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A Case Study by Type of Experience Marketing Based on Data Intelligence(DI)

  • Journal of Communication Design
  • Abbr : JCD
  • 2020, 73(), pp.397-414
  • DOI : 10.25111/jcd.2020.73.29
  • Publisher : CDAK Society of Communication Design
  • Research Area : Arts and Kinesiology > Design > Visual Information Design > Information Design
  • Received : September 4, 2020
  • Accepted : October 26, 2020
  • Published : October 31, 2020

Kim, Soo jung 1

1을지대학교

Accredited

ABSTRACT

While considering various cases of data intelligence (DI) technology that enables segmented and elaborate targeting and DI-based experience marketing using the foregoing with the advent of data economy, this study aims to raise awareness of the necessity of differentiated marketing communication and segmentation of follow-up studies by classifying types through a survey targeting experts and hands-on workers. Although data intelligence using data, algorism and AI technology has settled down as a new marketing trend, definition of theoretical concept and studies related to the marketing still remain insufficient. Thus, this study classified the types through analysis of various cases and survey targeting hands-on workers and experts in addition to extensive literature review of DI and typological approach focusing on the ‘core technology’ which is embedded for collection of consumer information. Based on the result of analysis, this study classified types of DI-based experience marketing finally as 4 kinds of SNS-connected, location-based, identification technology and programmatic type. This study confirmed that DI-based experience marketing includes AI technology and different forms of algorithm formula, which is collecting and using personal information with more aggressive and various methods through connection with SNS, location-based, identification, programmatic technology that are the core technology loaded for collecting data of segmented consumers. Through the aforementioned, this study made an in-depth consideration of DI-based experience marketing, and this study is considered meaningful in a sense that it enabled segmentation of follow-up studies through classification of types. With the standard for type classification, however, this study still has a limit that it failed to use various methods of approach. This study aims to provide academic and working-level implications for follow-up studies on DI-based experience marketing environment that enables hyper-personalized targeting through advancement of an innovative data technology.

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