A game operation management decision method and system based on user behavior data

Abstract

The application discloses a game operation management decision method and system based on user behavior data, relates to the technical field of game operation management, and comprises user behavior data acquisition, user behavior analysis, game operation management decision analysis and early warning prompt. Through monitoring the playing behavior of users in the game, the satisfaction state of the users to the game is evaluated, timely game operation management adjustment is realized, a game corresponding playing method adjustment direction set is generated, behavior data of the user to the game corresponding playing method adjustment direction set is collected, the state of the user to the game corresponding playing method adjustment direction is analyzed, effective game operation management adjustment decisions are obtained, correct and efficient game operation management is realized, the game is efficiently promoted, the current market of the game is widened, the market value of the game is improved, and the interest degree and the retention rate of the user to the game are further ensured.

Description

Technical Field

[0001] This invention relates to the field of game operation and management technology, specifically to a game operation and management decision-making method and system based on user behavior data. Background Technology

[0002] With the continuous innovation of the gaming industry, competition among games is becoming increasingly fierce. Therefore, a game operation management decision-making method and system based on user behavior data is proposed. By continuously gaining a deeper understanding of users' behavior data related to the game, correct and effective game operation management decisions can be made, thereby enhancing the game's competitiveness, efficiently expanding its competitive advantages, avoiding deviations in game operation decision-making, and preventing increased game operation costs.

[0003] Existing technologies, such as the invention patent application CN120094212A, disclose a method for analyzing player game data, including data collection, data preprocessing, feature extraction, data analysis, and result presentation steps. By comprehensively collecting various behavioral data of players in the game, and after preprocessing and feature extraction, the data is analyzed using multiple data analysis algorithms and deep learning algorithms. Finally, the analysis results are presented in a visual manner. This invention can deeply mine player behavioral data, providing valuable decision-making support for game developers and operators, improving game content optimization and operational efficiency, and enhancing player experience and game revenue.

[0004] The above-mentioned solutions have the following technical problems: While the invention primarily utilizes various data analysis algorithms and deep learning algorithms to analyze player needs and provide valuable decision-making support for game developers and operators, it does not monitor user behavior within the game. Therefore, it cannot obtain user behavior data corresponding to the game, leading to an inability to understand user satisfaction levels, determine the correct direction of user behavior based on their attitudes towards the game, and create targeted adjustments to gameplay. This results in a failure to promptly rectify game errors, reducing the game's competitiveness in the market. Furthermore, the invention does not present the pre-generated gameplay adjustment set to users in the form of gameplay keywords, making it impossible to understand user interests in a real-time and efficient manner. Without collecting user behavior data related to the gameplay adjustment set, it is impossible to analyze the basic state of the user's gameplay adjustment set and, based on the user's basic state, analyze the game's operational direction for users. This ultimately reduces the game's competitiveness, player base, and overall revenue, hindering effective game promotion. Summary of the Invention

[0005] To address the aforementioned technical shortcomings, the purpose of this invention is to provide a game operation management decision-making method and system based on user behavior data.

[0006] To solve the above technical problems, the present invention adopts the following technical solution: The present invention provides a game operation management decision-making method based on user behavior data, including: Step 1, user behavior data acquisition: by monitoring the playing behavior of users in the game, the playing behavior data of the user corresponding to the game is obtained, and the user's satisfaction status of the corresponding game is evaluated.

[0007] Step 2, User Behavior Analysis: When a user's satisfaction with the game is unsatisfactory, corresponding behavioral detection is performed on the user to pre-generate a set of gameplay adjustment directions for the game.

[0008] Step 3: Game Operation Management Decision Analysis: By presenting the pre-generated set of gameplay adjustment directions to users in the form of gameplay keywords, behavioral data of users corresponding to the set of gameplay adjustment directions is collected. The basic state of the user's corresponding set of gameplay adjustment directions is analyzed, and the corresponding operational direction of the game for users is determined.

[0009] Step 4: Warning Prompt: A warning prompt will be issued when the user's satisfaction with the corresponding game is unsatisfactory or when the user is dissatisfied with the basic state of the set of game gameplay adjustment directions.

[0010] In a second aspect, the present invention provides a game operation management decision system based on user behavior data, comprising: a user behavior data acquisition module, used to monitor the playing behavior of users in the game, thereby obtaining the playing behavior data of the user in the corresponding game, and evaluating the user's satisfaction status in the corresponding game.

