南美博彩市场-拉丁美洲 iGaming市场
南美博彩市场-拉丁美洲 iGaming市…
Now the gambling industry is growing, especially since many gambling investors began to use white label iGaming, the overseas gambling market has ushered in unprecedented prosperity. For example, in recent years, the gambling markets in countries such as Vietnam, Brazil, and Indonesia have been extremely hot. However, in such a hot gambling market, competition is inevitable, which is a huge challenge for every gambling practitioner. Therefore, how to accurately grasp the needs of gambling players has become the primary problem that gambling platform operators must face. With the continuous increase in gambling platforms and the differences in overseas gambling players due to cultural, religious, and other factors, the user portraits and behavioral analyses of gambling players are different. This leads to an important topic: how to successfully meet the needs of these gambling players. TC-Gaming editor will explore this issue in depth in this issue. What exactly is the user portrait and behavioral analysis of gambling players? If you can accurately understand the needs of players, it will play a key role in this regard. This will not only help to enhance the competitiveness of the platform but also better provide personalized services to players, to stand out in the fierce market competition.
The analysis of gambling players and user portraits is a complex and comprehensive process. It divides players into different groups through in-depth collection and analysis of data on gambling players' behaviors, preferences, habits, etc., and then constructs a detailed portrait of each group. These player portraits can include key information such as the player's age, gender, occupation, hobbies, payment ability, and other valuable data such as geographic location and frequency of activity participation. Through the analysis of gambling players and user portraits, gambling companies can better understand players' preferences, gambling habits, and satisfaction with the gambling platform experience. The analysis can not only provide a strong basis and help for gambling platforms from design, and function optimization to marketing and promotion, but also enable the platform to accurately locate the target user group in the competition, and improve user retention and platform interactivity.
To put it simply, it is to guess a person's income level based on his behavior and trends in the gambling industry, and how to better serve these people to encourage them to generate more bets. This method also has a similar name: audience targeting. However, for the editor of TC-Gaming, the most noteworthy thing in the portrait of a gambler should be the various attributes of the gambler, such as their living conditions, income level, personality characteristics, and other static or dynamic information. This information not only helps us understand the players' betting habits but also provides important data support for us to formulate more effective marketing strategies.
The process of building an accurate user profile of gambling players relies on a large amount of detailed and diverse data. This data can not only be obtained through traditional questionnaires but also be improved by collecting detailed feedback from users. In addition, deeper insights can be obtained by observing and studying the interactive behaviors of users on some social platforms. Most importantly, the records of actual gambling betting behaviors provide data that directly reflect user preferences and habits. These records can help us understand users' gambling betting patterns and motivations more comprehensively, thereby building a more accurate user profile of gambling players.
Generally, we collect information about gamblers in the following ways:
Use data to verify assumptions and judgments about users and find patterns; commonly used methods include: questionnaire surveys, background data, experiments, and industry report analysis;
Research and intuitively judge user types, characteristics, and future trends; commonly used methods include observation, interview, and diary analysis.
The last type is qualitative + quantitative analysis.
First determine the core user group, which may require backend data and questionnaires, and then use observation, interviews, diary analysis, etc. to adjust your operational strategy.
Segment the players based on the data collected to find out the characteristics that clearly distinguish different groups. This process involves analyzing the players' behavioral patterns in gambling games and classifying them according to the length of time they spend in the game, the number of bets they make, and the specific time and date they enter the platform. Through such segmentation, players can be classified as "casual bettors", "high rollers" and "potential players". Casual bettors generally tend to invest less time and money in the game, and more for entertainment. High rollers are players who are willing to invest a lot of money and time in gambling games, and they are usually more interested in high-risk games. Potential players are those who show the potential to increase their activity on the platform, and they may change their gambling habits over time. Therefore, through detailed player segmentation, the platform can more effectively formulate marketing strategies for different player groups.
Different gambling players are labeled through static data and dynamic data. Through the weight and arrangement of the labels, many user labels can be obtained. The required user labels can be selected according to one's own needs to find the corresponding users.
For example: In addition to basic user data, gambling platforms also need to know the user's interest in game types, single betting amount, amount of each recharge, date records of platform visits, duration of gambling games, historical betting records, etc. Then, they can recommend gambling game types and activities with higher label standards in a prominent place on the front desk, thereby encouraging gambling players to visit other games of the same type more frequently and generate more betting behavior.
