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Data Insights

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

How Real-World Data Powers Programmatic OOH Advertising

Programmatic OOH advertising uses automation and real-world data to make out-of-home campaigns more flexible, targeted, and measurable. By combining movement patterns, location context, audience signals, and external conditions, advertisers can improve timing, placement, media efficiency, and real-world campaign performance.

The Gap Between AI and Real-World Data (And Why It Matters)

Factori MCP helps close the gap between AI and real-world data by connecting AI agents to current signals on people, places, movement, demand, competition, and market activity. This gives teams more relevant context for forecasting, marketing, expansion planning, and faster location-based decision-making.

Digital Out of Home Advertising: A Data-Driven Guide to Smarter Campaigns

Digital out-of-home advertising helps brands reach audiences through digital screens in high-traffic physical locations such as billboards, malls, airports, and transit systems. By using real-world movement, visit, POI, and audience data, brands can improve DOOH planning, placement, measurement, and campaign outcomes.

How AI Is Starting to Interact with Real World Data in Real Time

Factori MCP connects AI agents to real-world data on people, places, and movement, helping teams make decisions with current market context instead of static historical inputs. By making external signals accessible through AI workflows, businesses can improve forecasting, marketing, site selection, and location-sensitive decision-making.
Site Selection Analysis: A Data-Driven Guide

Site Selection Analysis: A Data-Driven Guide to Choosing High-Performing Locations

Site selection analysis helps businesses evaluate potential locations using demand, foot traffic, demographics, competition, accessibility, trade area, and commercial viability signals. By comparing sites with a structured, data-driven framework, businesses can reduce expansion risk, improve decision quality, and choose locations with stronger long-term performance potential.
High street vs mall_ Retail Opportunities and Risks

High street vs mall: Retail Opportunities and Risks

The high street vs mall decision helps retailers choose locations that best match their customers, store format, cost structure, and growth goals. By comparing footfall quality, visibility, accessibility, surrounding businesses, audience fit, and profitability potential, retailers can reduce site risk and make more confident location decisions.
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.

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