MS Dynamics CRM Training - Dynamics 365 CRM Course

1. Data Quality and Duplicate Detection in Microsoft Dynamics CRM Importance of Data Quality in CRM Systems Managing Duplicate Records Effectively Best Practices for Maintaining Clean Customer Data Presenter Name Date / Organization

2. Introduction to Data Quality in Dynamics CRM • Data quality refers to the accuracy, completeness, consistency, and reliability of CRM data. • High-quality data enables better decision-making and improved customer relationships. • Microsoft Dynamics CRM relies heavily on clean data for automation, analytics, and reporting. • Poor data quality leads to operational inefficiencies and incorrect insights. • Data governance and validation processes help maintain data integrity.

3. Importance of Maintaining Data Quality • Improves customer experience through accurate information. • Enables better marketing segmentation and targeting. • Enhances reporting accuracy and business intelligence. • Prevents miscommunication across teams. • Supports compliance and regulatory requirements. • Reduces operational costs associated with data correction.

4. Common Data Quality Issues in CRM • Duplicate records created by multiple users or integrations. • Missing or incomplete customer information. • Inconsistent formatting and naming conventions. • Outdated or incorrect contact details. • Data entry errors caused by manual processes. • Data silos across different systems.

5. Overview of Duplicate Detection in Microsoft Dynamics CRM • Duplicate detection identifies similar or matching records. • Helps prevent redundant entries for accounts, contacts, or leads. • Uses predefined or custom matching rules. • Can run during record creation, updates, imports, or scheduled jobs. • Supports data consistency and avoids confusion in customer management.

6. Duplicate Detection Rules and Configuration • Define matching criteria such as: • Email address • Phone number • Account name • Combination of multiple fields • Configure rules for specific entities (Accounts, Contacts, Leads). • Publish rules to activate detection. • Set sensitivity levels to reduce false positives. • Regularly review and refine matching logic.

7. Methods for Managing Duplicate Records • Real-time duplicate detection during data entry. • Bulk detection jobs for existing records. • Merge duplicate records while retaining important information. • Use workflows or automation to validate data. • Apply standard naming conventions. • Restrict duplicate creation through business rules.

8. Best Practices for Data Quality Management • Establish clear data governance policies. • Train users on correct data entry procedures. • Use mandatory fields and validation rules. • Schedule periodic data audits. • Implement automated cleansing tools. • Monitor integrations and data imports carefully. • Maintain standardized data formats.

9. Benefits and Conclusion • Improved data accuracy and reliability. • Increased user trust in CRM information. • Better analytics and decision-making. • Enhanced customer engagement. • Reduced duplication and operational inefficiencies. • Continuous monitoring ensures long-term data quality.

10. If you want, I can also give you: • High-quality corporate-level version (MBA/project submission standard) • Interview presentation version • Dynamics 365-specific advanced technical version (including Power Platform and Data verse concepts) • Ready-made speaker notes for each slide

11. For More Information About • Microsoft Dynamics CRM • Address:- Flat no: 205, 2nd Floor, • Nilgiri Block, Aditya Enclave, Ameerpet, Hyderabad-16 • Ph. No: +91-998997107 • Visit: www.visualpath.in • E-Mail: online@visualpath.in

12. Thank You • Visit: www.visualpath.in