I-Corps: D-Ready Mobile Guide

该项目的重点是调查分析技术，可以为决策提供信息-可能在广泛的领域。D-Ready将使用现代机器学习技术来处理和过滤团队将整理的数据，这些数据涉及选择偏好等领域。这项技术的部署将考虑到两个目标。 将采用一种调查设计方法，以帮助确保决策选择准则对个人用户没有偏见。这一点很重要，因为决策支持产品越无偏见，它就越受信任和使用。该团队还将使用光标跟踪技术来开发个人用户如何查看决策支持网站应用程序的深入统计图。这将允许团队使用非线性回归和分类方法将用户划分为不同的类型。从这些分析中获得的见解将对支持广泛应用的决策者很有价值。在I-Corps课程中应用客户发现流程，该团队打算提出一个更完整的价值主张，它将提供和完善最有用的产品功能。D-Ready被设想为一个在线和移动的决策支持指南，为用户创建简单，方便和公正的定制信息。所提出的技术在包括营销在内的多个领域具有潜在的广泛应用，例如，其中三步策略1）定义针对特定人群的吸引力，2）在用户对该吸引力做出反应时收集详细的交互行为数据，最后3）出于市场细分的目的分析该数据，代表了一种强大的新形式的调查收集。

This project focuses on techniques for survey analysis that can inform decision making -- potentially in a broad range of areas.D-Ready will use contemporary machine learning techniques to process and filter the data the team will collate regarding such areas as choice preferences. The proposed technology will be deployed with two goals in mind. A survey design methodology will be used to help ensure that decision-selection guidelines are unbiased for individual user. This is important because the more unbiased the decision support product, the more widely it will be trusted and used. The team will also use cursor-tracking technology to develop an in-depth statistical picture of how individual users view decision-support site-apps. This will allow for the team to use nonlinear regression and classification methods to segment users into distinct types. The insights learned from these analyses will be valuable to support decision makers in a broad range of applications. Applying the customer discovery process during the I-Corps curriculum, the team intends to come up with a more complete value proposition that it will provide and refine the product features that will be most useful.D-Ready is envisioned as an online and mobile decision support guide that creates customized information for users that is simple, convenient and unbiased. The proposed technology has potentially broad applications in several areas including marketing, for example, where a three-step strategy of 1) defining an attraction for a certain population, 2) harvesting detailed interactive behavior data while users react to that attraction, and finally 3) analyzing that data for the purpose of market segmentation, represents a powerful new form of survey collection.