Intelligent delivery-based delivery value evaluation method

Abstract

The invention relates to the field of artificial intelligence, and discloses an intelligent delivery-based delivery value evaluation method, which comprises the following steps of S01, intelligent advertisement delivery data acquisition, S02, advertisement value data and delivery risk data processing, S03, data processing, S04, data processing, S05, data processing, S06, data processing, and S06, data processing. S03, value evaluation is carried out on intelligent advertisement putting based on advertisement value data before and after advertisement putting, S04, risk evaluation is carried out on intelligent advertisement putting based on putting risk data before and after advertisement putting, and S05, putting adjustment analysis is carried out on intelligent advertisement putting according to a putting value evaluation result. And step S06, performing delivery interruption analysis on intelligent advertisement delivery according to a delivery risk assessment result, analyzing data changes before and after advertisement delivery, assessing potential risks of advertisement delivery, and providing scientific delivery strategy suggestions for advertisers so as to maximize the advertisement delivery effect.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence, and more specifically to a method for evaluating the value of an investment based on intelligent investment. Background Art

[0002] Before the birth of the Internet, advertising mainly relied on traditional media such as newspapers, television, and radio. The evaluation of advertising effectiveness at this stage mainly relied on traditional media indicators such as ratings, listening rates, and circulation. Although these indicators can reflect the coverage of advertisements to a certain extent, it is difficult to achieve accurate delivery and effect evaluation; Internet platform evaluation stage: With the development of the Internet, advertising began to shift to Internet platforms. At this stage, advertising was mainly delivered through search engines, social networks, etc. Advertisers can deliver advertisements based on keywords, interests, and other dimensions.

[0003] With the advent of the big data era, the advertising industry is facing profound changes. Intelligent advertising, with its advantages of precise delivery, efficient reach, and personalized customization, has gradually become the mainstream trend in the advertising market. Advertisers and advertising platforms have increased their research and development and investment in intelligent advertising in order to stand out in the fierce market competition. By collecting and analyzing user behavior data, advertising delivery data, market environment data, etc., they provide a data foundation for intelligent delivery. Data sources include advertising platforms, social media, search engines, CRM systems, etc.

[0004] In the era of intelligent advertising, how to scientifically evaluate the effectiveness of advertising has become an urgent problem to be solved in the industry. Traditional advertising effectiveness evaluation methods often rely on manual statistics and experience judgment, and have problems such as strong subjectivity, inaccurate data, and low efficiency. Therefore, a delivery value evaluation method based on intelligent delivery is needed to achieve real-time, accurate, and comprehensive evaluation of advertising effectiveness. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method for evaluating the value of an investment based on intelligent investment to solve the problems existing in the above-mentioned background technology.

[0006] The present invention provides the following technical solution: a method for evaluating the value of an investment based on intelligent investment, comprising the following steps:

[0007] Step S01: Intelligent advertising data collection: using website analysis tools to collect advertising value data and advertising risk data from the advertising platform to obtain advertising data;

[0008] Step S02: Processing the advertising value data and the advertising risk data: Processing the advertising value data and the advertising risk data through data cleaning, and dividing the processed data into pre-advertising data and post-advertising data;

[0009] Step S03: conducting value assessment on smart advertising delivery based on the advertising value data before and after the advertisement delivery: establishing a smart delivery value assessment model, inputting the advertising value data before and after the advertisement delivery as variables into the smart delivery value assessment model for analysis, and obtaining the delivery value assessment result;

[0010] Step S04: Conduct risk assessment on smart advertising delivery based on delivery risk data before and after the advertisement delivery: Establish a smart delivery risk assessment model, input the delivery risk data before and after the advertisement delivery as variables into the smart delivery risk assessment model for analysis, and obtain delivery risk assessment results;

[0011] Step S05: Performing an analysis on smart advertising delivery based on the delivery value assessment result: receiving the delivery value assessment result, comparing the delivery value assessment result with the expected delivery value assessment value, and determining whether to adjust the delivery of smart advertising;

[0012] Step S06: Performing a delivery interruption analysis on the smart advertisement delivery based on the delivery risk assessment result: receiving the delivery risk assessment result, comparing the delivery risk assessment result with a preset delivery risk threshold, and determining whether to interrupt the smart advertisement delivery.

