Petavue analyzed all 124,150 HubSpot contacts to quantify lead-status completeness and pinpoint exactly which teams and sources were driving the gaps. The result: a clear, validated view of data quality and where to focus cleanup.
Gap Drivers
Identified the exact teams and traffic sources contributing to missing lead-status data.
Data Issues
Surfaced high-volume issues such as unassigned contacts and inconsistent source completeness.
Decision Impact
Gave GTM teams a verified foundation for funnel reporting and operational decisions.
Craft the Plan
Petavue interpreted the request as a data-completeness audit and selected the relevant HubSpot contacts table, including lifecycle stage, team assignment, and analytics source. It prepared grouping logic for three levels: overall, by team, and by source.
Petavue produced a structured, step-by-step plan describing how unique contacts would be counted, how filled vs. missing statuses would be identified, and how each segment would be ranked by completeness.
Ensure Accurate Execution
Before running calculations, Petavue applied automated checks to confirm column availability, ensure lifecycle stage values were non-null for “filled,” and verify that grouping fields existed with reliable fill rates.
During execution, Petavue validated each step: count totals, distribution checks, and segment completeness to ensure no duplicate inflation or filter mismatch affected results. Any intermediate anomalies (e.g., empty teams or zero-volume sources) were handled automatically.
Surface the Insights
After execution, Petavue summarized the findings in a clear, structured output: overall completeness, team-level variation, source-level variation, and actionable recommendations.
It highlighted both best-performing segments and the areas with the highest missing volume, giving operators a direct path to remediation.