Head-to-head comparison
story at macy's - nyc vs upside
upside leads by 20 points on AI adoption score.
story at macy's - nyc
Stage: Early
Key opportunity: Leverage AI to dynamically price and package experiential retail spaces based on real-time demand, foot traffic, and brand affinity data, maximizing occupancy and revenue per square foot.
Top use cases
- Dynamic Space Pricing Engine — AI model that adjusts leasing rates for pop-ups and events in real-time based on demand forecasts, seasonality, and loca…
- Predictive Tenant Matching — Recommendation system that matches available spaces with ideal brands using historical sales data, visitor demographics,…
- Visitor Flow & Heatmap Analytics — Computer vision on anonymized camera feeds to analyze foot traffic patterns, dwell times, and engagement zones, informin…
upside
Stage: Advanced
Key opportunity: Leverage AI to hyper-personalize cash-back offers and predict consumer purchase intent, increasing merchant ROI and user engagement.
Top use cases
- Personalized Offer Recommendations — Use collaborative filtering and deep learning to serve individualized cash-back offers based on past purchases, location…
- Dynamic Pricing Optimization — Apply reinforcement learning to adjust cash-back percentages in real time, balancing merchant margins with user conversi…
- Fraud Detection — Deploy anomaly detection models to identify and block fraudulent transactions, such as receipt manipulation or fake chec…
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