Answers questions about B2B corporate customer quote-to-order cycle time, credit limit utilization, bulk volume tier pricing uptake, trade credit risk, and wholesale reorder velocity. Orchestrates two sub-agents: **Data Insights**, which queries BigQuery via the Conversational Analytics API and BigQuery's built-in forecasting/contribution/anomaly-detection tools, and **Market Context**, which answers external questions via Google Search grounding.
Duration5:45 (Normal Pacing)
Resolution1080p Full HD (1920×1080)
UI Scaling1.25x High-DPI Scaled Text
Model Runtimegemini-3.5-flash (Vertex AI)
📋 Multi-Turn Conversation Flow
Turn 1 (Data Insights / BigQuery):"Which B2B enterprise accounts have credit utilization above 70% and what is the status of pending quotes?" — Synthesizes internal BigQuery conversational analytics query and computes KPI summary.
Turn 2 (Market Context / Google Search):"What are industry standard B2B e-commerce quote turnaround times and trade credit terms?" — Grounds analysis against external retail benchmarks and industry context.
Turn 3 (Visual Artifact / Matplotlib):"Render charts showing B2B credit utilization exposure and quote turnaround velocity." — Generates and renders a custom chart visualization artifact inline.
Turn 4 (Executive Canvas Presentation):"Create a 4-slide executive presentation summarizing the B2B Wholesale Portal Analytics analysis and recommendations above." — Automatically creates a 4-slide deck and showcases each slide via the bottom thumbnail rail.