Product operation method and device, and computer readable storage medium

Abstract

This application relates to the field of product operation technology, and provides a product operation method, apparatus, and computer-readable storage medium. The method includes: acquiring product operation demand information of a target product; determining a target product operation strategy based on the product operation demand information and a preset first AI model; using the preset first AI model to determine the target product operation strategy; calling a preset information publishing API of a target information publishing platform to publish the target product operation strategy to the target information publishing platform; acquiring user feedback information on the target product operation strategy on the target information publishing platform; and adjusting the target product operation strategy based on the user feedback information. This solution can improve the efficiency of product operation.

Description

Technical Field

[0001] This application relates to the field of product operation technology, and in particular to product operation methods, apparatus and computer-readable storage media. Background Technology

[0002] Currently, product operation work still relies entirely on manual processes, lacking systematic and automated tools and workflows. From daily user communication and maintenance, content editing and publishing, event planning and execution, to user data statistics and organization, feedback collection and processing, and problem follow-up and closure, each step requires operations personnel to handle and operate one by one.

[0003] This purely manual mode not only has long processing cycles for individual tasks and involves numerous repetitive tasks, but it is also prone to data deviations, delayed feedback, and execution omissions due to limited staff capacity and inconsistent operations. As business volume continues to increase and user needs become more refined, the limitations of manual operations are further amplified, resulting in significantly low overall operational efficiency. This not only consumes a large amount of human and time resources but also makes it difficult to achieve large-scale and refined operations, hindering rapid response to market changes and business iterations, and directly impacting operational effectiveness and user experience. Summary of the Invention

[0004] This application provides a product operation method, apparatus, and computer-readable storage medium that can improve the efficiency of product operation.

[0005] To achieve the above objectives, this application adopts the following technical solution: Firstly, a product operation method is provided, which includes: obtaining product operation requirement information of a target product; determining a target product operation strategy based on the product operation requirement information and a preset first AI model; using the preset first AI model to determine the target product operation strategy; calling a preset information publishing API of a target information publishing platform to publish the target product operation strategy to the target information publishing platform; obtaining user feedback information on the target product operation strategy on the target information publishing platform; and adjusting the target product operation strategy based on the user feedback information.

[0006] In conjunction with the first aspect, in certain embodiments of the first aspect, determining the target product operation strategy for the target product based on product operation requirement information and a preset AI model includes: invoking a preset second AI model; the preset second AI model is used to decompose product operation requirements into multiple sub-operation tasks; inputting product operation requirement information and a preset first command into the preset second AI model to obtain multiple sub-operation tasks of the AI ​​model; the preset first command is used to instruct the preset second AI model to decompose product operation requirements into multiple sub-operation tasks; for each sub-operation task among the multiple sub-operation tasks, inputting the sub-operation task and the preset second command corresponding to the sub-operation task into the preset first AI model to obtain the target product operation strategy for the target product; the target product operation strategy includes the sub-operation strategy for each sub-operation task.

[0007] In conjunction with the first aspect, in certain embodiments of the first aspect, calling a preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform includes: obtaining the target information publishing rules of the target information publishing platform; determining whether the target product operation strategy conforms to the target information publishing rules; when the target product operation strategy conforms to the target information publishing rules, calling the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; when the target product operation strategy does not conform to the target information publishing rules, inputting the target product operation strategy, the target information publishing rules, and a preset third command into a preset third AI model to obtain an adjusted target product operation strategy, and calling the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; the preset third command is used to instruct the preset third AI model to adjust the target product operation strategy according to the target information publishing rules so that the adjusted target product operation strategy conforms to the target information publishing rules.

[0008] In conjunction with the first aspect, in certain embodiments of the first aspect, user feedback information includes user comment text information. Adjusting the target product operation strategy based on user feedback information includes: inputting user feedback information and a preset fourth AI instruction into a preset fourth AI model to obtain user satisfaction with the target product operation strategy; the preset fourth AI instruction is used to instruct the preset fourth AI model to determine user satisfaction based on user feedback information; when user satisfaction is less than a preset satisfaction threshold, inputting user comment text information, the target product operation strategy, and a preset fifth AI instruction into a preset first AI model to obtain an optimized target product operation strategy; the preset fifth AI instruction is used to instruct the preset first AI model to optimize the target product operation strategy based on user comment text information.

[0009] Secondly, a product operation device is provided for implementing the product operation method described in the first aspect. This product operation device includes modules, units, or means corresponding to the above method. These modules, units, or means can be implemented in hardware, software, or by hardware executing corresponding software. The hardware or software includes one or more modules or units corresponding to the above functions.

[0010] In conjunction with the second aspect, in some embodiments of the second aspect, the apparatus includes: an acquisition module and a processing module; the acquisition module is used to acquire product operation requirement information of the target product; the processing module is used to determine the target product operation strategy of the target product based on the product operation requirement information and a preset first AI model; the preset first AI model is used to determine the target product operation strategy of the target product; the processing module is further used to call a preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; the processing module is further used to acquire user feedback information on the target product operation strategy on the target information publishing platform; the processing module is further used to adjust the target product operation strategy based on the user feedback information.

