RevSure's Entity Resolution Framework: A Comprehensive Overview

In the world of B2B marketing and sales, having clean and accurate data is paramount. Duplicate records, mismatched information, and conflicting data sources can lead to incorrect attributions, inefficient campaigns, and ultimately, lost revenue. RevSure's Entity Resolution Framework is designed to solve these challenges by providing a robust and flexible solution to deduplicate and harmonise records across multiple systems, ensuring that your data is accurate, consistent, and reliable.

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Objective

The primary goal of RevSure’s Entity Resolution Framework is to resolve duplicate records that arise when data from multiple systems are synchronised into a master system. One could have duplicates coming from multiple campaign management systems, ad systems, multiple CRM and Marketing automation systems deployed in the enterprise across regions, brands, or multiple data enrichment sources. This duplication can lead to inaccurate attribution results, multi-counting, and other data inconsistencies. By leveraging an advanced matching and merging algorithm, this framework ensures that records are deduplicated and accurately linked.

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Key Features of the Entity Resolution Framework

1. Multiple Configurations: Users can create multiple configurations for different entities, such as leads, accounts, and campaigns. This flexibility allows for tailored deduplication and linking strategies based on specific business needs.
2. Entity and Dimension Selection: Users can select the entity they wish to resolve (e.g., lead, account, campaign) and choose the dimensions they want to focus on for deduplication or linking. This ensures that the resolution process is targeted and relevant to the data being analysed.
3. Source System Resolution: The framework allows users to choose source systems for resolution. Users can either deduplicate records from a specific source or link and merge records from multiple sources, designating primary and secondary sources as needed.
4. Fuzzy vs. Exact Matching: Depending on the complexity of the data, users can opt for either fuzzy matching, which allows for slight variations in data (e.g., misspellings or different formats), or exact matching for stricter data resolution.
5. Filters and Probability Thresholds: Advanced filters can be applied to refine the resolution process, and users can set probability thresholds to determine which records should be flagged as duplicates. This allows for greater control over the deduplication process.
6. Cluster Formation and Manual Overrides: The framework identifies clusters of potential duplicates and allows users to manually review and adjust the records. Users can decide which records to replace, keep, or exclude from the resolution process, ensuring that no data is lost without thorough review.
7. Automated Sync and Reversion: The system runs on an automated sync schedule, regularly checking for duplicates and resolving them based on the configurations set by the user. Additionally, users can revert changes if needed, providing a safety net for data management.

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How the Entity Resolution Framework Works

1. Data Input: Users begin by selecting the entities and dimensions they want to resolve. They choose the source systems and set parameters for deduplication or linking, such as filters and match types.
2. Algorithm Execution: The probabilistic matching algorithm runs, identifying potential duplicates and forming clusters based on the selected criteria. The algorithm considers both fuzzy and exact matches, depending on user preferences.
3. Review and Adjustment: Once the clusters are formed, users can review the results. The system allows for manual adjustments, where users can select which records to keep or replace.
4. Final Resolution: After the review, the framework finalises the resolution process, updating RevSure with the clean, deduplicated data. The system continues to monitor and sync data regularly, ensuring ongoing accuracy.
5. Reporting and Feedback: The framework provides detailed reports on the deduplication process, including the records resolved and any clusters that were manually adjusted. This transparency helps teams track data quality improvements over time.

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The Benefits of RevSure’s Entity Resolution Framework

• Improved Data Accuracy: By eliminating duplicates and linking records correctly, the framework ensures that your CRM and other systems are populated with accurate, reliable data.
• Enhanced Attribution Accuracy: With clean data, attribution models can more accurately track the impact of marketing efforts across channels and touchpoints, leading to better insights and decision-making.
• Increased Efficiency: Automating the deduplication process saves time and reduces the risk of human error, allowing teams to focus on strategic tasks rather than manual data cleaning.
• Flexibility and Control: The framework offers a high degree of customization, allowing users to tailor the resolution process to their specific needs while maintaining control over the final outcome.
• Seamless Integration: The Entity Resolution Framework integrates smoothly with existing systems, ensuring that data remains consistent across all platforms without disrupting ongoing operations.

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Conclusion

RevSure’s Entity Resolution Framework is a powerful tool for Enterprise distributed B2B organisations looking to enhance their data accuracy and marketing effectiveness. By resolving duplicates, linking records, and providing ongoing data management, this framework ensures that your data is always clean, consistent, and ready for action. With RevSure, you can trust that your data is working as hard as you are.