CN113222656A - Programmed advertisement putting method, system, device, equipment and storage medium - Google Patents
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Abstract
The invention provides a programmed advertisement putting method, a system, a device, equipment and a storage medium, wherein the programmed advertisement putting method comprises the following steps: the method comprises the steps of obtaining log processing data and real-time characteristic data related to the programmed advertisements to be launched; performing characteristic processing on the log processing data and the real-time characteristic data, and estimating the click rate and the conversion rate of the programmed advertisement to be launched based on a characteristic processing result; calibrating the click rate and the conversion rate by using historical posterior data, and calculating the real bid of the programmed advertisement according to the calibrated click rate and conversion rate and the set target ROI; and performing programmed advertisement quotation to be released and releasing with the real bid price. The invention solves the problems of advertisement cold start, flow quality fluctuation, unstable bid price and the like in the programmed delivery in the prior art, thereby causing poor delivery effect.
Description
Technical Field
The present invention relates to the technical field of advertisement delivery, and in particular, to a programmed advertisement delivery method, system, device, apparatus, and storage medium.
Background
In the internet field, programmed advertisement delivery refers to a way for advertisers to automatically complete advertisement acquisition and delivery through a media platform and continuously optimize delivery effects by using feedback data in real time. The conventional programming method is to manually launch for a period of time, automatically host and launch and optimize after enough data is accumulated, and the cycle of launching cold start for the new advertisement programming becomes long and the cost becomes high; the flow quality of a media side is unstable, the effect fluctuation of a traditional model is large, automatic bidding is not facilitated, and the whole ROI is reduced.
Disclosure of Invention
The implementation of the invention provides a programmed advertisement putting method, a system, a device, equipment and a storage medium, which solve the problems of cold start of advertisements, fluctuation of flow quality, unstable bid price and the like in programmed putting in the prior art, thereby causing the putting effect to be poor.
In order to achieve the purpose, the invention adopts the following technical scheme:
a programmed advertising method, comprising the steps of:
acquiring log processing data and real-time characteristic data related to the programmed advertisement to be launched;
performing characteristic processing on the log processing data and the real-time characteristic data, and estimating the click rate and the conversion rate of the programmed advertisement to be launched based on a characteristic processing result;
calibrating the click rate and the conversion rate by using historical posterior data, and calculating the real bid of the programmed advertisement according to the calibrated click rate and conversion rate and the set target ROI;
and performing programmed advertisement quotation to be released and releasing with the real bid price.
As a further improvement of the present invention, the log processing data includes context scenes, advertisement behavior data, and media data;
the real-time features use scene features, advertisement features, and media features.
As a further improvement of the invention, the feature engineering processing package is to discretize all real-time features.
As a further improvement of the method, the step of predicting the click rate and the conversion rate of the programmed advertisement to be launched based on the feature processing result means that the feature of discretization processing is subjected to automatic feature cross processing by adopting a DeepFM model to obtain the click rate and the conversion rate of the predicted programmed advertisement.
As a further improvement of the present invention, the calibration of click through and conversion using historical a posteriori data comprises:
and carrying out order-preserving regression on the estimated values of the click rate and the conversion rate of the estimated programmed advertisement by using the real posterior data of the delivered advertisement.
As a further improvement of the invention, the following steps are adopted for calculating the real bid of the programmed advertisement:
setting a target ROI and calculating an accurate bid based on the calibrated estimated CTR/IVR, wherein the specific formula is as follows:
wherein bid is bid, pivr/pctr is a click rate value and a conversion rate value after calibration respectively, and ROI is a set target return on investment; price is price.
A programmatic advertising system, comprising:
the acquisition module is used for acquiring log processing data and real-time characteristic data related to the programmed advertisement to be launched;
the pre-estimation module is used for performing characteristic processing on the log processing data and the real-time characteristic data and pre-estimating the click rate and the conversion rate of the programmed advertisement to be launched based on the characteristic processing result;
the bid module is used for calibrating the click rate and the conversion rate by utilizing historical posterior data, setting a target ROI according to the calibrated click rate and conversion rate and calculating the real bid of the programmed advertisement;
and the releasing module is used for performing programmed advertisement quotation to be released and releasing the programmed advertisement with the real bid price.
