Advertisement putting monitoring management system based on data acquisition

Abstract

The invention discloses an advertisement putting monitoring management system based on data acquisition, and relates to the technical field of monitoring management, and the system comprises the following steps: collecting and processing advertisement putting data, and obtaining the advertisement putting data; performing advertisement effect evaluation according to the advertisement putting data to obtain an advertisement effect evaluation result; performing budget allocation adjustment according to the advertisement effect evaluation result to obtain adjusted budget configuration; performing advertisement putting time period optimization according to the adjusted budget configuration to obtain a time period optimization result; and performing advertisement exposure frequency optimization according to the time period optimization result to obtain an advertisement exposure frequency optimization result. According to the method, the utilization rate of advertisement putting budget resources is improved, budget allocation can be adjusted in real time along with the change of the advertisement market, the real-time performance of budget allocation is improved, the advertisement effect of each channel can be accurately reflected, and the accuracy of budget allocation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring and management, and in particular to an advertising delivery monitoring and management system based on data collection. Background Art

[0002] As a key tool in modern marketing, advertising has gradually evolved into a process that relies heavily on data analysis and real-time monitoring. With the diversification of advertising platforms and channels, comprehensive monitoring and real-time adjustments to advertising effectiveness are necessary to improve both advertising effectiveness and budget efficiency.

[0003] In the existing technology, there are deficiencies in the allocation and adjustment of advertising budgets: existing budget allocation methods often rely on historical data and have a low adjustment frequency, making it difficult to dynamically adjust the budget based on real-time effects, resulting in waste of budget resources or failure to maximize advertising effects. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides an advertisement placement monitoring and management system based on data collection to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, an embodiment of the present invention provides an advertising delivery monitoring and management system based on data collection, comprising the following steps: S1. Collect and process advertising data to obtain advertising data; S2. Evaluate the advertising effect based on the advertising data to obtain an advertising effect evaluation result; S3. Adjust the budget allocation based on the advertising effectiveness evaluation results to obtain the adjusted budget configuration; S4. Optimize the advertising delivery time period based on the adjusted budget configuration to obtain the time period optimization result; S5. Optimize the advertising exposure frequency according to the time period optimization result to obtain the advertising exposure frequency optimization result.

[0006] To further optimize this technical solution, the budget allocation adjustment in S3 includes: Based on the advertising effectiveness evaluation results, the budget adjustment model is used to adjust the budget allocation of each advertising channel. While ensuring the overall budget constraints, the input-output ratio is maximized and the adjusted budget configuration is obtained.

[0007] To further optimize this technical solution, the budget adjustment model includes: ; in: : The budget amount allocated to the i-th advertising channel; : The total budget amount of all advertising channels; : Contribution score of the i-th advertising channel; : Contribution score of the jth advertising channel; : sensitivity coefficient of the i-th advertising channel; : sensitivity coefficient of the jth advertising channel; : The total number of advertising channels.

[0008] To further optimize this technical solution, the advertising channel contribution score includes: ; ; in: : The weight coefficient of the conversion rate of the advertising channel; : Weight coefficient of the total advertising revenue of the advertising channel; : Conversion rate of the i-th advertising channel; : The number of conversions of the i-th advertising channel; : The number of clicks on the i-th advertising channel; : The total advertising revenue of the i-th advertising channel; : The largest advertising revenue among all advertising channels; The contribution score of the advertising channel is calculated by combining the conversion rate and advertising revenue indicators of the advertising channel.

[0009] To further optimize this technical solution, the advertising channel sensitivity coefficient includes: In practical applications, it is difficult to obtain continuously changing data, so finite difference approximation is used instead of partial derivative calculation; ; ; in: : partial derivative of the key performance indicator; : The partial derivative of the contribution score of the i-th advertising channel; : The contribution score of the i-th advertising channel is The size of the key performance indicators at the time; : The contribution score of the i-th advertising channel is The size of the key performance indicators at the time; : Change in advertising channel contribution score; Calculate the impact of the advertising channel on the overall advertising goal, i.e., the key performance indicator, based on the performance changes of the advertising channel.

[0010] To further optimize this technical solution, the key performance indicators include: ; in: : Key performance indicators of the advertising channel; : The weight coefficient of the conversion quantity of the i-th advertising channel; : The weight coefficient of the total advertising revenue of the i-th advertising channel; The overall effectiveness of advertising on an advertising channel is measured based on the number of conversions and total advertising revenue of the advertising channel, that is, the key performance indicators of the advertising channel are calculated.

