Company & Contact Fill Rate Improvements (Phase 1)

Signal deliveries now contain more populated fields for both company and contact records. This is the first phase of a systematic effort to close coverage gaps across all signal types.

What improved

Company records:

• company_name fill rate increased across signals that previously delivered domain-only records
• industry, employee_count, and headquarters fields now populated on signal types that had them in schema but rarely filled (SEC filings, earnings transcripts, hiring signals)
• Company LinkedIn URL resolution improved — fewer null company_linkedin_url fields

Contact records:

• contact_title and contact_company fill rates improved on LinkedIn-sourced signals (posts, comments, work milestones)
• Email resolution coverage expanded for contact-level signals

How we measured it

We run automated fill rate audits against every delivery batch, comparing field-level population percentages against historical baselines. Phase 1 targeted fields that were present in the schema but had < 80% fill rates without a valid business reason for nulls.

What stays the same

• All schema structures unchanged — no new required fields, no removed fields
• Delivery schedule and format unchanged
• Fields that are legitimately sparse (e.g. fiscal_year_end on 8-K filings) retain their natural fill rates

What's next (Phase 2)

Phase 2 will focus on cross-signal entity resolution — linking the same company or contact across different signal types to improve downstream joins and reduce manual matching work.