Big Data in Casino Affiliate Marketing: How to Apply the Tool

In the era of hyper-competition and active digital promotion, operators are increasingly turning to Big Data as a strategic asset.

Deep analytics of user behaviour, referral sources, and the LTV indicator help not just “drive traffic” but also qualitatively scale an affiliate network, control costs, and predict efficiency precisely to a click.

Rosloto experts talk about the technology’s role in the promotion of gambling projects and the successful experience of market leaders.

What is Big Data in Casino Affiliate Marketing

In modern digital advertising, especially in the entertainment field, the concept is not just a large amount of information, but the key to:

• deep personalisation;
• prediction of user behaviour;
• identification of hidden patterns that are inaccessible during the superficial analysis.

The tool enables operators and partner networks to make data-driven decisions, from selecting promotional channels to evaluating traffic quality and combating fraud.

Details Included in Big Data Affiliate Marketing

Let us consider the key types of information.

Traffic Sources

Each player comes to an online casino through a specific channel.

The technology allows entrepreneurs to collect, compare, and analyse the following aspects:

1. SEO traffic. These are details on keywords, pages, and sites that customers use to visit a gambling portal or mobile betting application.
2. PPC (Pay-Per-Click). The metric shows which ads, creatives, or offers that best resonate with the audience.
3. Push notifications and email newsletters. The category includes open and click-through rates, as well as the response time.
4. Social networks and content platforms. The emphasis is placed on the interaction with clients through TikTok, YouTube, Telegram, and other digital resources.

The obtained information allows business owners to understand which sources bring active and solvent players, and which ones can drive only garbage traffic or bots.

Geolocation, Devices, and Technical Parameters

Big Data collects the details not only on the audience’s behaviour but also on the following aspects:

1. Geography. This is the IP address, city, country, and other parameters that are necessary to confirm the legality of the game.
2. Device. Both the type of gadgets (desktops or tablets) and the operating system used (Android, iOS) are important.
3. Browser and OS. The study of data allows operators to identify non-standard scenarios or suspicious activities (for example, fraud from emulators).
4. Internet provider and connection speed. Sudden changes affect the customer experience and can signal cases of scams.

The creation of a technical profile of a casino visitor helps quickly target advertising by selected countries, exclude risky geolocations (for example, with a high level of chargeback), and track suspicious patterns.

Actions Before and After Registration

This is a behavioural analysis of a client on the path from a click to real operations:

1. Pre-signup indicators. The technology records the number of pages viewed, the amount of time spent on them, and return indicators.
2. Post-signup actions. The system analyses whether gamblers made a deposit, how often they visited the online casino after that, what content was launched, and how long they played.

The behaviour before and after registration helps predict the LTV metric, evaluate the webmaster’s effectiveness, and eliminate the audience’s drop-off points.

Conversion and LTV

The most valuable data is related to the turnover of funds:

1. CR. This is the ratio of registrations to clicks.
2. FDR. The metric shows what percentage of registered clients made a deposit.
3. ARPU. This is the average revenue per paying customer.
4. LTV. The parameter displays how much one player brings to a casino over the entire period of his or her activity on the website.

The analysis of such indicators allows entrepreneurs to identify the best affiliates, predict the income, and dynamically re-allocate budgets.

Signs of Fraud and Anomalies

Big Data plays an important role in detecting scammers and identifying the following aspects:

• IP and device matches between different accounts;
• suspiciously high conversion on a single digital portal;
• identical behaviour among hundreds of casino visitors (for example, bots with one user agent);
• too fast registration after a click;
• gaming activity at unnatural hours and with an unrealistic duration of sessions.

It is theoretically impossible to identify such patterns manually, especially when there are tens of thousands of clicks and logins per day.

How Big Data Increases the Efficiency of Affiliate Networks

The collection of huge amounts of information is just the beginning. The main value is revealed when these details are analysed and implemented into business processes in real time.

The tool allows operators and their partners to monitor the numbers and make dynamic decisions that grow income, reduce risks, and increase competitiveness.

Optimisation of CPA and RevShare Models

One of the key tasks of Big Data is the flexible management of affiliate payments depending on the quality of traffic.

A system based on such technology performs the following tasks:

• ranking partners taking into account the quality of attracted clients (deposits, LTV, and churn rate);
• increased payments to affiliates that provide high conversion and profitable traffic;
• reduction of rates for managers who attract fraud or insolvent users.

