CN112150219A - Online advertisement delivery system and use method thereof - Google Patents
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Abstract
The invention provides an online advertisement delivery system and a using method thereof, and the online advertisement delivery system comprises a user tag matching module, a CTR estimation module, an advertisement sequencing module, a frequency control module and an advertisement delivery module, wherein advertisements generated by the system are used for being delivered to various advertisement display devices or various mobile terminals, the system can automatically identify behavior data of users through the user tag module, analyze unique user tags of the refined users, match the user tags with the advertisement tags to select advertisements most suitable for the corresponding users, send the advertisements to the CTR estimation module, send the advertisements to the advertisement sequencing module for processing, and the advertisement sequencing module can preferentially send the advertisements most suitable for the users to the advertisement delivery module and then send the advertisements to the advertisement display devices. The method can well ensure high accuracy of advertisement putting, and can accurately put the advertisement to advertisement audiences with demands, so that the investment return rate is high, and the method well meets the increasingly developed market demands.
Description
Technical Field
The invention relates to the technical field of internet, in particular to an online advertisement delivery system and a using method thereof.
Background
The online advertisement putting is internet advertisement putting, and the internet advertisement is put on the network through a network advertisement platform. A high-tech advertisement operation mode is to publish or publish advertisement on the Internet by using advertisement banner, text link and multimedia method on website and to transmit to Internet user through network.
Compared with the traditional four-large-size broadcast media (newspaper, magazine, television and radio) advertisement and the outdoor advertisement which is prepared by the blue-green broadcast, the internet advertisement has the unique advantages and is an important part for implementing the modern marketing media strategy. The Internet is a brand new advertising medium, has the highest speed and ideal effect, is a good way for medium and small enterprises to expand and develop greatly, and is particularly suitable for companies which widely develop international business.
The existing online advertisement delivery is delivered through an online advertisement delivery system, and the existing online advertisement delivery system has the main problems that: the accuracy of advertisement putting is poor, can not accurate putting to the advertisement audience who has the demand, and the problem that the advertisement of low accuracy put leads to is that the putting effect is poor, and the return on investment rate is low, still can arouse simultaneously that user's aversion leads to the not sustainable development of advertising action, can't be fine satisfies the market demand that develops day by day.
Disclosure of Invention
In order to solve the problems, the invention adopts the following technical scheme: an online advertising system, comprising: the system comprises a user tag matching module, a CTR estimation module, an advertisement sequencing module, a frequency control module and an advertisement issuing module;
the output end of the user tag matching module is connected with the input end of the CTR pre-estimation module, the output end of the CTR pre-estimation module is connected with the input end of the advertisement sorting module, the output end of the advertisement sorting module is connected with the input end of the frequency control module, and the output end of the frequency control module is connected with the output end of the advertisement issuing module.
Further, the user tag matching module is used for analyzing and refining the behavior data generated by the user to generate the adjectives with different characteristics to form user tags, matching and comparing the user tags with the advertisement tags to find out a batch of advertisements with the maximum similarity, and then sending the advertisements to the CTR estimation module.
Further, the CTR estimation module is configured to receive a batch of advertisements with the largest similarity sent by the user tag matching module, predict whether the user clicks or does not click on the click condition of each advertisement, screen out a batch of advertisements with the largest click probability, and input the batch of advertisements into the advertisement sorting module for further processing.
Further, the advertisement sorting module is configured to receive the advertisement sent by the CTR estimation module, sort the advertisements according to the potential revenue each time the advertisement is displayed, sort the advertisements with higher potential revenue at the top, and input the sorted advertisement list to the frequency control module for further processing.
Further, the frequency control module is used for receiving the advertisements sent by the advertisement sorting module, then controlling the times of seeing an advertisement in a specified time through frequency, and inputting the advertisements meeting the conditions to the advertisement issuing module.
Further, the advertisement issuing module is used for receiving the advertisements sent by the frequency control module and then issuing the advertisements to each advertisement display device through a network.
An online advertisement delivery method which is delivered by any one of the advertisement delivery systems comprises the following specific steps:
s1, matching advertisements according to user tags;
s2, screening advertisements according to the CTR estimated value;
s3, ordering the advertisements according to the potential income displayed each time;
and S4, determining whether to issue the advertisement according to frequency control.
Further, in step S2, the CTR estimates the relevance of the advertisement, the historical click rate of the advertisement, the historical performance of the account, the credit of the promotion merchant, the loading speed of the landing page, the relevance of the landing page, and the stay time of the landing page.