A programmed advertising device comprising:
a predictive model, comprising:
the log processing unit is used for acquiring log processing data related to the programmed advertisements to be launched;
the real-time characteristic unit is used for acquiring real-time characteristic data related to the programmed advertisement to be launched;
the characteristic engineering unit is used for discretizing all real-time characteristics;
the depth estimation unit is used for carrying out automatic characteristic cross processing on the discretization processed characteristics by adopting a DeepFM model to obtain the click rate and the conversion rate of the estimated programmed advertisement;
and an intelligent bidding model, comprising:
the order-preserving regression unit is used for carrying out order-preserving regression on the estimated values of the click rate and the conversion rate of the estimated programmed advertisement by utilizing the real posterior data of the delivered advertisement,
and the calculation bidding unit is used for calculating the real bidding of the programmed advertisement according to the calibrated click rate and conversion rate and the set target ROI.
An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the programmatic advertisement delivery method when executing the computer program.
A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the programmatic advertising method.
The invention has the beneficial effects that:
in order to solve the problem of cold start of a new advertisement, the delivery is divided into two stages, namely a cold start stage and a delivery optimization stage, wherein in the cold start stage, due to insufficient data such as conversion and the like, the click rate CTR is used for predicting a model to guide the bid, the conversion data is accumulated to a certain magnitude, the advertisement delivery enters the delivery optimization stage, and the conversion rate IVR is used for predicting the model to guide the bid. The new ad sets a transition volume threshold to control the stage at which the current programmatic placement is. The invention provides a whole set of solution for programmed advertisement putting, which estimates an intelligent bid from a model, introduces two-stage optimization and solves the problem of cold start of a new advertisement.
Furthermore, all the characteristics are subjected to discretization processing on the model, and the problem of unstable and fluctuating flow is solved.
Drawings
FIG. 1 is a flowchart of a programmatic advertisement delivery method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a programmed advertisement delivery apparatus according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a programmed advertising system;
fig. 4 is a schematic structural diagram of an electronic device.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For the convenience of clearly describing the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", and the like are used to distinguish the same items or similar items with basically the same functions or actions, and those skilled in the art can understand that the words "first", "second", and the like do not limit the quantity and execution order.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The term "comprises/comprising" when used herein refers to the presence of a feature, element or component, but does not preclude the presence or addition of one or more other features, elements or components.
The present invention will be described in further detail with reference to the accompanying drawings and examples. The examples are given solely for the purpose of illustration and are not intended to limit the scope of the invention.
In order to solve the problem of cold start of a new advertisement, the delivery is divided into two stages, namely a cold start stage and a delivery optimization stage, wherein in the cold start stage, due to insufficient data such as conversion and the like, the click rate CTR is used for predicting a model to guide the bid, the conversion data is accumulated to a certain magnitude, the advertisement delivery enters the delivery optimization stage, and the conversion rate IVR is used for predicting the model to guide the bid. The new ad sets a transition volume threshold to control the stage at which the current programmatic placement is.
Specifically, as shown in fig. 1, a first object of the present invention is to provide a method for programmatically delivering advertisements, which includes the following steps:
acquiring log processing data and real-time characteristic data related to the programmed advertisement to be launched;
performing characteristic processing on the log processing data and the real-time characteristic data, and estimating the click rate and the conversion rate of the programmed advertisement to be launched based on a characteristic processing result;
calibrating the click rate and the conversion rate by using historical posterior data, and calculating the real bid of the programmed advertisement according to the calibrated click rate and conversion rate and the set target ROI;
and performing programmed advertisement quotation to be released and releasing with the real bid price.
The method aims to solve the problems of large flow quality difference, large model estimation fluctuation, unstable bid price and the like. In the estimation model, all continuous features can be discretized, the continuous features cannot be directly used, and fluctuation is prevented; and after model estimation, carrying out posterior calibration on the estimated value, and carrying out calibration by using a sequence-preserving regression algorithm.
Wherein the log processing data comprises contextual scenes, advertising behavior data, and media data; the real-time features use scene features, advertisement features, and media features.