[0011] To further optimize this technical solution, the optimization of the advertising delivery time period in S4 includes: According to the adjusted budget configuration, use the time period optimization model to measure the delivery effect of each time period, and optimize the time period based on the delivery effect of each time period. Allocate different budgets to each time period to obtain the time period optimization results.

[0012] To further optimize this technical solution, the time period optimization model includes: ; in: : The budget amount allocated to advertising channel i in time period t; : The effectiveness of the advertising channel in time period t; : The sum of the effectiveness of the advertising channel in all time periods; : The total delivery time of this advertising channel; Allocate budget amounts based on the effectiveness of advertising channels in each time period.

[0013] Further optimizing this technical solution, the time period performance includes: ; in: : Contribution score of the i-th advertising channel at time period t; : Sensitivity coefficient of the i-th advertising channel at time period t; : The conversion rate of the i-th advertising channel at time period t; : The highest conversion rate in all time periods; Calculate the effectiveness of each time period under the advertising channel based on the contribution score, sensitivity coefficient and conversion rate of each time period of the advertising channel.

[0014] Further optimize this technical solution, including the following functional modules: Data collection and evaluation module, budget adjustment module, time period optimization module, and frequency management module.

[0015] In a second aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of an advertising delivery monitoring and management system based on data collection as described in the first aspect of the present invention are implemented.

[0016] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of an advertising delivery monitoring and management system based on data collection as described in the first aspect of the present invention are implemented.

[0017] Compared with the existing technology, the present invention provides an advertising placement monitoring and management system based on data collection, which has the following beneficial effects: This advertising monitoring and management system based on data collection introduces a sensitivity coefficient and contribution score through a budget adjustment model, making the budget more inclined to channels that have a real and significant driving effect on the overall key performance indicators, improving the utilization rate of advertising budget resources, and being able to adjust budget allocation in real time as the advertising market changes, thereby improving the real-time nature of budget allocation, and being able to accurately reflect the advertising effect of each channel, thereby improving the accuracy of budget allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1This is a flow chart of an advertising placement monitoring and management system based on data collection proposed by the present invention; Figure 2 This is a flow chart of a budget adjustment model for an advertising placement monitoring and management system based on data collection proposed by the present invention; Figure 3 This is a flow chart of a time period optimization model for an advertisement placement monitoring and management system based on data collection proposed by the present invention; Figure 4 This is a flow chart of a frequency adjustment model of an advertisement placement monitoring and management system based on data collection proposed by the present invention; Figure 5 This is a module diagram of an advertising placement monitoring and management system based on data collection proposed by the present invention. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1: Reference Figures 1 to 4 , which is the first embodiment of the present invention, provides an advertising delivery monitoring and management system based on data collection, including the following steps: S1. Collect and process advertising delivery data to obtain advertising delivery data.

[0024] In this embodiment, the advertisement delivery data collection and processing includes: Modern advertising often involves multiple platforms or channels, such as social media, search engines, video platforms, and display ad networks. Advertising performance across these channels can vary significantly. Therefore, to fully understand the effectiveness of each advertising channel, effective data collection methods are essential. This comprehensive and accurate data collection provides a reliable basis for subsequent steps like evaluating advertising effectiveness, adjusting budgets, and optimizing time periods.

[0025] The main purpose of this step is to collect advertising data from multiple channels and integrate it into a central platform or database. This ensures that subsequent analysis can be unified and processed, helps understand the effectiveness of advertising, and facilitates timely adjustments to advertising strategies. It also ensures the accuracy, completeness, and timeliness of data collection, avoids data omissions or errors, and ensures the reliability of subsequent analysis. This achieves the goals of data integration, comprehensive monitoring, and data quality assurance, ensuring that advertising effectiveness across all channels can be accurately recorded and monitored, providing comprehensive data support for subsequent advertising effectiveness analysis, budget allocation, and advertising optimization, so that accurate decisions can be made. Through data collection, comprehensive advertising effectiveness data can be obtained to support various subsequent optimizations. It can help identify differences in advertising effectiveness across different channels, allowing for targeted adjustments to advertising strategies. This can improve data-driven decision-making capabilities and achieve data-driven decisions, which are more scientific and accurate than traditional experience-based decisions. It can maximize the efficiency of advertising budget utilization, track advertising effectiveness in real time, and make every aspect of advertising delivery transparent, optimizing the transparency of advertising delivery and ensuring that the delivery results meet the expected goals.

