How does Blask AI power Customer Profile?

Picture this: you're running an online casino, and it feels like you're the new kid on the block, trying to fit in with the cool crowd. You want to be the go-to spot for all the gaming enthusiasts out there, but how do you get to know them better? It's like trying to remember the names and favorite games of all your classmates who skipped school to hang out at the arcade.

That's where Blask comes in, with the game-changing Customer Profile feature. It's like having a cheat sheet that tells you everything you need to know about your players. You'll learn that Ben is all about Pac-Man, while George can't get enough of Mario Bros. You'll discover that Max can only swing by once a week because his parents keep a tight leash on his allowance, while John prefers a good old-fashioned game of poker over anything else.

With Blask Customer Profile, you'll feel like you've known your audience forever like you've been skipping classes together and hanging out at the arcade for years.

What is Blask Customer Profile?

Imagine: you’re an iGaming operator looking to conquer new markets and take your offerings to the next level. You know the key to success is understanding your target audience inside and out, but the thought of conducting traditional market research makes you feel like “Harold, feel the pain.” The process is time-consuming, expensive, and often doesn’t give you the deep insights you crave.

Instead of a thousand questions (and user responses), here’s Blask Customer Profile.

Customer Profile leverages Blask's predictive AI capabilities to create a comprehensive, country-specific profile of your iGaming audience. Currently in beta, this groundbreaking feature offers a glimpse into the future of user analytics. We're continuously enhancing it, with plans to integrate our RAG (Retrieval-Augmented Generation) technology and extensive databases for even more precise insights.

Imagine having crystal-clear visibility into your online betting and gambling audience. Customer Profile delivers comprehensive breakdowns of age demographics, social status, motivations, and behavioral triggers – and that's just the beginning.

Blask’s journey to develop the Customer Profile feature.

Step 1: Conducting surveys to collect primary data.

Blask’s journey to develop the customer profile feature began with an extensive survey campaign. We conducted over 80,000 surveys to collect primary data on the thought patterns and preferences of users in the iGaming industry. These surveys were conducted over the first two quarters, Q3 and Q4 2023, in different countries across different continents, and were conducted manually to ensure the accuracy and reliability of the data collected.

A survey in one country (e.g. India) was conducted across the entire country, without targeting specific regions, to ensure a fair representation of players across the country. Blask targeted the general population aged 18 and above who had engaged in various iGaming activities in the past six months, such as online sports and eSports betting, online casino games and slots, live casino sessions, fantasy sports, and online poker or rummy (a game specific to India. For other surveys, we selected local sports or games to get a full picture). The number of survey participants varied depending on the popularity of iGaming in a particular country and the number of brands available.

Our primary objective is to obtain reliable data, with a target error rate of 4% and a confidence level of 95%. Our sample targets the entire adult population to ensure a comprehensive and unbiased representation of the iGaming audience, capturing insights from all relevant demographics.

To gather genuine opinions, Blask placed ads in mobile games and apps, encouraging participants to enhance their survey experience. We verified participants’ phone IDs and locations to ensure the reliability of their input, preventing incorrect information and ensuring honest responses. The survey used a variety of response formats, including free text, single-choice, and multiple-choice.

Step 2: Putting the Blask AI to the test and perfecting the questionnaire.

You might be wondering, "Where does the AI model come into play?" Don't worry; we'll get to that soon. But first, let's answer the question: why did we conduct so many surveys and research?

We had two main goals in mind when we carried out these surveys:

• To put our predictive AI model to the test and see how accurate it was.
• To figure out which questions, answer options, and sections would be the most interesting and useful for the final product.

By comparing the survey results with what our AI model predicted, we could check how well the model was performing and make any necessary tweaks to improve its accuracy.

But that's not all! The survey data also helped us fine-tune our questionnaire. We were able to pinpoint the most engaging and informative questions, answer options, and sections.

