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Explore our latest publications, from industry insights to in-depth tech analysis

AI Audience Targeting Map

AI Audience Targeting: What to Validate Before You Trust It

Learn what to validate before trusting AI audience targeting, from data quality and explainability to model behavior, marketer control, and baseline testing.
People Data for Audience Targeting: How to Find, Size, and Reach the Right Consumers

People Data for Audience Targeting: How to Find, Size, and Reach the Right Consumers

Learn how People Data helps marketers find, size, map, and reach target consumers using demographics, real-world behavior, geography, and audience insights.
Evaluating MCP Servers for Location Data

Evaluating MCP Servers for Location Data in 2026

Evaluate MCP servers for location data across POI, mobility, coverage, agent workflows, structured outputs, privacy, authentication, and production access.
Drive-Time Analysis Store Trade Areas

Using Drive Time Analysis to Evaluate Store Trade Areas

Learn how drive time analysis helps retailers evaluate store trade areas by comparing accessibility, competition, mobility, visitation, and market potential.

Real-World Data for Competitive Intelligence: Beyond Prices and Store Counts

Learn how data companies use POI, mobility, visitation, market, and other real-world data to build stronger competitive intelligence products and features.
SafeGraph Alternatives Richer Location Data

Best SafeGraph Alternatives for POI and Location Data in 2026

Compare the best SafeGraph alternatives for POI and location data in 2026 across coverage, mobility, mapping, delivery, data quality, and buyer fit.
Best Placer.ai Alternatives_ Location Intelligence 2026

Best Placer.ai Alternatives for Foot Traffic and Location Intelligence in 2026

Compare the best Placer.ai alternatives for foot traffic and location intelligence, including mobility data, POI, GIS, site selection, and spatial analytics platforms.

From Foot Traffic to a Defensible Number: How AI Forecasts New-Store Revenue

Learn how AI revenue forecasting combines mobility, POI, demographic, and store-performance data to build more explainable and defensible new-store forecasts.

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