Leveraging social analytics data for identifying customer segments for online news media

In this work, we describe a methodology for leveraging large amounts of customer interaction data with online content from major social media platforms in order to isolate meaningful customer segments. The methodology is robust in that it can rapidly identify diverse customer segments using solely o...

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Main Authors: JANSEN, Bernard J, JUNG, Soon-Gyo, AN, Jisun, KWAK, Haewoon, KWAK, HAEWOON
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Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/sis_research/6654
https://ink.library.smu.edu.sg/context/sis_research/article/7657/viewcontent/Leveraging_Social_Analytics_Data_for_Identifying_Customer_Segments_for_Online_News_Media.pdf
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spelling sg-smu-ink.sis_research-76572022-01-14T03:13:58Z Leveraging social analytics data for identifying customer segments for online news media JANSEN, Bernard J, JUNG, Soon-Gyo AN, Jisun KWAK, Haewoon KWAK, HAEWOON In this work, we describe a methodology for leveraging large amounts of customer interaction data with online content from major social media platforms in order to isolate meaningful customer segments. The methodology is robust in that it can rapidly identify diverse customer segments using solely online behaviors and then associate these behavioral customer segments with the related distinct demographic segments, presenting a holistic picture of the customer base of an organization. We validate our methodology via the implementation of a working system that rapidly and in near real-time processes tens of millions of online customer interactions with content posted on major social media platforms in order to identify both the distinct behavioral segments and corresponding impactful demographic segments. We illustrate the functionality of the methodology with real data from a major online content provider with millions of online interactions from more than thirty countries. We further show one possible use for such information via the automatic generation of personas for an organization, which can be used for the formulation of marketing strategy, implementation of advertising plans, or development of products. The research results offer insights into competitive marketing and product preferences for the consumers of online digital content. We conclude with a discussion of areas for future work. 2017-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6654 info:doi/10.1109/AICCSA.2017.64 https://ink.library.smu.edu.sg/context/sis_research/article/7657/viewcontent/Leveraging_Social_Analytics_Data_for_Identifying_Customer_Segments_for_Online_News_Media.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University customer segmentation digital marketing online news social analytics social media web analytics Artificial Intelligence and Robotics Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic customer segmentation
digital marketing
online news
social analytics
social media
web analytics
Artificial Intelligence and Robotics
Databases and Information Systems
spellingShingle customer segmentation
digital marketing
online news
social analytics
social media
web analytics
Artificial Intelligence and Robotics
Databases and Information Systems
JANSEN,
Bernard J,
JUNG, Soon-Gyo
AN, Jisun
KWAK, Haewoon
KWAK, HAEWOON
Leveraging social analytics data for identifying customer segments for online news media
description In this work, we describe a methodology for leveraging large amounts of customer interaction data with online content from major social media platforms in order to isolate meaningful customer segments. The methodology is robust in that it can rapidly identify diverse customer segments using solely online behaviors and then associate these behavioral customer segments with the related distinct demographic segments, presenting a holistic picture of the customer base of an organization. We validate our methodology via the implementation of a working system that rapidly and in near real-time processes tens of millions of online customer interactions with content posted on major social media platforms in order to identify both the distinct behavioral segments and corresponding impactful demographic segments. We illustrate the functionality of the methodology with real data from a major online content provider with millions of online interactions from more than thirty countries. We further show one possible use for such information via the automatic generation of personas for an organization, which can be used for the formulation of marketing strategy, implementation of advertising plans, or development of products. The research results offer insights into competitive marketing and product preferences for the consumers of online digital content. We conclude with a discussion of areas for future work.
format text
author JANSEN,
Bernard J,
JUNG, Soon-Gyo
AN, Jisun
KWAK, Haewoon
KWAK, HAEWOON
author_facet JANSEN,
Bernard J,
JUNG, Soon-Gyo
AN, Jisun
KWAK, Haewoon
KWAK, HAEWOON
author_sort JANSEN,
title Leveraging social analytics data for identifying customer segments for online news media
title_short Leveraging social analytics data for identifying customer segments for online news media
title_full Leveraging social analytics data for identifying customer segments for online news media
title_fullStr Leveraging social analytics data for identifying customer segments for online news media
title_full_unstemmed Leveraging social analytics data for identifying customer segments for online news media
title_sort leveraging social analytics data for identifying customer segments for online news media
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/sis_research/6654
https://ink.library.smu.edu.sg/context/sis_research/article/7657/viewcontent/Leveraging_Social_Analytics_Data_for_Identifying_Customer_Segments_for_Online_News_Media.pdf
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