[0013] Preferably, the specific content of the step S01 of intelligent advertising delivery data collection is: using website analysis tools to collect advertising value data and delivery risk data of the advertising platform, the advertising value data includes: the number of clicks before and after the advertising delivery, the number of impressions before and after the advertising delivery, the number of conversions before and after the advertising delivery, the revenue generated by the advertising, and the advertising expenses; the delivery risk data includes: the number of abnormal clicks before and after the advertising delivery, the cost per click before and after the advertising delivery, the number of invalid conversions before and after the advertising delivery, and the cost per action before and after the advertising delivery.

[0014] Preferably, the specific content of the data processing of the advertising value data and the placement risk data in step S02 is: removing abnormal values, duplicate values and irrelevant data in the data through data filtering, data conversion and data normalization;

[0015] The data before advertisement delivery includes advertisement value data and delivery risk data before advertisement delivery; the data after advertisement delivery includes advertisement value data and delivery risk data after advertisement delivery.

[0016] Preferably, the specific contents of step S03 of evaluating the value of smart advertising delivery based on the advertising value data before and after the advertising delivery are as follows:

[0017] Calculate key indicators of advertising value data before and after advertising, and calculate the click-through rate before advertising. The calculation formula is: CTR a Indicates the click-through rate before the ad is released, W 点击 Indicates the number of clicks before the ad is delivered, W 展示 Indicates the number of impressions before the ad is served;

[0018] Calculate the conversion rate before advertising. The formula is: Among them CR a represents the conversion rate before advertising, W 转化 Indicates the number of conversions before the ad is delivered, W 点击 Indicates the number of clicks before the ad is served;

[0019] Calculate the advertising return on investment for advertising, the calculation formula is: ROI represents the return on investment of advertising, L 收入 Indicates the revenue from advertising, L 费用 represents advertising expenses;

[0020] Based on the above calculation, the click-through rate (CTR) after the ad is delivered is obtained. b and the conversion rate CR after advertising b ;

[0021] The advertising value data before and after the advertisement is placed is input as a variable into the intelligent placement value evaluation model for analysis. The expression of the intelligent placement value evaluation model is: P = ln[1 + ω1 × (CTR b -CTR a )+ω2×(CR b -CR a )+ω3×ROI], where P represents the evaluation output value of the intelligent delivery value evaluation model, ω1 represents the weight of the click-through rate of advertising delivery, ω2 represents the weight of the conversion rate of advertising delivery, and ω3 represents the weight of the return on advertising investment.

[0022] Preferably, the specific content of step S04 of performing risk assessment on smart advertising delivery based on delivery risk data before and after the advertisement delivery is as follows:

[0023] When the delivery risk data is obtained, the smart advertisement has been delivered n times, i=1, 2, 3, ..., n, where i represents the number of smart advertisement delivery times;

[0024] The risk cost before advertising is calculated based on the risk data before advertising is launched. The calculation formula is: Rc a =X a异常 ×C a +Y a无效 ×M a , where Rc a represents the risk cost before advertising, X a异常 Indicates the number of abnormal clicks before the ad is delivered, C a represents the cost per click before the ad is delivered, Y a无效 Indicates the number of invalid conversions before the ad is delivered, M a Indicates the cost per action before advertising;

[0025] The risk cost after each ad placement is calculated based on the risk data after placement. The calculation formula is: Rc i =X bi ×C bi +Y bi ×M bi , where Rc i represents the risk cost after each advertisement launch, X bi Indicates the number of abnormal clicks after each ad delivery, C bi It represents the cost per click after each ad delivery, Y bi Indicates the number of invalid conversions after each ad delivery, M bi Indicates the cost per action after each ad delivery;

[0026] An intelligent delivery risk assessment model is established. The expression of the intelligent delivery risk assessment model is: Where D represents the output value of the intelligent delivery risk assessment model.

[0027] Preferably, in step S05, the smart advertising delivery is analyzed for delivery adjustment based on the delivery value evaluation result: the delivery value evaluation result is received, and the delivery value evaluation result is compared with the expected delivery value evaluation value. If the delivery value evaluation result is greater than or equal to the expected delivery value evaluation value, the judgment result is that no delivery adjustment is made to the smart advertising delivery; if the delivery value evaluation result is less than the expected delivery value evaluation value, the judgment result is that the smart advertising delivery is adjusted.

