16 Jan 2026: BigQuery Improvements

Ricardo Updated by Ricardo

We've improved our BigQuery integration to deliver richer analytics data, easier queries, and better performance. Here's what's new.

Journey Analytics

New Tables

We've added three new tables to give you deeper visibility into your journeys:

  • journey_summary — High-level journey metrics including completion rates and interaction times, synced every 15 minutes
  • journey_insights — Card-level performance data with daily and monthly aggregations, synced daily
  • journey_logs — Complete journey execution logs for analyzing errors, troubleshooting, and understanding customer behavior patterns

Journey Context in Messages

Messages now include three new fields—journey_uuid, journey_name, and card_name—so you can directly see which journeys and cards are driving customer engagement without additional lookups.

Consistent Phone Number Identification

We've added the urn_phone_number field to consistently identify customers across inbound and outbound messages. This enables simple joins to your contacts table:

JOIN contacts ON messages.urn_phone_number = contacts.urn

Simplified access to Template Information

New template_name and template_language fields make template performance analysis straightforward. No JSON extraction required.

Contact Profile Fields

Contact profile fields are now denormalized into individual columns prefixed with profile_ (e.g., profile_name, profile_age, profile_active). This makes querying contact data intuitive and eliminates complex extraction logic:

-- Before
WHERE JSON_EXTRACT(details, '$.age') > 25

-- After
WHERE profile_age > 25

Start exploring these new tables and fields in your BigQuery workspace today.

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