Further, in step S3, the advertisements are ranked according to the potential revenue each time the advertisement is displayed, and the advertisement with the more potential revenue is ranked the top. The potential revenue is represented by an index eCPM, which is calculated as follows: eCPM is Price × CTR × 1000, where eCPM is revenue for displaying thousands of times, Price is bid for displaying the advertisement, and CTR is the predicted value of CTR calculated in step S2.
Further, in step S4, the frequency control is used to control the number of times an advertisement is seen within a specified time, and the frequency control includes a hard control and a soft control, where the hard control refers to the total number of times that the same user can display the same advertisement or multiple advertisements at most within the specified time, and after the total number of times, the advertisement is not displayed at all within a certain time. Whereas soft control means that the accumulation of the number of impressions only reduces the probability of the same advertisement appearing.
The invention has the beneficial effects that: the advertisements generated by the system are used for being delivered to various advertisement display devices or various mobile terminals, such as mobile phone terminals or computer terminals. The system can automatically identify the behavior data of the user through the user label module, analyze the unique user label of the user after extraction, match the user label with the advertisement label to select the advertisement which is most suitable for the corresponding user, then send the advertisements to the CTR estimation module, further select the advertisement with the largest click probability through the CTR estimation module, then send the advertisement to the advertisement sorting module for processing, the advertisement sorting module can preferentially sort the advertisement which is most matched with the user, the advertisement with the highest profit is sorted at the front, then send the sorted advertisement list to the frequency control module for processing, finally send the processed advertisement list to the advertisement issuing module, and send the processed advertisement list to each advertisement display device. The method can well ensure high accuracy of advertisement putting, and can accurately put the advertisement to advertisement audiences with demands, so that the investment return rate is high, and the method well meets the increasingly developed market demands.
Drawings
The figures further illustrate the invention, but the examples in the figures do not constitute any limitation of the invention.
FIG. 1 is a block diagram illustrating a connection of modules of an online advertisement delivery system according to an embodiment;
fig. 2 is a flowchart of an online advertisement delivery method according to an embodiment.
Detailed Description
The technical solutions of the present invention will be further described below with reference to the accompanying drawings of the embodiments of the present invention, and the present invention is not limited to the following specific embodiments. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
As shown in fig. 1, an online advertisement delivery system includes: the system comprises a user tag matching module 101, a CTR pre-estimation module 102, an advertisement sequencing module 103, a frequency control module 104 and an advertisement issuing module 105;
the output end of the user tag matching module 101 is connected with the input end of the CTR estimation module 102, the output end of the CTR estimation module 102 is connected with the input end of the advertisement sorting module 103, the output end of the advertisement sorting module 103 is connected with the input end of the frequency control module 104, and the output end of the frequency control module 104 is connected with the output end of the advertisement issuing module 105.
Specifically, the user tag matching module 101 is configured to analyze and refine behavior data generated by a user to generate words with different characteristics to form user tags, match and compare the user tags with advertisement tags to find a batch of advertisements with the maximum similarity, and send the advertisements to the CTR estimation module 102, the CTR estimation module 102 is configured to receive a batch of advertisements with the maximum similarity sent by the user tag matching module 101, predict whether the user clicks or does not click on the clicking condition of each advertisement, screen out a batch of advertisements with the maximum clicking probability, and input the batch of advertisements into the advertisement ranking module 103 for further processing, the advertisement ranking module 103 is configured to receive the advertisements sent by the CTR estimation module 102, rank the advertisements according to potential revenue displayed each time, and rank the advertisements with higher potential revenue at the top, and inputting the sorted advertisement list into the frequency control module 104 for further processing, wherein the frequency control module 104 is configured to receive the advertisement sent by the advertisement sorting module 103, then control the number of times of seeing an advertisement in a specified time through frequency, and input an advertisement meeting the conditions into the advertisement issuing module 105, and the advertisement issuing module 105 is configured to receive the advertisement sent by the frequency control module 104, and then issue the advertisement to each advertisement display device through a network.
