On the taxonomy of social media marketing approach: Extended abstract

Hiroshi Koga, Sachiko Yanagihara

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a reference framework for the social media marketing that has attracted attention in recent years. In other words, in this paper, we attempt to classify the focus of marketing that utilizes social media. Generally, it is thought that corporate control is possible for "owned media" and "paid media." On the other hand, utilization of "earned media" or "social media" is understood as a factor that companies cannot control. In this paper, we will use two types of context and marketing approach as a point of utilization of uncontrollable media. That is, (1) customer journey or customer retention, and (2) which context is focused on contexts formed through social media. Therefore, this paper is organized as follows; First, the two dimensions of taxonomy are introduced. Second, three cases corresponding to each context are shown. Differences in the marketing approach in each case will also be discussed. Thirdly, the effectiveness of the proposed type (reference framework) is examined.

Original languageEnglish
Title of host publicationProceedings of the 5th Multidisciplinary International Social Networks Conference, MISNC 2018
PublisherAssociation for Computing Machinery
ISBN (Print)9781450364652
DOIs
StatePublished - 2018/07/16
Event5th Multidisciplinary International Social Networks Conference, MISNC 2018 - Saint-Etienne, France
Duration: 2018/07/162018/07/18

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th Multidisciplinary International Social Networks Conference, MISNC 2018
Country/TerritoryFrance
CitySaint-Etienne
Period2018/07/162018/07/18

Keywords

  • Context
  • Customer Journey
  • Customer Retention
  • Social Media Marketing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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