[0028] Preferably, in step S06, a delivery interruption analysis is performed on the smart advertising delivery based on the delivery risk assessment result: the delivery risk assessment result is received, and the delivery risk assessment result is compared with a preset delivery risk threshold. If the delivery risk assessment result is greater than or equal to the preset delivery risk threshold, the judgment result is to interrupt the smart advertising delivery; if the delivery risk assessment result is less than the preset delivery risk threshold, the judgment result is not to interrupt the smart advertising delivery.

[0029] The technical effects and advantages of the present invention are as follows:

[0030] The present invention is provided with step S01: intelligent advertising delivery data collection, step S02: data processing of advertising value data and delivery risk data, step S03: value assessment of intelligent advertising delivery based on advertising value data before and after advertising delivery, step S04: risk assessment of intelligent advertising delivery based on delivery risk data before and after advertising delivery, step S05: delivery adjustment analysis of intelligent advertising delivery based on delivery value assessment results, and step S06: delivery interruption analysis of intelligent advertising delivery based on delivery risk assessment results, thereby realizing real-time, accurate and comprehensive evaluation of the effect of intelligent advertising delivery, and solving the problems of strong subjectivity, inaccurate data and low efficiency in traditional advertising delivery effect evaluation methods. At the same time, the present invention also provides advertisers with a scientific delivery adjustment and interruption decision-making basis by comparing data before and after advertising delivery, as well as preset delivery value assessment values and delivery risk thresholds, which helps advertisers optimize advertising delivery strategies, improve advertising delivery effects and reduce delivery risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The figure is a flowchart of a method for evaluating the value of an investment based on intelligent investment. DETAILED DESCRIPTION

[0032] The technical solutions of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures described in the following embodiments are merely examples. The method for evaluating the value of an investment based on intelligent investment involved in the present invention is not limited to the various structures described in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] like Figure 1 As shown, the present invention provides a method for evaluating the value of an investment based on intelligent investment, comprising the following steps:

[0034] Step S01: Intelligent advertising data collection: using website analysis tools to collect advertising value data and advertising risk data from the advertising platform to obtain advertising data;

[0035] Step S02: Processing the advertising value data and the advertising risk data: Processing the advertising value data and the advertising risk data through data cleaning, and dividing the processed data into pre-advertising data and post-advertising data;

[0036] Step S03: conducting value assessment on smart advertising delivery based on the advertising value data before and after the advertisement delivery: establishing a smart delivery value assessment model, inputting the advertising value data before and after the advertisement delivery as variables into the smart delivery value assessment model for analysis, and obtaining the delivery value assessment result;

[0037] Step S04: Conduct risk assessment on smart advertising delivery based on delivery risk data before and after the advertisement delivery: Establish a smart delivery risk assessment model, input the delivery risk data before and after the advertisement delivery as variables into the smart delivery risk assessment model for analysis, and obtain delivery risk assessment results;

[0038] Step S05: Performing an analysis on smart advertising delivery based on the delivery value assessment result: receiving the delivery value assessment result, comparing the delivery value assessment result with the expected delivery value assessment value, and determining whether to adjust the delivery of smart advertising;

[0039] Step S06: Performing a delivery interruption analysis on the smart advertisement delivery based on the delivery risk assessment result: receiving the delivery risk assessment result, comparing the delivery risk assessment result with a preset delivery risk threshold, and determining whether to interrupt the smart advertisement delivery.

[0040] In this embodiment, it should be specifically explained that the specific content of the step S01 of intelligent advertising delivery data collection is: using website analysis tools to collect advertising value data and delivery risk data of the advertising platform, the advertising value data includes: the number of clicks before and after the advertisement delivery, the number of impressions before and after the advertisement delivery, the number of conversions before and after the advertisement delivery, the revenue generated by the advertisement, and the advertising expenses; the delivery risk data includes: the number of abnormal clicks before and after the advertisement delivery, the cost per click before and after the advertisement delivery, the number of invalid conversions before and after the advertisement delivery, and the cost per action before and after the advertisement delivery.