[0011] In conjunction with the second aspect, in some embodiments of the second aspect, the processing module is used to determine the target product operation strategy for the target product based on product operation requirement information and a preset AI model, including: invoking a preset second AI model; the preset second AI model is used to decompose the product operation requirements into multiple sub-operation tasks; inputting the product operation requirement information and a preset first command into the preset second AI model to obtain multiple sub-operation tasks of the AI ​​model; the preset first command is used to instruct the preset second AI model to decompose the product operation requirements into multiple sub-operation tasks; for each sub-operation task among the multiple sub-operation tasks, inputting the sub-operation task and the preset second command corresponding to the sub-operation task into the preset first AI model to obtain the target product operation strategy for the target product; the target product operation strategy includes the sub-operation strategy of each sub-operation task.

[0012] In conjunction with the second aspect, in some embodiments of the second aspect, the processing module is further configured to call a preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform, including: obtaining the target information publishing rules of the target information publishing platform; determining whether the target product operation strategy conforms to the target information publishing rules; when the target product operation strategy conforms to the target information publishing rules, calling the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; when the target product operation strategy does not conform to the target information publishing rules, inputting the target product operation strategy, the target information publishing rules, and a preset third command into a preset third AI model to obtain an adjusted target product operation strategy, and calling the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; the preset third command is used to instruct the preset third AI model to adjust the target product operation strategy according to the target information publishing rules so that the adjusted target product operation strategy conforms to the target information publishing rules.

[0013] In conjunction with the second aspect, in some embodiments of the second aspect, the user feedback information includes user comment text information. The processing module is further used to adjust the target product operation strategy based on the user feedback information, including: inputting the user feedback information and a preset fourth AI instruction into a preset fourth AI model to obtain the user satisfaction of the target product operation strategy; the preset fourth AI instruction is used to instruct the preset fourth AI model to determine the user satisfaction based on the user feedback information; when the user satisfaction is less than a preset satisfaction threshold, inputting the user comment text information, the target product operation strategy, and a preset fifth AI instruction into a preset first AI model to obtain an optimized target product operation strategy; the preset fifth AI instruction is used to instruct the preset first AI model to optimize the target product operation strategy based on the user comment text information.

[0014] Thirdly, a product operation apparatus is provided, comprising: at least one processor and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method provided by the first aspect and any possible implementation thereof.

[0015] Fourthly, a computer-readable storage medium is provided, wherein when the instructions in the computer-readable storage medium are executed by a processor of a product operating device, the product operating device is enabled to perform the method provided in the first aspect and any possible implementation thereof.

[0016] Fifthly, a computer program product containing instructions is provided that, when run on a computer, enables the computer to perform the methods provided in the first aspect and any possible implementation thereof.

[0017] The technical effects of any one of the second to fifth aspects can be found in the technical effects of the different embodiments of the first aspect described above, and will not be repeated here. Attached Figure Description

[0018] Figure 1 A schematic diagram of the architecture of a product operation system provided in this application; Figure 2 A flowchart illustrating a product operation method provided in this application; Figure 3 A structural schematic diagram of a product operation device provided in this application; Figure 4 This is a structural schematic diagram of another product operating device provided in this application. Detailed Implementation

[0019] In the description of this application, unless otherwise stated, "multiple" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0020] Furthermore, to facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0021] In this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being better or more advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner to facilitate understanding.

[0022] It is understood that the term "embodiment" used throughout the specification means that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, various embodiments throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It is understood that in the various embodiments of this application, the sequence number of each process does not imply the order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0023] It is understood that in this application, "when," "if," and "if" all refer to the corresponding processing that will be carried out under certain objective circumstances, and are not limited to a specific time, nor do they require that there must be a judgment action when implemented, nor do they imply any other limitations.

[0024] It is understood that some optional features in the embodiments of this application can be implemented independently in certain scenarios without relying on other features, such as the current solution on which they are based, to solve the corresponding technical problems and achieve the corresponding effects. Alternatively, they can be combined with other features as needed in certain scenarios. Correspondingly, the apparatus given in the embodiments of this application can also implement these features or functions, which will not be elaborated here.

[0025] In this application, unless otherwise specified, the same or similar parts between the various embodiments can be referred to each other. In the various embodiments and implementation methods of the various embodiments in this application, unless otherwise specified or logically conflicting, the terminology and / or descriptions between different embodiments and between the implementation methods of the various embodiments are consistent and can be mutually referenced. The technical features in different embodiments and between the implementation methods of the various embodiments can be combined according to their inherent logical relationships to form new embodiments, implementation methods, implementation methods, or implementation approaches. The following embodiments of this application do not constitute a limitation on the scope of protection of this application.

[0026] Currently, product operation work still relies entirely on manual processes, lacking systematic and automated tools and workflows. From daily user communication and maintenance, content editing and publishing, event planning and execution, to user data statistics and organization, feedback collection and processing, and problem follow-up and closure, each step requires operations personnel to handle and operate one by one.

