Data Analytics in Gambling: Increased Brand Recognition
Experts of the Rosloto studio explain how big data is used in the casino and sports betting industry. You will learn about the advantages of the solution, as well as the experience of top entertainment companies.
Analytics Based on the Tool
In this case, we are talking about the collection and processing of huge amounts of insights from different sources. This can be internal details of iGaming sites, data from social networks, search queries, and mentions in the media and news feeds.
There is a lot of fragmented info, and it is constantly updated. To process it, special software and powerful analytical services are needed.
The term “big data” became popular in the early 2000s when large enterprises first encountered an increased volume of provided details. In the 2010s, as land-based and virtual casinos developed, the solution began to be actively used in gambling as well.
Today, the industry manages huge amounts of information:
- more than 2 million active players generate 50 TB per day;
- multiplayer entertainment (from classic board solutions to action missions) creates 1 TB of data for the same period, including through in-game telemetry;
- social casino products generate 150 GB;
- users launch 2.5 billion sessions per month, which is comparable to 50 billion minutes of playing time.
The video game sector is a leader in the implementation of analytical tools. For example, in the well-known MOBA League of Legends, images of all characters are created after an in-depth study of customer preferences.
Therefore, during the passage of missions, people receive only attractive personalities, which can then be exchanged in the internal environment.
How Big Data Analytics Works
Let us consider the main stages of information handling:
- Collection of all details. They come from various sources. The gambling industry uses text, audio, and video materials, as well as fragments of computer code, the Internet of Things (digital footprint), content created independently by customers, etc.
- Processing. This is the transformation of fragmented data into a single, understandable form for use. After that, it is purified and duplicated (irrelevant details are removed).
- Analysis. For qualitative assessment, intelligent and predictive analytics of the info, deep learning, and other methods are used.
Many gambling companies also install GPU-class databases. This ensures the viewing of longer histories and provides a better study of trends, as well as accurate forecasts for future periods.
Operators also use various cloud-based offerings, such as Google BigQuery with PubSub or SQream DB on AWS, which give them the following benefits:
- access to an unlimited number of event logs;
- high compression ratio with disk space saving;
- real-time analytics that requires minimal start-up costs.
How Data Interpretation is Changing the Gambling Sector
The tool is transforming the entertainment industry in several ways.
Studying the Behaviour of Clients
Arrays of structured information are used to track players’ actions and provide them with individual promotions, bonuses and games, as well as other functions within the digital platform.
With the help of big data, it is possible to maintain high customer engagement for a long time. To do this, entrepreneurs use a wide variety of details, from website traffic statistics to demographic nuances.
In July 2023, the UK Gambling Commission conducted a study on how personalised experience affects the audience:
- 27% increase in the involvement of casino visitors, reaction to new content, missions, promotions, and other offers;
- 14% growth of retention indicators.
Customisation begins with the website recommending entertainment (slots, cards, or lotteries) based on previous solutions that a person has chosen. Besides, it includes the adaptation of bonuses based on past behaviour patterns.
The user interface can also be personalised. This allows operators to adjust to the individual needs of clients and their way of playing.
Targeted Marketing
Thanks to big data, businessmen can segment the audience and conduct narrowly focused advertising campaigns. This is a promotion of an exact digital platform with addressed messages, high-quality targeting, and division of the audience into groups depending on the requests and preferences.
This kind of marketing provides increased engagement and monetisation rates for the following reasons:
- individual in-game advertising;
- personalised e-mails;
- special offers and surveys on social networks created based on the interests of casino visitors.
Development of Entertainment Content
Predictive analytics allows entrepreneurs to anticipate the needs of gamblers and eliminate problems before they arise. Thanks to this, it is possible to completely or partially replace the testing stage, as well as simplify and speed up the release of new products.
Studying big data allows project owners to:
- determine which game functions are popular and which require improvement;
- adjust mechanics, difficulty levels, or other characteristics based on real feedback and audience reactions;
- reduce the budget for the development and promotion of new solutions.
