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Saved 100s of hours of manual processes when predicting game viewership when using Domo’s automated dataflow engine.

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Sales Floor Allocation

Sales Floor Allocation

It predicts traffic by zone, section, and shift using footfall and event data, then compares it with staffing to flag areas as Understaffed, Sufficient, or Overstaffed, suggesting reallocation as needed.

Details
TOOLS / INTEGRATIONS
Snowflake
Shopify
PARTNERS
GWC DATA.AI
RESOURCES
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Benefits

It analyzes historical footfall data and special event schedules to predict traffic by zone, section, and shift. It then compares predicted demand with current staffing to classify sections as Understaffed, Sufficient, or Overstaffed. It highlights urgent needs and suggests staff reallocation accordingly.

Problem Addressed:

This agent addresses inefficiencies in retail staffing by aligning workforce allocation with predicted footfall. It reduces understaffing risks during peak hours and prevents resource waste from overstaffing in low-traffic zones.

What the Agent Does:

It analyzes historical footfall data and special event schedules to predict traffic by zone, section, and shift. It then compares predicted demand with current staffing to classify sections as Understaffed, Sufficient, or Overstaffed. It highlights urgent needs and suggests staff reallocation accordingly

Standout Features:

• Hourly footfall prediction using historical and event-driven trends
• Real-time staffing sufficiency analysis with reasoning
• Urgency scoring for immediate leadership attention
• Actionable reallocation recommendations with impact projections

Business Automation
Magic ETL
App Studio
Workflows
Agent Catalyst