[0027] This purely manual mode not only has long processing cycles for individual tasks and involves numerous repetitive tasks, but it is also prone to data deviations, delayed feedback, and execution omissions due to limited staff capacity and inconsistent operations. As business volume continues to increase and user needs become more refined, the limitations of manual operations are further amplified, resulting in significantly low overall operational efficiency. This not only consumes a large amount of human and time resources but also makes it difficult to achieve large-scale and refined operations, hindering rapid response to market changes and business iterations, and directly impacting operational effectiveness and user experience.

[0028] To address the aforementioned issues, this application provides a product operation method, comprising: obtaining product operation requirement information for a target product; determining a target product operation strategy for the target product based on the product operation requirements and a preset first AI model; using the preset first AI model to determine the target product operation strategy; calling a preset information publishing API of a target information publishing platform to publish the target product operation strategy to the target information publishing platform; obtaining user feedback information on the target product operation strategy on the target information publishing platform; and adjusting the target product operation strategy based on the user feedback information.

[0029] Based on this solution, firstly, a pre-set AI model automatically generates matching operational strategies based on product operation needs, replacing the complex process of manual research, analysis, and strategy formulation. This avoids the time-consuming nature of subjective judgment and decision-making delays, achieving intelligent and efficient strategy generation. Secondly, by calling the pre-set API interface of the information publishing platform, operational strategies are automatically published directly, eliminating repetitive operations such as manually logging into the platform, editing content, and uploading in stages. This significantly shortens the time cycle for strategy implementation and improves the standardization and smoothness of the publishing process. Simultaneously, the solution can obtain real-time user feedback from the platform and dynamically adjust strategies accordingly. There is no need for manual collection and organization of feedback data or repeated reviews and optimizations, forming a fully automated closed loop from requirement input, strategy generation, automatic publishing to feedback iteration. This reduces a large amount of manual intervention and time-consuming intermediate steps, resulting in faster operational strategy formulation, more efficient execution, and more timely optimization. Overall, the technical solution effectively improves the overall efficiency and responsiveness of product operations.

[0030] Figure 1 This application provides a schematic diagram of the architecture of a product operation system. The technical solutions of the embodiments of this application can be applied to... Figure 1 The product operation system shown is as follows: Figure 1 As shown, the product operation system 10 includes a product operation device 11 and an electronic device 12.

[0031] The product operation device 11 is directly or indirectly connected to the electronic device 12. This connection can be wired or wireless, and this application embodiment does not limit this.

[0032] Data interaction can occur between the product operation device 11 and the electronic device 12.

[0033] It should be noted that the product operating device 11 and the electronic device 12 can be independent devices or integrated into the same device; this application does not make specific limitations in this regard.

[0034] When the product operating device 11 and the electronic device 12 are integrated into the same device, the communication method between the product operating device 11 and the electronic device 12 is the communication between modules within the device. In this case, the communication process between the two is the same as that when the product operating device 11 and the electronic device 12 are independent of each other.

[0035] In the following embodiments provided in this application, the product operation device 11 and the electronic device 12 are described as being configured independently of each other.

[0036] In practical applications, the product operation method provided in this application embodiment can be applied to the product operation device 11, or to the devices included in the product operation device 11.

[0037] The product operation method provided in this application embodiment will be described below with reference to the accompanying drawings, taking the application of the product operation method to the product operation device 11 as an example.

[0038] Figure 2 A flowchart illustrating a product operation method provided in this application, such as Figure 2 As shown, the method includes the following steps: S201, The product operation device acquires product operation requirement information for the target product.

[0039] It should be noted that the product can be a physical product, such as a television set or clothing, or a virtual product, such as a course or software service. This application does not impose any specific restrictions on this.

[0040] Product operation requirements information may include basic product information, operation target information, and operation constraint information. Of course, product operation requirements information may also include other information, and this application does not impose specific restrictions on this.

[0041] Basic product information includes the type of target product, its features, target user group, product life cycle stage, core selling points, and product positioning.

[0042] Operational objectives include specific operational goals and quantifiable metrics such as user acquisition, user retention, activity improvement, product promotion, sales conversion, brand promotion, and traffic generation through events.

[0043] Operational constraints include operating budget, operating cycle, restrictions on promotion channels, compliance requirements, geographical scope, time period for campaigning, and resource allocation restrictions.

[0044] As one possible implementation method, combined with Figure 1 The user inputs the product operation requirements information of the target product on the input device of the electronic device. The electronic device encapsulates the product operation requirements information of the target product into first information and sends the first information to the product operation device.

[0045] Correspondingly, the product operation device receives the first information from the electronic device and obtains the product operation requirement information of the target product from the first information.

[0046] S202. The product operation device determines the target product operation strategy based on the product operation demand information and the preset first AI model.

[0047] Among them, the first preset AI model is used to determine the target product operation strategy.

