CN116823351A - Advertisement delivery flow monitoring and controlling system based on electronic commerce - Google Patents
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Abstract
The invention relates to the technical field of Internet advertisement delivery, in particular to an advertisement delivery flow monitoring control system based on electronic commerce. The system collects and comprehensively analyzes the exposure, click rate and conversion number of the delivered advertisements, further reflects the effect evaluation coefficient of the advertisement flow, and obtains the advertisement delivery effect through comparing the advertisement flow effect evaluation coefficient with the planned delivery effect, so that the accurate measurement index of flow control is achieved, more accurate, efficient and sustainable advertisement delivery is achieved, the effectiveness of the advertisements is greatly improved, and unbalance of advertisement cost and benefit is reduced.
Description
Technical Field
The invention relates to the technical field of Internet advertisement delivery, in particular to an advertisement delivery flow monitoring and controlling system based on electronic commerce.
Background
Traffic monitoring is the process of monitoring and analyzing traffic in a network, web site, or application in real time by collecting and analyzing traffic data. With the rapid development of electronic commerce, more and more enterprises and advertisers turn advertisement delivery to an electronic commerce platform. However, simply placing advertisements on a platform is not sufficient, and monitoring and controlling the flow of advertisements is also required to ensure that the advertisements are able to achieve the desired effect and return.
The existing charging mode for the advertisement putting flow rate usually charges for a single condition, most commonly charges in time units, and an advertiser pays a fee according to the duration of the advertisement being displayed, whether the advertisement is clicked or converted or not, and only pays attention to the exposure of the advertisement. However, this way of charging is not reasonable, and is embodied in the following ways: 1. the lack of accurate measurement indexes, the effect and return of the advertisement cannot be accurately reflected only by taking the advertisement time as a charging basis, and the time release may not accurately measure the key indexes such as the exposure, click rate, conversion rate and the like of the advertisement, so that the performance of the advertisement is difficult to evaluate.
2. There is potential waste, billing for the duration may result in the advertiser paying a fee without actually obtaining a valid reach. The user may simply scroll through the page quickly or have no real interest, but the advertiser still needs to pay full fees. In this case, the advertiser may waste a lot of resources without a corresponding return.
3. Pricing is unfair and charging for advertising time alone may not be fair because traffic values are not the same for different time periods. The supply and demand relationships of traffic and audience liveness may result in large traffic price differences over time periods. Advertisers may encounter excessive competition for peak advertising spots and high advertising costs if charged for only a single period of time.
Disclosure of Invention
The invention solves the technical problems, and adopts the following technical scheme: an advertisement delivery flow monitoring control system based on electronic commerce, the advertisement delivery flow monitoring control system comprising: the advertisement flow data parameter acquisition module is used for acquiring flow data parameters of advertisements which are put into the electronic commerce platform in each acquisition time period in a preset time in the putting process, wherein the flow data parameters comprise exposure, click quantity and conversion number.
And the advertisement delivery flow evaluation module is used for analyzing and obtaining the effect evaluation coefficient of the advertisement flow according to the acquired flow data parameters of the advertisement in the delivery process.
The flow control module is used for comparing the acquired advertisement flow data parameters with planned advertisement flow data parameters in the flow delivery management database, further analyzing and obtaining advertisement delivery quantity when the planned effect is achieved, and simultaneously analyzing and obtaining an increase value of the flow in unit time according to the acquired advertisement flow data parameters, and further obtaining the time length required by the distance planned flow delivery effect when the planned effect is not achieved.
And the visual feedback module is used for feeding back the monitored flow data parameters in the advertisement putting process to the advertiser and the platform in real time, and analyzing and generating a detailed visual report and a detailed form according to the advertisement putting flow data parameters.
And the A/B test acquisition module is used for respectively monitoring flow data in the advertisement putting process of different platforms by simultaneously putting advertisements on each platform to obtain flow data parameters of the advertisements in the advertisement putting process of different platforms.
The A/B test analysis module is used for acquiring flow data parameters of advertisements in the process of putting different platforms, and further analyzing and obtaining the putting effect evaluation coefficients of the platforms.
The traffic delivery management database is used for storing traffic data parameters of the advertisement plan, the advertisement delivery quantity, traffic delivery cost and user click unit price.
Preferably, the advertisement delivery amount of the traffic delivery management database further comprises advertisement delivery amounts, planned delivery amounts and actual delivery amounts of each acquisition time period in a preset time.
Preferably, the advertisement flow data parameter acquisition module specifically comprises: the advertisement flow data parameter acquisition module comprises an advertisement exposure parameter acquisition unit, a user click rate acquisition unit and a conversion rate acquisition unit.