[0041] In this embodiment, it should be specifically explained that the specific content of the data processing of the advertising value data and the placement risk data in step S02 is: removing abnormal values, duplicate values and irrelevant data in the data through data filtering, data conversion and data normalization;

[0042] The data before advertisement delivery includes advertisement value data and delivery risk data before advertisement delivery; the data after advertisement delivery includes advertisement value data and delivery risk data after advertisement delivery.

[0043] In this embodiment, it should be specifically explained that the specific contents of step S03 of evaluating the value of smart advertising delivery based on the advertising value data before and after the advertising delivery are as follows:

[0044] Calculate key indicators of advertising value data before and after advertising, and calculate the click-through rate before advertising. The calculation formula is: CTR a Indicates the click-through rate before the ad is released, W 点击 Indicates the number of clicks before the ad is delivered, W 展示 Indicates the number of impressions before the ad is served;

[0045] Calculate the conversion rate before advertising. The formula is: Among them CR a represents the conversion rate before advertising, W 转化 Indicates the number of conversions before the ad is delivered, W 点击 Indicates the number of clicks before the ad is served;

[0046] Calculate the advertising return on investment for advertising, the calculation formula is: ROI represents the return on investment of advertising, L 收入 Indicates the revenue from advertising, L 费用 represents advertising expenses;

[0047] Based on the above calculation, the click-through rate (CTR) after the ad is delivered is obtained. b and the conversion rate CR after advertising b , where the click-through rate (CTR) after the ad is released b The calculation formula is: CTR b Indicates the click-through rate after the ad is released, W′ 点击 Indicates the number of clicks after the ad is delivered, W′ 展示 Indicates the number of times an ad is displayed after it is served;

[0048] Conversion rate CR after advertising b The calculation formula is: Among them CR b Represents the conversion rate after advertising, W′ 转化 Represents the number of conversions after the ad is delivered, W′ 点击 Indicates the number of clicks after the ad is served;

[0049] The advertising value data before and after the advertisement is placed is input as a variable into the intelligent placement value evaluation model for analysis. The expression of the intelligent placement value evaluation model is: P = ln[1 + ω1 × (CTR b -CTR a )+ω2×(CR b -CR a )+ω3×ROI], where P represents the evaluation output value of the intelligent delivery value evaluation model, ω1 represents the weight of the click-through rate of advertising delivery, ω2 represents the weight of the conversion rate of advertising delivery, and ω3 represents the weight of the return on advertising investment.

[0050] In this embodiment, it should be specifically explained that the specific content of step S04 of performing risk assessment on smart advertising delivery based on delivery risk data before and after the advertisement delivery is as follows:

[0051] When the delivery risk data is obtained, the smart advertisement has been delivered n times, i=1, 2, 3, ..., n, where i represents the number of smart advertisement delivery times;

[0052] The risk cost before advertising is calculated based on the risk data before advertising is launched. The calculation formula is: Rc a =X a异常 ×C a +Y a无效 ×M a , where Rc a represents the risk cost before advertising, X a异常 Indicates the number of abnormal clicks before the ad is delivered, C a represents the cost per click before the ad is delivered, Y a无效 Indicates the number of invalid conversions before the ad is delivered, M a Indicates the cost per action before advertising;

[0053] The risk cost after each ad placement is calculated based on the risk data after placement. The calculation formula is: Rc i =X bi ×C bi +Y bi ×M bi , where Rc i represents the risk cost after each advertisement launch, X bi Indicates the number of abnormal clicks after each ad delivery, C bi It represents the cost per click after each ad delivery, Y bi Indicates the number of invalid conversions after each ad delivery, M bi Indicates the cost per action after each ad delivery;

[0054] An intelligent delivery risk assessment model is established. The expression of the intelligent delivery risk assessment model is: Where D represents the output value of the intelligent delivery risk assessment model.

[0055] In this embodiment, it should be specifically explained that in step S05, the smart advertising delivery is analyzed for delivery adjustment based on the delivery value evaluation result: the delivery value evaluation result is received, and the delivery value evaluation result is compared with the expected delivery value evaluation value. If the delivery value evaluation result is greater than or equal to the expected delivery value evaluation value, the judgment result is that no delivery adjustment is made to the smart advertising delivery; if the delivery value evaluation result is less than the expected delivery value evaluation value, the judgment result is that the smart advertising delivery is adjusted.