[0026] The specific method of data collection needs to be customized according to the different advertising channels and platforms. Common methods include: API interface integration: For most advertising platforms (such as Google Ads, Facebook Ads, Instagram, Twitter, etc.), open API interfaces are provided. By integrating with the API interfaces of these platforms, you can obtain real-time advertising data, including impressions, clicks, conversions, user behavior, advertising spending, etc. This data will be directly imported into the data platform for unified processing and analysis.

[0027] Technical tools: For example, using the Google Ads API or Facebook Marketing API to connect to advertising platforms. These tools can automate data collection and real-time monitoring to ensure timely acquisition of advertising data.

[0028] Third-party data platforms: Integrate data from different platforms through third-party tools. For example, using Google Analytics, Adobe Analytics, or other cross-platform data management platforms can uniformly collect advertising data from various platforms for aggregation and further analysis. These tools can automatically integrate data from various advertising channels, reduce manual intervention, and improve the efficiency and accuracy of data collection.

[0029] Data format and storage: The collected advertising data is stored in a data warehouse (such as Amazon Redshift or Google BigQuery) for management, ensuring centralized data storage and facilitating subsequent data analysis.

[0030] S2. Evaluate the advertising effect based on the advertising delivery data to obtain the advertising effect evaluation result.

[0031] In this embodiment, the advertising effect evaluation includes: During the advertising process, multiple channels are typically selected for ad display (e.g., Google Ads, Facebook, Instagram, YouTube, Twitter, etc.). The effectiveness of each advertising channel may be affected by various factors, including user behavior, ad format, content, and audience differences across platforms. Relying solely on intuitive perception or single ad performance data cannot accurately assess the effectiveness of each channel. Therefore, a comprehensive performance evaluation of the advertising data collected in step S1 is required to deeply analyze the specific performance of each channel.

[0032] The purpose of this step is to analyze and evaluate the advertising data collected from various advertising channels, quantify the advertising effects, and obtain specific performance indicators for each channel. Through specific quantitative indicators, we can understand the actual performance of each advertising channel, identify effective channels, provide a basis for budget allocation, identify channels with the best advertising effects, higher conversion rates or lower costs, concentrate more budgets on efficient channels, improve the overall effect of advertising, improve delivery efficiency, improve the accuracy of delivery decisions, dynamically optimize and adjust the budget, ensure the efficiency of budget allocation, achieve long-term optimization and adjustment, discover and improve problems, and reduce resource waste.

[0033] The process of advertising effectiveness evaluation involves data analysis, indicator calculation, and comparative evaluation. The specific steps include: Select evaluation indicators: First, you need to clarify which indicators can effectively measure advertising effectiveness. Common advertising effectiveness evaluation indicators include impressions (the number of times an ad is displayed, usually used to measure the coverage of an ad), clicks (the number of times a user clicks on an ad, a measure of the attractiveness of an ad), click-through rate (the ratio of clicks to impressions, usually used to measure the attractiveness and relevance of an ad), conversion rate (the proportion of users who complete a predetermined action, such as a purchase or registration, a measure of whether the ad can bring actual business value), average cost per click (CPC) (reflects the cost-effectiveness of advertising), average cost per conversion (CPA) (measures the cost of the actual value brought by the ad), and the ratio of advertising investment to advertising revenue (ROAS) (used to measure the return on investment of advertising).

[0034] Benchmarking and horizontal analysis: By comparing the performance of different advertising channels over the same time period, you can evaluate the performance of each channel. For example, you can compare the click-through rate, conversion rate, and other metrics of Google Ads and Facebook Ads under the same budget to identify which channel performs better.

[0035] A / B testing: To verify ad effectiveness, you can conduct A / B testing. This involves delivering different ad versions (e.g., different copy, images, or videos) to the same audience under the same delivery conditions to evaluate which ad version delivers the best results. A / B testing can help identify the most engaging ad content and optimize delivery strategies.