[0011] The user behavior analysis module is used to detect the user's behavior when the user's satisfaction with the game is unsatisfactory, and then pre-generate a set of gameplay adjustment directions for the game.

[0012] The game operation management decision analysis module is used to present the pre-generated set of gameplay adjustment directions to users in the form of gameplay keywords in the set, and then collect user behavior data corresponding to the set of game gameplay adjustment directions. The module analyzes the basic status of the user's corresponding set of game gameplay adjustment directions and analyzes the corresponding operational direction of the game for the user.

[0013] The early warning terminal is used to issue early warnings when a user's satisfaction with the game is unsatisfactory or when the user is dissatisfied with the basic state of the set of game gameplay adjustment directions.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention provides a game operation management decision-making method and system based on user behavior data. By monitoring the gameplay behavior of users in the game, the system assesses the user's satisfaction with the game, thereby enabling timely adjustments to game operation management. It generates a set of gameplay adjustment directions for the game and collects behavioral data on the user's corresponding gameplay adjustment direction set. The system analyzes the user's status in the corresponding gameplay adjustment direction to obtain effective game operation management adjustment decisions. This achieves correct and efficient game operation management, enabling efficient promotion of the game, expanding the game's existing market, increasing the game's market value, ensuring user interest and retention rates, avoiding significant user churn, generating more game revenue, and effectively promoting the game.

[0015] 2. By monitoring user behavior in the game, we can obtain user behavior data for the corresponding game and assess the user's satisfaction level. This allows us to understand the game's popularity among current users and make timely adjustments if the game's satisfaction level is unsatisfactory, thereby further expanding the game's reach and attracting more players.

[0016] 3. By detecting user behavior, a set of gameplay adjustment directions can be pre-generated to further attract user interest, increase user play rate, and effectively promote the game.

[0017] 4. By collecting behavioral data on user behavior related to game gameplay adjustments, we can analyze the basic state of these adjustments and determine the corresponding operational direction for the game. This allows us to efficiently understand user interests, implement appropriate game operations, effectively increase the game's popularity in the market, and generate more revenue based on these operations. Furthermore, by making effective game operation and management decisions, we can achieve effective promotion of the game. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the implementation steps of the method of the present invention.

[0020] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see Figure 1 As shown, a game operation management decision-making method based on user behavior data includes: Step 1, user behavior data acquisition: by monitoring the gameplay behavior of users in the game, the gameplay behavior data of the corresponding user in the game is obtained, and the user's satisfaction status in the corresponding game is evaluated.

[0023] By monitoring user behavior in games, we can obtain data on user behavior and assess user satisfaction with the games. This allows us to understand the game's popularity among current users and make timely adjustments if user satisfaction is not satisfactory, thereby increasing the game's reach and attracting more players.

[0024] In a specific embodiment of the present invention, the play behavior data includes user retention rate, user engagement rate, new user influx rate, and user spending.

[0025] It should be noted that the following steps are taken: First, obtain the number of new users within a preset time period from the game platform, and extract the number of new users who remain active within the preset time period. Divide the number of active users by the number of new users and multiply by 100% to obtain the game's user retention rate. Second, obtain the total number of active users within the corresponding period in the latest tasks on the game platform, and extract the number of users who participated in and executed the latest tasks. Divide the number of users who participated in and executed the latest tasks by the total number of active users within the period and multiply by 100% to obtain the game's user participation rate. Third, based on the number of users logging into the game for the first time and the number of users registering for the first time, divide the number of users registering for the first time by the number of users logging into the game for the first time and multiply by 100% to obtain the game's new user influx rate. Fourth, extract the number of purchases made by users after the latest character was released in the game and the total number of active users. Divide the total number of active users by the number of purchases made by users and multiply by 100% to obtain the game's user spending value.

[0026] In a specific embodiment of the present invention, the evaluation obtains the user's satisfaction status for the corresponding game. The specific evaluation process is as follows: the user retention rate, user participation rate, new user influx rate, and user spending value for the corresponding game are denoted as θ, η, ρ, and ω, respectively. When (θ≥θ″)∧(η≥η″)∧(ρ≥ρ″)∧(ω≥ω″), it is determined that the user's play rate for the corresponding game is high and the user's gameplay for the corresponding game is in a satisfactory state. θ″ is the set reference user retention rate, η″ is the set reference user participation rate, ρ″ is the set reference new user influx rate, ω″ is the set reference user spending value, and ∧ represents the sum.