Fraud Detection
This is the identification of atypical behaviour of clients, seemingly unrelated accounts, hacking attempts, and theft of confidential information. Special software instantly blocks suspicious activity on the website and notifies operators about it.
iGaming brands can create secure management systems, thus supporting fair play. This implies timely rewarding of real customers, protection from bots and scammers, and prevention of minors or socially vulnerable people from entering the digital resource.
Optimisation of the Entertainment Platform
Analytics gives an accurate idea of the peak load time on the IT infrastructure of the online casino, the correct power distribution, and bottlenecks in the operation of the equipment.
The obtained information allows to:
- optimise server performance;
- ensure smooth gameplay and work without delays or failures.
Use of Big Data in the Industry
Let us consider how large companies apply analytics.
Kindred Group
In early 2023, the casino and sports betting provider presented its updated Kindred Sportsbook (KSP) platform. The product was created using behavioural research, which makes it one of the best in the market.
Big data in the digital platform provided:
- deep audience segmentation and creation of personalised offers for each selected group;
- formation of a high-quality event line with different types of odds and their adjustment in real time;
- effective fight against the spread of rates and other types of fraud in betting.
According to the results of 2023, the company's net revenue (after-tax) reached £893 million.
Today, Kindred Group is one of the 5 largest operators in Western Europe and is present in 7 out of 10 major markets of this region. These are the Netherlands, Great Britain, France, Sweden, and Belgium.
Playtech
IMS Platform is one of the leading solutions of the brand. It is based on deep data analysis and provides high efficiency and personalised experience.
The product was presented at the end of 2021. In just one year, the manufacturer recorded the registration of more than 38 million new accounts and an increase in profits by 20%.
The income growth is explained by many factors. The key one is the individual user experience. For example, the IMS Platform generated more than 500 thousand targeted messages sent by e-mail or through social networks.
The program also helped in the creation of about 900 titles and intros that the enterprise’s B2B partners of Playtech placed on their websites and third-party resources.
Segmentation based on big data is also used in other solutions of the firm. This is a PAM application, a SaaS affiliate aggregator, which is a portal for playing poker iPoker.
iSoftBet
The European provider implements new gaming functions using analytical tools. The company has long been cooperating with Snowflake Computing, an advanced service for generating and securely storing information in the cloud.
Today, the brand produces its slots and bingo entertainment and also works with more than 45 licensed suppliers to integrate games into the proprietary GAP platform. Content personalisation is achieved through advanced analytics and localisation of processed details in the Snowflake Computing storage.
The Main Thing about Big Data in the Casino Niche
What is Big Data Analytics in Gambling?
Collecting and processing data sets from casino internal sources, social networks, search queries, and media.
Daily Data Volume
Data from 2+ million active players
Information from multiplayer games
Data from social casino games
Gaming sessions per month (around 50 billion minutes of gameplay)
Data Processing Stages
Impact of Analytics on Gambling
Personalized offers, content, and bonuses. Engagement increases by 27%, retention by 14%
Audience segmentation, quality targeting, and ad campaigns
Adjusting games and features based on data analysis, reducing budgets, and accelerating launch
Detecting suspicious activity, preventing bots, and protecting data
Improving server performance and ensuring smooth gameplay
Examples of Big Data Analytics Implementation by Major Companies
Benefits for Operators
Tools and Methods
Google BigQuery, SQream DB — enable the analysis of large data volumes
Prevent fraudulent activities and protect player privacy
The tool is one of the catalysts for industry growth in the coming years.
Key aspects that business owners need to take into account:
- The advantages of using the option include the customer behaviour study, the development of interesting and engaging content, and the detection of fraud. Analytics also helps optimise the iGaming platform and launch targeted marketing campaigns.
- Today, big data is applied by many entrepreneurs and software vendors. Branded products can be found in the assortment of Kindred Group, Playtech, iSoftBet, and other industry leaders.
From the Rosloto studio, it is possible to order a turnkey online casino and other profitable solutions.
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- games for sale and rent;
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- preparation of a business plan;
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