The implementation of Big Data ensures fair motivation, budget control, and a focus on the long-term value of players.

Dynamic Pricing

The technology allows entrepreneurs to implement automatic changes in CPL or CPA depending on the forecast of the LTV. Machine learning algorithms and predictive behavioural models are used for this purpose.

If, for example, the system projects that a client will deposit $100, then the rate for this affiliate can automatically increase from $40 to $70.

Gamblers with a low expected LTV will cost less, which will protect operators from overspending and higher expenses.

Personalisation of Landing Pages and Offers

Big Data allows casino owners to change the content depending on the user's profile.

The system takes into account the following factors:

• gender and age (including the behaviour or cookie profile);
• device and operating system (iOS users, for example, are more inclined toward casual gameplay);
• geography, language, and time zone;
• traffic source (e-mail, SEO, or teaser network).

The female audience that uses iPhones will be offered a landing page with a lifestyle plot, slots like Sweet Bonanza, and a no-deposit bonus. Men who use Android will be offered a sports theme, matches, and bets.

Automatic Detection and Ban of Scammers

Fraud in affiliate networks is a huge problem. Entrepreneurs face click bots, multi-accounting, spoofing, and other types of offenses that reduce the effectiveness of marketing.

The use of Big Data and special algorithms helps to perform the following tasks:

• track suspicious activity (identical IP, user agent, and cookie);
• see the same behavioural patterns (for example, 50 registrations with the same actions);
• automatically transfer a suspicious partner to quarantine or for manual verification;
• stop payments until the audit is completed.

If operators manage a crypto casino, it is worth additionally connecting blockchain analytics tools (TRM Labs and Elliptic).

Optimisation of Marketing Costs

When business owners have accurate data on the ROI of each channel, it is possible to:

• increase the budget for high-yield traffic (for example, allocate money for Facebook Ads in Canada);
• suspend or reduce rates on sources with a large number of zero deposits;
• impose limits on ineffective affiliates without the risk of losing LTV;
• use lookalike models (search for similar players who behave like top online gamblers).

The application of the technology helps entrepreneurs save up to 20–40% of their budget during the first 6 months after the tool’s implementation.

Legal Aspects of Working with Big Data

Using large amounts of information opens up vast opportunities for precise targeting, personalisation, and protection against fraud. However, with the power of details comes serious legal liability, especially in highly regulated jurisdictions.

GDPR

The European Data Protection Directive is a key document that describes the collection, storage, and processing of EU citizens’ private information.

The main principles of GDPR are:

1. Transparency. Players must be clearly notified about what details are required, why, and how they will be used.
2. Consent. To process non-essential data (for example, marketing cookies or geolocation), it is necessary to obtain explicit approval from customers.
3. Right to be forgotten. At the user's request, all information that he provided must be deleted without delay.
4. Data minimisation. Operators have no right to collect or keep more personal details than are needed for a specific purpose.
5. Storage limitation. Entrepreneurs should have the info no longer than is necessary.

Using tracking pixels and behavioural analytics without notification or consent of casino visitors can result in fines of up to €20 million (or 4% of the global annual turnover).

ePrivacy Directive and Cookie Legislation

The document complements the GDPR and regulates the application of special files, trackers, and other identifiers, including pixel data and fingerprinting.

Key requirements for entrepreneurs:

• before installing necessary cookies (in the field of marketing or analytics), it is necessary to obtain user consent;
• customers must be able to refuse and change settings at any time;
• banners must be informative, not masked or manipulative.

In some countries (France, Germany, and Italy), supervisory authorities penalise companies for collecting cookies without consent panels.

UK Data Protection Act (DPA 2018)

After Brexit, Great Britain implemented its adaptation of the GDPR. The document regulates the same processes but has several local features.

For example, special attention is paid to the transfer of information to third parties and outside the UK. The regulation obliges operators to conduct a Data Protection Impact Assessment if sensitive or large-scale user details are processed.

Affiliates and advertising networks are also subject to the DPA, so liability for offences is shared.

PIPEDA (Canada)

The Personal Information Protection and Electronic Documentation Act applies to Canadian commercial organisations and requires:

• obtaining consent to collect data;
• explaining the purposes of the acquisition and use of personal details;
• providing user access to the info;
• protecting data from unauthorised disclosure.