[0027] If (θ<θ″)∨(η<η″)∨(ρ<ρ″)∨(ω<ω″), then it is determined that the user's play rate for the corresponding game is low and the user is dissatisfied with the gameplay of the corresponding game. ∨ represents or.

[0028] It should be noted that reference user retention rate, reference user engagement rate, reference new user influx rate, and reference user spending are set by professional managers. These reference user retention rate, reference user engagement rate, reference new user influx rate, and reference user spending are benchmark values ​​used to evaluate user satisfaction with the corresponding gameplay. This allows for a more intuitive understanding of the game's popularity in the current market and user interest trends, thereby enabling more effective operational and marketing management decisions for the game's development.

[0029] Step 2, User Behavior Analysis: When a user's satisfaction with the game is unsatisfactory, corresponding behavioral detection is performed on the user to pre-generate a set of gameplay adjustment directions for the game.

[0030] By detecting user behavior, a set of gameplay adjustment directions can be pre-generated to further attract user interest, increase user play rate, and effectively promote the game.

[0031] In a specific embodiment of the present invention, the corresponding behavior detection of users is carried out as follows: the popularity value of game topics on each platform is obtained, and then the popularity value of the game on each platform is arranged in descending order. The top three platforms are selected as the main platforms for user monitoring. At the same time, unified behavior detection is carried out on the social circles of users on the game platform to obtain the main directions of user behavior monitoring. Meanwhile, by obtaining the comments about the game published by users under each main direction, behavioral feature data about game gameplay is extracted from them, including game dungeon data, game character data, and game content data, thereby realizing the corresponding behavior detection of users.

[0032] It should be noted that game dungeon data includes game difficulty and number of game tasks; game character data includes character combat power and character skin price; game content data includes game dungeon type and number of game dungeon types, such as game dungeon type being battle rewards or task points.

[0033] In a specific embodiment of the present invention, the pre-generated set of gameplay adjustment directions for the game is generated as follows: based on the monitored user behavior feature data for the game, a preliminary adjustment direction for the game's corresponding operational gameplay is generated according to the specific data contained in the behavior feature data. If the monitored user behavior feature data specifically refers only to game instance data, then the keyword features of the user's published game instance data are extracted, and the keyword features are used as the operational direction for the current game's corresponding existing instance.

[0034] If the monitored user behavior data specifically refers only to game character data, then the character keyword features of the user's published game character data will be extracted, and the operational direction for the current game's corresponding existing instance will be adjusted based on the character keyword features. If the monitored user behavior data specifically refers only to game content data, then the content keyword features of the user's published game content data will be extracted, and the operational direction for the current game's corresponding existing instance will be adjusted based on the content keyword features.

[0035] If all the data contained in the user's corresponding behavioral feature data are detected, then the gameplay adjustment based on the comprehensive game behavioral feature data will be implemented. The set of gameplay adjustment directions for the game will be constructed by comprehensively adjusting various aspects of game dungeon data, game character data, and game content data.

[0036] It should be noted that if the keyword feature extracted from the user's published game dungeon data is "difficult," then the difficulty of the existing dungeons in the current game will be reduced, or the number of random auxiliary items dropped in the dungeons will be increased to help users complete the tasks. If the keyword feature extracted from the user's published game character data is "low damage value of the character's ultimate skill or few enemies hit," then the character's combat power will be upgraded and the range of the character's ultimate skill will be expanded. If the keyword feature extracted from the user's published game content data is "few types of game dungeons," then the corresponding number of game dungeons will be increased. This will be done by conducting a survey among users and ranking the survey results according to the voting value from highest to lowest, with the content ranked first being used as the type of dungeon to be added.

[0037] Step 3: Game Operation Management Decision Analysis: By presenting the pre-generated set of gameplay adjustment directions to users in the form of gameplay keywords, behavioral data of users corresponding to the set of gameplay adjustment directions is collected. The basic state of the user's corresponding set of gameplay adjustment directions is analyzed, and the corresponding operational direction of the game for users is determined.

[0038] By collecting behavioral data on user adjustments to gameplay, we can analyze the basic state of these adjustments and determine the corresponding operational direction for the game. This allows us to efficiently understand user interests, implement appropriate game operations, effectively increase the game's popularity in the market, generate more revenue, and make effective game operation and management decisions to promote the game effectively.

