Method and System for Associating Automotive User Experience with Consumer Portrait

Abstract

The present invention is applicable to the field of consumer portrait analysis, and provides a method and system for associating automotive user experience with consumer portraits. The system includes: a touchpoint definition module, a primary consumer portrait construction module, a user portrait update module, and a push plan generation module. This method systematically connects automotive user experience with consumer portraits and demonstrates various beneficial effects. First, by mapping the user journey and identifying each touchpoint, enterprises can comprehensively understand the needs and pain points of users during the car purchase, use, and after-sales service processes. This visual analysis helps identify key links and optimize service processes, thereby enhancing user satisfaction. By combining user feedback and historical service records, enterprises can continuously optimize the user experience, flexibly adjust marketing strategies and service content, and improve conversion rates. This data-driven decision-making method not only enhances the user experience but also provides strong support for enterprises to maintain their competitive advantages.

Description

Technical Field

[0001] The present invention belongs to the field of consumer portrait analysis, and particularly relates to a method and system for associating automotive user experience with consumer portraits. Background Art

[0002] Automotive consumer portrait analysis technology mainly involves collecting and analyzing user data to construct and update detailed descriptions of consumers' characteristics. This field integrates technologies such as data mining, machine learning, user behavior analysis, and market research, aiming to identify consumers' preferences, needs, and behavior patterns. By comprehensively analyzing consumers' basic information, purchase history, driving habits, and feedback data, dynamic consumer portraits can be formed. These portraits help automotive manufacturers and dealers achieve precision marketing, personalized services, and product recommendations, thereby improving user satisfaction and loyalty. In addition, consumer portraits can also support product development and optimization, enhancing market competitiveness.

[0003] In the past, when analyzing automotive user portraits, there has often been a lack of comprehensive user journey analysis, resulting in the inability to accurately capture the real needs and pain points of users during the car purchase, use, and after-sales service processes. At the same time, changes in users' driving habits and preferences have not been promptly reflected in products and services, making it difficult for enterprises to provide personalized experiences. In addition, the existing technology lacks initiative in maintenance reminders and risk management, which easily leads to users neglecting vehicle maintenance, thereby affecting safety and service life. These problems limit the effective interaction between enterprises and users and reduce customer satisfaction and loyalty. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for associating automotive user experience with consumer portraits, aiming to solve the technical problems existing in the prior art identified in the background art.

[0005] The present invention is implemented as follows. A method for associating automotive user experience with consumer portraits, the method comprising:

[0006] During the car purchase, use, and after-sales service processes, draw a user journey map, define the touchpoints at each stage, and analyze the information contained in each touchpoint;

[0007] Obtain the full-process usage information of the user, analyze the user's driving habits and purchase history, construct a primary consumer portrait, and update the primary consumer portrait in combination with the information contained in each touchpoint;

[0008] Analyze real-time driving data, combine it with the updated user portrait, evaluate the changes in vehicle performance, and analyze the potential risks and changes in driving habits caused to the vehicle;

[0009] Based on the analysis results of the dynamically updated consumer portraits and driving habits, identify user experience optimization strategies, and combine the user's historical service records with the consumer portraits to generate a push plan.

[0010] As a further solution of the present invention, during the process of vehicle purchase, use, and after-sales service, draw a user journey map, define the touchpoints at each stage, and analyze the information contained in each touchpoint, specifically including:

[0011] Identify the various stages and links of the user using the vehicle, and visualize the journey at each stage to form a journey map;

[0012] Identify the interactions between the user and the vehicle at each stage, mark them as touchpoints, and define the nature of each touchpoint;

[0013] Collect the information contained in each touchpoint, classify it into qualitative data and quantitative data, and combine the user feedback information contained in each touchpoint to judge the priority of each touchpoint.

[0014] As a further solution of the present invention, obtain the user's full-course usage information, analyze the user's driving habits and purchase history, construct a primary consumer portrait, and update the primary consumer portrait in combination with the information contained in each touchpoint, specifically including:

[0015] Collect the user's driving data and the user's behavior data during driving, and at the same time collect the user's after-sales data;

[0016] Analyze the collected data, identify the user's driving patterns, detect the changing trends of the user's driving habits, and integrate the user's basic information with the driving habit data to form a primary consumer portrait;

[0017] Extract the information and priority data of each touchpoint, identify the changes in the user's preferences, and update the primary consumer portrait:

[0018] ;

[0019] Wherein, is the eigenvalue of the updated consumer portrait, is the eigenvalue of the primary consumer portrait, is the eigenvalue of the newly collected user feedback, is the weight coefficient.

