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Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery

The present study is the first to examine account-based tracking data of Portuguese online lottery players comprising the gambling activity of all active players over a one-year period (N = 154,585). The main research goal was the identification of groups or segments of players by their engagement l...

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Autores principales: Chagas, Bernardo T., Gomes, J. F. S., Griffiths, Mark D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437336/
https://www.ncbi.nlm.nih.gov/pubmed/34518986
http://dx.doi.org/10.1007/s10899-021-10072-9
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author Chagas, Bernardo T.
Gomes, J. F. S.
Griffiths, Mark D.
author_facet Chagas, Bernardo T.
Gomes, J. F. S.
Griffiths, Mark D.
author_sort Chagas, Bernardo T.
collection PubMed
description The present study is the first to examine account-based tracking data of Portuguese online lottery players comprising the gambling activity of all active players over a one-year period (N = 154,585). The main research goal was the identification of groups or segments of players by their engagement levels (high, neutral, low) and to assess preferences in product category with the use of CHAID (Chi-Square Automatic Interaction Detection) segmentation models, based on expenditure and sociodemographic variables. Findings showed that (1) age was found to be the most influential differentiating variable in player segmentation and had a positive correlation with expenditures and wagers, (2) gender was the second most influential variable (males represented 78.7% of players), (3) education the third most influential variable and had a negative correlation with expenditure, and (4) region was the least relevant variable. The models generated several players segments that engaged in different games. Older males (54–64 years; ≥ 65 years) were the most engaged overall. Younger males (18–34 years) were the least engaged but showed preferences for lotto as did females (35–49 years). Lower educated males and older males (49 years+) with a high school education were the most engaged in instant lottery games. These findings show that Portuguese lottery players can be grouped into several segments with distinct demographic characteristics and corresponding engagement levels. These findings help support more effective marketing segmentation and will help in the targeting of responsible gambling approaches.
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spelling pubmed-84373362021-09-14 Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery Chagas, Bernardo T. Gomes, J. F. S. Griffiths, Mark D. J Gambl Stud Original Paper The present study is the first to examine account-based tracking data of Portuguese online lottery players comprising the gambling activity of all active players over a one-year period (N = 154,585). The main research goal was the identification of groups or segments of players by their engagement levels (high, neutral, low) and to assess preferences in product category with the use of CHAID (Chi-Square Automatic Interaction Detection) segmentation models, based on expenditure and sociodemographic variables. Findings showed that (1) age was found to be the most influential differentiating variable in player segmentation and had a positive correlation with expenditures and wagers, (2) gender was the second most influential variable (males represented 78.7% of players), (3) education the third most influential variable and had a negative correlation with expenditure, and (4) region was the least relevant variable. The models generated several players segments that engaged in different games. Older males (54–64 years; ≥ 65 years) were the most engaged overall. Younger males (18–34 years) were the least engaged but showed preferences for lotto as did females (35–49 years). Lower educated males and older males (49 years+) with a high school education were the most engaged in instant lottery games. These findings show that Portuguese lottery players can be grouped into several segments with distinct demographic characteristics and corresponding engagement levels. These findings help support more effective marketing segmentation and will help in the targeting of responsible gambling approaches. Springer US 2021-09-13 2022 /pmc/articles/PMC8437336/ /pubmed/34518986 http://dx.doi.org/10.1007/s10899-021-10072-9 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Chagas, Bernardo T.
Gomes, J. F. S.
Griffiths, Mark D.
Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery
title Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery
title_full Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery
title_fullStr Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery
title_full_unstemmed Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery
title_short Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery
title_sort consumer profile segmentation in online lottery gambling utilizing behavioral tracking data from the portuguese national lottery
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437336/
https://www.ncbi.nlm.nih.gov/pubmed/34518986
http://dx.doi.org/10.1007/s10899-021-10072-9
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