[0056] In this embodiment, it should be specifically explained that in step S06, the smart advertising delivery is analyzed for interruption based on the delivery risk assessment result: the delivery risk assessment result is received, and the delivery risk assessment result is compared with the preset delivery risk threshold. If the delivery risk assessment result is greater than or equal to the preset delivery risk threshold, the judgment result is to interrupt the smart advertising delivery; if the delivery risk assessment result is less than the preset delivery risk threshold, the judgment result is not to interrupt the smart advertising delivery.

[0057] The main difference between this embodiment and the prior art is that this embodiment is provided with step S01: intelligent advertising delivery data collection, step S02: data processing of advertising value data and delivery risk data, step S03: value assessment of intelligent advertising delivery based on advertising value data before and after advertising delivery, step S04: risk assessment of intelligent advertising delivery based on delivery risk data before and after advertising delivery, step S05: delivery adjustment analysis of intelligent advertising delivery based on delivery value assessment results, step S06: delivery interruption analysis of intelligent advertising delivery based on delivery risk assessment results, thereby realizing real-time, accurate and comprehensive evaluation of the effect of intelligent advertising delivery, solving the problems of strong subjectivity, inaccurate data and low efficiency in traditional advertising delivery effect evaluation methods, and at the same time, by comparing data before and after advertising delivery, as well as preset delivery value assessment values and delivery risk thresholds, providing advertisers with a scientific delivery adjustment and interruption decision-making basis, which helps advertisers optimize advertising delivery strategies, improve advertising delivery effects and reduce delivery risks.

[0058] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0059] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for evaluating the value of an investment based on intelligent investment, characterized by: The following steps are involved: Step S01: Intelligent advertising data collection: using website analysis tools to collect advertising value data and advertising risk data from the advertising platform to obtain advertising data; Step S02: Processing the advertising value data and the advertising risk data: Processing the advertising value data and the advertising risk data through data cleaning, and dividing the processed data into pre-advertising data and post-advertising data; Step S03: conducting value assessment on smart advertising delivery based on the advertising value data before and after the advertisement delivery: establishing a smart delivery value assessment model, inputting the advertising value data before and after the advertisement delivery as variables into the smart delivery value assessment model for analysis, and obtaining the delivery value assessment result; Step S04: Conduct risk assessment on smart advertising delivery based on delivery risk data before and after the advertisement delivery: Establish a smart delivery risk assessment model, input the delivery risk data before and after the advertisement delivery as variables into the smart delivery risk assessment model for analysis, and obtain delivery risk assessment results; Step S05: Performing an analysis on smart advertising delivery based on the delivery value assessment result: receiving the delivery value assessment result, comparing the delivery value assessment result with the expected delivery value assessment value, and determining whether to adjust the delivery of smart advertising; Step S06: Performing a delivery interruption analysis on the smart advertisement delivery based on the delivery risk assessment result: receiving the delivery risk assessment result, comparing the delivery risk assessment result with a preset delivery risk threshold, and determining whether to interrupt the smart advertisement delivery.

2. The method for evaluating the value of an investment based on intelligent investment according to claim 1, characterized in that: The specific content of the step S01 of intelligent advertising delivery data collection is: using website analysis tools to collect advertising value data and delivery risk data of the advertising platform, the advertising value data includes: the number of clicks before and after the advertising delivery, the number of impressions before and after the advertising delivery, the number of conversions before and after the advertising delivery, the revenue generated by the advertising, and the advertising expenses; the delivery risk data includes: the number of abnormal clicks before and after the advertising delivery, the cost per click before and after the advertising delivery, the number of invalid conversions before and after the advertising delivery, and the cost per action before and after the advertising delivery.

3. The method for evaluating the value of an investment based on intelligent investment according to claim 1, characterized in that: The specific content of step S02 of processing the advertising value data and the placement risk data is: removing abnormal values, duplicate values and irrelevant data in the data through data filtering, data conversion and data normalization; The data before advertisement delivery includes advertisement value data and delivery risk data before advertisement delivery; the data after advertisement delivery includes advertisement value data and delivery risk data after advertisement delivery.

