Harnessing Business Insights from Unstructured Customer Data

利用非结构化客户数据的业务洞察

• 批准号: DP230101490
• 负责人: Prof Stephan Ludwig
• 金额: $ 21.93万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP230101490
• 关键词: Harnessing; Business; Insights; Unstructured; Customer

Resulting from customers’ widespread uptake of online channels to buy and communicate has been a surge in online reviews and social media posts. This textual information offers a viable alternative to surveys that Australian businesses currently conduct to obtain customer insights. However, these reviews are unstructured and require substantial pre-processing to extract underlying customer perceptions. Therefore, this project aims to develop a novel machine learning approach to quantify the business-relevant information contained in textual information shared by customers online. This alternative approach will provide significant cost-saving benefits for a range of Australian companies, such as retailers, hotels, airlines and restaurants.

由于客户广泛采用在线渠道进行购买和沟通，在线评论和社交媒体帖子激增。这种文本信息提供了一个可行的替代调查，澳大利亚企业目前进行，以获得客户的见解。然而，这些评论是非结构化的，需要大量的预处理来提取潜在的客户感知。因此，该项目旨在开发一种新的机器学习方法来量化客户在线共享的文本信息中包含的业务相关信息。这一替代方法将为零售商、酒店、航空公司和餐馆等一系列澳大利亚公司节省大量成本。