Factori AI & ML Training Data | Point of Interest Data (POI) | Global | Machine Learning Data

Our POI Data connects people's movements to over 14M physical locations globally. These are aggregated and anonymized data that are only used to offer context for the volume and patterns of visits to certain locations. This data feed is compiled from different data sources around the world. Reach: Our POI/Place/OOH level insights are calculated based on Factori’s Mobility & People Graph data aggregated from multiple data sources globally. To achieve the desired foot-traffic attribution, specific attributes are combined to bring forward the desired reach data. For instance, in order to calculate the foot traffic for a specific location, a combination of location ID, day of the week, and part of the day can be combined to give specific location intelligence data. There can be a maximum of 40 data records possible for one POI based on the combination of these attributes. Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method at a suitable interval (daily/weekly/monthly). Use Cases: Credit Scoring: Financial services can use alternative data to score an underbanked or unbanked customer by validating locations and persona. Retail Analytics: Analyze footfall trends in various locations and gain an understanding of customer personas. Market Intelligence: Study various market areas, the proximity of points or interests, and the competitive landscape Urban Planning: Build cases for urban development, public infrastructure needs, and transit planning based on fresh population data. Data Attributes Included: Location ID n_visitors day_of_week distance_from_home do_date month part_of_day travelled_countries Visitor_country_origin Visitor_home_origin Visitor_work_origin year

搜集汇总

背景与挑战

背景概述

该数据集提供全球超过1400万个兴趣点的匿名化移动数据，包括访问量、时间模式和访客属性，适用于信用评分、零售分析和城市规划等多种机器学习应用。数据通过动态收集和属性组合生成，涵盖位置ID、访问者数量、时间维度等关键信息。