When you understand user habits, it is also very useful for advertising on your gambling platform. For example, advertising betting on FB, Google, TikTok, etc. will select tags based on user attributes when you place ads. This allows for more accurate advertising.
Using data mining technology and statistical methods, we conduct a comprehensive and in-depth analysis of the information collected by gambling users. This analysis does not just stay on the surface, but through detailed calculations and evaluations, we can build sophisticated virtual models that can accurately represent the characteristics and behavior patterns of different player groups. By identifying and understanding these characteristics, we can better predict players' preferences and behaviors and provide them with more personalized and optimized services. This service not only helps to improve the gambling platform's user experience for players but also can greatly promote the growth and development of the gambling platform's performance, ensuring that the platform maintains a leading position in the highly competitive market.
The first step in building a gambling user portrait model is to collect a large amount of gambling player user data. This data may come from multiple channels, including user registration information, game history, recharge records, withdrawal data, customer service interaction records, and behavior logs on the platform. By collecting these diverse data, we can gain a more comprehensive understanding of the platform's gambling player users.
Next, preprocessing and cleaning the collected data is a key step. These gambling player user data may have missing values, outliers, or inconsistencies. By cleaning and converting the data, the accuracy and consistency of the analysis results can be guaranteed. In addition, it is necessary to extract features from the data to convert the raw data into meaningful variables, such as the user's active time, average game time, preferred game type, etc. These variables are the basis for building a user portrait model. By extracting these variables, we can better depict the user's behavior map, thereby providing strong and accurate support for the marketing and personalized recommendations and services of precision gambling players.
Once the gamblers' data is ready, we can start to apply data mining techniques such as clustering, classification algorithms, and association rule mining. Clustering can help us divide users with similar behaviors and characteristics into different groups (or clusters), each of which represents a specific user type. For example, some players may tend to bet large amounts, while others prefer frequent but small games. When building a model, classification algorithms (such as decision trees, random forests, etc.) can also be used to predict which player group a new user may belong to.
The characteristics and behavior patterns of each group will help the platform better understand the needs of users and tailor services for them. For example, high-value player groups may pay more attention to VIP services and customized rewards, while novice players may need more game guidance and a lower entry threshold. By optimizing these user experiences, the platform can improve retention, recharge rates, and user satisfaction among different user groups.
(I will not go into details about what clustering is, how to operate these methods and application scenarios, etc., so there will be algorithm rules involving AI network neural networks. I will only write about it in general, otherwise, it will just be a waste of words.)
1. What is Clustering?
Cluster analysisis a powerful unsupervised learning method whose core goal is to divide objects in a data set into different groups (called "clusters") based on their similarities. This method has a wide range of application prospects in gambling platforms. Through cluster analysis, the platform can accurately identify groups of players with similar behavior patterns or characteristics, thereby gaining in-depth insights into the needs and preferences of different types of players.
2. What is a classification algorithm?
The classification algorithmis a powerful supervised learning method that can classify and predict new, unlabeled data by training models with historical data with known labels. It is applied in gambling platforms. For example, it can be used to predict the potential behavior patterns of new users, identify users who may be at risk of churn, and even predict the user's interest in specific games or promotions. By segmenting players into different groups, such as high-value users, casual players, or high-risk, excitement-seeking players, gambling platforms can develop more accurate and personalized marketing strategies, optimize user experience, and improve overall operational efficiency. Improving user retention rates can also make gambling platforms stand out in the competition in the overseas gambling market and achieve sustainable growth in benefits.
3. Association Rule Mining
Association rule miningis a data mining technique used to discover relationships or patterns between different items or events in a data set. Its goal is to find sets of frequently occurring associated items and predict user behavior tendencies through these association rules. In gambling platforms, association rule mining can help understand players' behavior patterns in games or the correlation between different games, thereby optimizing game recommendations and cross-selling strategies.
Support functions: Cluster analysis: SAS's PROC CLUSTER and PROC FASTCLUS support various clustering methods.
Classification algorithm:SAS provides models such as decision trees, random forests, support vector machines, etc.
Association rule mining: SAS's PROC ARULE supports the Apriori algorithm
Applicable to:Large gambling platforms can use SAS to conduct sophisticated user analysis and help formulate complex marketing strategies.