The feature engineering processing package is to discretize all real-time features. The method for estimating the click rate and the conversion rate of the programmed advertisement to be launched based on the feature processing result means that the DeepFM model is adopted to perform automatic feature cross processing on the discretization processed features to obtain the estimated click rate and the estimated conversion rate of the programmed advertisement.
Calibrating click through and conversion using historical a posteriori data includes: and carrying out order-preserving regression on the estimated values of the click rate and the conversion rate of the estimated programmed advertisement by using the real posterior data of the delivered advertisement.
Setting a target ROI and calculating an accurate bid based on the calibrated estimated CTR/IVR, wherein price represents the unit price of each conversion,
the bid is thus formulated as follows:
for example: setting our target ROI at the present stage to 10%, price per conversion price to 5$, and estimated PIVR of the current advertisement request model to 0.1, so that bid $ (0.1 × 5)/(1+0.1) $ 0.45 at the present stage.
As shown in fig. 2, a second object of the present invention is to provide a programmed advertisement delivery device, the system is mainly divided into a large number of modules: and the model pre-estimation and intelligent bidding module is used for pre-estimating according to two models of CTR and IVR, the CTR pre-estimates the click rate of the advertisement according to the context scene, the advertisement data and the media data, and the IVR expresses the pre-estimated advertisement conversion rate in the same way. The CTR and the IVR respectively correspond to model estimated values of two stages of the advertisement; the intelligent bidding model carries out model calibration by utilizing historical posterior data according to the model estimated value, and then sets ROI to calculate the real bidding.
Wherein, the prediction model comprises:
the log processing unit is used for acquiring log processing data related to the programmed advertisements to be launched;
the real-time characteristic unit is used for acquiring real-time characteristic data related to the programmed advertisement to be launched;
the characteristic engineering unit is used for discretizing all real-time characteristics;
the depth estimation unit is used for carrying out automatic characteristic cross processing on the discretization processed characteristics by adopting a DeepFM model to obtain the click rate and the conversion rate of the estimated programmed advertisement;
an intelligent bidding model, comprising:
the order-preserving regression unit is used for carrying out order-preserving regression on the estimated values of the click rate and the conversion rate of the estimated programmed advertisement by utilizing the real posterior data of the delivered advertisement,
and the calculation bidding unit is used for calculating the real bidding of the programmed advertisement according to the calibrated click rate and conversion rate and the set target ROI.
The model pre-estimation module comprises CTR pre-estimation and IVR pre-estimation, and advertisement behavior data within 30 days are used; the feature use scene features, the advertisement features and the media features are 121 in total, the feature latitude is ten million, and in order to eliminate the influence of unstable flow, all the features are discretized, for example, the display amount of the advertisement in one week is subjected to barreling; the model uses the deep FM model and has the advantage of automatic feature crossing.
The intelligent bidding module: firstly, the real posterior data of the advertisement is utilized to carry out order-preserving regression on the predicted value of the pre-estimated model, and finally the real bid price is calculated.
As shown in FIG. 2, the module is largely divided into two block model projections and intelligent bids. Model prediction is carried out according to the characteristics required by the log and the real-time data extraction model, and PCTR and PIVR are input into the model prediction. The intelligent bidding firstly carries out order-preserving regression according to PCTR and PIVR estimated by the model, then calculates the real bidding according to the set target ROI, and then carries out the bidding.
As shown in fig. 3, another object of the present invention is to provide a programmed advertisement delivery system, which includes:
a programmatic advertising system, comprising: the acquisition module is used for acquiring log processing data and real-time characteristic data related to the programmed advertisement to be launched;
the pre-estimation module is used for performing characteristic processing on the log processing data and the real-time characteristic data and pre-estimating the click rate and the conversion rate of the programmed advertisement to be launched based on the characteristic processing result;
the bid module is used for calibrating the click rate and the conversion rate by utilizing historical posterior data, setting a target ROI according to the calibrated click rate and conversion rate and calculating the real bid of the programmed advertisement;
and the releasing module is used for performing programmed advertisement quotation to be released and releasing the programmed advertisement with the real bid price.
