Over the past decade, the gambling industry has widely adopted responsible gambling (RG) tools to promote player protection and harm minimization, as required by gambling regulators for operating licenses. Recent studies have provided evidence on the effectiveness of these tools in promoting responsible gambling behavior and reducing excessive gambling among high-intensity gamblers.
Examples of RG tools include:
- Behavioral analytic tools for identifying problem gamblers
- Personalized messaging systems for at-risk gamblers
- Player cards and identification measures
- Rewards for responsible gambling practices
- Online techniques such as limit-setting features, loss-limit reminders, and temporary self-exclusions
One valuable source of data for RG research is the use of account-based tracking data provided by gambling operators. This data allows for large-scale, ecologically valid studies on real gamblers in real time, providing a more objective and accurate understanding of gambling behavior compared to self-report or experimental data. For example, survey studies based on self-report data may not accurately reflect actual gambling behavior, as shown by our research that disproved claims of increased online gambling during Covid-19 lockdowns.
Our research has also focused on evaluating the efficacy of limit-setting features. Studies have shown that limit setting effectively reduces gambling expenditure among high-intensity players, including problem gamblers. While gambling operators may be concerned about reduced profits, it is important to prioritize long-term customer loyalty and sustainable business practices.
Another area of research has examined the impact of personalized messaging on gambling behavior. Our studies have demonstrated that online gamblers who receive targeted feedback and personalized information tend to gamble less, supporting the use of this tool by online gambling companies in promoting responsible gambling.
Furthermore, our research has utilized algorithms and behavioral tracking data to compare gambling behavior and markers of harm among different types of gamblers, such as online casino players and sports bettors. The findings highlighted distinct predictors for problem gambling-related exclusion in each group, providing insights for tailored interventions and harm prevention strategies.
It is important to acknowledge the limitations of behavioral tracking data, as it represents only one gambling site and does not capture an individual’s complete gambling behavior across multiple platforms. Additionally, the data cannot explain the motivations behind gambling, which self-report data can provide. Despite these limitations, the use of account-based tracking data has significantly advanced the field of responsible gambling research.
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