[0039] It should be noted that the pre-generated set of gameplay adjustment directions will be presented to users in the form of gameplay keywords within the set: for example, if the set of gameplay adjustment directions will adjust the combat power value of a character, then the keywords will be the unique character characteristics and unique ultimate moves of that character, thus presenting them to users in the form of keywords.

[0040] In a specific embodiment of the present invention, the behavioral data includes direct feedback data and indirect behavioral data.

[0041] It should be noted that direct feedback data includes the opposition rate and the percentage of negative complaints. The opposition rate is obtained by obtaining the total number of users voting for the corresponding set of gameplay adjustment directions and the number of users voting against the option within the game platform. The number of users voting against the option is divided by the total number of users voting and multiplied by 100%. The percentage of negative complaints is obtained by obtaining the total number of new complaints received by the game under the corresponding set of gameplay adjustment directions and the total number of complaints against the game. The percentage of negative complaints is obtained by dividing the total number of new complaints by the total number of complaints against the game and multiplying by 100%. Indirect behavioral data includes click-through rate and negative readership. The click-through rate is obtained by obtaining the total number of viewers and participants during the voting period when the corresponding set of gameplay adjustment directions was released to users. The click-through rate is obtained by dividing the number of participants by the total number of viewers and multiplying by 100%. Negative readership refers to user comments or actions related to the anticipated changes in gameplay, such as reading or commenting on topics related to player withdrawal announcements. The negative readership is obtained by obtaining the readership of withdrawal announcement topics.

[0042] In a specific embodiment of the present invention, the analysis obtains the basic state of the user's corresponding game play adjustment direction set. The specific analysis process is as follows: The direct feedback data and indirect behavior data of the user's corresponding game play adjustment direction set are denoted as H and P, respectively. When (H≤H′)∧(P≤P′), it is determined that the user's corresponding game play adjustment direction set is in a satisfactory state, which conforms to the user's interests and does not deviate from the user's ideas. H′ is the set reference direct feedback data, P is the set reference indirect behavior data, and ∧ represents the sum.

[0043] If (H>H′)∨(P>P′), it is determined that the user's corresponding game gameplay adjustment direction set is in a state of dissatisfaction and differs from the user's ideas. In this case, the corresponding game operation direction will be re-adjusted. ∨ represents or.

[0044] It should be noted that professional managers set up reference direct feedback data and reference indirect behavioral data. Reference direct feedback data and reference indirect behavioral data are used to evaluate whether the set of game gameplay adjustments meets the basic satisfaction of the general public. This allows for efficient understanding of the correctness of the current game operation and management direction, and facilitates timely correction of errors in operation and management.

[0045] In a specific embodiment of the present invention, the analysis yields the user-oriented operational direction of the game. The specific analysis process is as follows: Based on the opinion area of ​​the user participation in the voting on the game gameplay adjustment direction set, the opposition feature data of each user who expressed opposition opinions is extracted. Based on the extracted opposition feature data, the dissatisfaction composition features under the user's game gameplay adjustment direction set are obtained. The dissatisfaction composition features are then used as the secondary adjustment decision direction for the game's operation. At the same time, the performance features of each opposing user's dissatisfaction composition features in the game are obtained. The game direction with high performance points for each opposing user in the performance features is extracted. The common feature data between the game directions are used as the adjustment target under the secondary adjustment decision direction for the game's operation. This constitutes the adjustment management decision measures for the game's user-oriented operation, and the user-oriented operational direction of the game is obtained through analysis.

[0046] It should be noted that, for example, if the opinion area of ​​the user participation voting on the direction of game gameplay adjustments extracts the opposition feature data of each user who expressed opposition, and the data shows that the power damage value of a certain game character is low, then adjusting the power value of that character will be used as a secondary adjustment decision direction. At the same time, the historical reference power value output by users when using this character in battles during normal gameplay will be obtained, and the historical power value will be used as the reference benchmark for adjusting the character. Based on the corresponding reference power value of the character and combined with the difficulty value of the corresponding dungeon in the game, the power value will be increased accordingly. This constitutes the adjustment and management decision measures for the game's user-oriented operation, and the analysis yields the game's user-oriented operational direction.

[0047] Step 4: Warning Prompt: A warning prompt will be issued when the user's satisfaction with the corresponding game is unsatisfactory or when the user is dissatisfied with the basic state of the set of game gameplay adjustment directions.

[0048] Please see Figure 2 As shown, a control method based on the construction site of a power substation includes a user behavior data acquisition module, a user behavior analysis module, a game operation management decision analysis module, an early warning terminal, and a database.