Support functions: Cluster analysis: K-means, two-step clustering, etc.
Classification algorithm:decision tree, random forest, SVM, etc.
Association rule mining: Apriori algorithm
Applicable to:Gambling companies can use SPSS Modeler to quickly build user portrait models and analyze data through an easy-to-use interface.
Support functions: Tableau can integrate R and Python for advanced machine learning analysis, and has powerful data visualization capabilities, suitable for displaying user behavior patterns.
Applicable to:Gambling platform management can use Tableau’s visualization to display user portraits and behavior patterns and make data-driven decisions.
Classification algorithm:support decision tree, SVM, random forest, etc.
Association rule mining: Apriori algorithm, etc.
Applicable to:Gambling companies can use KNIME to process large-scale datasets and conduct complex user behavior analysis.
By deeply applyingCluster analysisandThe classification algorithmandAssociation rule mining, gambling platforms can extract valuable insights from data, provide personalized services to users, and improve overall operational efficiency. These technologies combined can create an intelligent data-driven model for the platform, allowing gambling platforms to gain an advantage in market competition.
Based on the gambling player portrait model, the gambling platform can build a personalized recommendation system to recommend suitable game types, discounts, and bonus activities for different groups of players. By analyzing the gambling habits, preferences, and historical behaviors of players, the system can predict games that may attract specific types of players and accurately push them according to their behavior patterns. For example, for a user who frequently plays chess and card games, the system can give priority to recommending new chess and card games or related discount activities.
In addition, personalized recommendations also apply to recharge and bonus strategies. By understanding each player's consumption habits and behaviors, the gambling platform can provide the most suitable reward mechanism to enhance the user's sense of participation and willingness to recharge.
The user portrait model is a powerful tool for gambling platforms to identify potential churn users. By deeply analyzing the dynamic changes in user behavior, such as the reduction in game participation time, the decrease in recharge frequency, or the change in game types, the model can accurately predict the risk of user churn. This prediction is not based on a single indicator but takes into account multiple factors, including the user's historical behavior pattern, game frequency, and responsiveness to platform promotions.
Once users with a high risk of churn are identified, the platform can develop a series of targeted intervention strategies. These strategies may include providing personalized targeted promotions, such as pushing rewards for specific games based on user preferences; sending warm reminders to reawaken user interest; or arranging a dedicated customer service team to conduct one-on-one follow-up to understand user needs and concerns. In addition, the platform can also recommend new game types or social functions based on users' historical preferences to increase user engagement and stickiness.
This type of churn warning system can not only significantly improve the overall user retention rate, but also effectively prevent the loss of high-value users. For those long-term active or high-value users, the platform can formulate more generous retention plans, such as providing exclusive VIP services, higher rebate ratios, or exclusive game experiences. Through this refined user management, the gambling platform can maximize the life cycle value of each user while improving user satisfaction and loyalty.
Through continuous data analysis and model optimization, gambling platforms can continuously improve their operational efficiency and business decision-making capabilities. The feedback provided by the user portrait model enables the platform to accurately locate business areas that need improvement. For example, if it is found that the recharge rate of a specific user group is low, this may indicate that this type of gambling player needs more preferential incentives or more targeted promotions. By continuously optimizing business strategies, the platform can maximize the lifetime value (LTV) of each user. This data-driven approach not only improves user satisfaction but also significantly improves the overall profitability of the platform.
Building a gambling user portrait model based on data analysis enables gambling platforms to better understand and serve their gambling player groups, thereby achieving personalized recommendations for players, effective player churn warnings, and precise optimization of gambling marketing strategies. By deeply mining player user behavior data, the platform can accurately predict player preferences and needs, and develop targeted marketing and operational strategies. This can not only improve gambling players' experience satisfaction with the platform but also significantly improve the platform's overall performance.
Therefore, for gambling platforms, establishing a player portrait model tailored to the target gambling market and the characteristics of their own platforms will become a key competitive advantage when entering or operating overseas gambling markets. In the fierce competition among many gambling platforms, this data-based intelligent decision-making model will become an important tool for success. It can not only help the platform better understand and meet user needs, but also maintain flexibility and adaptability in a rapidly changing market environment, thereby maintaining a leading position in long-term competition.
