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

SBIR 第一阶段：基于位置的移动消费者分析系统

• 批准号: 1013624
• 负责人: Thaddeus Fulford-Jones
• 金额: --
• 依托单位: Cadio Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1013624&HistoricalAwards=false
• 关键词: SBIR; Phase; System; Location; Based

This Small Business Innovation Research (SBIR) Phase I project aims to develop a data mining system to analyze semi-continuous GPS data generated by consumer mobile devices. The system will thereby detect emergent patterns and draw inferences about each consumer's behavior, preferences, and lifestyle for market research. The proposed data mining system would utilize state-of-the-art pattern recognition and machine learning techniques to dynamically process and interpret GPS data. The objectives of this proposal are, first, to develop and deploy a scalable, extensible database of collected and processed location data from opted-in mobile consumer devices, second, to develop a machine learning system to classify consumer behaviors, third, to develop a real-time visit detection engine that triggers an action based in part on an individual's dwell time within a geofenced zone, and fourth, to evaluate and refine this system by conducting a one-month pilot study with GPS data. If successful, this research will prove the feasibility of a system that can draw inferences about consumer behavior by analyzing semi-continuous GPS data.Analysis of consumer behavior using electronically-derived location data can both supplement and contextualize existing market research methods, thereby providing quantitative actionable inferences to retailers and brands. If this research effort is successful, the proposed system would allow businesses to more efficiently and accurately conduct consumer-focused market research. Such a system would address a broad range of market research opportunities, from shopper loyalty research to store siting to marketing effectiveness measurements. Recent changes in the marketplace indicate that market and technology conditions are now favorable for the development of the proposed data mining system. Specifically, the accelerating penetration of GPS-equipped mobile phones is accompanied by a growing need for brands and retailers to more robustly justify marketing spend and business decisions by using verifiable analytics that go beyond self-reported survey data. Additional future impacts of the proposed effort include the ability to combine GPS-derived mobile consumer analytics with Geographic Information Systems for improved public safety, municipal planning and transit systems design.

这个小型企业创新研究（SBIR）第一阶段项目旨在开发一个数据挖掘系统，以分析消费者移动的设备产生的半连续GPS数据。该系统将因此检测紧急模式，并得出关于每个消费者的行为，偏好和生活方式的推论，用于市场研究。 拟议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，动态处理和解释全球定位系统数据。该提议的目标是，首先，开发和部署从选择加入的移动的消费者设备收集和处理的位置数据的可缩放的、可扩展的数据库，其次，开发机器学习系统以分类消费者行为，第三，开发实时访问检测引擎，其部分地基于个人在地理围栏区域内的停留时间来触发动作，以及第四，利用全球定位系统数据进行为期一个月的试点研究，以评估和完善这一系统。如果成功的话，这项研究将证明一个系统的可行性，可以通过分析半连续的GPS数据来推断消费者的行为。使用电子衍生的位置数据来分析消费者的行为可以补充和情境化现有的市场研究方法，从而为零售商和品牌提供定量的可操作的推论。如果这项研究取得成功，拟议的系统将使企业能够更有效、更准确地进行以消费者为中心的市场研究。这样一个系统将解决广泛的市场研究机会，从购物者忠诚度研究到商店选址到营销效果测量。市场上最近的变化表明，市场和技术条件，现在的发展所提出的数据挖掘系统是有利的。具体而言，随着配备GPS的移动的手机的加速普及，品牌和零售商越来越需要通过使用超越自我报告的调查数据的可验证分析来更有力地证明营销支出和业务决策的合理性。拟议工作的其他未来影响包括将联合收割机GPS衍生的移动的消费者分析与地理信息系统相结合的能力，以改善公共安全、市政规划和交通系统设计。