Preferably, the advertisement exposure parameter acquisition unit is used for obtaining the exposure corresponding to each acquisition time period of the advertisement according to the number of times the advertisement is displayed to the audience in each acquisition time period within the preset time, and marking the exposure as E i I denotes the number of the i-th acquisition period, i=1, 2, …, q; the user click amount acquisition unit is used for acquiring the user click times of the advertisement in the preset time in the throwing period of each acquisition time period, taking the user click times as the click amount of the advertisement corresponding to each acquisition time period, and marking the click amount as C i The method comprises the steps of carrying out a first treatment on the surface of the By a means ofThe conversion number acquisition unit is used for acquiring the total number of times of registration, subscription and purchase completed by the user in each acquisition time period in preset time, taking the total number of times as the conversion amount of the advertisement corresponding to each acquisition time period, and recording the conversion amount as CV i 。
Preferably, the specific evaluation method of the effect evaluation coefficient of the advertisement traffic executes the following steps: the first step, the obtained exposure, click quantity and conversion number of the advertisement in each acquisition time period in the preset time period are respectively substituted into a formulaFurther, click rate CTR and conversion rate CR are obtained.
Step two, reading the advertisement delivery quantity, click rate and set click unit price and substituting the same into a formulaAnd analyzing to obtain the investment return rate psi of the advertisement, wherein ρ represents the clicking unit price of the user, ν represents the flow delivery cost, and γ represents the delivery quantity of the advertisement.
Thirdly, comprehensively analyzing the effect evaluation weight factor of the advertisement delivery by weight distribution of the advertisement click rate, the conversion rate and the return on investment rate, wherein the calculation formula of the effect evaluation weight factor is delta=CTR [ mu ] 1 +CR*μ 2 +ψ*μ 3 Mu 1, mu 2 and mu 3 respectively represent the weight factor of click rate, the weight factor of conversion rate and the weight factor of return on investment, and mu 1 +μ 2 +μ 3 =1 by introducing the effect evaluation weight factor into the formulaEffect evaluation coefficient for obtaining advertisement traffic>
Preferably, the specific method of the flow control module performs the following steps: firstly, reading the exposure, click quantity and conversion number of the platform advertisement putting flow in each acquisition time period in a preset time period, comparing the exposure, the click quantity and the conversion number with the planned exposure, the click quantity and the conversion number obtained in a flow putting management database, and if the exposure, the click quantity and the conversion number of the platform advertisement putting flow in a certain acquisition time period are higher than the planned exposure, the click quantity and the conversion number, taking the acquisition time period as a coincidence acquisition time period.
Step two, screening out the actual delivery amount of each coincidence acquisition time period, acquiring the planned delivery amount of each coincidence acquisition time period from a database, acquiring the planned delivery amount from the database, and substituting the planned delivery amount into a formulaThereby obtaining the advertisement flow quantity eta according with the acquisition time period r ，γ r Planning For the r-th planned delivery amount according with the acquisition time period, gamma r Actual practice is that of For the actual delivery quantity of the r-th coincidence acquisition time period, lambda represents the correction coefficient of flow plan delivery, ρ r For the r-th deviation influence coefficient conforming to the planned delivery effect of the acquisition time period, ρ r The calculation formula of (2) is as follows: />γ i For the r-th advertisement delivery amount according to the acquisition time period, r represents the number of the acquisition time period, r=1, 2, k; k is the number of acquisition time periods.
Thirdly, screening out advertisement flow data parameters which do not reach the planned acquisition time period, and substituting the advertisement flow data parameters into a formulaThereby obtaining the average increase value Q, phi of the flow in unit time 1 、φ 2 、φ 3 Advertisement flow rate duty ratio weights corresponding to unit exposure amount, unit click amount and unit conversion number respectively, t represents a time interval, j does not reach the number of the planned acquisition time period, j=1, 2, and m, E j Starting from the beginning Indicating the initial exposure of the advertisement in the jth period,/->Indicating the exposure of the advertisement after the end of the j-th time period,indicating the initial click-through amount of the advertisement in the j-th time period,>indicating the click-through amount reached by the advertisement after the end of the j-th time period,/for the advertisement>Indicating the initial conversion number of the advertisement in the j-th time period,/for the advertisement>And (5) representing the conversion number reached by the advertisement when the j-th time period is ended, and calculating the time length required by the planned flow delivery effect according to the obtained flow increment value in the unit time.
Preferably, the A/B test acquisition module is used for monitoring the exposure, click rate and conversion number of the flow put in by each platform advertisement in each acquisition time period.
