SBIR Phase II: System for Location-Based Mobile Consumer Analytics

SBIR 第二阶段：基于位置的移动消费者分析系统

• 批准号: 1127482
• 负责人: Thaddeus Fulford-Jones
• 金额: $ 50万
• 依托单位: Cadio Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1127482&HistoricalAwards=false
• 关键词: SBIR; Phase; II; System; Location

This Small Business Innovation Research Phase II project aims to improve data mining technologies for location analytics. This project will focus on the analysis of semi-continuous GPS and/or WiFi-based location data generated by consumer mobile devices. The anticipated improvements would allow consumer insights professionals and advertising effectiveness researchers to better detect emergent patterns and to draw stronger inferences about consumer behaviors, preferences, and lifestyle attributes. The enhanced data mining system would utilize state-of-the-art pattern recognition and machine learning techniques to dynamically process and interpret location and other types of data. If successful, this research will impact the state-of-the-art in location analytics.This research has the potential to meet the need of consumer insights professionals to better understand how consumers behave, without the use of lengthy surveys. In a broader sense, this research aims to accelerate progress in the emerging field of location analytics. This research can lead to the creation of a location analytics dashboard, similar to existing dashboards for web analytics. Most web analytics dashboards measure metrics such as site visits, page views and time spent for given online properties; analogously, the location analytics dashboard would measure visits by real consumers to physical locations. Such a location analytics dashboard could be offered on a subscription basis to companies that depend on consumer behaviors in the physical world ? including retailers, hotel/resort chains, restaurants, and travel companies. Such a dashboard would address a broad range of market research opportunities, from shopper loyalty research to store sitting to marketing effectiveness measurement. Additional future impacts of the proposed effort include the ability to integrate location analytics data into Geographic Information Systems for improved public safety, municipal planning and transit systems design.

这项小型企业创新研究阶段项目旨在改善用于位置分析的数据挖掘技术。该项目将重点介绍由消费者移动设备生成的半连续GPS和/或基于WiFi的位置数据的分析。预期的改进将使消费者见解专业人士和广告有效性研究人员更好地检测出紧急模式，并提出有关消费者行为，偏好和生活方式属性的更强有力的推断。增强的数据挖掘系统将利用最先进的模式识别和机器学习技术来动态处理和解释位置以及其他类型的数据。如果成功的话，这项研究将影响位置分析中最新的研究。这项研究有可能满足消费者见解专业人员的需求，以更好地了解消费者在不使用冗长调查的情况下的行为。从广义上讲，这项研究旨在加快位置分析领域的进步。这项研究可以导致创建位置分析仪表板，类似于现有的Web Analytics仪表板。大多数Web Analytics仪表板衡量指标，例如网站访问，页面视图和给定在线属性所花费的时间；类似地，位置分析仪表板将测量实际消费者对物理位置的访问。这样的位置分析仪表板可以以订阅为基础向依赖物理世界中消费者行为的公司提供？包括零售商，酒店/度假胜地，餐馆和旅行公司。这样的仪表板将解决广泛的市场研究机会，从购物者的忠诚度研究到存储坐着到营销有效性测量。拟议的工作的其他未来影响包括将位置分析数据集成到地理信息系统中，以改善公共安全，市政计划和运输系统设计。