The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/fffc883e-6adb-4042-bc69-4e4c53dc4a24

Paulino, Emmanuel (2024): Survey Data - Cluster Analysis of Pet Owners. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/fffc883e-6adb-4042-bc69-4e4c53dc4a24.v1

Dataset

• Marketing
• Other Studies in Human Society
• Business and Management
• Psychology
• Sociology
• Commercial Services
• Commerce, Management, Tourism and Services
• Psychology and Cognitive Sciences
• Studies in Human Society

Cluster Analysis, Consumer Behavior, Market Segmentation, Pet Attachment, Pet Care, Pet Ownership, RFM Analysis

February 22 to October 6 2024

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Emmanuel Paulino

The "Cluster Analysis of Pet Owners" dataset, consisting of 250 entries, provides a detailed view of various dimensions of pet ownership. It contains Likert scale items answered from 1 - Strongly Disagree to 4 - Strongly Agree. It includes personal assessments of the impact pets have on owners' well-being, with statements like "Owning a pet has helped my health" and "Owning a pet adds to my happiness." Additionally, it captures attachment levels and the emotional bonds owners feel toward their pets through statements such as "I am very attached to my pet" and "My pet and I have a close relationship." This dimension reflects how pet ownership affects emotional well-being and connection, critical for understanding the strength of these owner-pet relationships.

Beyond emotional bonds, the dataset explores the interaction frequency and nature between owners and pets, such as through statements like "I play with my pet quite often" and "I often take my pet along when I visit friends." A separate set of variables examines companionship, with items like "My pet is like a friend that can keep me from being lonely," highlighting pets' social and emotional roles. Furthermore, the dataset includes Recency, Frequency, and Monetary (RFM) metrics, likely indicating recent engagement levels, frequency of interaction, and expenditures on pets. This mix of emotional, social, and financial metrics provides a rich basis for clustering pet owners based on their behaviors, attachment levels, and perceived benefits of pet ownership.

• 2024-11-11 first online, published, posted

4TU.ResearchData

.csv

De La Salle University Dasmarinas