SBIR Phase I: An Innovative and More Effective Means to Manage the Communication Process Between Colleges and Prospective Students

SBIR 第一阶段：管理大学和未来学生之间沟通过程的创新且更有效的方法

• 批准号: 0839300
• 负责人: Greg Perfetto
• 金额: $ 10万
• 依托单位: 422 Group
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-01-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0839300&HistoricalAwards=false
• 关键词: SBIR; Phase; Innovative; More; Effective

This Small Business Innovation Research Phase I project seeks to develop a more effective means to manage the communication process between colleges and prospective students by automating the response logic needed to successfully transition critical decision making steps. Data mining techniques and geo-demographic analysis have recently gained limited popularity in college recruiting as a means to segment prospect populations based on historical data and then to recalibrate manual communication strategies. However, these static methods are retrospective in nature and require several years of consistent historical data for implementation, limiting their appeal. The approach proposed in this research employs an automated system that analyzes the ongoing interaction between colleges and prospects. Through the application of database-embedded and integrated modeling and pattern analysis techniques, key decision points are identified in the communication process as they occur. The recruitment process in higher education is becoming increasingly complex and compressed. Students are waiting longer to reveal their interest to colleges and submitting applications to more colleges. There exists only a brief window, between the point a prospect becomes 'known' to a college and the actual matriculation decision, when the opportunity exists for targeted communications to simultaneously inform and influence each students' decision-making process. As competition for students increases dramatically over the next decade in the face of rising attendance costs, changing demographics, and a decline in the number of college-bound students, each institutions' ability to survive, much less prosper, will depend directly on its ability to identify, qualify, and communicate with prospective students in an more efficient and cost-effective manner. If successful, the effort proposed will provide a means for measurable value for those institutions that embrace this approach.

这个小企业创新研究第一阶段项目旨在开发一种更有效的方法，通过自动化成功过渡关键决策步骤所需的响应逻辑来管理大学和未来学生之间的沟通过程。 数据挖掘技术和地理人口分析最近在大学招聘中获得了有限的普及，作为一种手段，根据历史数据划分前景人群，然后重新校准人工沟通策略。然而，这些静态方法本质上是回顾性的，并且需要几年的一致历史数据来实现，这限制了它们的吸引力。在这项研究中提出的方法采用了一个自动化系统，分析高校和前景之间正在进行的互动。通过应用数据库嵌入式和集成建模和模式分析技术，关键决策点在通信过程中，因为它们发生确定。高等教育的招聘过程变得越来越复杂和紧凑。学生们等待更长的时间来向大学透露他们的兴趣，并向更多的大学提交申请。只有一个短暂的窗口，点之间的前景成为“已知”的大学和实际的录取决定，当有针对性的通信存在的机会，同时通知和影响每个学生的决策过程。随着未来十年学生竞争的急剧增加，面对不断上升的出勤成本，不断变化的人口统计数据，以及大学生数量的下降，每个机构的生存能力，更不用说繁荣了，将直接取决于其识别能力，资格，以及以更有效和更具成本效益的方式与潜在学生进行沟通。 如果成功，拟议的努力将为采用这一方法的机构提供一种可衡量价值的手段。