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Social Network Analysis and Mining (2018) 8:54
https://doi.org/10.1007/s13278-018-0531-0
ORIGINAL ARTICLE
Customer segmentation using online platforms: isolating behavioral
anddemographic segments forpersona creation viaaggregated user
data
JisunAn1 · HaewoonKwak1· Soon‑gyoJung1· JoniSalminen1,2· BernardJ.Jansen1
Received: 21 December 2017 / Revised: 28 April 2018 / Accepted: 5 August 2018 / Published online: 23 August 2018
© Springer-Verlag GmbH Austria, part of Springer Nature 2018
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 inte-
grated 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 Web analytics· Social computing· Personas· Marketing· System design· Customer segmentation
1 Introduction
One use of social media and other web analytics data is cus-
tomer segmentation (Jansen 2009), which is an approach
for separating an overall customer population based on
segment differences defined by a specific set of attributes.
Customer segmentation is a common practice across many
industries with the set of attributes utilized being relevant
to the particular domain. Examples of such domains include
marketing, advertising, education, and system design.
E-commerce companies and other organizations rely on cus-
tomer segmentation to target specific customer groups with
content and products that the consumers within a segment
would likely find relevant. Additionally, customer segmenta-
tion might also lead to a deeper understanding of customer
preferences, needs, and wants by isolating what each seg-
ment finds most valuable. Based on these insights, organi-
zations can more effectively engage with their customers,
audience, or users. In software design, marketing planning,
and advertising development, there are continuing efforts for
identifying and assessing segments of people (i.e., custom-
ers, audience, or markets) to optimize some performance
metric (e.g., the speed of task, buying preferences, or ease
of use).
Major online social media platforms used for distrib-
uting content and other products present unique chal-
lenges for customer segmentation efforts attempting to
rely on online customer data. The customer segmentation
approach relies on identifying key attributes from which
one can separate customers into segments (Cooil etal.
2008). Targeting customers via behavioral segmenta-
tion involves dividing the customer base based on their
collective behavior. A behavior can be a single attribute
* Jisun An
jisun.an@acm.org
Haewoon Kwak
haewoon@acm.org
Soon-gyo Jung
sjung@hbku.edu.qa
Joni Salminen
jsalminen@hbku.edu.qa
Bernard J. Jansen
bjansen@hbku.edu.qa
1 Qatar Computing Research Institute, HBKU, ArRayyān,
Qatar
2 Turku School ofEconomics, Turku, Finland
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