[0049] The user behavior data acquisition module is connected to the user behavior analysis module, the early warning terminal, and the database, respectively. The user behavior analysis module is connected to the game operation management decision analysis module and the database, respectively. The game operation management decision analysis module is connected to the early warning terminal and the database, respectively.

[0050] The user behavior data acquisition module is used to monitor user behavior in the game, thereby obtaining user behavior data for the corresponding game and assessing the user's satisfaction level with the game.

[0051] The user behavior analysis module is used to detect the user's behavior when the user's satisfaction with the game is unsatisfactory, and then pre-generate a set of gameplay adjustment directions for the game.

[0052] The game operation management decision analysis module is used to present the pre-generated set of gameplay adjustment directions to users in the form of gameplay keywords in the set, and then collect user behavior data corresponding to the set of game gameplay adjustment directions. The module analyzes the basic status of the user's corresponding set of game gameplay adjustment directions and analyzes the corresponding operational direction of the game for the user.

[0053] The early warning terminal is used to issue early warnings when a user's satisfaction with the game is unsatisfactory or when the user is dissatisfied with the basic state of the set of game gameplay adjustment directions.

[0054] The database is used to store play behavior data, reference user retention rate, reference user engagement rate, reference new user influx rate, reference user spending, behavioral characteristic data, behavioral data, reference direct feedback data, and reference indirect behavioral data.

[0055] This invention monitors user behavior within a game to assess user satisfaction, enabling timely adjustments to game operations and management. It generates a set of gameplay adjustment directions and collects behavioral data related to these directions, analyzing the user behavior to arrive at effective game operation and management decisions. This leads to correct and efficient game operation and management, resulting in efficient game promotion, expanded market reach, increased market value, maintained user interest and retention, reduced user churn, and increased game profitability, ultimately achieving effective game promotion.

[0056] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A game operation management decision-making method based on user behavior data, characterized in that, include: Step 1: User Behavior Data Acquisition: By monitoring user behavior in the game, we can obtain user behavior data for the corresponding game and assess the user's satisfaction with the game. Step 2, User Behavior Analysis: When a user's satisfaction with the game is unsatisfactory, the user's behavior is detected, and a set of gameplay adjustment directions is pre-generated. Step 3: Game Operation Management Decision Analysis: By presenting the pre-generated set of gameplay adjustment directions to users in the form of gameplay keywords, behavioral data of users corresponding to the set of gameplay adjustment directions is collected, the basic status of the set of gameplay adjustment directions of users is analyzed, and the corresponding operational direction of the game for users is analyzed. Step 4: Warning Prompt: A warning prompt will be issued when the user's satisfaction with the corresponding game is unsatisfactory or when the user is dissatisfied with the basic state of the set of game gameplay adjustment directions.

2. The game operation management decision-making method and system based on user behavior data as described in claim 1, characterized in that, The game behavior data includes user retention rate, user engagement rate, new user influx rate, and user spending.

3. The game operation management decision-making method and system based on user behavior data as described in claim 2, characterized in that, The evaluation yields the user's satisfaction level with the corresponding game. The specific evaluation process is as follows: Let θ, η, ρ, and ω represent the user retention rate, user engagement rate, new user influx rate, and user spending for the corresponding game. When (θ≥θ″)∧(η≥η″)∧(ρ≥ρ″)∧(ω≥ω″), it is determined that the user's play rate for the corresponding game is high and the user is satisfied with the gameplay of the corresponding game. θ″ is the set reference user retention rate, η″ is the set reference user engagement rate, ρ″ is the set reference new user influx rate, ω″ is the set reference user spending, and ∧ represents the sum. If (θ<θ″)∨(η<η″)∨(ρ<ρ″)∨(ω<ω″), then it is determined that the user's play rate for the corresponding game is low and the user is dissatisfied with the gameplay of the corresponding game. ∨ represents or.

4. The game operation management decision-making method and system based on user behavior data as described in claim 3, characterized in that, The specific detection process for the user's corresponding behavior is as follows: The system acquires the popularity scores of game topics across various platforms, then ranks the games by popularity scores from highest to lowest, selecting the top three platforms as the primary platforms for user monitoring. Simultaneously, it performs unified behavioral detection on users' social circles within the game platforms to identify the key areas for monitoring user behavior. Furthermore, it extracts behavioral characteristic data related to gameplay from user comments posted about the game within these key areas, including game instance data, game character data, and game content data, thereby enabling corresponding user behavior detection.