That is, the advertisement generated by the system is used for being delivered to various advertisement display devices or various mobile terminals, such as a mobile phone terminal or a computer terminal. That is to say, the system can automatically identify the behavior data of the user through the user tag module, then analyze the unique user tag of the user after extraction, then match the user tag with the advertisement tag to select the advertisement which is most suitable for the corresponding user, then send the batch of advertisements to the CTR estimation module 102, further select the advertisement with the largest click probability through the CTR estimation module 102, then send the advertisement to the advertisement sorting module 103 for processing, that is to say, the advertisement sorting module 103 can preferentially sort the advertisement which is most matched with the user and has the highest profit in the front, then send the sorted advertisement list to the frequency control module 104 for processing, finally send to the advertisement issuing module 105, and then send to each advertisement display device. Therefore, the method can well ensure high accuracy of advertisement delivery, and can accurately deliver the advertisement to advertisement audiences with demands, so that the investment return rate is high, and the increasingly developed market demands are well met. Therefore, the frequency control of the frequency control module 104 effectively avoids user fatigue, anger and advertisement blind areas, increases the number of the audience, and avoids the limited budget of the advertiser always consumed on the advertisements continuously displayed to the same group of people, so that more audiences can see the advertisements, thereby improving CTR and CVR; through CTR estimation, the accuracy of bidding in bidding ranking and bidding is effectively improved, and a basis is provided for programmed purchase.
As shown in fig. 2, an online advertisement delivery method, which is delivered by any one of the above advertisement delivery systems, includes the following specific steps:
s1, matching advertisements according to the user tags.
Specifically, the advertisement type preferred by each user is determined according to the advertisement clicked by the user each time, so that different user tags are determined, then the user tags are placed in the user tag matching module 101, and then the user tags are matched with the advertisement tags, so that different users corresponding to different advertisements can be matched quickly.
And S2, screening advertisements according to the CTR estimated value.
Specifically, the CTR pre-estimation comprises the relevance of the advertisement, the historical click rate of the advertisement, the historical performance of an account, the credit of a promotion merchant, the loading speed of landing pages, the relevance of the landing pages and the stay time of the landing pages.
And S3, carrying out advertisement sequencing according to the potential revenue displayed each time.
Specifically, the advertisements are ranked according to the potential revenue for each presentation, with the more recent advertisements ranked first. The potential revenue is represented by an index eCPM, which is calculated as follows: eCPM is Price × CTR × 1000, where eCPM is revenue for displaying thousands of times, Price is bid for displaying the advertisement, and CTR is the predicted value of CTR calculated in step S2.
And S4, determining whether to issue the advertisement according to frequency control.
Specifically, the number of times an advertisement is seen within a specified time is controlled by frequency, and the frequency control comprises hard control and soft control, wherein the hard control refers to the total number of times that the same advertisement or multiple advertisements can be displayed at most within the specified time for the same user, and the advertisement is not displayed within a period of time after the total number of times is reached. Whereas soft control means that the accumulation of the number of impressions only reduces the probability of the same advertisement appearing.
That is, by the method, user fatigue, irritation and advertisement blind areas can be effectively avoided, the number of the contacted audiences is increased, the limited budget of an advertiser is prevented from being always consumed to continuously show advertisements to the same group of people, so that more audiences can see the advertisements, and the CTR (conversion rate) and the CVR (conversion rate) are improved; through CTR estimation, the accuracy of bidding in bidding ranking and bidding is effectively improved, and a basis is provided for programmed purchase.
Example 1
An online advertisement delivery method which is delivered by any one of the advertisement delivery systems comprises the following specific steps:
s1, matching advertisements according to the user tags.
Specifically, behavioral data generated by a user are analyzed and refined to generate words with different characteristics to form user target characteristic vectors, similarity is calculated by using a similarity calculation method in combination with the advertisement target characteristic vectors, and the first N advertisements with the maximum similarity are taken as input of the next step. The similarity calculation method may use cosine similarity, pearson coefficient, adjusted cosine similarity, or the like.
And S2, screening advertisements according to the CTR estimated value.
Specifically, a CTR estimation model is established through feature engineering so as to calculate a CTR estimation value, a batch of advertisements with the maximum click probability are screened out and used as input of the next step, wherein the CTR estimation model comprises LR mass high latitude discrete features, a gradient lifting decision tree, FM, FFM and the like.
And S3, carrying out advertisement sequencing according to the potential revenue displayed each time.
Specifically, the higher the potential revenue, the top ranked the advertisement. The potential revenue is represented using the index eCPM (thousands of revenues shown).
And S4, determining whether to issue the advertisement according to frequency control.