[0020] As a further solution of the present invention, analyze the real-time driving data, combine it with the updated user portrait, evaluate the vehicle performance changes, and analyze the potential risks and driving habit changes caused to the vehicle, specifically including:

[0021] Based on the obtained vehicle driving data, identify the change status of vehicle performance and analyze the existing abnormal changes;

[0022] Based on the changing trend of the user's driving habits, evaluate the potential risks of the vehicle:

[0023] ;

[0024] wherein, represents the probability of the vehicle having risks under a given feature and, represents the intercept, that is, the risk probability when all features are zero, is the regression coefficient of each feature, indicating the degree of influence of the feature on the risk change, represents the feature parameters of different features affecting risks;

[0025] Based on the combination of real-time driving data and the updated user portrait, identify and analyze the changes in user preferences and their impact on driving behavior.

[0026] As a further solution of the present invention, based on the dynamically updated consumer portrait and the analysis results of driving habits, identify user experience optimization strategies, and combine the user's historical service records with the consumer portrait to generate a push plan, specifically including:

[0027] Integrate the dynamically updated consumer portrait, the analysis results of driving habits, user feedback, and historical service records;

[0028] Combined with the information of each touch point in the journey map, identify the concerns of users during the car purchase, use, and after-sales service processes, and update the concerns in combination with the changes in the user's usage behavior and preferences;

[0029] Based on the identification of concerns, analyze the potential patterns of user preferences, and combine with the consumer portrait to generate a personalized push plan for users.

[0030] The beneficial object of the present invention is to provide an automotive user experience and consumer portrait association system, and the system includes:

[0031] A touch point definition module, used to draw a user journey map during the car purchase, use, and after-sales service processes, define the touch points at each stage, and analyze the information contained in each touch point;

[0032] A primary consumer portrait construction module, used to obtain the full-process usage information of users, analyze the driving habits and purchase history of users, construct a primary consumer portrait, and update the primary consumer portrait in combination with the information contained in each touch point;

[0033] A user profile update module, which is used to analyze real-time driving data, combine it with the updated user profile, evaluate vehicle performance changes, and analyze potential risks to the vehicle and changes in driving habits;

[0034] A push plan generation module, which is used to identify user experience optimization strategies based on the dynamically updated consumer profile and the analysis results of driving habits, and combine the user's historical service records with the consumer profile to generate a push plan.

[0035] As a further solution of the present invention, the contact point definition module includes:

[0036] A journey map formation unit, which is used to identify each stage and link in the user's vehicle usage, visualize the journey of each stage, and form a journey map;

[0037] A contact point identification unit, which is used to identify the user's interactions with the vehicle at each stage, mark them as contact points, and define the nature of each contact point;

[0038] A contact point information collection unit, which is used to collect the information contained in each contact point, classify it into qualitative data and quantitative data, and combine the user feedback information contained in each contact point to judge the priority of each contact point.

[0039] As a further solution of the present invention, the primary consumer profile construction module includes:

[0040] A behavior data collection unit, which is used to collect the user's driving data and the user's behavior data during driving, and at the same time collect the user's after-sales data;

[0041] A driving mode analysis unit, which is used to analyze the collected data, identify the user's driving mode, detect the changing trend of the user's driving habits, and integrate the user's basic information and driving habit data to form a primary consumer profile;

[0042] A profile update unit, which is used to extract the information and priority data of each contact point, identify the user's preference changes, and update the primary consumer profile.

[0043] As a further solution of the present invention, the user profile update module includes:

[0044] A vehicle performance change status identification unit, which is used to combine the obtained vehicle driving data, identify the change status of the vehicle performance, and analyze the existing abnormal changes;

[0045] A potential risk analysis unit, which is used to evaluate the potential risks of the vehicle in combination with the changing trend of the user's driving habits:

[0046] ;

[0047] Among them, represents the probability of vehicle risk under a given feature, represents the intercept, that is, the risk probability when all features are zero, is the regression coefficient of each feature, indicating the degree of influence of the feature on the risk change, represents the feature parameters of different features affecting risk;

[0048] The driving behavior impact analysis unit is used to identify and analyze the preference changes of users and their impacts on driving behavior by combining real-time driving data with the updated user profile.