[0048] It should be noted that the first AI model can be Doubao, Wenxin Yiyan, or Qianwen, etc., and this application does not impose specific restrictions on it.

[0049] The target product operation strategy may include content operation strategy, user operation strategy, and event operation strategy. Of course, the target product operation strategy may also include other strategy information, and this application does not impose specific restrictions on this.

[0050] Content operation strategy includes information such as promotional copy, promotional materials, product introductions, event themes, graphic / video content planning and publishing formats.

[0051] User operation strategies include information such as target user group segmentation, user outreach methods, interaction formats, user incentive rules, and user acquisition and retention plans.

[0052] The event operation strategy includes information such as the type of marketing event, preferential rules, promotion methods, event cycle, participation threshold, and conversion guidance path.

[0053] As one possible implementation, the product operation device invokes a preset second AI model; the preset second AI model is used to decompose product operation requirements into multiple sub-operation tasks; the product operation requirements and a preset first command are input into the preset second AI model to obtain multiple sub-operation tasks of the AI ​​model; the preset first command is used to instruct the preset second AI model to decompose product operation requirements into multiple sub-operation tasks; for each sub-operation task, the sub-operation task and the corresponding preset second command are input into the preset first AI model to obtain the target product operation strategy; the target product operation strategy includes the sub-operation strategy of each sub-operation task.

[0054] It should be noted that the second AI model can be Doubao, Wenxin Yiyan, or Qianwen, etc., and this application does not impose any specific restrictions on it.

[0055] When product operation requirements information includes basic product information, operation target information, and operation constraint information, multiple sub-operation tasks can include content operation tasks, user operation tasks, and event operation tasks.

[0056] As an example, the product operation device first obtains the product operation requirements information of the target product. The product operation device then invokes a preset second AI model, inputting the aforementioned product operation requirements information and a preset first command into the preset second AI model. The preset first command instructs the preset second AI model to decompose the product operation requirements into tasks. Based on the product operation requirements and the preset first command, the preset second AI model intelligently analyzes and breaks down the overall operation requirements, resulting in multiple independent and executable sub-operation tasks.

[0057] Subsequently, the product operation device performs a strategy generation step for each sub-operation task: each sub-operation task and its corresponding preset second command are sequentially input into the preset first AI model. The preset second command instructs the preset first AI model to generate a matching execution strategy for the current sub-operation task. The preset first AI model generates corresponding sub-operation strategies based on the content and constraints of each sub-operation task.

[0058] Based on this possible implementation method, the solution constructs an intelligent and standardized technical path for operational demand decomposition and strategy generation through the collaborative application of a preset second AI model and a preset first AI model. This effectively solves the technical pain points of traditional product operation, such as reliance on manual demand decomposition, low efficiency in strategy formulation, and insufficient targeting. Under the instruction of a preset first command, the preset second AI model can automatically decompose product operation demand information into multiple independent and executable sub-operation tasks, replacing the cumbersome process of manual decomposition, reducing subjective errors and time costs, and achieving efficient and structured demand decomposition. At the same time, for each sub-operation task, by inputting the corresponding preset second command, the preset first AI model is instructed to accurately generate a sub-operation strategy adapted to that sub-operation task. Finally, these strategies are combined to form a complete target product operation strategy, ensuring that each sub-operation strategy is highly matched with the overall operation demand and sub-task objectives, significantly improving the accuracy and efficiency of operation strategy formulation, and reducing the cost of manual intervention.

[0059] S203. The product operation device calls the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform.

[0060] It should be noted that the target information publishing platform can be Douyin, Xiaohongshu, etc., and this application does not impose specific restrictions on this.

[0061] Preset information publishing API refers to the API provided by the target information publishing platform that can automatically publish information to the target information publishing platform.

[0062] As one possible implementation, the product operation device acquires the target information publishing rules of the target information publishing platform; determines whether the target product operation strategy conforms to the target information publishing rules; when the target product operation strategy conforms to the target information publishing rules, it calls the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; when the target product operation strategy does not conform to the target information publishing rules, it inputs the target product operation strategy, the target information publishing rules, and the preset third command into the preset third AI model to obtain the adjusted target product operation strategy, calls the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; the preset third command is used to instruct the preset third AI model to adjust the target product operation strategy according to the target information publishing rules so that the adjusted target product operation strategy conforms to the target information publishing rules.

[0063] The rules for publishing target information may include content compliance rules, video length rules, format specification rules, rules on time period restrictions for placement, and review standards for promotional content. Of course, the rules for publishing target information may also include other content, and this application does not impose specific restrictions on this.

[0064] As an example, firstly, the product operation device obtains the target information publishing rules corresponding to the platform through the rule query interface opened by the target information publishing platform.

[0065] The product operation device acquires the target product operation strategy generated in the early stage through the first AI model and the second AI model, and determines whether the target product operation strategy conforms to the target information release rules acquired above.

