Cited by 131Customer churn and segmentationSurvey Methodology and NonresponseSurvey Sampling and Estimation Techniques

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Increasing sample size compensates for data problems in segmentation studies

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Dolnicar, Sara, Grün, Bettina, Leisch, Friedrich·2016·Journal of Business Research

DOI 10.1016/j.jbusres.2015.09.004

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Abstract

Survey data frequently serve as the basis for market segmentation studies. Survey data, however, are prone to a range of biases. Little is known about the effects of such biases on the quality of data-driven market segmentation solutions. This study uses artificial data sets of known structure to study the effects of data problems on segment recovery. Some of the data problems under study are partially under the control of market research companies, some are outside their control. Results indicate that (1) insufficient sample sizes lead to suboptimal segmentation solutions; (2) biases in survey data have a strong negative effect on segment recovery; (3) increasing the sample size can compensate for some biases; (4) the effect of sample size increase on segment recovery demonstrates decreasing marginal returns; and—for highly detrimental biases—(5) improvement in segment recovery at high sample size levels occurs only if additional data is free of bias.

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Authors: Dolnicar, S., Grün, B., & Leisch, F.
Affiliations: Johannes Kepler University of Linz (AT)
BOKU University (AT)
ORCID: Grün, Bettina
Leisch, Friedrich
Venue: Journal of Business Research
Publisher: Elsevier BV
Published: 2016-02
Volume: 69
Issue: 2
Pages: 992-999
ISSN: 0148-2963 (ISSN-L)
DOI: 10.1016/j.jbusres.2015.09.004
OpenAlex: W2177427102
Cited by: 131
References: 72
Citations by year: 2026: 7 · 2025: 9 · 2024: 20 · 2023: 17 · 2022: 12 · 2021: 14 · 2020: 14 · 2019: 17 · 2018: 12 · 2017: 6 · 2016: 3
FWCI: 17.37
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Journal of Business Research (publishedVersion, cc-by)
RePEc: Research Papers in Economics (submittedVersion)
WU Research (submittedVersion)
Funders: Australian Research Council (ARC)
Austrian Science Fund (FWF) (DP110101347, LX0881890, V170-N18)
Topics: Social Sciences › Business, Management and Accounting › Marketing › Customer churn and segmentation
Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
Keywords: market segmentation, sample size, data quality, artificial datasets, survey sampling, data-driven segmentation

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Increasing sample size compensates for data problems in segmentation studies

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