Big Data in Online Gambling: Using Analytics for Competitive Advantage

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Big data refers to large data sets collected by companies. In a competitive business environment, the information is used to gain more knowledge about users, their preferences and wants, and larger market trends. The gambling industry is one of the most competitive markets out there, so it’s no surprise that operators are collecting, analysing and using big data to improve their competitive advantage and get ahead of the game.

Understanding the data

Like most apps, websites, search engines, and other businesses, gambling companies collect big data on their consumers. Big data encompasses everything, and not all information is useful; much is background noise. 

For big data to be valuable, it must be sorted and analysed by advanced tech and analytics, machine learning and data processing software. From the results, businesses can then use the information to take actionable steps, profile different customers, and design strategies to target them best and improve the user experience.

There are many analytics tools in the gambling industry that are involved in data collection and analysis, such as Customer Relationship Management (CRM) software, business intelligence (BI) tools, performance analytics, player tracking software, A/B testing tools, fraud detection tools, and social media analytics.

Product personalisation and prediction

Big data allows gambling companies to profile customers and design marketing strategies that work for different consumers. This also allows gambling operators to create the best possible experience for consumers based on their typical betting and game preferences, spending habits, loyalty preferences and more. 

When it comes down to segmenting the market and targeting new consumers, this means gambling sites that have used and analysed the data well can appropriately advertise different types of welcome bonuses and games for different kinds of players, as they’ve already profiled players and know what’s most likely to result in a sign-up, based on what other players in same grouping have found attractive in the past.

Similarly, knowing more about consumers can lead to better customer retention through predictive analysis. Modern AI and machine learning can predict what customers will likely enjoy next based on their past actions, bet types and game preferences. This information is also used when deciding when to launch a new promotion and who to show it to.

The use of big data isn’t limited to gambling operators; it can also be used for marketing purposes by affiliates like which can also collect and analyse big data to profile players, segment the market and make the best recommendations on where a consumer should play based on the gambling profile they fit. 

Getting ahead of competitors

Big data can also be instrumental for SEO and competitor analysis in that stakeholders in the gambling industry can use data and analytics to assess what their competitors are doing, such as marketing strategies and retention tactics, and design products based on what’s been proven to work, potentially innovating on it further and getting ahead of the market.

Game design and engagement

Collecting data on which games players like, how much they spend, and how long they play different options can be directly used by gambling content suppliers to create products and games that fit players’ preferences. In the same way, real-time analytics allow all gambling platforms to understand betting trends and behaviours, adapting their products or promotions to fit the latest trends and events.

Consumer protection and safer gambling

For gambling sites to be successful and legal, they must be secure, responsible and protect consumers. Recent research into gamblers has shown that most millennial (75%) and Gen Z (77%) consumers are more likely to consider operators they feel want them to live a sustainable lifestyle. In short, safety and responsible gambling policy can be a competitive advantage in today’s market. 

A great example of this is FanDuel, which last year got ahead of this trend and upcoming regulation by introducing mandatory account limits in the UK and Ireland for players aged 18-24 (this is the age group most vulnerable to gambling harms), thus firmly demonstrating to consumers that they place sustainability and safety above profiteering. When FanDuel later asked this age group how they felt about the policy, 77% supported it.

Big data and AI are being widely implemented by gambling sites to monitor consumer accounts for signs of gambling harms, ensuring that potentially damaging behaviours (like rapid and significant spending) are flagged for intervention. Some interventions are automated by AI and in more severe cases, customer actions can be flagged for further investigation and human handling. Based on past modelling of at-risk players, big data and AI can also be used to predict which players may encounter difficulties in the future, allowing for greater support to be provided earlier to those fitting the profile.

Gambling companies have always used big data to follow player behaviours and monitor for harm. The difference now is that AI has improved real-time processing and analysis capabilities.

While big data and AI do not replace the need for human intervention in cases of potential gambling harms, it is far more adept than older systems at flagging unusual account activity and, therefore, means at-risk players are supported earlier. Plus, as some interactions, like playtime or spending reminders, can be automated, there’s wider awareness. 

Responsible gambling research

According to prominent RG expert and psychologist Mark Griffiths, some gambling companies share data sets with researchers, which has been instrumental in researching the efficiency of different responsible gambling tools and approaches. 

Unlike self-reporting studies, the consumer data collected by gambling operators doesn’t come with the same bias; it also provides a much larger data set than can be collected by researchers conducting first-hand studies.

Thanks to big data and academic analysis, we know that gambling-intense players who set financial limits spend less than those who do not and that personalised messaging in responsible gambling interactions is more successful than non-personalised messages. Predictive modelling and behavioural tracking of big data sets have also allowed comparative analysis between betting verticals and problem gamblers, providing insight into behavioural differences. 

The more we know about problem gamblers, the better safeguarding techniques become. This is crucial for public health, personal livelihoods, and gambling operators’ success. Having sustainable, safe and more ethical policies is a competitive advantage in today’s market.

Fraud detection

Big data and real-time analysis are used for fraud detection in the gambling industry. This includes monitoring for player cheating, bonus fraud, and outside threats, like brute force hacking attempts and is achieved through AI recognising patterns and unusual activity through monitoring user accounts in real-time.

Data safety and storage concerns

The use of big data by companies has caused concerns among consumers regarding its use and storage, especially in the face of recent cyber-attacks (in September 2023, both Caesars and MGM were hacked in the US, with the same ransomware group claiming responsibility for the attacks and accessing consumer data). 

Collecting and storing large amounts of data can be a challenge. Still, it’s not the wild west, and there are protections in place, as in most geographical locations, companies that collect data have legal obligations regarding how it is stored, collected and managed. 

In Europe, this is regulated by the General Data Protection Regulation (GDPR), which, according to the EU, is the world’s strictest privacy and security law. GDPR applies to companies targeting or collecting data related to people in the EU, so its application is wide-reaching. 

GDPR includes in which scenarios companies can collect data, the limitations of this, how it should be updated and stored and who is accountable. It is up to companies to prove that they comply with GDPR, and penalties for not following rules amount to millions of euros (the maximum set at €20m). For the most part, this regulation ensures that gambling companies do their utmost to protect consumer data and employ the latest security protocols.

What’s the bottom line?

The more gambling companies know about players and their behaviours, the better they can provide a service. Big data can help companies understand customer needs, predict what they’ll enjoy next, improve the user experience, and optimise their operations internally. 

Hence, when big data is appropriately analysed and understood, operators can take actions that lead to a competitive advantage, such as creating products and promotions based on what’s trending with players. It has also proved instrumental in furthering the field of player protection and responsible gambling research.

Disclaimer: This article contains sponsored marketing content. It is intended for promotional purposes and should not be considered as an endorsement or recommendation by our website. Readers are encouraged to conduct their own research and exercise their own judgment before making any decisions based on the information provided in this article.


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