Definition
Entity Resolution is determining when two or more records in a dataset refer to the same real-world entity, even with variations in how the entity is represented.
Why It Matters
B2B databases decay at 30% per year. Without proper attention to entity resolution, your CRM loses accuracy every quarter. Gartner estimates the average cost of poor data quality at $15 million per year for large organizations. Even for smaller teams, the impact shows up in bounced emails, misrouted leads, and wasted selling time.
Entity Resolution directly affects your team's ability to target the right accounts, personalize outreach, and report accurately. When this area of your data strategy breaks down, everything downstream, from lead scoring to pipeline forecasting, produces unreliable results.
How It Works
Entity Resolution involves several steps depending on your specific data challenges. At a high level:
- Assessment: Analyze your current data to identify gaps, inconsistencies, and quality issues related to entity resolution.
- Processing: Apply the relevant techniques, whether that's enrichment from external sources, validation against reference data, or normalization to standard formats.
- Verification: Cross-reference results against multiple sources and apply human QA to catch edge cases that automated processes miss.
- Delivery: Return cleaned, enriched data to your CRM in a format ready for immediate use.
- Maintenance: Schedule periodic refreshes to prevent data decay from undoing the improvements.
Example
Your CRM has 50,000 records. After applying entity resolution, you discover that 15% need attention. Fixing those 7,500 records before your next campaign prevents bounces, misroutes, and wasted spend.
Common Mistakes
- Treating it as a one-time project. Data decays continuously. A one-time effort buys you a few months of clean data, then quality degrades right back to where it started.
- Relying on a single data source. No single vendor has complete or perfectly accurate data. Cross-referencing 50+ sources produces significantly better results than relying on one.
- Skipping human QA. Automated processes handle 90% of cases well. The remaining 10%, the edge cases and ambiguous matches, need human review to prevent errors from entering your database.
Frequently Asked Questions
What is entity resolution?
Determining when two or more records in a dataset refer to the same real-world entity, even with variations in how the entity is represented.
Why does entity resolution matter for B2B teams?
B2B data decays at 30% per year. Without entity resolution, your database loses accuracy every month. Clean, complete data drives better targeting, higher conversion rates, and more accurate reporting.
How does Verum help with entity resolution?
We handle entity resolution as part of our data cleaning and enrichment services. Send us your data, and we'll apply best practices using 50+ sources with human QA. Most projects complete in 24-48 hours.
Related Terms
Related: All Glossary Terms | Enrichment Services | Cleaning Services