5. The game operation management decision-making method and system based on user behavior data as described in claim 4, characterized in that, The pre-generated set of gameplay adjustment directions for the game is obtained, and the specific generation process is as follows: Based on the monitored user behavior data for the corresponding game, the initial adjustment direction of the game's operation and gameplay is generated according to the specific data contained in the behavior data. If the monitored user behavior data specifically refers only to game instance data, the keyword features of the user's published game instance data are extracted, and the keyword features are used as the operational direction for the current game instance. If the monitored user's behavioral characteristic data specifically refers only to game character data, then the character keyword feature corresponding to the game character data published by the user will be extracted, and the operational direction for the current game corresponding to the existing instance will be adjusted based on the character keyword feature. If the monitored user's behavioral characteristic data specifically refers only to game content data, then the content keyword feature corresponding to the game content data published by the user will be extracted, and the operational direction for the current game corresponding to the existing instance will be adjusted based on the content keyword feature. If all the data contained in the user's corresponding behavioral feature data are detected, then the gameplay adjustment based on the comprehensive game behavioral feature data will be implemented. The set of gameplay adjustment directions for the game will be constructed by comprehensively adjusting various aspects of game dungeon data, game character data, and game content data.

6. The game operation management decision-making method and system based on user behavior data as described in claim 5, characterized in that, The behavioral data includes direct feedback data and indirect behavioral data.

7. The game operation management decision-making method and system based on user behavior data as described in claim 6, characterized in that, The analysis yields the basic state of the user's corresponding game play adjustment direction set. The specific analysis process is as follows: Let H and P be the direct feedback data and indirect behavior data of the user's corresponding game gameplay adjustment direction set. When (H≤H′)∧(P≤P′), it is determined that the user's corresponding game gameplay adjustment direction set is in a satisfactory state, which is in line with the user's interests and does not deviate from the user's ideas. H′ is the set reference direct feedback data, P is the set reference indirect behavior data, and ∧ represents the sum. If (H>H′)∨(P>P′), it is determined that the user's corresponding game gameplay adjustment direction set is in a state of dissatisfaction and differs from the user's ideas. In this case, the corresponding game operation direction will be re-adjusted. ∨ represents or.

8. The game operation management decision-making method and system based on user behavior data as described in claim 7, characterized in that, The analysis yields the game's corresponding user-oriented operational direction, and the specific analysis process is as follows: Based on the opinion area extracted from the voting on the set of game gameplay adjustment directions by users, the dissatisfaction characteristics of each user who expressed opposing opinions are obtained. These dissatisfaction characteristics are then used as the secondary adjustment decision direction for the game's operation. Simultaneously, the performance characteristics of each opposing user's dissatisfaction characteristics in the game are obtained, and the game directions with high performance points for each opposing user are extracted. The common characteristic data between these game directions are used as the adjustment targets under the secondary adjustment decision direction for the game's operation. This constitutes the adjustment management decision measures for the game's user-oriented operation, and the user-oriented operation direction of the game is thus analyzed.

9. A game operation management decision-making system that implements the game operation management decision-making method based on user behavior data according to any one of claims 1-8, characterized in that, include: The user behavior data acquisition module is used to monitor the gameplay behavior of users in the game, thereby obtaining the gameplay behavior data of the user in the corresponding game, and evaluating the user's satisfaction status in the corresponding game. The user behavior analysis module is used to detect the user's behavior when the user's satisfaction with the game is not satisfactory, and then pre-generate a set of gameplay adjustment directions for the game. The game operation management decision analysis module is used to present the pre-generated set of gameplay adjustment directions to users in the form of gameplay keywords in the set, and then collect user behavior data corresponding to the set of game gameplay adjustment directions, analyze the basic status of the user's corresponding set of game gameplay adjustment directions, and analyze the corresponding operation direction of the game to users. The early warning terminal is used to issue early warnings when a user's satisfaction with the game is unsatisfactory or when the user is dissatisfied with the basic state of the set of game gameplay adjustment directions.

10. A game operation management decision-making system based on user behavior data as described in claim 9, characterized in that, It also includes a database used to store play behavior data, reference user retention rate, reference user engagement rate, reference new user influx rate, reference user spending, behavioral characteristic data, behavioral data, reference direct feedback data, and reference indirect behavioral data.

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