In particular, the number of times an advertisement or similar advertisement is seen within a specified time is controlled by the frequency. The frequency control comprises hard control and soft control, wherein the hard control refers to the total times that the same advertisement or a plurality of advertisements can be displayed at most in a specified time for the same user, and the advertisements are not displayed in a period of time after the times are reached. For example, a user is limited to see an advertisement 3 times a day at most, and no advertisement is shown on the day after 3 times; the soft control means that the accumulation of the showing times only reduces the probability of the same advertisement, but does not show the advertisement completely after reaching a certain number of times.
That is, by the method, user fatigue, irritation and advertisement blind areas can be effectively avoided, the number of the contacted audiences is increased, the limited budget of an advertiser is prevented from being always consumed to continuously show advertisements to the same group of people, so that more audiences can see the advertisements, and the CTR (conversion rate) and the CVR (conversion rate) are improved; through CTR estimation, the accuracy of bidding in bidding ranking and bidding is effectively improved, and a basis is provided for programmed purchase.
In summary, the above embodiments are not intended to be limiting embodiments of the present invention, and modifications and equivalent variations made by those skilled in the art based on the spirit of the present invention are within the technical scope of the present invention.
Claims (10)
1. An online advertising system, comprising: the system comprises a user tag matching module, a CTR estimation module, an advertisement sequencing module, a frequency control module and an advertisement issuing module;
the output end of the user tag matching module is connected with the input end of the CTR pre-estimation module, the output end of the CTR pre-estimation module is connected with the input end of the advertisement sorting module, the output end of the advertisement sorting module is connected with the input end of the frequency control module, and the output end of the frequency control module is connected with the output end of the advertisement issuing module.
2. The online advertising system according to claim 1, wherein: the user tag matching module is used for analyzing and refining the behavior data generated by the user to generate the adjectives with different characteristics to form user tags, matching and comparing the user tags with the advertisement tags to find out a batch of advertisements with the maximum similarity, and then sending the advertisements to the CTR estimation module.
3. The online advertising system according to claim 2, wherein: the CTR pre-estimating module is used for receiving a batch of advertisements with the maximum similarity sent by the user tag matching module, predicting whether the user clicks or does not click according to the clicking condition of each advertisement, screening out a batch of advertisements with the maximum clicking probability, and inputting the batch of advertisements into the advertisement sorting module for further processing.
4. The online advertising system according to claim 3, wherein: the advertisement sorting module is used for receiving the advertisements sent by the CTR estimation module, then sorting the advertisements according to the potential income displayed each time, the advertisements with higher potential income are ranked in the top, and the sorted advertisement list is input into the frequency control module for further processing.
5. The online advertising system according to claim 4, wherein: the frequency control module is used for receiving the advertisements sent by the advertisement sequencing module, then controlling the times of seeing an advertisement in a specified time through frequency, and inputting the advertisements meeting the conditions to the advertisement issuing module.
6. The online advertising system according to claim 5, wherein: the advertisement issuing module is used for receiving the advertisements sent by the frequency control module and then issuing the advertisements to each advertisement display device through a network.
7. An online advertisement delivery method is delivered through any one of the advertisement delivery systems, and is characterized by comprising the following specific steps:
s1, matching advertisements according to user tags;
s2, screening advertisements according to the CTR estimated value;
s3, ordering the advertisements according to the potential income displayed each time;
and S4, determining whether to issue the advertisement according to frequency control.
8. The online advertising method according to claim 7, wherein: in step S2, the CTR estimates the relevance of the advertisement, the historical click rate of the advertisement, the historical performance of the account, the credit of the promotion merchant, the loading speed of the landing page, the relevance of the landing page, and the stay time of the landing page.
9. The online advertising method according to claim 7, wherein: in step S3, the advertisements are ranked according to the potential revenue each time they are shown, and the advertisements with the potential revenue are ranked the first. The potential revenue is represented by an index eCPM, which is calculated as follows: eCPM is Price × CTR × 1000, where eCPM is revenue for displaying thousands of times, Price is bid for displaying the advertisement, and CTR is the predicted value of CTR calculated in step S2.
10. The online advertising method according to claim 9, wherein: in step S4, the frequency control is used to control the number of times an advertisement is seen within a specified time, and the frequency control includes a hard control and a soft control, where the hard control refers to the total number of times that the same user can display the same advertisement or multiple advertisements at most within the specified time, and after the total number of times is reached, the advertisement is not displayed within a period of time. Whereas soft control means that the accumulation of the number of impressions only reduces the probability of the same advertisement appearing.
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