Demand planning and forecasting help businesses predict future demand and turn those predictions into inventory, production, staffing, and supply chain decisions. By combining historical data with real-world signals like mobility, traffic, place activity, and economic indicators, teams can improve forecast accuracy, reduce planning risk, and build more responsive supply chains.
Demand forecasting methods help businesses estimate future demand across inventory, operations, and growth planning. By combining qualitative, quantitative, causal, and AI-based approaches with real-world signals like mobility, visit behavior, POI context, and audience data, teams can improve forecast accuracy, detect demand shifts earlier, and make smarter planning decisions.
Corporate site selection helps businesses choose expansion, relocation, or optimization sites using real-world signals instead of static assumptions. By analyzing mobility, footfall, trade areas, competition, places, and audience data, companies can validate demand, compare locations, reduce investment risk, and make more confident site decisions.
A site selection strategy helps businesses choose stronger locations through a structured, data-driven process. By combining business goals, customer demand, mobility, footfall, trade areas, POI context, competition, and performance forecasting, teams can reduce expansion risk and make more confident location decisions.
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.
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 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.
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.
OOH advertising helps brands build visibility across billboards, transit ads, street furniture, and digital screens in high-traffic physical locations. By using real-world movement, place, and visit data, brands can improve OOH site selection, reduce wasted exposure, measure real-world impact, and make campaigns more precise and accountable.