[0036] Time period and audience analysis: Performance evaluation also requires considering the time period during which the ad is run and the characteristics of the target audience. For example, an ad may perform better during specific times (such as holidays or weekends), while another ad may be more effective on weekdays. By segmenting the time period and audience groups, a more detailed performance evaluation can be obtained.

[0037] S3. Adjust the budget allocation based on the advertising effectiveness evaluation results to obtain the adjusted budget configuration.

[0038] In this embodiment, the budget allocation adjustment includes: After completing the effectiveness evaluation of each advertising channel, knowing only the performance of each channel is not enough to improve the overall effectiveness of advertising. In order to maximize the return on advertising, it is necessary to dynamically adjust budget allocation based on the actual performance of each channel.

[0039] This step uses the performance data of the advertising channels and the budget adjustment model based on the advertising effectiveness evaluation results to adjust the budget allocation of each advertising channel, so that the budget is preferentially tilted to the advertising channels with better overall performance, and while ensuring the overall budget constraints, the input-output ratio is maximized to obtain the adjusted budget configuration.

[0040] Furthermore, the budget adjustment model includes: ; in: : The budget amount allocated to the i-th advertising channel; : The total budget amount of all advertising channels; : The contribution score of the i-th advertising channel, reflecting the performance of the advertising channel; : The contribution score of the jth advertising channel, reflecting the performance of the advertising channel; : The sensitivity coefficient of the i-th advertising channel, which reflects the impact of changes in the advertising channel effect on the overall advertising goal; : The sensitivity coefficient of the jth advertising channel, which reflects the impact of changes in the advertising channel effect on the overall advertising goal; : The total number of advertising channels.

[0041] Furthermore, the advertising channel contribution score includes: ; ; in: : The weight coefficient of the conversion rate of the advertising channel; : Weight coefficient of the total advertising revenue of the advertising channel; : The conversion rate of the i-th advertising channel, that is, the proportion of users who complete the intended action, such as purchase, registration, etc., to measure whether the advertising can bring actual business value; : The number of conversions for the i-th advertising channel, that is, the number of users who complete the intended action after clicking the ad, such as purchases, registrations, etc., which measures the actual value generated by the ad; : The number of clicks on the i-th advertising channel, that is, the number of times users click on the advertisement, which measures the attractiveness of the advertisement; : The total advertising revenue of the i-th advertising channel, used to measure the actual value brought by advertising; : The largest advertising revenue among all advertising channels; The contribution score of the advertising channel is calculated by combining the conversion rate and advertising revenue indicators of the advertising channel.

[0042] Furthermore, the advertising channel sensitivity coefficient includes: In practical applications, it is difficult to obtain continuously changing data, so finite difference approximation is used instead of partial derivative calculation; ; ; in: : The partial derivative of the key performance indicator, which reflects the change in the key performance indicator after a small change in the advertising channel contribution score; : The partial derivative of the contribution score of the i-th advertising channel, reflecting the change in the contribution score of the advertising channel; : The contribution score of the i-th advertising channel is The size of the key performance indicators at the time; : The contribution score of the i-th advertising channel is The size of the key performance indicators at the time; : Change in advertising channel contribution score; Calculate the impact of the advertising channel on the overall advertising goal, i.e., the key performance indicator, based on the performance changes of the advertising channel.

[0043] Furthermore, the key performance indicators include: ; in: : The key performance indicator of the advertising channel, used as a standard to measure the overall effectiveness of advertising; : The weight coefficient of the conversion number of the i-th advertising channel, which is used to balance the importance of the conversion number and the total advertising revenue. The sum of the two weight coefficients is 1; : The weight coefficient of the total advertising revenue of the i-th advertising channel, which is used to balance the importance of the number of conversions and the total advertising revenue. The sum of the two weight coefficients is 1; The overall effectiveness of advertising on an advertising channel is measured based on the number of conversions and total advertising revenue of the advertising channel, that is, the key performance indicators of the advertising channel are calculated.

[0044] This model describes how to adjust the budget allocation of each advertising channel based on the performance of the advertising channel in the advertising effectiveness evaluation results.