[0066] When the target product's operational strategy conforms to the aforementioned target information release rules, and the product operation device verifies that the promotional material format, content description, and placement time of the target product's operational strategy all comply with the target information release rules, the product operation device directly calls the preset information release API pre-configured on the target information release platform. This API interface has completed identity authentication and permission configuration in advance, enabling automated uploading and release of the operational strategy. The product operation device uses this API to synchronously release all content, including promotional materials, placement plans, and new user acquisition rules, corresponding to the target product's operational strategy to the target information release platform, eliminating the need for manual operation of the release process and ensuring release efficiency.

[0067] In scenarios where the target product operation strategy does not conform to the aforementioned target information release rules, the product operation device verifies that the promotional material duration in the target product operation strategy is 80 seconds, which does not meet the "duration 15-60 seconds" format requirement in the target information release rules. In this case, the product operation device inputs the currently non-compliant target product operation strategy, the obtained complete target information release rules, and a preset third command into a preset third AI model. Specifically, the preset third command can be: "Based on the input target information release rules, make targeted adjustments to the target product operation strategy, focusing on correcting the promotional material duration to ensure that the adjusted target product operation strategy fully complies with all release rules without changing the core objectives and content of the original operation strategy."

[0068] The pre-set third AI model is a deep learning model based on platform rule matching and content optimization. This model is pre-trained with rule bases and operational strategy optimization samples from various information publishing platforms. It can accurately identify parts of the operational strategy that do not conform to platform rules and intelligently adjust them according to rule requirements. After receiving input information, the pre-set third AI model optimizes and adjusts the original target product's operational strategy. Specifically, the adjustment involves: editing the promotional materials to 50 seconds, retaining the core function demonstration content, and keeping the rest of the operational strategy content unchanged, thus generating the adjusted target product's operational strategy.

[0069] The third AI model can be Doubao, Wenxin Yiyan, or Qianwen, etc., and this application does not impose specific restrictions on it.

[0070] After obtaining the adjusted target product operation strategy, the product operation device verifies again whether it conforms to the target information release rules. Then, it calls the preset information release API of the target information release platform to release the adjusted target product operation strategy to the target information release platform, thus completing the entire operation strategy release process.

[0071] Based on this possible implementation method, the solution first obtains the target information release rules of the target information release platform through the product operation device, and builds a compliance verification mechanism before the release of the operation strategy. This avoids problems such as release failure and rework due to the strategy not conforming to the platform rules, and reduces invalid operations and time loss. It accurately judges whether the strategy conforms to the rules. When it conforms to the rules, it directly calls the preset information release API to realize automated release, ensuring the efficiency of the release process. When it does not conform to the rules, it uses a preset third AI model combined with the target information release rules and a preset third command (used to instruct the model to adjust the strategy according to the rules) to intelligently adjust the original operation strategy. There is no need for manual modification and optimization, which greatly shortens the strategy adjustment cycle. At the same time, it ensures that the adjusted strategy meets the platform release requirements, realizes the fully automated closed loop, reduces the manual intervention links, and improves the compliance, efficiency and stability of the operation strategy release.

[0072] S204. The product operation device obtains user feedback information on the target product operation strategy on the target information release platform.

[0073] User feedback information may include user click data, dwell time, user comment text information, likes, favorites and forwarding behavior data. Of course, user feedback information may also include other information, and this application does not impose specific restrictions on this.

[0074] As one possible implementation, the product operation device obtains user feedback information on the target product operation strategy by calling the user feedback API provided by the target information publishing platform.

[0075] S205. The product operation device adjusts the target product operation strategy based on user feedback information.

[0076] As one possible implementation, the product operation device inputs user feedback information and a preset fourth AI instruction into a preset fourth AI model to obtain user satisfaction with the target product operation strategy. The preset fourth AI instruction is used to instruct the preset fourth AI model to determine user satisfaction based on user feedback information. When user satisfaction is less than a preset satisfaction threshold, user comment text information, the target product operation strategy, and a preset fifth AI instruction are input into a preset first AI model to obtain an optimized target product operation strategy. The preset fifth AI instruction is used to instruct the preset first AI model to optimize the target product operation strategy based on user comment text information.

[0077] The fourth AI model can be Doubao, Wenxin Yiyan, or Qianwen, etc., and this application does not impose specific restrictions on it.

[0078] As an example, after publishing the target product operation strategy to the target information publishing platform, the product operation device collects user feedback information generated by the platform in real time. The product operation device inputs this user feedback information along with a preset fourth AI instruction into a preset fourth AI model. The preset fourth AI instruction specifically states: "Perform multi-dimensional sentiment analysis and behavioral quantification analysis on the input user feedback information, comprehensively calculate and output the user satisfaction score corresponding to this target product operation strategy." The preset fourth AI model is a pre-trained user satisfaction evaluation model that integrates natural language sentiment recognition and user behavior feature analysis capabilities, outputting a user satisfaction score from 0 to 100 based on the input content.