[0049] As a further solution of the present invention, the push solution generation module includes:

[0050] The information integration unit is used to integrate the dynamically updated consumer profile, driving habit analysis results, user feedback, and historical service records;

[0051] The user concern update unit is used to identify the concerns of users in the process of purchasing, using, and after-sales service by combining the information of each touch point in the journey map, and update the concerns by combining the user's usage behavior and preference changes;

[0052] The personalized push solution generation unit is used to analyze the potential pattern of user preferences based on the identification of concerns, and generate a personalized push solution for users by combining the consumer profile.

[0053] The beneficial effects of the present invention are:

[0054] This method shows various beneficial effects by systematically connecting the automotive user experience with the consumer profile. First, by drawing the user journey map and identifying each touch point, the enterprise can comprehensively understand the needs and pain points of users in the process of purchasing, using, and after-sales service. This visual analysis helps to identify key links and optimize the service process, thereby improving user satisfaction.

[0055] Obtaining and analyzing the driving habits and purchase history of users in real time can build a dynamically updated consumer profile, ensuring the accuracy of products and services. Based on the user profile, the enterprise can targetedly push personalized marketing policies, increasing user participation and loyalty. In addition, by analyzing driving data in real time, the enterprise can identify vehicle performance changes and potential risks, improving safety and reducing maintenance costs. The proactive push of maintenance and servicing reminders helps users handle problems in a timely manner, thereby extending the service life of the vehicle.

[0056] By combining user feedback and historical service records, enterprises can continuously optimize the user experience, flexibly adjust marketing strategies and service content, and improve conversion rates. This data-driven decision-making method not only enhances the user experience but also provides strong support for enterprises to maintain an advantage in the competition. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a flowchart of the method for associating automotive user experience with consumer portraits provided by an embodiment of the present invention;

[0058] Figure 2 It is a flowchart of drawing a user journey map, defining touchpoints at each stage, and analyzing the information contained in each touchpoint provided by an embodiment of the present invention;

[0059] Figure 3 It is a flowchart of constructing a primary consumer portrait and updating the primary consumer portrait by combining the information contained in each touchpoint provided by an embodiment of the present invention;

[0060] Figure 4 It is a flowchart of evaluating vehicle performance changes and analyzing potential risks and driving habit changes caused to the vehicle provided by an embodiment of the present invention;

[0061] Figure 5 It is a flowchart of combining the user's historical service records with the consumer portrait to generate a push plan provided by an embodiment of the present invention;

[0062] Figure 6 It is a structural block diagram of the system for associating automotive user experience with consumer portraits provided by an embodiment of the present invention;

[0063] Figure 7 It is a structural block diagram of the touchpoint definition module provided by an embodiment of the present invention;

[0064] Figure 8 It is a structural block diagram of the primary consumer portrait construction module provided by an embodiment of the present invention;

[0065] Figure 9 It is a structural block diagram of the user portrait update module provided by an embodiment of the present invention;

[0066] Figure 10 It is a structural block diagram of the push plan generation module provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0068] It can be understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of this application, the first xx script may be referred to as the second xx script, and similarly, the second xx script may be referred to as the first xx script.

[0069] Figure 1 FIG. is a flowchart of a method for associating automotive user experience with consumer portraits provided by an embodiment of the present invention. As Figure 1 shown, the method includes:

[0070] S100, during the car purchase, use, and after-sales service processes, draw a user journey map, define the touchpoints at each stage, and analyze the information contained in each touchpoint;

[0071] This step makes the various stages of the user journey and their touchpoints more intuitive through visualization means. Such visualization not only helps the team quickly understand user needs but also serves as an important communication tool in internal discussions to ensure that different departments have a consistent understanding of the user experience.

[0072] Contact point analysis provides a clear optimization direction for the enterprise. By identifying the interactions between users and vehicles and marking the nature of the touchpoints, the enterprise can quickly locate the key pain points in the user experience. Such positioning makes subsequent improvement measures more precise and can truly touch the core needs and emotional resonances of users.