Preferably, the specific extraction method of the advertisement traffic data parameters of each platform of the A/B test acquisition module comprises the following steps: the first step, sequentially reading the exposure, click quantity and conversion number of each platform in each acquisition time period, analyzing to obtain the effect evaluation weight factors of each platform, and forming an advertisement putting flow effect evaluation weight factor set delta (delta) 1 ,δ 2 ,...,δ n ,...,δ g ) N represents the nth land, n=1, 2,.. n The nth platform effect evaluation weight factor is represented.
Secondly, comparing the flow data parameters of the same platform advertisement in the adjacent acquisition time period in the platform advertisement delivery flow data parameter set, and substituting the flow data parameters into a formula
Obtaining average growth index theta of flow data parameters in corresponding acquisition time periods of each platform n ，E n i Indicating the exposure of the advertisement in the ith period of time of the nth plateau, +.>Indicating the exposure of the advertisement in the ith-1 time period of the nth plateau, +.>Indicating the click-through amount of the advertisement in the ith time period of the nth platform, +.>Indicating the click-through amount of advertisement in the ith-1 time period of the nth platform, +.>Representing the conversion number of the advertisement in the ith time period of the nth platform,/for the nth platform>Indicating the conversion number of the advertisement in the ith-1 time period of the nth platform.
Third, substituting the average growth index of the flow data parameters in the corresponding acquisition time period of each platform into a formula The advertisement delivery effect evaluation coefficient is represented as an nth platform.
Preferably, the visual feedback module is used for feeding back the monitored advertisement delivery flow data index to the advertiser and the platform in real time, arranging the advertisement delivery effect evaluation coefficients of the platforms according to the sequence from big to small, and displaying the arranged results.
The beneficial effects of the invention are as follows: 1. according to the invention, the advertisement click rate, conversion rate and return on investment rate of the advertisement delivery flow monitoring control system are obtained through monitoring the exposure, click rate and conversion number of the platform advertisement delivery flow in each preset time period, the advertisement delivery flow data parameters are comprehensively analyzed by weight distribution of each parameter, the effect evaluation coefficient of the advertisement flow is obtained, the effect evaluation coefficient of the advertisement flow is compared with the planned delivery effect, the advertisement delivery effect is obtained by analysis, the accurate measurement index of flow control is achieved, and therefore more accurate, efficient and sustainable advertisement delivery is realized, and the effectiveness of advertisements is greatly improved.
2. According to the invention, the exposure, click rate and conversion number data of the advertisement are obtained from the advertisement putting flow monitoring control system, and are compared with the flow plan putting effect set in the flow putting management module, so that whether the actual effect of advertisement putting accords with the expectation is judged, and the flow distribution is reasonably managed and optimized according to the result, so that the waste phenomenon caused by excessive investment or insufficient budget is effectively avoided, the reasonable utilization of resources is ensured, the maximum benefit is obtained, and the potential waste is avoided.
3. According to the invention, the monitored advertisement delivery flow related data indexes are fed back to the advertiser and the platform in real time, and the advertisement delivery effect coefficients corresponding to advertisements in each time slot of each platform are displayed in descending order and sequentially arranged, so that the advertiser or the advertisement platform can intuitively see the flow delivery effect, and the advertisement delivery time is adjusted according to the information, so that a plurality of advertisements can be prevented from competing for limited advertisement slots in the same time slot, and excessive competition of the advertisement slots is reduced. Meanwhile, the average growth index of the flow data parameters corresponding to the advertisements of each platform is obtained through the A/B test, so that the corresponding throwing effect coefficient of the advertisements of each platform is evaluated, corresponding adjustment and decision can be made for different platforms, the advertising throwing effect and the advertising return rate are improved, the advertising resources are effectively utilized, and the unbalanced advertising cost and benefit caused by competition are reduced.
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The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a schematic diagram of the module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an advertisement delivery flow monitoring control system based on electronic commerce is used for monitoring advertisement delivery flow of an electronic commerce platform and adjusting a flow delivery plan in a flow calculation mode, and comprises a flow delivery management database, an advertisement flow data parameter acquisition module, an advertisement delivery flow evaluation module, a flow control module, an a/B test acquisition module, an a/B test analysis module and a visual feedback module.
The traffic management database in the module is connected with the advertisement delivery traffic evaluation module, the traffic control module, the A/B test analysis module and the visualization and feedback module, the advertisement delivery traffic evaluation module is connected with the advertisement delivery traffic effect parameter acquisition module, the traffic control module is connected with the advertisement delivery traffic evaluation module, the A/B test acquisition module is connected with the A/B test analysis module, and the visualization and feedback module is connected with the advertisement delivery traffic evaluation module and the A/B test analysis module.