4. The method for evaluating the value of an investment based on intelligent investment according to claim 1, characterized in that: The specific contents of step S03 of evaluating the value of smart advertising delivery based on the advertising value data before and after the advertising delivery are as follows: Calculate key indicators of advertising value data before and after advertising, and calculate the click-through rate before advertising. The calculation formula is: CTR a Indicates the click-through rate before the ad is released, W 点击 Indicates the number of clicks before the ad is delivered, W 展示 Indicates the number of impressions before the ad is served; Calculate the conversion rate before advertising. The formula is: Among them CR a represents the conversion rate before advertising, W 转化 Indicates the number of conversions before the ad is delivered, W 点击 Indicates the number of clicks before the ad is served; Calculate the advertising return on investment for advertising, the calculation formula is: ROI represents the return on investment of advertising, L 收入 Indicates the revenue from advertising, L 费用 represents advertising expenses; Based on the above calculation, the click-through rate (CTR) after the ad is delivered is obtained. b and the conversion rate CR after advertising b ; The advertising value data before and after the advertisement is placed is input as a variable into the intelligent placement value evaluation model for analysis. The expression of the intelligent placement value evaluation model is: P = ln[1 + ω1 × (CTR b -CTR a )+ω2×(CR b -CR a )+ω3×ROI], where P represents the evaluation output value of the intelligent delivery value evaluation model, ω1 represents the weight of the click-through rate of advertising delivery, ω2 represents the weight of the conversion rate of advertising delivery, and ω3 represents the weight of the return on advertising investment.

5. The method for evaluating the value of an investment based on intelligent investment according to claim 1, characterized in that: The specific contents of step S04 of performing risk assessment on smart advertising delivery based on delivery risk data before and after the advertisement delivery are as follows: When the delivery risk data is obtained, the smart advertisement has been delivered n times, i=1, 2, 3, ..., n, where i represents the number of smart advertisement delivery times; The risk cost before advertising is calculated based on the risk data before advertising is launched. The calculation formula is: Rc a =X a异常 ×C a +Y a无效 ×M a , where Rc a represents the risk cost before advertising, X a异常 Indicates the number of abnormal clicks before the ad is delivered, C a represents the cost per click before the ad is delivered, Y a无效 Indicates the number of invalid conversions before the ad is delivered, M a Indicates the cost per action before advertising; The risk cost after each ad placement is calculated based on the risk data after placement. The calculation formula is: Rc i =X bi ×C bi +Y bi ×M bi , where Rc i represents the risk cost after each advertisement launch, X bi Indicates the number of abnormal clicks after each ad delivery, C bi It represents the cost per click after each ad delivery, Y bi Indicates the number of invalid conversions after each ad delivery, M bi Indicates the cost per action after each ad delivery; An intelligent delivery risk assessment model is established. The expression of the intelligent delivery risk assessment model is: Where D represents the output value of the intelligent delivery risk assessment model.

6. The method for evaluating the value of an investment based on intelligent investment according to claim 1, characterized in that: In step S05, the smart advertising delivery is analyzed for delivery adjustment based on the delivery value evaluation result: the delivery value evaluation result is received, and the delivery value evaluation result is compared with the expected delivery value evaluation value. If the delivery value evaluation result is greater than or equal to the expected delivery value evaluation value, the judgment result is that no delivery adjustment is made to the smart advertising delivery; if the delivery value evaluation result is less than the expected delivery value evaluation value, the judgment result is that the smart advertising delivery is adjusted.

7. The method for evaluating the value of an investment based on intelligent investment according to claim 1, characterized in that: In step S06, the smart advertising delivery is analyzed for interruption based on the delivery risk assessment result: the delivery risk assessment result is received, and the delivery risk assessment result is compared with a preset delivery risk threshold. If the delivery risk assessment result is greater than or equal to the preset delivery risk threshold, the judgment result is to interrupt the smart advertising delivery; if the delivery risk assessment result is less than the preset delivery risk threshold, the judgment result is not to interrupt the smart advertising delivery.

Images