[0045] Traditional budget allocation adjustment methods usually use average allocation or static allocation methods based on click-through rate (CTR) or conversion rate (CVR). These methods often fail to respond to market changes in real time, nor can they fully leverage the potential of high-performing channels, resulting in low utilization of advertising resources. This model introduces sensitivity coefficients and contribution scores, making the budget more inclined to channels that have a significant actual impact on overall key performance indicators, thereby improving the utilization of advertising budget resources. This model also supports real-time adjustment of budget allocation as the advertising market changes, improving real-time and adaptability, and accurately reflecting the advertising effect of each channel, thereby improving the accuracy of budget allocation.

[0046] The steps for using this model include: Data acquisition: Get the advertising channel's delivery data and effect evaluation results from steps S1 and S2, and get the total budget allocated to the advertising channel , conversion rate , total advertising revenue , number of conversions and click count and other parameters; Parameter calculation: Calculate the contribution score of the advertising channel based on the obtained data , Sensitivity coefficient of advertising channels and key performance indicator parameters ; Budget adjustment: Adjust the budget amount allocated to each advertising channel based on the calculated parameters , thereby improving the utilization rate of advertising budget resources and improving the overall delivery effect.

[0047] S4. Optimize the advertising delivery time period according to the adjusted budget configuration to obtain the time period optimization result.

[0048] In this embodiment, the optimization of the advertising delivery time period includes: The purpose of optimizing advertising time periods is to maximize the effectiveness of advertising in different time periods by adjusting the time of advertising delivery, thereby improving the advertising return on investment, avoiding wasting advertising budgets in inefficient time periods, reducing delivery in inefficient time periods, and concentrating resources on efficient time periods.

[0049] This step uses the time period optimization model based on the adjusted budget configuration to measure the delivery effect of each time period, and optimizes the time period based on the delivery effect of each time period, allocating different budgets to each time period, so that the budget of the time period with high delivery effect is increased, and the budget of the time period with low delivery effect is reduced, so as to improve the overall return of advertising and reduce ineffective delivery.

[0050] Furthermore, the time period optimization model includes: ; in: : The budget amount allocated to advertising channel i in time period t; : The effectiveness of the advertising channel in time period t; : The sum of the effectiveness of the advertising channel in all time periods; : The total delivery time of this advertising channel; The budget amount is allocated based on the effectiveness of the advertising channel in each time period, so that the budget for the time period with high delivery effect is increased and the budget for the time period with low delivery effect is reduced, thereby improving the overall return of the advertising.

[0051] Furthermore, the time period performance includes: ; in: : The contribution score of the i-th advertising channel at time period t, reflecting the performance of the advertising channel during this period; : The sensitivity coefficient of the i-th advertising channel at time period t, reflecting the impact of the change in the advertising channel effect during this period on the overall advertising goal; : The conversion rate of the i-th advertising channel at time period t, that is, the proportion of users who complete the intended action, such as purchase, registration, etc., to measure whether the advertising can bring actual business value; : The highest conversion rate in all time periods; Calculate the effectiveness of each time period under the advertising channel based on the contribution score, sensitivity coefficient and conversion rate of each time period of the advertising channel.

[0052] This model describes how to calculate the effectiveness of each time period under the advertising channel based on the contribution score, sensitivity coefficient and conversion rate of each time period of the advertising channel, so as to allocate the budget amount for each time period to improve the overall return of advertising.

[0053] Traditional methods for optimizing ad time periods often rely on simple time period segmentation based on historical data (such as the daily morning rush hour and lunch break), or rely on fixed strategies to allocate budgets to time periods. These methods generally fail to deeply analyze the performance differences of advertising channels across time periods, lacking adaptability and effectively allocating budgets to high-performing time periods. This reduces overall advertising returns and increases the proportion of ineffective advertising. This model, however, considers the performance differences of advertising channels across time periods and can flexibly allocate budget amounts based on the performance of each channel within each time period. This increases budgets for high-performance time periods and reduces them for low-performance time periods, thereby improving overall advertising returns and reducing ineffective advertising. This improves the model's adaptability and flexibility.

[0054] The steps for using the above model include: Data acquisition: Confirm the time periods for advertising channel ads, such as different hours of the day or different days of the week, and ensure that these time periods cover all possible delivery periods. Obtain the conversion rate of each time period of the advertising channel from step S2. , and calculate the contribution score of each time period through the model in step S3 , sensitivity coefficient and the budget amount allocated to that advertising channel ; Time period parameter calculation: Calculate the effectiveness of each time period of the advertising channel based on the acquired data The sum of the effectiveness ; Time period optimization: Calculate the budget allocation amount for each time period based on the performance of each time period , allocate different budgets to each time period, increase the budget of the time period with high delivery effect, and reduce the budget of the time period with low delivery effect, so as to improve the overall return of advertising, reduce ineffective delivery, and thus achieve optimization effect.