A fourth object of the present invention is to provide an electronic device, as shown in fig. 4, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the programmed advertisement delivery method when executing the computer program.
A fifth object of the present invention is to provide a computer-readable storage medium, which stores a computer program, which, when executed by a processor, implements the steps of the programmatic advertisement delivery method.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A programmed advertisement delivery method, comprising the steps of:
acquiring log processing data and real-time characteristic data related to the programmed advertisement to be launched;
performing characteristic processing on the log processing data and the real-time characteristic data, and estimating the click rate and the conversion rate of the programmed advertisement to be launched based on a characteristic processing result;
calibrating the click rate and the conversion rate by using historical posterior data, and calculating the real bid of the programmed advertisement according to the calibrated click rate and conversion rate and the set target ROI;
and performing programmed advertisement quotation to be released and releasing with the real bid price.
2. The method of claim 1,
the log processing data comprises context scenes, advertisement behavior data and media data;
the real-time features use scene features, advertisement features, and media features.
3. The method of claim 1,
the feature engineering processing package is to discretize all real-time features.
4. The method of claim 1,
the method for estimating the click rate and the conversion rate of the programmed advertisement to be launched based on the feature processing result means that the DeepFM model is adopted to perform automatic feature cross processing on the discretization processed features to obtain the estimated click rate and the estimated conversion rate of the programmed advertisement.
5. The method of claim 1,
calibrating click through and conversion using historical a posteriori data includes:
and carrying out order-preserving regression on the estimated values of the click rate and the conversion rate of the estimated programmed advertisement by using the real posterior data of the delivered advertisement.
6. The method of claim 1,
the following steps are adopted for calculating the real bid of the programmed advertisement:
setting a target ROI and calculating an accurate bid based on the calibrated estimated CTR/IVR, wherein the specific formula is as follows:
wherein bid is bid, pivr/pctr is a click rate value and a conversion rate value after calibration respectively, and ROI is a set target return on investment; price is the unit price per conversion.
7. A programmatic advertisement delivery system, comprising:
the acquisition module is used for acquiring log processing data and real-time characteristic data related to the programmed advertisement to be launched;
the pre-estimation module is used for performing characteristic processing on the log processing data and the real-time characteristic data and pre-estimating the click rate and the conversion rate of the programmed advertisement to be launched based on the characteristic processing result;
the bid module is used for calibrating the click rate and the conversion rate by utilizing historical posterior data, setting a target ROI according to the calibrated click rate and conversion rate and calculating the real bid of the programmed advertisement;
and the releasing module is used for performing programmed advertisement quotation to be released and releasing the programmed advertisement with the real bid price.
8. A programmed advertising device, comprising:
a predictive model, comprising:
the log processing unit is used for acquiring log processing data related to the programmed advertisements to be launched;
the real-time characteristic unit is used for acquiring real-time characteristic data related to the programmed advertisement to be launched;
the characteristic engineering unit is used for discretizing all real-time characteristics;
the depth estimation unit is used for carrying out automatic characteristic cross processing on the discretization processed characteristics by adopting a DeepFM model to obtain the click rate and the conversion rate of the estimated programmed advertisement;
and an intelligent bidding model, comprising:
the order-preserving regression unit is used for carrying out order-preserving regression on the estimated values of the click rate and the conversion rate of the estimated programmed advertisement by utilizing the real posterior data of the delivered advertisement,
and the calculation bidding unit is used for calculating the real bidding of the programmed advertisement according to the calibrated click rate and conversion rate and the set target ROI.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the programmatic advertisement delivery method of any one of claims 1-7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the programmatic advertising method according to any one of claims 1 to 7.
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| CN114757717B (en) * | 2022-05-10 | 2023-05-12 | 青岛自成一派教育科技有限公司 | Price adjustment method and price adjustment system for bid advertisement |
| CN116823353A (en) * | 2023-08-29 | 2023-09-29 | 阿里巴巴(成都)软件技术有限公司 | Method and equipment for predicting advertisement putting effect |
| CN116823353B (en) * | 2023-08-29 | 2024-01-19 | 阿里巴巴(成都)软件技术有限公司 | Method and equipment for predicting advertisement putting effect |
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