A1 Refereed original research article in a scientific journal
Customer segmentation using online platforms: isolating behavioral and demographic segments for persona creation via aggregated user data
Authors: An J, Kwak H, Jung SG, Salminen J, Jansen BJ
Publisher: SPRINGER WIEN
Publishing place: Wien
Publication year: 2018
Journal: Social Network Analysis and Mining
Journal name in source: SOCIAL NETWORK ANALYSIS AND MINING
Journal acronym: SOC NETW ANAL MIN
Article number: ARTN 54
Volume: 8
Issue: 1
Number of pages: 19
ISSN: 1869-5450
eISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-018-0531-0
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/35657656
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.
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