[0055] S5. Optimize the advertising exposure frequency according to the time period optimization result to obtain the advertising exposure frequency optimization result.

[0056] In this embodiment, the advertisement exposure frequency optimization includes: The goal of ad frequency management is to ensure that ads are displayed at the appropriate frequency across different time periods and channels, thereby maximizing advertising effectiveness and minimizing budget waste. By properly controlling frequency, we avoid overexposure or underexposure, optimizing the user experience and increasing conversion rates.

[0057] Based on the obtained time period optimization results, the frequency adjustment model is used to calculate the optimal advertising frequency for each time period through the size of the time period effectiveness and the conversion rate of each time period, thereby achieving accurate advertising delivery.

[0058] Furthermore, the frequency adjustment model includes: ; in: : The advertising frequency of the advertising channel in time period t; : The maximum ad frequency cap is determined through a comprehensive assessment of factors such as the advertiser's budget constraints and ad effectiveness. It avoids interference with users caused by excessive ad frequency while controlling budget efficiency.

[0059] This model describes how to calculate the optimal advertising frequency for each time period based on the obtained time period optimization results and the conversion rate of each time period.

[0060] In traditional advertising frequency management methods, commonly used frequency control methods include fixed exposure frequency or simple adjustments based on historical data. These methods cannot reflect the delivery effects of different channels and time periods in real time, easily resulting in waste of resources and low flexibility. This model combines the time period efficiency coefficient and conversion rate to make frequency control more refined and dynamic, improve control accuracy, and can adjust frequency in real time with greater flexibility, thereby ensuring that advertisements are properly displayed in the most effective time periods and channels, thereby improving the return on investment of advertising.

[0061] The steps for using the model include: Data acquisition: Get the time period performance from step S4 , get the conversion rate of each time period of the advertising channel from step S2 ; Advertising frequency calculation: based on the energy efficiency of the obtained time period and the conversion rate of advertising channels in each time period , calculate the optimal advertising frequency for each time period, and obtain the optimal advertising frequency for each time period ; Ad frequency adjustment: Based on the calculated optimal ad frequency for each time period Optimize the frequency of ad exposure to ensure that ads are properly displayed in the most effective time periods and channels, thereby improving the return on investment of advertising.

[0062] Example 2: Reference Figure 5, which is the second embodiment of the present invention, provides an advertising delivery monitoring and management system based on data collection, including the following functional modules: Data Collection and Evaluation Module: This module collects advertising data from various advertising platforms (such as social media, search engines, and video platforms), including impressions, clicks, conversion rates, and budget consumption for each advertising channel. It then analyzes the collected advertising data and calculates evaluation indicators for each advertising channel, thereby assessing the effectiveness of each advertising channel. Budget adjustment module: Calculates the advertising budget for each channel based on the effectiveness evaluation results of each advertising channel, dynamically adjusts and allocates the budget for each advertising channel, and optimizes the budget usage for advertising delivery; Time period optimization module: optimizes the time period for advertising delivery to ensure that ads are displayed during the most effective time period, increases delivery during efficient time periods, and reduces delivery during inefficient time periods, thereby improving the click-through rate and conversion rate of ads; Frequency management module: Dynamically adjust the frequency of advertising delivery based on the effectiveness and conversion rate of each time period. By adjusting the advertising frequency in real time, it avoids overexposure or underexposure of advertisements and optimizes the user experience of advertisements.

[0063] Example 3: This embodiment also provides a computer device, which is suitable for an advertising delivery monitoring and management system based on data collection, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement an advertising delivery monitoring and management system based on data collection as proposed in the above embodiment.

[0064] This embodiment further provides a storage medium storing a computer program, which, when executed by a processor, implements an advertisement delivery monitoring and management system based on data collection as proposed in the above embodiment.

