Summary

Checked the CSV cohort from /Users/samaguiar/Documents/Projects/Repos/sail-litify-hub-mdt/Litify_AI_Integration_Project/output/webform-gclid-sync/dry-run-120d-2026-04-24T03-03-54Z/webform-gclid-intake-updates.csv against live LITIFY_ORG on 2026-05-28.

Work Completed

• Read the CSV and confirmed it contains 34 unique litify_pm__Intake__c records and 34 linked Web_Form__c records.
• Validated live Salesforce access with sf org list --all --json against LITIFY_ORG.
• Queried live Intake, Matter, Case Type, Sub Case Type, Matter Plan, and paired Web Form narrative fields.
• Aggregated conversion, auto accident, and trucking counts.

Results

• Total cohort: 34 intakes.
• Converted into matters: 9.
• Auto accident leads, explicit Intake Case Type = Automobile Accident: 17.
• Converted auto accident matters: 9.
• Explicit trucking leads, Sub Case Type = Trucking: 2.
• Converted explicit trucking matters: 1.
• Broader truck-related candidates from narrative keyword review: 4, including the 2 explicit Trucking records.

Handoff

This was read-only. No Litify records, CSV files, repo files, Google Ads settings, or automations were changed. A future agent can reproduce the answer by querying the CSV IDs against litify_pm__Intake__c, joining litify_pm__Matter__r for converted records, and checking paired Web_Form__c narrative fields for truck-related terms. Treat the explicit field count as the cleaner operational number and the broader narrative count as an audit candidate set.

QA Reflection

QA status: Clean. The only useful improvement would be to create a small reusable script for this exact cohort-style Litify attribution query if Sam asks for this repeatedly.