• DocumentCode
    2123918
  • Title

    Study on the VOC Analyzing Methods Based on Concentrated Web Data

  • Author

    Hongbin, Yu ; Minghua, Shi ; Xinhua, Xiao

  • Author_Institution
    Sch. of Mech. & Electron. Eng., Tianjin Polytech. Univ., Tianjin
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    23
  • Lastpage
    28
  • Abstract
    Voice of customer (VOC) is a key driving force for product development, as well as a fundamental base of marketing decision-making. The traditional approaches for VOC analysis using face-to-face customer interviews often result in high cost and long lead-time. Thus it is no longer suitable for dynamic response to changing market conditions. With fast growth and application of internet technology, extensive VOC with dynamic information can be collected and exchanged through the web media. In this paper, a new method of exploring and analyzing customer requirements on Web data source is presented. The scope and advantages of this approach are discussed. A systematic mapping framework, from the original web data to structured marketing setting, is constructed. Supporting knowledge base and rule-driven mining methods are also developed. Finally, a case study using car users data is presented to demonstrate the effectiveness of the proposed approach.
  • Keywords
    Internet; customer satisfaction; data mining; knowledge based systems; marketing data processing; Internet technology; concentrated Web data source; face-to-face customer interviews; knowledge base method; marketing decision-making; rule-driven mining method; systematic mapping framework; voice of customer; Consumer electronics; Costs; Data analysis; Data engineering; Information analysis; Internet; Knowledge acquisition; Knowledge engineering; Product development; Speech analysis; Data analysis; Voice of customer; Web data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3488-6
  • Type

    conf

  • DOI
    10.1109/KAM.2008.20
  • Filename
    4732779