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

这项小型企业创新研究（SBIR）第一阶段项目旨在开发一个数据挖掘系统，以分析消费者移动设备产生的半连续GPS数据。因此，该系统将检测出出现的模式，并推断出每个消费者的行为、偏好和生活方式，以进行市场研究。提出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GPS数据。该提案的目标是，首先，开发和部署一个可扩展的、可扩展的数据库，从可选的移动消费者设备中收集和处理位置数据，其次，开发一个机器学习系统来分类消费者行为，第三，开发一个实时访问检测引擎，该引擎在一定程度上基于个人在地理隔离区域内的停留时间触发行动，第四，通过对GPS数据进行为期一个月的试点研究来评估和完善这一系统。如果成功，本研究将证明通过分析半连续GPS数据推断消费者行为的系统的可行性。利用电子定位数据对消费者行为进行分析，既可以补充现有的市场研究方法，也可以将其背景化，从而为零售商和品牌提供定量的可操作推断。如果这项研究工作取得成功，拟议中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，再到营销效果测量。最近市场的变化表明，市场和技术条件现在有利于所提出的数据挖掘系统的发展。具体来说，随着配备gps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商业决策的合理性。拟议工作的其他未来影响包括将基于gps的移动消费者分析与地理信息系统相结合，以改善公共安全、市政规划和交通系统设计。

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.