Answers questions about Buy Online Pick Up In Store (BOPIS) order processing, curbside wait time analytics, pick accuracy tracking, and omnichannel fulfillment performance. 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):"What is our Buy-Online-Pick-Up-In-Store (BOPIS) SLA compliance and average curbside pickup wait time by store?" — Synthesizes internal BigQuery conversational analytics query and computes KPI summary.
Turn 2 (Market Context / Google Search):"What are industry standard BOPIS fulfillment SLA and curbside pickup wait time benchmarks for retail stores?" — Grounds analysis against external retail benchmarks and industry context.
Turn 3 (Visual Artifact / Matplotlib):"Render a bar chart comparing store curbside pickup wait times against our 15-minute maximum SLA limit." — Generates and renders a custom chart visualization artifact inline.
Turn 4 (Executive Canvas Presentation):"Create a 4-slide executive presentation summarizing the Store Fulfillment & Execution analysis and recommendations above." — Automatically creates a 4-slide deck and showcases each slide via the bottom thumbnail rail.