Gambling player behaviorrefers to a series of decisions and behavior patterns when players make gambling bets. This includes what type of games players choose, betting strategies, changes in betting frequency, and reactions to different gambling games. Therefore, user behavior segmentation is indispensable for highly personalized marketing. By analyzing the data provided by players every time they visit your gambling platform, you can improve player retention and ultimately increase the platform's revenue.
The behavior of gamblers is influenced and shaped by a complex combination of factors. For example: personal interests and preferences, current psychological and emotional state, economic conditions, social environment, and deeper cultural background. Each of these factors will affect the player's decision-making process and behavior patterns.
For example, some players may see gambling as an excitement and challenge, seeking high-risk, high-reward experiences, while others may see gambling as a leisurely entertainment, preferring a low-risk, long-term gambling approach. This difference not only reflects personal preferences, but may also stem from their financial situation, risk tolerance, or even cultural attitudes toward gambling.
In addition, external environmental factors also have a significant impact on the behavior of gamblers. Market trends, seasonal events (such as major sporting events), and changes in the regulatory environment can cause fluctuations in player behavior. For example:
Therefore, gambling platforms need to have a deep understanding of these diverse influencing factors, which will not only allow them to more accurately predict player demand but also enable them to quickly respond to market changes and adjust their operating strategies promptly.
Regardless of the region, industry, or gambling platform, people expect to be highly personalized but to achieve this, it is necessary to group gambling players according to common characteristics. In this way, a large number of users with specific characteristics can be attracted during marketing. For iGaming platforms, the most useful method at present is behavioral segmentation grouping. Just like what is mentioned above, starting from the game items and modes of the players' bets, betting frequency, betting amount, etc. Every time the player deposits or bets, etc., we can divide it into 6 question groups.
The marketing funnel model will be different at different stages in the life cycle of gambling players. Generally, players will go through several stages:
Awareness-Interest and Consideration-Conversion-Activity and Loyalty-Advocacy and Promotion.
Therefore, the information conveyed by players at each stage will be different. For players who have just learned about your gambling platform brand, the way you communicate with players is different from the way you communicate with them at home.
For example, newly registered players will not have customer service to follow up immediately, and players in the promotion stage will not be attracted by your registration bonus or recharge bonus at all. Therefore, segment the players according to each stage and provide them with suitable marketing plans according to the stage of the player's life cycle.
You may have also discovered that the current e-commerce and video media seem to know what you like and what you need and recommend things to you. This is the algorithm. These software or applications collect and analyze the things or videos you liked in the past to launch them for later marketing. So this is what the gambling platform should do.
The mindset of a bettor is that if he tends to choose a game he likes, he will generally stick to it. For example, some online bettors only like slot machines. Some only like poker or baccarat and don't play anything else. Just like sports bettors, many only like football, while others may stick to fighting (MMA) or horse racing. Or if you recommend blackjack to a player who plays baccarat, this can also generate more cross-conversions.
The following are common types of gambling games and key points to look for in behavioral analysis:
a. Sports Betting
Player behavior analysis: their betting behavior is closely related to the season and game schedule. Provide them with personalized event information and reward programs.
b. Slot Machines
Player behavior analysis: high frequency, small amount of bets. Analyze betting time, frequency, and game type to optimize promotions.
c. Poker and board games
Player behavior analysis: Long-term games, emphasizing strategy. Analyze the duration, and win-loss ratio, and formulate personalized recommendations and rewards.
d. Lottery
Player behavior analysis: Analyze participation frequency and launch regular reminders.
e. Live Casino
Player behavior analysis: Pursue real interaction and high-value long-term betting. Analyze preferences, provide VIP services, and customize high-value activities.
f. Virtual Sports
Player behavior analysis: Quick experience and betting. Analyze frequency and amount, and recommend other instant gambling games.
Tracking the time players are active is essential to developing an effective marketing strategy. Each player's betting pattern is unique: some may only bet once a week, while others may bet once a month. Special events, such as major sporting events or holidays, often attract more players. Some players have a fixed gambling habit, such as spending 30 minutes playing slots a few times a week, or only betting on the team they support. In contrast, there is another group of players who are more active and bet on games that seem to have good odds almost every day.