[0073] In addition, collecting and classifying the information of each touchpoint, especially in combination with user feedback, can provide important data support for the iteration of products and services. The combination of qualitative and quantitative data makes the analysis results more comprehensive and can reveal the potential expectations and behavior patterns of users. Such in-depth user insights are not only the basis for precision marketing but also provide inspiration for product innovation.

[0074] This step also creates conditions for dynamically updating the consumer portrait. By monitoring users' interactions and feedback in real time, the enterprise can flexibly adjust its user strategy to ensure that it always matches the user needs. Such a dynamic adjustment mechanism enables the enterprise to quickly adapt to changes in the highly competitive market and improve user satisfaction and loyalty.

[0075] Through the detailed journey map and contact point analysis, the enterprise can obtain a comprehensive user perspective, which helps to identify key user pain points and concerns. Such in-depth understanding not only promotes the improvement of the user experience but also provides data support for personalized services and precision marketing.

[0076] As Figure 2As shown, during the process of purchasing, using, and after-sales service of a vehicle, a user journey map is drawn, contact points at each stage are defined, and the information contained in each contact point is analyzed, specifically including:

[0077] S110, identify each stage and link in the user's vehicle usage, and visualize the journey at each stage to form a journey map;

[0078] S120, identify the user's interactions with the vehicle at each stage, mark them as contact points, and define the nature of each contact point;

[0079] S130, collect the information contained in each contact point, classify it as qualitative data and quantitative data, and combine the user feedback information contained in each contact point to judge the priority of each contact point.

[0080] S200, obtain the user's full-course usage information, analyze the user's driving habits and purchase history, construct a primary consumer portrait, and update the primary consumer portrait in combination with the information contained in each contact point;

[0081] In this step, by collecting the user's driving data and behavior data in real time, it is possible to deeply understand the user's driving habits, including driving frequency, mileage, driving style, etc. These data not only reflect the user's personalized needs but also can reveal potential risks and preference changes. If the user's driving pattern changes, this will directly affect their vehicle needs and usage experience, thus requiring continuous adjustment of the primary consumer portrait to ensure its accuracy and timeliness.

[0082] Secondly, by combining the information of each contact point with the user's feedback, effectively compare the user's historical data with current behavior, and update the consumer portrait in real time. This dynamic update method enables automobile manufacturers or dealers to quickly identify changes in user preferences, adjust services and product recommendations accordingly, and thus improve user satisfaction and loyalty. By analyzing the user's driving patterns and purchase history, enterprises can better understand the user's needs at different stages, and thus provide personalized services and experiences.

[0083] The real-time updated consumer portrait can not only enhance the user experience but also help enterprises better formulate marketing strategies and product development decisions. By accurately identifying changes in user preferences and behaviors, enterprises can design marketing activities more precisely, push personalized products and services, and improve conversion rates and customer satisfaction. In addition, based on the analysis of the user's driving habits, it is possible to pre-warn potential risks of the vehicle, provide proactive maintenance suggestions, thereby reducing the failure rate and enhancing safety.

[0084] Such as Figure 3As shown, obtaining the user's full-course usage information, analyzing the user's driving habits and purchase history, constructing a primary consumer portrait, and updating the primary consumer portrait in combination with the information contained in each touchpoint specifically include:

[0085] S210, collecting the user's driving data and the user's behavior data during driving, and simultaneously collecting the user's after-sales data;

[0086] S220, analyzing the collected data, identifying the user's driving patterns, detecting the changing trend of the user's driving habits, and integrating the user's basic information and driving habit data to form a primary consumer portrait;

[0087] S230, extracting the information and priority data of each touchpoint, identifying the user's preference changes, and updating the primary consumer portrait:

[0088] ;

[0089] Among them, is the characteristic value of the updated consumer portrait, is the characteristic value of the primary consumer portrait, is the characteristic value of the newly collected user feedback, is the weight coefficient.

[0090] S300, analyzing the real-time driving data, combining it with the updated user portrait, evaluating the vehicle performance changes, and analyzing the potential risks and driving habit changes caused to the vehicle;

[0091] This step monitors the real-time driving data of the user and combines it with the updated user portrait to deeply analyze the vehicle performance changes and potential risks. This process first involves monitoring the real-time driving data of the vehicle to identify which performance indicators have abnormal changes. These data include but are not limited to engine status, braking performance, fuel efficiency, etc., thus laying a foundation for evaluating the overall health of the vehicle. Through continuous data stream analysis, possible fault signs or performance degradation trends can be effectively identified, providing timely maintenance suggestions for the user.

