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GLOSSARY

Tenant-Level Analytics

Tenant-Level Analytics

What is Tenant-Level Analytics?

Tenant-level analytics is the practice of measuring and analyzing visitor behavior at the individual tenant or storefront level within a larger property, such as a shopping mall, mixed-use development, or airport. It provides visibility into how visitors interact with specific tenants rather than viewing the property as a single environment.

Tenant-level analytics helps operators understand tenant performance using metrics like foot traffic, dwell time, and visit patterns.

What else should you know?

Tenant-level analytics enables property teams to make data-driven leasing, marketing, and operational decisions. By understanding how each tenant performs, landlords and operators can identify high-performing brands, uncover underutilized spaces, and support tenant success.

These insights help improve tenant mix, strengthen leasing conversations, and demonstrate measurable value to tenants using real-world behavioral data.

How does Tenant-Level Analytics work?

 

Tenant-level analytics works by defining digital boundaries around tenant spaces and analyzing anonymized visitor activity within those areas. Using WiFi analytics and location intelligence, platforms capture metrics such as visits, dwell time, and repeat behavior at the tenant level.

This data is aggregated into dashboards and reports, allowing teams to compare tenant performance over time while remaining privacy-first and compliant.

Common use cases for Tenant-Level Analytics

 

  • Tenant performance benchmarking: Compare foot traffic and engagement across tenants

  • Leasing and renewal support: Use data to inform leasing strategy and renewals

  • Marketing effectiveness: Measure how campaigns impact individual tenants

  • Operational planning: Align services and staffing with tenant demand

 

Tenant-level analytics gives property teams clear visibility into how individual tenants perform within a larger environment. By grounding leasing, marketing, and operational decisions in real visitor behavior, organizations can better support tenant success and maximize overall property performance.