Status & Known Issues

This page tracks known issues and ongoing improvements for the Signal Database. We update this regularly as issues are resolved and new items are identified.

Active Issues

1. New User Access to Historical Data

Status: 🟡 In Progress

Newly provisioned users may not have access to the previous period's data dumps. As a result, some buckets may appear empty upon initial access.

Workaround: If you're a new user and see empty buckets, please contact your account manager to request backfill access.

2. Entity Enrichment Quality

Status: 🟡 In Progress

Enrichment resolution at both the company and contact level is not yet perfect. Some records may have incomplete or missing resolved identifiers.

What we're doing: We're actively improving our resolution pipeline. Upcoming releases will include significantly better resolved data in signal payloads—expect major improvements to match rates and data completeness.

3. Data Quality: NaN Values

Status: 🟡 In Progress

Some fields contain NaN values where they should be null. This can cause issues in downstream processing depending on your data pipeline.

Workaround: When ingesting data, treat NaN values as null/missing values.

4. Schema Inconsistencies

Status: 🟡 In Progress

We're aware of several schema-related inconsistencies:

• Many fields across signal types: We're working toward a unified schema to standardize field names and structures across all signal types.

• Similar field names: Some fields have similar names with subtle differences (e.g., relevance vs sales_relevance). These will be consolidated in future releases.

• API vs. Signal payload differences: Some example files in our Insight Schema documentation show payloads in a slightly different format (e.g., insights vs signal). While the core schema is consistent, the structure differs based on retrieval method:

  • API retrieval: Returns insights with API-specific accompanying fields
  • Signal Database dumps: Returns signals with bulk-delivery-specific fields

  We're working to make these differences clearer in our documentation and align the structures where possible.

5. Audience Size Optimization

Status: 🟡 In Progress

Certain signal types—particularly GitHub and Glassdoor—have audience sizes that need optimization to improve our hit rate on monitored profiles.

What we're doing: We're actively optimizing which profiles make it into the refresh pool for each signal type, prioritizing coverage for signals with the highest intent value.

6. Refresh Pool Optimization

Status: 🟡 In Progress

We're continuously working to optimize the overall size and composition of our refresh pool to balance coverage, freshness, and data quality across all signal types.

Questions?

If you encounter issues not listed here or need assistance, contact us at [email protected].