For example, let's look at how the responses for Casino Online Betting Motivations differ between Bangladesh and India:

Bangladesh (4 options):

India (15 options):

The comparison between the surveys conducted in Bangladesh and India reveals a striking difference in the depth and breadth of insights gathered. While the Bangladesh survey offered a basic understanding with just four options, the Indian survey provided a rich, multifaceted view of online casino betting motivations with 15 distinct options.

Step 3: Developing the Predictive AI Model.

Blask’s predictive AI, which forms the core of the customer profile feature, was developed using a comprehensive approach that included extensive data collection, training, and refinement. The model was designed to accurately categorize and analyze user profiles using data from a variety of sources, including proprietary databases and third-party data.

Data collection and training.

To ensure the accuracy and reliability of the AI ​​model, we used a multi-faceted data collection strategy:

• Survey data (from Step 1) served as the basis for training the AI ​​model.
• External sources: We supplemented the survey data with information obtained from external sources such as industry reports, market research, and publicly available data on user behavior and preferences.
• Proprietary database: Blask utilized its proprietary database, which contains valuable insights and data points specific to the iGaming industry. This database provided a unique advantage in training the AI ​​model to understand the nuances and dynamics of the market.

Blask AI: Industry knowledge.

One of the core strengths of Blask’s AI model is its deep understanding of the iGaming industry. We build the model using a wide range of industry knowledge.

What does it include:

• Regulatory data: Blask AI has a deep understanding of each market’s regulatory landscape, allowing it to consider the impact of legal and regulatory issues on user behavior and preferences.
• Market dynamics: Blask AI understands the unique dynamics of each brand and market, including factors such as competition, market share, and growth potential (and with them, changes in player patterns).
• Sporting events: Blask AI takes into account the impact of major sporting events on user behavior, as these events can significantly impact player engagement and preferences.
• Player psychology: Third-party data and a huge amount of research and documentation (we counted 64 GB of data) allowed the AI ​​to identify motivations, preferences, and behavioral patterns, allowing it to make accurate predictions about user behavior. Yes, Blask AI is inside the head of everyone who has ever visited a casino website.

Step 4: Compare the AI ​​model output with the survey results.

After developing the predictive AI model, we tested it by asking it the same questions as the surveys we had previously conducted. The model’s answers were then compared to the survey results to assess its accuracy (this is what Step 1 was for, because data accuracy is the new oil).

Dmitry Belianin, co-founder of Blask, explains the process:

We started with surveys, and then that evolved into an AI model. When we saw that our AI-based predictive model, built on information from external sources and a closed database, matched the real survey data, it worked.

This is the first iteration of the feature, designed to showcase our approach and elicit feedback from the industry. Our goal is to demonstrate the potential of AI-driven customer profiling in iGaming.

At the heart of this innovation is the Blask AI RAG (Retrieval-Augmented Generation) model. RAG combines the power of large language models with the ability to retrieve and incorporate relevant information from a vast database. This approach allows our AI to generate more accurate and contextually relevant profiles by drawing on a wide range of up-to-date industry data, market trends, and user behavior patterns.

The RAG model will enhance our Customer Profile feature by:

• Improving accuracy through real-time data retrieval
• Providing more nuanced and market-specific insights
• Adapting quickly to changing trends in the iGaming industry

Your feedback will directly contribute to the evolution of this feature, helping us to build a more robust, accurate, and industry-tailored AI model for customer profiling. We invite you to be part of our mission to revolutionize the approach of iGaming analytics.

Unlock your iGaming potential with Blask!

Blask empowers you to make data-driven decisions, optimize marketing strategies, and drive significant GGR increases by providing unparalleled clarity about the iGaming market and your performance.

Curious about our precision? Discover our article "What is Blask?" and how Blask's cutting-edge technology is transforming iGaming analytics.

Ready to experience Blask in action?

• Sign up for free demo access and explore real data on the TOP-5 brands per country: Get a firsthand look at Blask's capabilities.

• Request a personalized demo with full access to data tailored to your niche and objectives. Fill out the form at blask.com to help us prepare use cases specific to your needs.

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