[0079] Taking a preset satisfaction threshold of 80 points as an example, the preset fourth AI model calculates a user satisfaction score of 72 points, which is lower than the preset threshold. Therefore, the product operation device determines that the current target product operation strategy needs to be optimized. Subsequently, the product operation device inputs the corresponding user comment text information, the currently executed target product operation strategy, and the preset fifth AI instruction into the preset first AI model. The preset fifth AI instruction specifically states: "Based on the problems and needs reflected in the user comment text, without changing the core product operation goals, optimize the content format, promotion methods, interaction rules, and delivery methods of the existing target product operation strategy to generate an optimized operation strategy that better suits user preferences." The preset first AI model adjusts the operation strategy based on the above information, generating the optimized target product operation strategy. The product operation device then re-releases and executes the optimized strategy through the information publishing API.

[0080] Based on this possible implementation, by inputting user feedback information and preset fourth AI instructions into the fourth AI model, the system can automatically and quantitatively assess user satisfaction, replacing manual statistics and subjective judgment, and improving the efficiency and objectivity of feedback analysis. When user satisfaction falls below a preset threshold, the system further combines user comment text information, existing operational strategies, and fifth AI instructions to automatically generate optimized operational strategies using the first AI model. This enables iterative optimization of strategies based on real user needs, eliminating the need for manual feedback analysis and repeated adjustments, effectively shortening the operational strategy optimization cycle. Simultaneously, it forms a closed-loop technical process of "user feedback - intelligent assessment - automatic optimization," significantly improving the timeliness, accuracy, and intelligence of operational adjustments. This allows product operational strategies to quickly adapt to user needs, enhancing overall operational effectiveness and the practicality of the technical solution.

[0081] Based on S201-S205, firstly, a pre-set first AI model automatically generates matching operational strategies based on product operation needs, replacing the complex process of manual research, analysis, and strategy formulation. This avoids the time-consuming nature of subjective judgment and decision-making delays, achieving intelligent and efficient strategy generation. Secondly, by calling the pre-set API interface of the information publishing platform, the operational strategies are automatically published directly, eliminating repetitive operations such as manually logging into the platform, editing content, and uploading in steps. This significantly shortens the time cycle for strategy implementation and improves the standardization and smoothness of the publishing process. Simultaneously, the solution can obtain real-time user feedback from the platform and dynamically adjust strategies accordingly. There is no need for manual collection and organization of feedback data or repeated reviews and optimizations, forming a fully automated closed loop from requirement input, strategy generation, automatic publishing to feedback iteration. This reduces a large amount of manual intervention and time-consuming intermediate steps, resulting in faster operational strategy formulation, more efficient execution, and more timely optimization. Overall, the technical solution effectively improves the overall efficiency and responsiveness of product operations.

[0082] The above primarily describes the solutions provided in this application's embodiments from the perspective of a product operation device executing a product operation method. To achieve the above functions, the product operation device includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0083] This application embodiment can divide the product operating device into functional modules according to the above method example. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. Optionally, the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation. Furthermore, "module" here can refer to an application-specific integrated circuit (ASIC), a circuit, a processor and memory that executes one or more software or firmware programs, integrated logic circuits, and / or other devices that can provide the above functions.

[0084] When using functional module division Figure 3A schematic diagram of a product operation device is shown. (For example...) Figure 3 As shown, the product operation device 30 includes an acquisition module 301 and a processing module 302.

[0085] In some embodiments, the product operating device 30 may further include a storage module ( Figure 3 (not shown in the image) is used to store program instructions and data.

[0086] The module 301 is used to acquire product operation requirement information of the target product; the processing module 302 is used to determine the target product operation strategy of the target product based on the product operation requirement information and a preset first AI model; the preset first AI model is used to determine the target product operation strategy of the target product; the processing module 302 is also used to call the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; the processing module 302 is also used to acquire user feedback information on the target product operation strategy on the target information publishing platform; the processing module 302 is also used to adjust the target product operation strategy based on the user feedback information.

[0087] Optionally, the processing module 302 is used to determine the target product operation strategy for the target product based on product operation requirement information and a preset AI model, including: calling a preset second AI model; the preset second AI model is used to decompose product operation requirements into multiple sub-operation tasks; inputting product operation requirement information and a preset first command into the preset second AI model to obtain multiple sub-operation tasks of the AI ​​model; the preset first command is used to instruct the preset second AI model to decompose product operation requirements into multiple sub-operation tasks; for each sub-operation task, inputting the sub-operation task and the corresponding preset second command into the preset first AI model to obtain the target product operation strategy for the target product; the target product operation strategy includes the sub-operation strategy for each sub-operation task.

[0088] Optionally, the processing module 302 is further configured to call the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform, including: obtaining the target information publishing rules of the target information publishing platform; determining whether the target product operation strategy conforms to the target information publishing rules; when the target product operation strategy conforms to the target information publishing rules, calling the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; when the target product operation strategy does not conform to the target information publishing rules, inputting the target product operation strategy, the target information publishing rules, and the preset third command into the preset third AI model to obtain the adjusted target product operation strategy, calling the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; the preset third command is used to instruct the preset third AI model to adjust the target product operation strategy according to the target information publishing rules so that the adjusted target product operation strategy conforms to the target information publishing rules.