The advertisement flow data parameter acquisition module is used for acquiring flow data parameters of advertisements which are put into the electronic commerce platform in each acquisition time period in preset time in the putting process, wherein the flow data parameters comprise exposure, click quantity and conversion number; the advertisement flow data parameter acquisition module comprisesThe system comprises an advertisement exposure parameter acquisition unit, a user click rate acquisition unit and a conversion rate acquisition unit; the advertisement exposure parameter acquisition unit is used for obtaining the exposure corresponding to each acquisition time period of the advertisement according to the number of times of displaying the advertisement to the audience in each acquisition time period in the preset time, and marking the exposure as E i I denotes the number of the i-th acquisition period, i=1, 2, …, q; the user click quantity acquisition unit is used for acquiring the user click times of the advertisement in the throwing period in each acquisition time period in the preset time, taking the user click times as the click quantity of the advertisement corresponding to each acquisition time period, and marking the click quantity as C i The method comprises the steps of carrying out a first treatment on the surface of the The conversion number acquisition unit is used for acquiring the total number of times of registration, subscription and purchase completed by the user in each acquisition time period in preset time, taking the total number of times as the conversion amount of the advertisement corresponding to each acquisition time period, and recording the conversion amount as CV i The method comprises the steps of carrying out a first treatment on the surface of the The system evaluates the exposure effect of the advertisement on a specific platform or an advertisement channel by collecting the advertisement exposure data, so that the exposure degree of the advertisement and the knowledge of the advertisement reaching the target audience capacity are increased; through the click volume data collected for the advertisement flow, the knowledge of the advertisement owner on the interests and behaviors of the target audience is increased, the advertisement creative is correspondingly optimized, and the advertisement effect and the conversion capability are improved; by collecting conversion number data in the advertisement flow, influence and conversion rate of advertisements on audiences can be estimated, effectiveness of advertisement investment is improved, accurate measurement index of flow control is achieved, more accurate, efficient and sustainable advertisement delivery is achieved, and effectiveness of advertisements is greatly improved.
The advertisement delivery flow evaluation module is used for analyzing and obtaining the effect evaluation coefficient of the advertisement flow according to the acquired flow data parameters of the advertisement in the delivery process.
The specific evaluation method of the effect evaluation coefficient of the advertisement flow carries out the following steps: the first step, the obtained exposure, click quantity and conversion number of the advertisement in each acquisition time period in the preset time period are respectively substituted into a formula Further obtaining click rate CTR and conversion rate CR; by analyzing the click rate and the conversion rate, the conversion effect and the return on investment of the advertisement are improved, so that an advertiser can more intuitively know the effect and the benefit of the advertisement.
Step two, reading the advertisement delivery quantity, click rate and set click unit price and substituting the same into a formulaAnalyzing to obtain the investment return rate psi of the advertisement, wherein ρ represents the clicking unit price of a user, ν represents the flow delivery cost, and γ represents the delivery quantity of the advertisement; through the return on investment, the profit level of the advertisement traffic investment can be known, the economic benefit of the advertisement traffic investment can be evaluated, the comparison between different advertisement traffic investments is more convenient, and the investment risk is reduced.
Thirdly, comprehensively analyzing the effect evaluation weight factor of the advertisement delivery by weight distribution of the advertisement click rate, the conversion rate and the return on investment rate, wherein the calculation formula of the effect evaluation weight factor is delta=CTR [ mu ] 1 +CR*μ 2 +ψ*μ 3 Mu 1, mu 2 and mu 3 respectively represent the weight factor of click rate, the weight factor of conversion rate and the weight factor of return on investment, and mu 1 +μ 2 +μ 3 =1 by introducing the effect evaluation weight factor into the formulaEffect evaluation coefficient for obtaining advertisement traffic>The advertisement effect is converted into specific numbers or ratios through the advertisement effect evaluation coefficients, so that the advertisement effect is easier to understand and compare, objective standards are provided for evaluating the advertisement effect through quantitative indexes, and the accuracy for measuring the advertisement effect and the return rate is improved.
The flow control module is used for comparing the acquired advertisement flow data parameters with planned advertisement flow data parameters in the flow delivery management database, further analyzing and obtaining advertisement delivery quantity when the planned effect is achieved, and simultaneously analyzing and obtaining a flow increment value in unit time according to the acquired advertisement flow data parameters, and further obtaining the time length required by the distance planned flow delivery effect when the planned effect is not achieved; the increased value of traffic per unit time may reflect the popularity of a web site or application, and a high increased traffic value generally means greater market impact and opportunity, indicating a higher interest and engagement of the user in the web site or application, and by comparing the traffic increase values over different time periods, the user's appeal and trend of the web site or application may be assessed.