By analyzing players’ betting frequency in groups, we can develop personalized marketing strategies more accurately. For example, for those players who bet frequently, we can provide special promotions before their regular betting period. For players who prefer specific sports events, we can prepare unique odds offers for them before major tournaments. And for those who like slot games, we can provide some free spins during the period when they are usually online. This kind of precision marketing based on player behavior can not only improve player engagement but also increase their loyalty and the overall revenue of the platform.
The betting behavior of bettors can generally be divided into three main categories: small bets, medium bets, and large bets. This classification is particularly important in the online gambling (iGaming) industry because it directly affects the interaction strategy between the platform and the players:
Therefore, the gambling platform needs to understand these different types of players and their preferences, develop effective marketing strategies, and provide personalized services. Adjust the frequency and content of communication according to the player's betting behavior to ensure that every gambling player can get the best experience on your gambling platform.
Bettors have a variety of motivations for participating in gambling activities, and everyone has their unique reasons. Some people seek excitement and adrenaline rush and crave the feeling of excitement with every bet. Others see gambling as a potential money-making opportunity, hoping to get a considerable return through their skills and luck. Still, others use gambling as a form of leisure and entertainment, enjoying the fun and social interaction of the betting process. For sports betting enthusiasts, betting can also increase the excitement of watching the game and allow them to participate more deeply in their favorite sports.
However, as a gambling platform operator, we need to shift our focus from why players place gambling bets to why they choose to place bets on our platform. The answer to this question may involve multiple aspects: Does our platform offer more attractive odds than our competitors? Do we provide a richer and more diverse selection of games to meet the needs of different players? Or is our payment system more convenient and secure, providing players with a better experience? Is our customer service more thoughtful and able to solve players' problems promptly? Is the platform's user interface more friendly and smoother to use? These are all aspects that we need to think deeply about and continuously optimize.
No matter what the reason is for players to choose our platform, the primary task is to continue to maintain the status quo, keep innovating, constantly collect and analyze user feedback, and timely adjust the strategy of our gambling platform.
The revenue of a gambling platform is that a small number of core players contribute the vast majority of revenue. You can think of this as the "80/20 rule" or the "Pareto principle". Specifically, about 20% of active players generate up to 80% of the total revenue for the platform. Therefore, core players with high loyalty are extremely important to the operation of a gambling platform. Therefore, maintaining the stickiness of these high-value players and providing them with excellent service experience have become the top priorities for the operation of a gambling platform.
For these core players, we provide a series of unique value-added services and exclusive benefits, such as personalized customer service, a higher rebate ratio, exclusive VIP activities, faster withdrawal processing, etc. Although it may increase the operating costs of the platform in the short term, in the long run, it is an important investment to ensure the continued activity and satisfaction of core players and extend their life cycle value, thereby bringing continuous and stable income to the platform.
In contrast, for new players who have just joined the platform, in the initial stage, new players do not need too much special treatment. However, it is necessary to pay close attention to the behavior patterns and betting habits of these new players. Once a new player shows the potential to become a high-value user, such as an increase in betting frequency or a single bet amount, the platform should quickly adjust its strategy. Timely strategy adjustments not only reflect the platform's attention to potential players but also lay the foundation for establishing long-term and stable player relationships.
TC-Gaming editor has said so much. It is nothing more than to illustrate the importance of user portrait and behavior analysis of gambling players. At the same time, how to build a player portrait model and behavior segmentation through data mining technology can bring several benefits to the gambling platform:
Therefore, by fully implementing the user portrait and behavior analysis strategy for gambling players, gambling platforms can significantly improve their operational efficiency, marketing accuracy, and player satisfaction. This can not only optimize the user experience, increase player retention, and enable them to quickly adapt to changes in the gambling market, but also enable gambling platforms to maintain long-term competitiveness in the fiercely competitive overseas gambling market, laying a solid foundation for the long-term operation and development of gambling platforms.
With 17 years of experience in the gambling industry, TC-Gaming has become a trusted and established company. Our business covers many countries, and our team has 18 multinational local language experts and designers to ensure the localized user experience of the white label iGaming platform. TC-Gaming provides customers with personalized one-to-one services and is also equipped with 24-hour security team support to ensure the stable operation of your gambling platform. At the same time, we continue to innovate technology and optimize the platform to help customers stand out in the new overseas gambling market. I believe that TC-Gaming will be a stable and reliable partner for you.
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thomas
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