May 30, 2023
Data Quality Improvement: LinkedIn Person Profile Matching
We are pleased to announce a major upgrade to our LinkedIn person profile matching algorithm. This development has improved accuracy by an impressive 7%, allowing it to better account for diversified user conventions such as multiple last names or nicknames. Additionally, the system now successfully identifies and matches profiles that only display partial names on the platform.
Changes, improvements, and bug fixes
Enhancement: We introduced a migration tool to streamline the transition from our legacy HubSpot integration to the new one. This seamless migration ensures continuity of operations while unlocking the power of our advanced features and capabilities.
Enhancement: Further enriched our B2B dataset with the inclusion of 6-digit NAICS and 4-digit SIC codes to more data fields.
Fix: Rectified the issue of a single record being generated per Clearbit Capture destination, ensuring accurate and efficient data collection.
Fix: Resolved a glitch in the Schedule Email Digest option that previously hindered the creation of destinations.
Fix: Corrected the anomaly that triggered additional data ingestion when establishing a connection to Marketo for forms. The fix ensures that reconnecting to Marketo to set up the forms solution will not increase customers’ Marketo API consumption.
Fix: Addressed and resolved the delay in Salesforce data enrichment for some customers, ensuring all users enjoy timely and accurate data insights.
Fix: Fixed a bottleneck that was hindering the CSV exports for "all companies". The export functionality is now fully operational, ensuring timely delivery of data.
Fix: Successfully resolved data discrepancies related to parked domains, thus enhancing the accuracy and reliability of our domain data.
Fix: Rectified the Logo API glitch which was previously causing substandard logo quality, thereby ensuring sharp and high-resolution logos.