The specific method of the flow control module performs the following steps: firstly, reading the exposure, click quantity and conversion number of the platform advertisement putting flow in each acquisition time period in a preset time period, comparing the exposure, the click quantity and the conversion number with the planned exposure, the click quantity and the conversion number obtained in a flow putting management database, and if the exposure, the click quantity and the conversion number of the platform advertisement putting flow in a certain acquisition time period are higher than the planned exposure, the click quantity and the conversion number, taking the acquisition time period as a coincidence acquisition time period.
Step two, screening out the actual delivery amount of each coincidence acquisition time period, acquiring the planned delivery amount of each coincidence acquisition time period from a database, acquiring the planned delivery amount from the database, and substituting the planned delivery amount into a formulaThereby obtaining the advertisement flow quantity eta according with the acquisition time period r ，γ r Planning For the r-th planned delivery amount according with the acquisition time period, gamma r Actual practice is that of For the actual delivery quantity of the r-th coincidence acquisition time period, lambda represents the correction coefficient of flow plan delivery, ρ r For the r-th deviation influence coefficient conforming to the planned delivery effect of the acquisition time period, ρ r The calculation formula of (2) is as follows: />γ i For the r-th coincidence acquisition periodAd impression, r represents the number of acquisition time period, r=1, 2, k; k is the number of acquisition time periods.
Thirdly, screening out advertisement flow data parameters which do not reach the planned acquisition time period, and substituting the advertisement flow data parameters into a formulaThereby obtaining the average increase value Q, phi of the flow in unit time 1 、φ 2 、φ 3 Advertisement flow rate duty ratio weights corresponding to unit exposure amount, unit click amount and unit conversion number respectively, t represents a time interval, j does not reach the number of the planned acquisition time period, j=1, 2, and m, E j Starting from the beginning Indicating the initial exposure of the advertisement in the jth period,/->Indicating the exposure of the advertisement after the end of the j-th time period,indicating the initial click-through amount of the advertisement in the j-th time period,>indicating the click-through amount reached by the advertisement after the end of the j-th time period,/for the advertisement>Indicating the initial conversion number of the advertisement in the j-th time period,/for the advertisement>Representing the conversion number reached when the advertisement is put at the end of the jth time period, and calculating the time length required by the planned flow putting effect according to the obtained flow increasing value in the unit time; by calculating the time length required by the flow increment value from the planned flow delivery effect, the method can help to set a reasonable target time frame, plan the budget of flow delivery, and track the actual increment condition of flow so as to ensure project progress to be carried out according to the plan.
The visual feedback module is used for feeding back the monitored flow data parameters in the advertisement putting process to the advertisers and the platforms in real time, arranging the advertisement putting effect evaluation coefficients of the platforms according to the advertisement putting flow data parameters from big to small, and displaying the arranged results.
The A/B test acquisition module is used for respectively monitoring flow data in the advertisement putting process of different platforms by simultaneously putting advertisements to each platform to obtain flow data parameters of the advertisements in the advertisement putting process of different platforms; the flow data parameters comprise exposure, click rate and conversion number of the flow put in by each platform advertisement in each acquisition time period.
The A/B test analysis module is used for acquiring flow data parameters of advertisements in the process of putting different platforms, and further analyzing and obtaining the putting effect evaluation coefficients of the platforms; through the analysis of the advertisement putting effect evaluation coefficients of different platforms, an advertiser can compare the putting effects of different platforms, so that the advertisement putting platform which is most suitable for the requirements and targets of the advertiser is selected, and the evaluation coefficients can help the advertiser to know indexes such as advertisement exposure, click rate, conversion rate and the like of the platform, and the characteristics and interests of the audience of the platform, so that an intelligent putting decision is made.
The specific extraction method of the advertisement flow data parameters of each platform of the A/B test acquisition module comprises the following steps: the first step, sequentially reading the exposure, click quantity and conversion number of each platform in each acquisition time period, analyzing to obtain the effect evaluation weight factors of each platform, and forming an advertisement putting flow effect evaluation weight factor set delta (delta) 1 ,δ 2 ,...,δ n ,...,δ g ) N represents the nth land, n=1, 2,.. n Representing an nth platform effect evaluation weight factor; the effect evaluation weighting factor allows multiple evaluation indicators to be considered together to generate a composite score or composite indicator. The comprehensiveness of evaluating the advertising effect is increased, the unilateralness of a single index is avoided, and meanwhile, the advertising effect can be comprehensively evaluated in a targeted manner by adjusting the weight factors according to the demands and the priorities of advertisers, so that more comprehensive data support is providedAnd maintaining and deciding the basis.
