replace data that you choose not to migrate with virtual entities, embedded canvas apps in the source connectors, or go with embedded Power BI reports. Thus, it is advised to consult professionals to finalize the most suitable option for you.
CRM Data Management Best Practices: Conclusion
Effective CRM data management is essential to maximize CRM value. By following best practices such as identifying valuable data, designing the CRM system appropriately, selecting relevant data fields, migrating historical data properly, emphasizing user training and data entry, and periodically monitoring data quality, businesses can ensure accurate and consistent data that supports informed decision-making.
Contact Duco Consultancy for expert data management consultation.