[0092] Secondly, combined with the changing trend of the user's driving habits, this step can not only evaluate the potential risks of the vehicle but also analyze the impact of the changes in driving behavior on the vehicle performance. For example, the user may change the driving style due to different driving environments or personal habit changes, thus affecting the vehicle's wear degree and safety. By establishing a model and conducting correlation analysis on the driving habits and vehicle performance data, the potential risks can be evaluated more accurately, and personalized maintenance suggestions can be provided for the user.

[0093] This step can achieve a comprehensive control of vehicle performance, timely detect problems and push maintenance reminders, thereby reducing failure rates and improving safety. In addition, the combination of real-time analysis of driving data and user portraits also provides enterprises with more accurate user insights, enabling them to provide personalized service and product recommendations based on changes in users' driving habits. By dynamically adjusting the recommendation strategy, enterprises can not only enhance the user experience, increase user satisfaction and loyalty, but also effectively reduce maintenance costs and extend the service life of vehicles. This data-driven decision-making method enables automobile manufacturers and service providers to have more advantages in the highly competitive market and provide higher-quality services and safer driving experiences.

[0094] As Figure 4 shown, it analyzes real-time driving data, combines it with the updated user portrait, evaluates changes in vehicle performance, and analyzes potential risks and changes in driving habits caused to the vehicle, specifically including:

[0095] S310, combining the obtained vehicle driving data, identifying the change status of vehicle performance, and analyzing existing abnormal changes;

[0096] S320, evaluating potential vehicle risks in combination with the changing trend of users' driving habits:

[0097] ;

[0098] Among them, represents the probability of vehicle risk under a given feature , represents the intercept, that is, the risk probability when all features are zero, is the regression coefficient of each feature, indicating the degree of influence of the feature on the risk change, represents the feature parameters of different risk-impacting features;

[0099] S330, identifying and analyzing changes in users' preferences and their impacts on driving behavior based on the combination of real-time driving data and the updated user portrait.

[0100] S400, identifying user experience optimization strategies based on the dynamically updated consumer portrait and driving habit analysis results, and combining the user's historical service records with the consumer portrait to generate a push plan.

[0101] As Figure 5 shown, based on the dynamically updated consumer portrait and driving habit analysis results, identifying user experience optimization strategies, and combining the user's historical service records with the consumer portrait to generate a push plan, specifically including:

[0102] S410, integrate the dynamically updated consumer portrait, driving habit analysis results, user feedback, and historical service records;

[0103] S420, combine the information of each touchpoint in the journey map, identify the concerns of users during the car purchase, usage, and after-sales service processes, and update the concerns in combination with the changes in users' usage behaviors and preferences;

[0104] S430, based on the identification of concerns, analyze the potential patterns of users' preferences, and generate personalized push plans for users in combination with the consumer portrait.

[0105] Figure 6 The structural block diagram of the automotive user experience and consumer portrait association system provided by the embodiments of the present invention is as shown in Figure 6 shown, and the system includes:

[0106] The touchpoint definition module 100 is used to draw the user journey map during the car purchase, usage, and after-sales service processes, define the touchpoints of each stage, and analyze the information contained in each touchpoint;

[0107] The primary consumer portrait construction module 200 is used to obtain the full-process usage information of users, analyze users' driving habits and purchase histories, construct the primary consumer portrait, and update the primary consumer portrait in combination with the information contained in each touchpoint;

[0108] The user portrait update module 300 is used to analyze real-time driving data, combine it with the updated user portrait, evaluate the changes in vehicle performance, and analyze the potential risks and driving habit changes caused to the vehicle;

[0109] The push plan generation module 400 is used to identify user experience optimization strategies based on the dynamically updated consumer portrait and driving habit analysis results, and combine the user's historical service records with the consumer portrait to generate a push plan.

[0110] As shown in Figure 7 shown, the touchpoint definition module 100 includes:

[0111] The journey map formation unit 110 is used to identify each stage and link of users using the vehicle, visualize the journey of each stage, and form a journey map;

[0112] The touchpoint identification unit 120 is used to identify the interactions between users and the vehicle at each stage, mark them as touchpoints, and define the nature of each touchpoint;

[0113] The contact point information collection unit 130 is used to collect the information contained in each contact point, classify it into qualitative data and quantitative data, and combine the user feedback information contained in each contact point to determine the priority of each contact point.