Secondly, comparing the flow data parameters of the same platform advertisement in the adjacent acquisition time period in the platform advertisement delivery flow data parameter set, and substituting the flow data parameters into a formulaObtaining average growth index theta of flow data parameters in corresponding acquisition time periods of each platform n ，E n i Indicating the exposure of the advertisement in the ith period of time of the nth plateau, +.>Indicating the exposure of the advertisement in the ith-1 time period of the nth plateau, +.>Indicating the click-through amount of the advertisement in the ith time period of the nth platform, +.>Indicating the click-through amount of advertisement in the ith-1 time period of the nth platform, +.>Representing the conversion number of the advertisement in the ith time period of the nth platform,/for the nth platform>Representing the conversion number of the advertisement in the ith-1 time period of the nth platform; by comparing the average growth indices of the traffic data parameters for different platforms, the trend of the traffic data parameters for different platforms over time can be assessed, with a higher growth index meaning that the platform grows faster on the index, potentially a potential growth opportunity, and advertisers can select the most potential platform to deliver advertisements based on these indices to achieve better traffic results.
Third, substituting the average growth index of the flow data parameters in the corresponding acquisition time period of each platform into a formula The advertisement putting effect evaluation coefficient is expressed as an nth platform; by calculating the evaluation coefficients of the advertisement putting effect, the advertisement performances of a plurality of platforms can be compared, the higher evaluation coefficients show that the advertisement putting on the platform obtains better effect, and the advertiser can select the platform which is most suitable for the requirement of the advertiser to carry out the advertisement putting according to the evaluation coefficients, wherein the index such as higher conversion rate or click rate is provided.
The traffic delivery management database is used for storing traffic data parameters of the advertisement plan, the advertisement delivery quantity, the traffic delivery cost and the clicking unit price of the user.
According to the invention, the advertisement click rate, conversion rate and return on investment rate of the advertisement delivery flow monitoring control system are obtained through monitoring the exposure, click rate and conversion number of the platform advertisement delivery flow in each preset time period, the advertisement delivery flow data parameters are comprehensively analyzed by weight distribution of each parameter, the effect evaluation coefficient of the advertisement flow is obtained, the effect evaluation coefficient of the advertisement flow is compared with the planned delivery effect, the advertisement delivery effect is obtained through analysis, the accurate measurement index of flow control is achieved, meanwhile, the flow conditions of different platforms are monitored through A/B test, the understanding of the user demands and the preferred layout or functions is increased, the understanding of the user behaviors and the insight user demands are facilitated, and therefore more accurate, efficient and sustainable advertisement delivery is realized, and the effectiveness of advertisements is greatly improved.
While embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention, which is also intended to be covered by the present invention.
Claims (8)
1. An advertisement delivery flow monitoring control system based on electronic commerce is characterized in that the advertisement delivery flow monitoring control system comprises: the system comprises a flow delivery management database, an advertisement flow data parameter acquisition module, an advertisement delivery flow evaluation module, a flow control module, an A/B test acquisition module, an A/B test analysis module and a visual feedback module;
the advertisement flow data parameter acquisition module is used for acquiring flow data parameters of advertisements which are put into the electronic commerce platform in each acquisition time period in preset time in the putting process, wherein the flow data parameters comprise exposure, click quantity and conversion number;
the advertisement delivery flow evaluation module is used for analyzing and obtaining an effect evaluation coefficient of advertisement flow according to the acquired flow data parameters of the advertisement in the delivery process;
the flow control module is used for comparing the acquired advertisement flow data parameters with planned advertisement flow data parameters in the flow delivery management database so as to analyze and acquire the advertisement delivery quantity when the planned effect is achieved, and analyzing and acquiring the flow increment value in unit time according to the acquired advertisement flow data parameters so as to acquire the time length required by the distance planned flow delivery effect when the planned effect is not achieved;
the visual feedback module is used for feeding back the monitored flow data parameters in the advertisement putting process to the advertiser and the platform in real time, and analyzing and generating a detailed visual report and a detailed form according to the advertisement putting flow data parameters;
the A/B test acquisition module is used for respectively monitoring flow data in the advertisement putting process of different platforms by simultaneously putting advertisements to each platform to obtain flow data parameters of the advertisements in the advertisement putting process of different platforms;
the A/B test analysis module is used for acquiring flow data parameters of advertisements in the process of putting different platforms, and further analyzing and obtaining the putting effect evaluation coefficients of the platforms;
the traffic delivery management database is used for storing traffic data parameters of the advertisement plan, the advertisement delivery quantity, traffic delivery cost and user click unit price.
