Report
Understanding and measuring consumer trust in the gambling industry - Full technical report
The understanding and measuring consumer trust in the gambling industry full technical report from The Gambling Commission.
Quantitative survey
An online survey was developed and conducted via Yonder Data Solutions proprietary online panel. The sample for the survey was 1,000 Great British adults aged 18 and over who had participated in any gambling activity in the past 12 months, to ensure that questions were posed to a relevant audience. Given the nature of the statements, it was decided that those who only used lottery products (such as National Lottery draws or scratchcards) would not be included in the survey sample.
Quotas were set on age, gender, work status and region to ensure the sample was designed to be broadly representative of the GB population. Weighting was then applied to the final achieved sample to ensure the key demographic groups are proportionally reflected in the final data, improving its accuracy and representativeness. A full list of quotas and weighting schemes are provided in the appendices. Fieldwork took place between 10 to 12 June 2024.
Questionnaire content
To inform the most important drivers of trust, the survey tool needed to incorporate 2 separate measures of these statements. One question was required to understand the relative importance of different themes, while the other was required to measure participant attitudes towards these trust themes, that would later be used for a factor analysis.
Two key questions were developed, one explicitly in relation to trust in the gambling industry, and the other more generally of how the gambling industry is perceived among consumers using an attitudinal Likert scale.
Trust specific question – Maximum Difference (MaxDiff) exercise
For the trust specific question, respondents were asked the following:
We’d now like to show you a series of statements relating to factors which might influence your level of trust in the gambling industry. You will see these statements over the next several screens. For each set of statements, we would like you to select which you think is most important and which you think is least important, in terms of trusting the gambling industry.
For this question, to ascertain the most pertinent themes that drive trust in the gambling industry and their relative importance, a Maximum Difference (MaxDiff) exercise was conducted. This technique is particularly effective for evaluating a set of statements by forcing respondents to make trade-offs between them.
In the MaxDiff exercise, respondents were presented with subsets of the 25 statements about trust. Each subset typically contains a smaller number of statements (for example, 3 to 4 at a time). For each subset, respondents indicate which statement they feel is the most important and which is the least important. This forced-choice approach ensures that respondents cannot give equal importance to all statements in any subset, compelling them to make a clear prioritisation. Each statement is shown multiple times in different combinations, ensuring robust data collection and minimising the influence of context or chance.
The data generated from these choices are analysed using advanced statistical models to derive a score for each statement. These scores, reflect the relative importance of each statement. The scores are then indexed at a total level, for ease of interpretation (in this case, between 1 to 10), providing a clear hierarchy of statements and themes.
Importantly, MaxDiff scores are relative rather than absolute. For example, if 1 statement has a score of 8 and another has a score of 2, this indicates that the first statement is considered 4 times more important than the second. These scores do not represent absolute levels of importance but highlight how much more or less influential one theme is compared to another in driving trust. This indexing method is particularly valuable in the context of identifying trust drivers in the gambling industry, where there are nuances and issues are multi-faceted. Results from the Max Diff test can be found in the published narrative report.
Gambling industry performance question
A second question was asked of respondents in relation to their attitudes towards the performance of the gambling industry:
Still thinking about gambling industry, to what extent do you agree or disagree with the following statements?
This question was asked in relation to 23 of the 25 statements. Only 2 statements were not included in this question. The first was “Gambling companies are licensed in Great Britain”, and the second was “Gambling companies are a familiar or a reputable name”. These statements were omitted from the performance question due to the more objective or factual nature of these questions, meaning that they were not suitable for the attitudinal Likert scale.
Wording of the remaining 23 statements was tweaked very slightly for this question, in order to fit the Likert agree or disagree scale used but remained fundamentally comparable to those used in the MaxDiff exercise. A full list of the statements used in the MaxDiff exercise can be found in the appendices.
Other survey questions were also used as a means of sub-analysis for the key questions. This included key sociodemographic questions, gambling activities, PGSI, and an attitudinal ‘gambling literacy’ question to measure general perceptions of the risks of gambling. A link to the full question set including the gambling literacy question can be found in the appendices.
Analysis and statement refinement
Upon completion of the survey, further data interrogation was undertaken via a factor analysis of the statements used in the performance question.
Factor analysis is a statistical method used to simplify complex data by grouping related items into a smaller set of categories or variables. This simplification works by identifying patterns in the responses. It looks at how different statements relate to each other, finding groups of items that people tend to respond to in similar ways. These groups are classed as factors, and they represent the underlying motivations or themes that drive the responses. This survey incorporated 23 statements relating to trust factors, and the factor analysis showed how these statements associate with each other, and which factors have the strongest bearing on answers given with the themes identified. Instead of dealing with all 23 statements individually, the analysis highlights the most notable drivers of trust in a robust way.
Using a combination of the Max Diff scores, factor analysis scores and consideration of meaningful sub-group differences for each exercise, each statement was analysed using an index spreadsheet to consider the merits and justification for inclusion or exclusion in the final list of statements considered to holistically reflect the most pertinent drivers of trust. A workshop took place in order to refine the list of statements down to 10 for inclusion the GSGB survey. This process considered statements that had the highest Max Diff scores and highest importance scores using the factor analysis, alongside a qualitative assessment of statements that were particularly important, for example due to their distinct nature. It was also considered that representation from each thematic category should be included in the final list of statements to ensure coverage against the Commission’s licencing objectives.
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Last updated: 23 July 2026
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