Customer segmentation using online platforms

isolating behavioral and demographic segments for persona creation via aggregated user data

Jisun An, Haewoon Kwak, Soon gyo Jung, Joni Salminen, Bernard Jansen

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer segments to automatically generate personas, which are fictional but accurate representations of each integrated behavioral and demographic segment. Results show that this approach can accurately identify both behavioral and demographical customer segments using actual online customer data from which we can generate personas representing real groups of people.

Original languageEnglish
Article number54
JournalSocial Network Analysis and Mining
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Dec 2018

Fingerprint

Factorization
customer
segmentation
social media
present
gender
methodology
interaction

Keywords

  • Customer segmentation
  • Marketing
  • Personas
  • Social computing
  • System design
  • Web analytics

ASJC Scopus subject areas

  • Information Systems
  • Communication
  • Media Technology
  • Human-Computer Interaction
  • Computer Science Applications

Cite this

@article{1980a8a266814b2f9f9e4f13d51353e5,
title = "Customer segmentation using online platforms: isolating behavioral and demographic segments for persona creation via aggregated user data",
abstract = "We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer segments to automatically generate personas, which are fictional but accurate representations of each integrated behavioral and demographic segment. Results show that this approach can accurately identify both behavioral and demographical customer segments using actual online customer data from which we can generate personas representing real groups of people.",
keywords = "Customer segmentation, Marketing, Personas, Social computing, System design, Web analytics",
author = "Jisun An and Haewoon Kwak and Jung, {Soon gyo} and Joni Salminen and Bernard Jansen",
year = "2018",
month = "12",
day = "1",
doi = "10.1007/s13278-018-0531-0",
language = "English",
volume = "8",
journal = "Social Network Analysis and Mining",
issn = "1869-5450",
publisher = "Springer Wien",
number = "1",

}

TY - JOUR

T1 - Customer segmentation using online platforms

T2 - isolating behavioral and demographic segments for persona creation via aggregated user data

AU - An, Jisun

AU - Kwak, Haewoon

AU - Jung, Soon gyo

AU - Salminen, Joni

AU - Jansen, Bernard

PY - 2018/12/1

Y1 - 2018/12/1

N2 - We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer segments to automatically generate personas, which are fictional but accurate representations of each integrated behavioral and demographic segment. Results show that this approach can accurately identify both behavioral and demographical customer segments using actual online customer data from which we can generate personas representing real groups of people.

AB - We propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to first identify behavioral customer segments and then to identify demographic customer segments. We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers. In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer segments to automatically generate personas, which are fictional but accurate representations of each integrated behavioral and demographic segment. Results show that this approach can accurately identify both behavioral and demographical customer segments using actual online customer data from which we can generate personas representing real groups of people.

KW - Customer segmentation

KW - Marketing

KW - Personas

KW - Social computing

KW - System design

KW - Web analytics

UR - http://www.scopus.com/inward/record.url?scp=85052204723&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052204723&partnerID=8YFLogxK

U2 - 10.1007/s13278-018-0531-0

DO - 10.1007/s13278-018-0531-0

M3 - Article

VL - 8

JO - Social Network Analysis and Mining

JF - Social Network Analysis and Mining

SN - 1869-5450

IS - 1

M1 - 54

ER -