2. The system of claim 1, wherein the advertisement delivery volume of the traffic delivery management database further comprises advertisement delivery volume, planned delivery volume and actual delivery volume for each acquisition period within a preset time.
3. The advertisement delivery flow monitoring and controlling system based on electronic commerce according to claim 1, wherein the advertisement flow data parameter acquisition module specifically comprises: the advertisement flow data parameter acquisition module comprises an advertisement exposure parameter acquisition unit, a user click rate acquisition unit and a conversion rate acquisition unit;
the advertisement exposure parameter acquisition unit is used for obtaining the exposure corresponding to each acquisition time period of the advertisement according to the number of times of displaying the advertisement to the audience in each acquisition time period in the preset time, and marking the exposure as E i I represents the number of the i-th acquisition period, i=1, 2, q; the user click amount acquisition unit is used for acquiring the user click times of the advertisement in the preset time in the throwing period of each acquisition time period, taking the user click times as the click amount of the advertisement corresponding to each acquisition time period, and marking the click amount as C i The method comprises the steps of carrying out a first treatment on the surface of the The conversion number acquisition unit is used for acquiring the total number of times of registration, subscription and purchase completed by a user in each acquisition time period in preset time, taking the total number of times as the conversion amount of the advertisement corresponding to each acquisition time period, and recording the conversion amount as CV i 。
4. The advertisement delivery flow monitoring and controlling system based on electronic commerce according to claim 3, wherein the specific evaluation method of the effect evaluation coefficient of the advertisement flow performs the following steps:
the first step, the obtained exposure, click quantity and conversion number of the advertisement in each acquisition time period in the preset time period are respectively substituted into a formulaFurther obtaining click rate CTR and conversion rate CR;
step two, reading the advertisement delivery quantity, click rate and set click unit price and substituting the same into a formulaAnalyzing to obtain the investment return rate psi of the advertisement, wherein ρ represents the clicking unit price of a user, ν represents the flow delivery cost, and γ represents the delivery quantity of the advertisement;
thirdly, comprehensively analyzing the effect evaluation weight factor of the advertisement delivery by weight distribution of the advertisement click rate, the conversion rate and the return on investment rate, wherein the calculation formula of the effect evaluation weight factor is delta=CTR [ mu ] 1 +CR*μ 2 +ψ*μ 3 Mu 1, mu 2 and mu 3 respectively represent the weight factor of click rate, the weight factor of conversion rate and the weight factor of return on investment, and mu 1 +μ 2 +μ 3 =1 by introducing the effect evaluation weight factor into the formulaEffect evaluation coefficient for obtaining advertisement traffic>
5. The e-commerce based advertising traffic monitoring and control system of claim 1, wherein the flow control module is configured to perform the following steps:
firstly, reading the exposure, click quantity and conversion number of the platform advertisement putting flow in each acquisition time period in a preset time period, comparing the exposure, the click quantity and the conversion number with the exposure, the click quantity and the conversion number which are obtained by a flow putting management database, and if the exposure, the click quantity and the conversion number of the platform advertisement putting flow in a certain acquisition time period are higher than the planned exposure, the click quantity and the conversion number, taking the acquisition time period as a coincidence acquisition time period;
second, screening out the corresponding acquisition timeThe actual delivery quantity of the segments is obtained from a database, the planned delivery quantity which accords with the acquisition time period is obtained from the database, and the planned delivery quantity is substituted into a formulaThereby obtaining the advertisement flow quantity eta according with the acquisition time period r ，γ r Planning For the r-th planned delivery amount according with the acquisition time period, gamma r Actual practice is that of For the actual delivery quantity of the r-th coincidence acquisition time period, lambda represents the correction coefficient of flow plan delivery, ρ r For the r-th deviation influence coefficient conforming to the planned delivery effect of the acquisition time period, ρ r The calculation formula of (2) is as follows: />γ i For the r-th advertisement delivery amount according to the acquisition time period, r represents the number of the acquisition time period, r=1, 2, k; k is the number of acquisition time periods;
thirdly, screening out advertisement flow data parameters which do not reach the planned acquisition time period, and substituting the advertisement flow data parameters into a formulaThereby obtaining the average increase value Q, phi of the flow in unit time 1 、φ 2 、φ 3 Advertisement flow rate duty ratio weights corresponding to unit exposure amount, unit click amount and unit conversion number respectively, t represents a time interval, j does not reach the number of the planned acquisition time period, j=1, 2, and m, E j Starting from the beginning Indicating the initial exposure of the advertisement in the jth period,/->Indicating the exposure of the advertisement after the end of the j-th time period,representing the initial point of the advertisement in the jth time periodQuantity of hits and/or->Indicating the click-through amount reached by the advertisement after the end of the j-th time period,/for the advertisement>Indicating the initial conversion number of the advertisement in the j-th time period,/for the advertisement>And (5) representing the conversion number reached by the advertisement when the j-th time period is ended, and calculating the time length required by the planned flow delivery effect according to the obtained flow increment value in the unit time.