Unlike the GDPR, the PIPEDA norms are more lenient but in the case of working with information of EU citizens, the European regulation is still in place.

Practical Legal Responsibilities of Operators

Regardless of the jurisdiction, any iGaming startup working with Big Data must implement the following basic compliance measures:

1. Documentation and notifications. This is a Privacy Policy with transparent explanations (what information, why and how it is processed, etc.), a Cookie Policy, and a user agreement (ToS), including a section on data protection.
2. Consent and interfaces. Entrepreneurs are obliged to develop a CMP platform with the option of selecting and managing cookies. It is also necessary to take into account user rights: access to personal details, their edition, and deletion. Such options are usually implemented through private accounts.
3. Technical protection. This is data encryption during transmission and storage (TLS, AES), role-based access, and audit logs.
4. Third-party agreements. All contractors, advertising portals, and affiliates that can see the information must sign a DPA and adhere to the same privacy policy as operators.

Real Cases and Strategies of Gambling Brands

Let us consider how top providers apply technology to optimise their marketing policies:

Betsson Group: Traffic Clustering and Chargeback Reduction

Casino owners have developed a unique system based on behavioural analytics.

The program studies more than 100 parameters for each lead, including:

• referral sources;
• geolocations and devices;
• the complexity of the path through the website (the number of clicks, the depth of viewing);
• behaviour within specific gaming verticals (casino, betting, or live);
• the average gap between the registration and the first deposit.

Based on this information, Betsson segments players and partners — from “high-quality traffic” to suspicious or “questionable ROI”. If, for example, a client is in a risky cluster, the service automatically lowers the affiliate’s rating and offers the payment by CPA, not RevShare.

The use of Big Data allowed to:

• reduce the number of chargebacks by 27%, especially for unauthorised transactions;
• find non-obvious patterns and, as a result, minimise losses within the partner network.

Kindred Group: Machine Learning for Evaluating Affiliates

The gaming holding has implemented an ML platform that automatically analyses the effectiveness of each webmaster in real-time.

The system takes into account the following factors:

• statistics on registrations, deposits, and retention;
• geographic indicators and compliance with target markets;
• behavioural patterns of players;
• fraud signals (duplicate IP, cookie stuffing, and low engagement);
• anomalies in refunds and churn rate after 3–7 days.

The model identifies “green”, “orange”, and “red” partners based on the expected LTV indicator and probability of return. Affiliates with a high score receive priority in promotional materials and bonus offers. Low-quality traffic was automatically transferred to the CPA model with a payout limit.

The implementation of the ML platform allowed Kindred Group to increase revenue from RevShare partners by 18% and also reduce the number of problematic settlements by 22%.

Entain: ROI Forecasting

The company launched its platform for analysing affiliate traffic based on Microsoft Azure and Apache Spark, processing more than 1 billion events per day. The system studies the following factors:

• the behaviour of each lead from the moment of click;
• dynamics across all verticals (betting, casino, or bingo);
• outflow, fraud level, and speed of deposits;
• comparison of traffic with the analogues in the segment.

Entain uses predictive models based on Big Data to forecast the long-term ROI for each affiliate even before the end of the first month of work. For example, if players brought by the partner stop being active after 2 days, in 90% of cases, the algorithm immediately signals the ineffectiveness.

The result of the operation was an increase in the company's ROI by 15–20%, including due to the redistribution of budgets and focus on strong customer acquisition channels.

The Main Things about Big Data in Casino Affiliate Marketing

The tool can be described as a full-fledged ecosystem for predictive analytics, segmentation, and traffic optimisation.

Key aspects that entrepreneurs should take into account:

• The advantages of the solution include enhancing CPA and RevShare models, dynamic pricing, as well as reduced user acquisition costs. The technology allows business owners to automatically identify and ban fraudsters, personalise landing pages and offers, etc.
• Collection, processing, and storage of large data must take place in accordance with GDPR, ePrivacy Directive, and cookie legislation.
• Industry leaders (Betsson, Kindred, and Entain) are actively implementing such technology in their software. Providers conduct a qualitative assessment of affiliates, test different monetisation strategies, predict ROI, and reduce chargeback.

Rosloto experts have vast experience in launching and promoting iGaming projects.

The studio offers different formats (turnkey casinos and White Label platforms), innovative payment systems, modern entertainment content, and other profitable solutions.