[0114] As Figure 8 shown, the primary consumer portrait construction module 200 includes:

[0115] The behavior data collection unit 210 is used to collect the driving data of the user and the behavior data of the user during driving, and at the same time collect the after-sales data of the user;

[0116] The driving mode analysis unit 220 is used to analyze the collected data, identify the driving mode of the user, detect the changing trend of the user's driving habits, and integrate the basic information of the user and the driving habit data to form a primary consumer portrait;

[0117] The portrait update unit 230 is used to extract the information and priority data of each contact point, identify the preference changes of the user, and update the primary consumer portrait.

[0118] As Figure 9 shown, the user portrait update module 300 includes:

[0119] The vehicle performance change state recognition unit 310 is used to combine the obtained vehicle driving data to identify the change state of the vehicle performance and analyze the existing abnormal changes;

[0120] The potential risk analysis unit 320 is used to evaluate the potential risks of the vehicle in combination with the changing trend of the user's driving habits:

[0121] ;

[0122] Among them, represents the probability that the vehicle has risks under a given feature , represents the intercept, that is, the risk probability when all features are zero, is the regression coefficient of each feature, indicating the degree of influence of the feature on the risk change, represents the feature parameters of different features that affect the risk;

[0123] The driving behavior impact analysis unit 330 is used to combine the real-time driving data with the updated user portrait to identify and analyze the preference changes of the user and their impact on driving behavior.

[0124] As Figure 10 shown, the push scheme generation module 400 includes:

[0125] An information integration unit 410 is configured to integrate the dynamically updated consumer portraits, driving habit analysis results, user feedback, and historical service records;

[0126] A user concern update unit 420 is configured to identify the concerns of users during the car purchase, use, and after-sales service processes by combining the information of each touchpoint in the journey map, and update the concerns in combination with the changes in the usage behaviors and preferences of the users;

[0127] A personalized push plan generation unit 430 is configured to analyze the potential patterns of user preferences based on the identified concerns, and generate a personalized push plan for the users in combination with the consumer portraits.

[0128] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the indications of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0129] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to the memory, storage, database, or other media provided in the various embodiments of the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0130] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0131] The above-described embodiments merely represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

[0132] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. Method for associating automotive user experience with consumer portrait, characterized in that The method includes: During the car purchase, use, and after-sales service processes, draw a user journey map, define the touchpoints at each stage, and analyze the information contained in each touchpoint. Obtain the user's full usage information, analyze the user's driving habits and purchase history, construct a primary consumer profile, and update the primary consumer profile by combining the information contained in each touchpoint. Analyze the real-time driving data, combine it with the updated user profile, evaluate the vehicle performance changes, and analyze the potential risks to the vehicle and changes in driving habits. Based on the dynamically updated consumer profile and the analysis results of driving habits, identify user experience optimization strategies, and combine the user's historical service records with the consumer profile to generate a push plan. During the car purchase, use, and after-sales service processes, draw a user journey map, define the touchpoints at each stage, and analyze the information contained in each touchpoint, specifically including: Identify the various stages and links in which the user uses the vehicle, and visualize the journeys at each stage to form a journey map. Identify the user's interactions with the vehicle at each stage, mark them as touchpoints, and define the nature of each touchpoint. Collect the information contained in each touchpoint, classify it into qualitative data and quantitative data, and combine the user feedback information contained in each touchpoint to determine the priority of each touchpoint. Obtain the user's full usage information, analyze the user's driving habits and purchase history, construct a primary consumer profile, and update the primary consumer profile by combining the information contained in each touchpoint, specifically including: Collect the user's driving data and the user's behavior data during driving, and at the same time collect the user's after-sales data. Analyze the collected data, identify the user's driving patterns, detect the changing trends of the user's driving habits, and integrate the user's basic information with the driving habit data to form a primary consumer profile. Extract the information and priority data of each touchpoint, identify the changes in the user's preferences, and update the primary consumer profile. ； Among them, is the updated eigenvalue of the consumer portrait feature, is the eigenvalue of the primary consumer portrait feature, is the eigenvalue of the newly collected user feedback feature, is the weight coefficient; Analyze the real-time driving data, combine it with the updated user profile, evaluate the vehicle performance changes, and analyze the potential risks to the vehicle and changes in driving habits, specifically including: Combine the obtained vehicle driving data to identify the changing state of the vehicle performance and analyze the existing abnormal changes. Combine the changing trends of the user's driving habits to evaluate the potential risks of the vehicle. ； Among them, represents the probability of vehicle risk under a given feature, represents the intercept, that is, the risk probability when all features are zero, is the regression coefficient of each feature, indicating the degree of influence of the feature on the risk change, represents the feature parameters of different features that affect risk; Based on the combination of the real-time driving data and the updated user profile, identify and analyze the changes in the user's preferences and their impact on driving behavior. Based on the dynamically updated consumer profile and the analysis results of driving habits, identify user experience optimization strategies, and combine the user's historical service records with the consumer profile to generate a push plan, specifically including: Integrate the dynamically updated consumer profile, the analysis results of driving habits, the user feedback, and the historical service records. Combine the information of each touchpoint in the journey map to identify the user's concerns during the car purchase, use, and after-sales service processes, and update the concerns by combining the user's usage behavior and preference changes. Based on concern-based recognition, analyze the potential patterns of user preferences, and combine with the consumer portrait to generate personalized push solutions for users.

