AI Retail Tenant Mix Optimization
The Problem
“Optimizing retail tenant mix amid shifting demand”
Organizations face these key challenges:
1
Limited ability to quantify how tenant adjacencies, anchors, and category balance drive total footfall, sales, and rent potential
2
Fragmented, inconsistent data across rent rolls, sales reports, foot traffic providers, and broker intelligence makes analysis slow and error-prone
3
High-stakes leasing decisions are made with static assumptions, resulting in mispriced deals, co-tenancy issues, and avoidable vacancy
Impact When Solved
Higher NOI through optimized mix, pricing, and reduced vacancy (1–3% NOI uplift)Faster, more confident leasing decisions with automated scenario testing (40–70% analyst time savings; 2–6 weeks faster cycles)Improved center resilience by reducing cannibalization and tenant failure risk (10–20% lower closure/underperformance probability)