[0089] Optionally, the user feedback information includes user comment text information. The processing module 302 is also used to adjust the target product operation strategy based on the user feedback information, including: inputting the user feedback information and a preset fourth AI instruction into a preset fourth AI model to obtain the user satisfaction of the target product operation strategy; the preset fourth AI instruction is used to instruct the preset fourth AI model to determine the user satisfaction based on the user feedback information; when the user satisfaction is less than a preset satisfaction threshold, inputting the user comment text information, the target product operation strategy, and a preset fifth AI instruction into a preset first AI model to obtain an optimized target product operation strategy; the preset fifth AI instruction is used to instruct the preset first AI model to optimize the target product operation strategy based on the user comment text information.

[0090] All relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0091] When the functions of the above modules are implemented in hardware... Figure 4 A schematic diagram of another product operation device is shown. For example... Figure 4 As shown, the product operating device 40 includes a processor 401, a memory 402, and a bus 403. The processor 401 and the memory 402 can be connected via the bus 403.

[0092] Processor 401 is the control center of product operating device 40. It can be a single processor or a collective term for multiple processing elements. For example, processor 401 can be a general-purpose central processing unit (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.

[0093] As one embodiment, processor 401 may include one or more CPUs, for example Figure 4 CPU 0 and CPU 1 are shown in the diagram.

[0094] The memory 402 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0095] As one possible implementation, the memory 402 can exist independently of the processor 401. The memory 402 can be connected to the processor 401 via a bus 403 and is used to store instructions or program code. When the processor 401 calls and executes the instructions or program code stored in the memory 402, it can implement the product operation method provided in the embodiments of this application.

[0096] In another possible implementation, the memory 402 can also be integrated with the processor 401.

[0097] Bus 403 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0098] It should be pointed out that, Figure 4 The structure shown does not constitute a limitation on the product operating device 40. Except... Figure 4 In addition to the components shown, the product operating device 40 may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0099] As an example, combined Figure 3 The functions implemented by the acquisition module 301 and the processing module 302 in the product operation device 30 are the same as those of the product operation device 30. Figure 4 The processor 401 in it has the same function.

[0100] Optional, such as Figure 4 As shown, the product operation device 40 provided in this application embodiment may also include a communication interface 404.

[0101] Communication interface 404 is used to connect with other devices via a communication network. This communication network can be Ethernet, a wireless access network, a wireless local area network (WLAN), etc. Communication interface 404 may include a receiving unit for receiving data and a transmitting unit for transmitting data.

[0102] In one possible implementation, the communication interface 404 in the product operation device 40 provided in this application embodiment can also be integrated into the processor 401, and this application embodiment does not specifically limit this.

[0103] As a possible product form, the product operating device of this application embodiment can also be implemented using the following: one or more field programmable gate arrays (FPGAs), programmable logic devices (PLDs), controllers, state machines, gate logic, discrete hardware components, any other suitable circuits, or any combination of circuits capable of performing the various functions described throughout this application.

[0104] Through the above description of the embodiments, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional units is used as an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the device can be divided into different functional units to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0105] This application also provides a computer-readable storage medium storing a computer program or instructions thereon, which, when executed, causes a computer to perform the various steps in the method flow shown in the above method embodiments.

[0106] Embodiments of this application provide a computer program product containing instructions that, when executed on a computer, cause the computer to perform the various steps in the method flow shown in the above-described method embodiments.

[0107] This application provides a chip system, including: a processor and an interface circuit; the interface circuit is used to receive computer programs or instructions and transmit them to the processor; the processor is used to execute the computer programs or instructions so that the chip system performs each step in the method flow shown in the above method embodiments.

[0108] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), registers, hard disks, optical fibers, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing, or any other form of computer-readable storage medium in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may reside in a purpose-specific ASIC. In the embodiments of this application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0109] Since the product operation device, computer-readable storage medium, and computer program product provided in this embodiment can be applied to the product operation method provided in this embodiment, the technical effects that can be obtained can also be referred to the above method embodiments. The embodiments of this application will not be repeated here.

[0110] Although this application has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings and the disclosure in carrying out the claimed application.

[0111] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely illustrative examples of this application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from the spirit and scope of this application. Thus, if such modifications and modifications of this application fall within the scope of equivalent technology of this application, this application also intends to include such modifications and modifications.

Claims

1. A product operation method, characterized in that the method include: Obtain information on the product operation requirements of the target product; Determine the target product operation strategy based on product operation needs information and the preset first AI model; A first AI model is preset to determine the target product operation strategy for the target product. Call the target information publishing platform's preset information publishing API to publish the target product operation strategy to the target information publishing platform; Obtain user feedback information on the target product's operational strategy on the target information publishing platform; Adjust the operational strategy for the target product based on user feedback.