2. The automotive user experience and consumer portrait association system is characterized in that The system includes: A touchpoint definition module, which is used to draw a user journey map during the car purchase, use, and after-sales service processes, define the touchpoints at each stage, and analyze the information contained in each touchpoint. A primary consumer portrait construction module, which is used to obtain the full-process usage information of users, analyze users' driving habits and purchase history, construct a primary consumer portrait, and update the primary consumer portrait in combination with the information contained in each touchpoint. A user portrait update module, which is used to analyze real-time driving data, combine it with the updated user portrait, evaluate the vehicle performance changes, and analyze the potential risks and driving habit changes caused to the vehicle. A push solution generation module, which is used to identify user experience optimization strategies based on the dynamically updated consumer portrait and driving habit analysis results, and combine the user's historical service records with the consumer portrait to generate push solutions. The touchpoint definition module includes: A journey map formation unit, which is used to identify each stage and link in the vehicle usage process of users, visualize the journey at each stage, and form a journey map. A touchpoint identification unit, which is used to identify the interactions between users and the vehicle at each stage, mark them as touchpoints, and define the nature of each touchpoint. A touchpoint information collection unit, which is used to collect the information contained in each touchpoint, classify it into qualitative data and quantitative data, and combine the user feedback information contained in each touchpoint to judge the priority of each touchpoint. The primary consumer portrait construction module includes: A behavior data collection unit, which is used to collect users' driving data and behavior data during driving, and at the same time collect users' after-sales data. A driving mode analysis unit, which is used to analyze the collected data, identify users' driving modes, detect the changing trends of users' driving habits, and integrate users' basic information and driving habit data to form a primary consumer portrait. A portrait update unit, which is used to extract the information and priority data of each touchpoint, identify the preference changes of users, and update the primary consumer portrait. The user portrait update module includes: A vehicle performance change status identification unit, which is used to combine the obtained vehicle driving data to identify the change status of vehicle performance and analyze the existing abnormal changes. A potential risk analysis unit, which is used to evaluate the potential risks of the vehicle in combination with the changing trends of users' driving habits. ； Among them, represents the probability of vehicle risk under a given feature, represents the intercept, that is, the risk probability when all features are zero, is the regression coefficient of each feature, indicating the degree of influence of the feature on the risk change, represents the feature parameters of different risk-influencing features; A driving behavior impact analysis unit, which is used to combine real-time driving data with the updated user portrait to identify and analyze the preference changes of users and their impacts on driving behavior. The push solution generation module includes: An information integration unit, which is used to integrate the dynamically updated consumer portrait, driving habit analysis results, user feedback, and historical service records. A user concern update unit, which is used to combine the information of each touchpoint in the journey map to identify the concerns of users during the car purchase, use, and after-sales service processes, and update the concerns in combination with the usage behaviors and preference changes of users. A personalized push plan generation unit, which is used to analyze the potential patterns of users' preferences based on the recognition of concerns, and combine with the consumer portrait to generate a personalized push plan for users.

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