Integrating Microsoft Dynamics 365 CRM with Customer Insights - Data (CI-D) opens up a world of possibilities for understanding your customers better. But as you navigate this integration, you might notice something peculiar: certain tables, like your trusty Contacts, get these columns prefixed with msdynci_
, while others seem to miss out. If you've ever wondered if your data sync is working correctly, you're not alone. The truth is, this isn't a random occurrence – it's a deliberate design that reflects how Customer Insights handles different types of data.
The Purpose Behind the Pattern: Why Only Some Tables Get the msdynci_
Prefix
Think of Customer Insights - Data as a platform built to create a unified and comprehensive view of your customers. To achieve this, it focuses on what it considers "profile" tables – primarily your Contact and Account entities.1 When you set up the synchronization between Dynamics 365 CRM and CI-D, the system identifies these key entities as central to building that single customer profile.1
To power features like profile unification, data enrichment, audience segmentation, and even predictive scoring, Customer Insights - Data automatically adds specific metadata fields to these designated profile tables 1. These are the columns you see with the msdynci_
prefix. They act as internal markers, helping Customer Insights track and manage profile-related data more effectively.1
Here are a few key msdynci_
columns you'll likely encounter in your core profile tables:
msdynci_isprofile
: This column likely acts as a simple yes/no indicator, telling the system whether a specific record (like a Contact) is actively contributing to your unified customer profile within Customer Insights - Data.2
msdynci_lastprofileupdate
: Think of this as a digital timestamp. It probably records the exact date and time when a record's profile information was last updated or refreshed by Customer Insights - Data.2 This is crucial for knowing how recent your unified customer data is.
msdynci_profilestatus
: This column likely holds a status code or value that reflects the current stage of a record's profile within the Customer Insights - Data processing pipeline.2 It could indicate if a profile is active, pending unification, or has been successfully unified.
Now, what about other tables in your Dynamics 365 environment, such as custom entities or standard tables like Activities? These are generally not automatically treated as core profiles in Customer Insights - Data.4 As a result, they don't automatically receive the msdynci_
columns unless you explicitly configure them within CI-D.4 This design helps keep the focus on the most critical customer data for unification.
Validating Your Integration: Ensuring Smooth Synchronization
To make sure your Dynamics 365 CRM and Customer Insights - Data integration is working as expected, here are a few key steps you can take 5:
- Examine Sync Health Metrics: Head over to the Power Platform Admin Center. Here, you can usually find a dashboard that shows the overall health of your data synchronization, including the status of individual tables.
- Verify Table Classifications in CI-D: Open up Customer Insights - Data and navigate to Data > Tables. This section allows you to see how each table is classified (e.g., as a profile, interaction, or relationship) and confirm which tables are being actively used.
- Configure Non-Profile Tables: If you have custom entities that you want to include in your Customer Insights data model, you'll likely need to manually map them within CI-D. This involves defining their schema and specifying how they relate to your core profile entities.
Key Insights for Administrators
Understanding the selective nature of msdynci_
columns is crucial for anyone managing a Dynamics 365 and Customer Insights - Data integration. It provides a clear view into how Customer Insights categorizes and processes your CRM data, helping to maintain a distinction between core profile information and other supporting data.1 When building your unified customer data models, recognizing this architectural choice ensures you can accurately interpret table structures and establish effective relationships between different entities.
Diving Deeper: Exploring Other msdynci_
Tables
Beyond the key columns mentioned earlier, the integration also creates several other tables in your Dataverse environment, all helpfully prefixed with msdynci_
.1 These tables serve specific purposes in managing and enriching your customer data:
Real-World Applications: Putting msdynci_
Columns to Work
Understanding these msdynci_
columns and tables opens up various practical applications :
- Smarter Segmentation: Use
msdynci_isprofile
to create highly targeted audience segments that include only fully unified customer profiles.
- Personalized Interactions: Leverage
msdynci_lastprofileupdate
to ensure your sales and service teams have the most up-to-date customer information for more relevant conversations.
- Troubleshooting Integration Issues: Monitor
msdynci_profilestatus
to quickly identify and address any records that may have failed to unify correctly.
- Comprehensive Customer Journeys: Utilize
msdynci_unifiedactivity
to gain a holistic view of customer interactions across all touchpoints, enabling more effective journey mapping.
- Data-Driven Insights: Employ
msdynci_customermeasure
to track key metrics like customer lifetime value and tailor business strategies accordingly.
- Targeted Marketing: Rely on
msdynci_segmentmembership
to deliver personalized marketing messages and offers based on specific customer segment affiliations.
Staying Informed: Recent Updates and Best Practices
The landscape of Dynamics 365 and Customer Insights is constantly evolving. Keeping an eye on recent release waves and updates is essential. Features like enhanced integration with Microsoft Fabric OneLake and improvements to the Dataverse connector can influence how msdynci_
data is managed.
For optimal management of your integration, remember these best practices :
- Strategic Synchronization: Only sync necessary entities to avoid performance bottlenecks.
- Data Quality First: Implement robust data unification processes within Customer Insights - Data to ensure accurate and complete customer profiles.
- Regular Monitoring: Keep a close watch on the data synchronization status in both Dynamics 365 CRM and Customer Insights - Data to identify and resolve any issues promptly.5
By understanding the role of msdynci_
columns and following these best practices, you can confidently navigate the integration between Microsoft Dynamics 365 CRM and Customer Insights - Data, unlocking the full potential of your customer data.