2. The method according to claim 1, characterized in that, Based on product operation needs information and pre-set AI models, determine the target product operation strategy, including: Call the preset second AI model; the preset second AI model is used to decompose product operation requirements into multiple sub-operation tasks; Input the product operation requirements information and the preset first command into the preset second AI model to obtain multiple sub-operation tasks of the AI ​​model; the preset first command is used to instruct the preset second AI model to decompose the product operation requirements into multiple sub-operation tasks; For each of the multiple sub-operation tasks, the sub-operation task and its corresponding preset second command are input into the preset first AI model to obtain the target product operation strategy; the target product operation strategy includes the sub-operation strategy of each sub-operation task.

3. The method according to claim 1, characterized in that, Calling the target information publishing platform's preset information publishing API to publish the target product operation strategy to the target information publishing platform includes: Obtain the target information publishing rules of the target information publishing platform; Determine whether the target product's operational strategy complies with the target information release rules; When the target product operation strategy conforms to the target information release rules, the preset information release API of the target information release platform is called to release the target product operation strategy to the target information release platform; When the target product operation strategy does not conform to the target information release rules, the target product operation strategy, the target information release rules, and the preset third command are input into the preset third AI model to obtain the adjusted target product operation strategy. The preset information release API of the target information release platform is then called to release the target product operation strategy to the target information release platform. The preset third command is used to instruct the preset third AI model to adjust the target product operation strategy according to the target information release rules so that the adjusted target product operation strategy conforms to the target information release rules.

4. The method according to any one of claims 1-3, characterized in that, User feedback information includes user comment text information. Adjusting the target product operation strategy based on user feedback includes: Input user feedback information and preset fourth AI instructions into the preset fourth AI model to obtain the user satisfaction of the target product operation strategy; the preset fourth AI instructions are used to instruct the preset fourth AI model to determine user satisfaction based on user feedback information. When user satisfaction is less than a preset satisfaction threshold, the user comment text information, the target product operation strategy, and the preset fifth AI instruction are input into the preset first AI model to obtain an optimized target product operation strategy; the preset fifth AI instruction is used to instruct the preset first AI model to optimize the target product operation strategy based on the user comment text information.

5. A product operating device, characterized in that, The device includes: Acquisition module and processing module; The acquisition module is used to acquire product operation requirements information for the target product. The processing module is used to determine the target product operation strategy for the target product based on product operation requirements information and a preset first AI model; the preset first AI model is used to determine the target product operation strategy for the target product. The processing module is also used to call the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform; The processing module is also used to obtain user feedback information on the target product operation strategy on the target information publishing platform; The processing module is also used to adjust the target product operation strategy based on user feedback.

6. The apparatus according to claim 5, characterized in that, The processing module is used to determine the target product operation strategy based on product operation needs information and a preset AI model, including: Call the preset second AI model; the preset second AI model is used to decompose product operation requirements into multiple sub-operation tasks; Input the product operation requirements information and the preset first command into the preset second AI model to obtain multiple sub-operation tasks of the AI ​​model; the preset first command is used to instruct the preset second AI model to decompose the product operation requirements into multiple sub-operation tasks; For each of the multiple sub-operation tasks, the sub-operation task and its corresponding preset second command are input into the preset first AI model to obtain the target product operation strategy; the target product operation strategy includes the sub-operation strategy of each sub-operation task.

7. The apparatus according to claim 5, characterized in that, The processing module is also used to call the preset information publishing API of the target information publishing platform to publish the target product operation strategy to the target information publishing platform, including: Obtain the target information publishing rules of the target information publishing platform; Determine whether the target product's operational strategy complies with the target information release rules; When the target product operation strategy conforms to the target information release rules, the preset information release API of the target information release platform is called to release the target product operation strategy to the target information release platform; When the target product operation strategy does not conform to the target information release rules, the target product operation strategy, the target information release rules, and the preset third command are input into the preset third AI model to obtain the adjusted target product operation strategy. The preset information release API of the target information release platform is then called to release the target product operation strategy to the target information release platform. The preset third command is used to instruct the preset third AI model to adjust the target product operation strategy according to the target information release rules so that the adjusted target product operation strategy conforms to the target information release rules.

8. The apparatus according to any one of claims 5-7, characterized in that, User feedback information includes user comment text information. The processing module is also used to adjust the target product operation strategy based on user feedback information, including: Input user feedback information and preset fourth AI instructions into the preset fourth AI model to obtain the user satisfaction of the target product operation strategy; the preset fourth AI instructions are used to instruct the preset fourth AI model to determine user satisfaction based on user feedback information. When user satisfaction is less than a preset satisfaction threshold, the user comment text information, the target product operation strategy, and the preset fifth AI instruction are input into the preset first AI model to obtain an optimized target product operation strategy; the preset fifth AI instruction is used to instruct the preset first AI model to optimize the target product operation strategy based on the user comment text information.

9. A product operating device, characterized in that, The product operating device includes: a processor coupled to a memory for storing programs or instructions, which, when executed by the processor, cause the device to perform the method as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed, they cause the computer to perform the method as described in any one of claims 1 to 4.

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