[0065] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0066] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0067] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0068] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0069] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0070] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An advertising placement monitoring and management system based on data collection, characterized in that: The following steps are involved: S1. Collect and process advertising data to obtain advertising data; S2. Evaluate the advertising effect based on the advertising data to obtain an advertising effect evaluation result; S3. Adjust the budget allocation based on the advertising effectiveness evaluation results to obtain the adjusted budget configuration; S4. Optimize the advertising delivery time period based on the adjusted budget configuration to obtain the time period optimization result; S5. Optimize the advertising exposure frequency according to the time period optimization result to obtain the advertising exposure frequency optimization result.

2. The advertising placement monitoring and management system based on data collection according to claim 1, characterized in that: The budget allocation adjustment in S3 includes: Based on the advertising effectiveness evaluation results, the budget adjustment model is used to adjust the budget allocation of each advertising channel. While ensuring the overall budget constraints, the input-output ratio is maximized and the adjusted budget configuration is obtained.

3. The advertising placement monitoring and management system based on data collection according to claim 2, characterized in that: The budget adjustment model includes: ； in: : The budget amount allocated to the i-th advertising channel; : The total budget amount of all advertising channels; : Contribution score of the i-th advertising channel; : Contribution score of the jth advertising channel; : sensitivity coefficient of the i-th advertising channel; : sensitivity coefficient of the jth advertising channel; : The total number of advertising channels.

4. The advertising placement monitoring and management system based on data collection according to claim 3 is characterized in that: The advertising channel contribution score includes: ； ； in: : The weight coefficient of the conversion rate of the advertising channel; : Weight coefficient of the total advertising revenue of the advertising channel; : Conversion rate of the i-th advertising channel; : The number of conversions of the i-th advertising channel; : The number of clicks on the i-th advertising channel; : The total advertising revenue of the i-th advertising channel; : The largest advertising revenue among all advertising channels; The contribution score of the advertising channel is calculated by combining the conversion rate and advertising revenue indicators of the advertising channel.

5. The advertising placement monitoring and management system based on data collection according to claim 3 is characterized in that: The advertising channel sensitivity coefficients include: In practical applications, it is difficult to obtain continuously changing data, so finite difference approximation is used instead of partial derivative calculation; ； ； in: : partial derivative of the key performance indicator; : The partial derivative of the contribution score of the i-th advertising channel; : The contribution score of the i-th advertising channel is The size of the key performance indicators at the time; : The contribution score of the i-th advertising channel is The size of the key performance indicators at the time; : Change in advertising channel contribution score; Calculate the impact of the advertising channel on the overall advertising goal, i.e., the key performance indicator, based on the performance changes of the advertising channel.

6. The advertising placement monitoring and management system based on data collection according to claim 5, characterized in that: The key performance indicators include: ； in: : Key performance indicators of the advertising channel; : The weight coefficient of the conversion quantity of the i-th advertising channel; : The weight coefficient of the total advertising revenue of the i-th advertising channel; The overall effectiveness of advertising on an advertising channel is measured based on the number of conversions and total advertising revenue of the advertising channel, that is, the key performance indicators of the advertising channel are calculated.

7. The advertising placement monitoring and management system based on data collection according to claim 1, characterized in that: The optimization of the advertising delivery time period in S4 includes: According to the adjusted budget configuration, use the time period optimization model to measure the delivery effect of each time period, and optimize the time period based on the delivery effect of each time period. Allocate different budgets to each time period to obtain the time period optimization results.

8. The advertising placement monitoring and management system based on data collection according to claim 7 is characterized in that: The time period optimization model includes: ； in: : The budget amount allocated to advertising channel i in time period t; : The effectiveness of the advertising channel in time period t; : The sum of the effectiveness of the advertising channel in all time periods; : The total delivery time of this advertising channel; Allocate budget amounts based on the effectiveness of advertising channels in each time period.

9. The advertising placement monitoring and management system based on data collection according to claim 8, characterized in that: The time period performance includes: ； in: : Contribution score of the i-th advertising channel at time period t; : Sensitivity coefficient of the i-th advertising channel at time period t; : The conversion rate of the i-th advertising channel at time period t; : The highest conversion rate in all time periods; Calculate the effectiveness of each time period under the advertising channel based on the contribution score, sensitivity coefficient and conversion rate of each time period of the advertising channel.

10. The advertising placement monitoring and management system based on data collection according to claim 1, characterized in that: Includes the following functional modules: Data collection and evaluation module, budget adjustment module, time period optimization module, and frequency management module.

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