6. The advertisement delivery flow monitoring and controlling system based on electronic commerce according to claim 1, wherein the a/B test acquisition module is configured to monitor exposure, click-through and conversion number of the delivery flow of each platform advertisement in each acquisition time period.
7. The advertisement delivery flow monitoring and controlling system based on electronic commerce according to claim 1, wherein the specific extraction method of the advertisement flow data parameters of each platform of the a/B test acquisition module comprises the following steps:
the first step, sequentially reading the exposure, click quantity and conversion number of each platform in each acquisition time period, analyzing to obtain the effect evaluation weight factors of each platform, and forming an advertisement putting flow effect evaluation weight factor set delta (delta) 1 ,δ 2 ,...,δ n ,...,δ g ) N represents the nth land, n=1, 2,.. n Representing an nth platform effect evaluation weight factor;
secondly, comparing the flow data parameters of the same platform advertisement in the adjacent acquisition time period in the platform advertisement delivery flow data parameter set, and substituting the flow data parameters into a formula
Obtaining average growth index theta of flow data parameters in corresponding acquisition time periods of each platform n ，E n i Indicating the exposure of the advertisement in the ith period of time of the nth plateau, +.>Indicating the exposure of the advertisement in the ith-1 time period of the nth plateau, +.>Indicating the click-through amount of the advertisement in the ith time period of the nth platform, +.>Indicating the click-through amount of advertisement in the ith-1 time period of the nth platform, +.>Representing the conversion number of the advertisement in the ith time period of the nth platform,/for the nth platform>Representing the conversion number of the advertisement in the ith-1 time period of the nth platform;
third, substituting the average growth index of the flow data parameters in the corresponding acquisition time period of each platform into a formula The advertisement delivery effect evaluation coefficient is represented as an nth platform.
8. The e-commerce based advertising traffic monitoring and control system of claim 1, wherein: the visual feedback module is used for feeding back the monitored advertisement delivery flow data index to the advertisers and the platforms in real time, arranging the advertisement delivery effect evaluation coefficients of the platforms according to the sequence from big to small, and displaying the arranged results.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117408750A (en) * | 2023-12-12 | 2024-01-16 | 广州宇中网络科技有限公司 | Network advertisement delivery method based on big data analysis |
| CN117408752A (en) * | 2023-10-19 | 2024-01-16 | 广州信日信息科技有限公司 | Advertisement flow monitoring system based on business intelligence |
| CN117422504A (en) * | 2023-10-31 | 2024-01-19 | 广州信日信息科技有限公司 | Advertisement delivery flow monitoring and controlling method and system based on electronic commerce |
| CN117422508A (en) * | 2023-10-24 | 2024-01-19 | 上海网萌网络科技有限公司 | Intelligent delivery analysis system and method based on big data |
| CN117593055A (en) * | 2023-11-21 | 2024-02-23 | 广州吴凡科技服务有限公司 | Advertisement effect intelligent analysis method and system based on big data |
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| CN117408752A (en) * | 2023-10-19 | 2024-01-16 | 广州信日信息科技有限公司 | Advertisement flow monitoring system based on business intelligence |
| CN117422508A (en) * | 2023-10-24 | 2024-01-19 | 上海网萌网络科技有限公司 | Intelligent delivery analysis system and method based on big data |
| CN117422504A (en) * | 2023-10-31 | 2024-01-19 | 广州信日信息科技有限公司 | Advertisement delivery flow monitoring and controlling method and system based on electronic commerce |
| CN117593055A (en) * | 2023-11-21 | 2024-02-23 | 广州吴凡科技服务有限公司 | Advertisement effect intelligent analysis method and system based on big data |
| CN117408750A (en) * | 2023-12-12 | 2024-01-16 | 广州宇中网络科技有限公司 | Network advertisement delivery method based on big data analysis |
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