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

Real Estate Site Selection_ A Practical Guide to Choosing the Right Location

Real Estate Site Selection: A Practical Guide to Choosing the Right Location

Real estate site selection helps investors choose stronger locations by analyzing demand, accessibility, foot traffic, mobility, nearby businesses, demographics, and competition. By using real-world data instead of assumptions alone, teams can compare sites more confidently, reduce investment risk, and identify locations with stronger long-term potential.
Retail Location Analysis: A Data-Driven Guide to Site Selection

Retail Location Analysis: A Data-Driven Guide to Site Selection

Retail location analysis helps businesses choose stronger store sites by combining foot traffic, mobility, demographics, POI, competitor, and trade area data. By moving beyond static market reports and using real-world behavior signals, retailers can better understand local demand, reduce site selection risk, and make more confident expansion decisions.
Factori Is Now Available on Snowflake Marketplace

Factori Is Now Available on Snowflake Marketplace

Factori is now available on Snowflake Marketplace, giving Snowflake customers direct access to real-world data on people, places, movement, visits, POIs, and audiences. Teams can discover, evaluate, and activate Factori datasets inside Snowflake to accelerate analytics, forecasting, enrichment, and decision-making without complex integrations.
Retail Store Cannibalization

Retail Store Cannibalization: Why New Store Openings Drain Sales and How to Stop It

Retail store cannibalization happens when a new location shifts visits and sales away from nearby stores instead of creating new demand. By using mobility and location intelligence to measure catchment overlap, simulate expansion scenarios, and track post-launch demand shifts, retailers can reduce expansion risk and protect network performance.
Customer Shopping Behavior Across Locations

Customer Shopping Behavior Across Locations: What Transactions Miss and How to Measure It

Customer shopping behavior data helps retailers understand how people visit, move between, and engage with physical locations over time. By combining privacy-safe people and visit data, businesses can uncover visit frequency, dwell time, cross-shopping, repeat behavior, and location-level differences that transaction data alone cannot explain.
How to Use Aggregated Mobility Data to Improve Demand Forecasting

How to Use Aggregated Mobility Data to Improve Demand Forecasting

Aggregated mobility data helps businesses improve demand forecasting by revealing real-world activity before it appears in sales, bookings, or orders. By using privacy-safe movement trends as early demand signals, teams can adjust forecasts, inventory, staffing, and capacity decisions with greater speed and confidence.
Micro-Catchment Footfall: How Retailers Can Spot Shifting Demand at a Street-Block Level

Micro-Catchment Footfall: How Retailers Can Spot Shifting Demand at a Street-Block Level

Micro-catchment footfall helps retailers understand demand at the block, street, and intersection level. By identifying where foot traffic is rising, weakening, or shifting around each store, retailers can improve hyper-local marketing, staffing, inventory planning, site selection, and competitive response.
Retail Geo-targeting Strategies for Holiday Marketing

Retail Geo-targeting Strategies for Holiday Marketing

Holiday geo-targeting helps retailers move beyond broad campaigns by using real-world signals like events, weather, traffic, footfall, competition, and local economics. By aligning media spend with store-level demand and operational capacity, brands can reduce wasted budget, improve ROI, and deliver more relevant holiday campaigns.
Audience Data for Digital Advertisement Targeting

How to Use Audience Data for Digital Ad Targeting

Audience data helps marketers understand who to reach, what they care about, and how they behave online and offline. By turning demographic, behavioral, location, and device signals into actionable segments, brands can improve digital ad targeting, reduce wasted impressions, personalize campaigns, and reach the right audience at the right moment.

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