Publication Type

Journal Article

Version

publishedVersion

Publication Date

8-2018

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 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

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

Discipline

Computer and Systems Architecture | Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Social Network Analysis and Mining

Volume

8

Issue

1

First Page

1

Last Page

19

ISSN

1869-5450

Identifier

10.1007/s13278-018-0531-0

Publisher

Springer Verlag (Germany)

Additional URL

https://doi.org/10.1007/s13278-018-0531-0

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