SBIR Phase I: Knowledge Modeling for Data Driven Optimization Based Strategic Promotion Design

SBIR 第一阶段：基于数据驱动优化的战略促销设计的知识建模

• 批准号: 0441316
• 负责人: Sridevi Sarma
• 金额: $ 10万
• 依托单位: Infolenz Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-01-01 至 2005-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0441316&HistoricalAwards=false
• 关键词: SBIR; Phase; Knowledge; Modeling; Data

This Small Business Innovation Research (SBIR) Phase I project is to develop a data-driven optimization-based approach to retail market modeling and strategic pricing. Retail companies are faced with the persistently renewed challenge and burden of designing sales promotions. The company's baseline technologies in retail market model building and strategic pricing have field-demonstrated the potential to turn large volumes of individual purchase history records into profitable decisions. The objective is to extend the reach of the baseline technologies to address a broader variety of promotion design problems. Specific technical objectives are: 1) Time-sensitive market models (Derive a market model of time sensitive behavior. Desirable elements include seasonality, timed follow-on and sequential purchase analysis.), 2) Multidimensional market models (Derive a market model of multidimensional associations in market behaviors, such as customer attributes, catalogue alignment, or store differentiation), and 3) Streamlined promotion optimization (Enable an "automation" of the promotion design process through the data driven extraction of market parameters, such as the expected response to joint product offers or multiple promotion offers, for mathematical promotion optimization). These advances to the baseline company's technology can form the foundation of a commercial product for strategic promotion design.This project will have a broader impact on education and career training. As part of its dissemination activities the company will offer a course on "Scientific Marketing" in the MIT Industrial Liaison Program. The added value specific to this project lies in its highly interdisciplinary nature, involving scientific marketing, large-scale optimization, pricing theory, and data analysis. Results from such activities inevitably allow cross-fertilization of concepts that catalyze new educational or research initiatives. Indeed it is in small companies where new economic theories emerging from academia have an opportunity to be evaluated in a true data driven environment. Regarding career training, Infolenz will continues its regular hiring of summer interns in a stock compensated arrangement to get first hand startup company experience.

这个小型企业创新研究（SBIR）第一阶段项目是开发一种基于数据驱动的优化方法，用于零售市场建模和战略定价。 零售公司面临着不断更新的挑战和设计促销活动的负担。 该公司在零售市场模型构建和战略定价方面的基线技术已经证明了将大量个人购买历史记录转化为盈利决策的潜力。 目的是扩大基线技术的范围，以解决更广泛的促销设计问题。 具体技术目标是：1）时间敏感市场模型（推导出时间敏感行为的市场模型。 理想的要素包括季节性、定时跟进和连续购买分析。2)多维市场模型（推导出市场行为中多维关联的市场模型，如客户属性，目录对齐或商店差异化），以及3）流线型促销优化（通过市场参数的数据驱动提取，例如对联合产品报价或多个促销报价的预期响应，实现促销设计过程的“自动化”，用于数学提升优化）。这些基线公司的技术进步可以为战略促销设计的商业产品奠定基础。该项目将对教育和职业培训产生更广泛的影响。 作为其传播活动的一部分，该公司将在麻省理工学院工业联络方案中开设“科学营销”课程。 该项目的附加值在于其高度跨学科的性质，涉及科学营销，大规模优化，定价理论和数据分析。 这些活动的结果不可避免地允许促进新的教育或研究倡议的概念的相互交流。 事实上，在小公司中，学术界提出的新经济理论有机会在真正的数据驱动环境中进行评估。 关于职业培训，Infolenz将继续定期招聘暑期实习生，以股票补偿安排获得第一手创业公司经验。