CN112561589B - Advertisement delivery method, device and storage medium - Google Patents
Advertisement delivery method, device and storage medium Download PDFInfo
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- CN112561589B CN112561589B CN202011511596.3A CN202011511596A CN112561589B CN 112561589 B CN112561589 B CN 112561589B CN 202011511596 A CN202011511596 A CN 202011511596A CN 112561589 B CN112561589 B CN 112561589B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
- G06Q30/0271—Personalized advertisement
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0242—Determining effectiveness of advertisements
- G06Q30/0244—Optimization
Abstract
The invention relates to the technical field of advertisement putting, and discloses an advertisement putting method, an advertisement putting device and a storage medium, wherein the method comprises the steps of determining first attribute distribution of offline audience population when a specified type of advertisement is played online; determining at least one set of second attribute distributions for an online audience population of a specified class of advertisements; determining a third attribute distribution of the target audience crowd of the specified advertisement class according to the first attribute distribution and at least one group of second attribute distributions so as to launch the specified advertisement class according to the third attribute distribution; the attribute distribution comprises the distribution of age groups or age groups and genders, and the target audience population is preset or determined according to the age groups of the offline audience population and the age groups of the online audience population. The method, the device and the storage medium disclosed by the invention can be used for determining the attribute distribution of the specified advertisements in the audience population, so that the accurate advertisement delivery to the audience population is facilitated, and the conversion rate of the delivered advertisements is improved.
Description
Technical Field
The invention relates to the technical field of advertisement putting, in particular to an advertisement putting method, an advertisement putting device and a storage medium.
Background
Since the advertisement is a means for distributing information on goods or services to consumers or users through advertisement media in a pay-per-view manner, the cost required for advertisement delivery is relatively high, and it is expected by each advertiser how to achieve accurate advertisement delivery and obtain the greatest advertising benefit as much as possible.
In order to realize accurate advertisement delivery, some advertisers often analyze and count the advertisement attention of the people under the line to obtain the attention of the people to various advertisements, and deliver the advertisements based on the attention of the people to various advertisements.
However, because the data source is single, the statistical advertisement attention data often cannot accurately reflect the actual attention of the crowd to various advertisements, and therefore the crowd cannot be accurately delivered when advertisement delivery is performed, and the expected delivery effect is difficult to achieve.
Disclosure of Invention
In order to solve the problem that the expected advertisement putting effect is difficult to achieve in the prior art, the invention aims to provide an advertisement putting method, an advertisement putting device and a storage medium, so that the advertisement is accurately put to the crowd in the designated area, and the conversion rate of the advertisement is improved.
In a first aspect, the present invention provides an advertisement delivery method, including:
determining first attribute distribution of offline audience population when the specified type of advertisement is played online;
determining at least one second set of attribute distributions for an online audience population for the specified class of advertisements;
determining a third attribute distribution of a target audience crowd of the specified advertisement class according to the first attribute distribution and the at least one group of second attribute distributions so as to deliver the specified advertisement class according to the third attribute distribution;
wherein, attribute distribution includes the distribution of age bracket or age bracket and gender, target audience crowd is predetermined, or according to off-line audience crowd's age bracket with on-line audience crowd's age bracket confirms.
Through the design, the first attribute distribution of the offline audience population and the second attribute distribution of the online audience population of the specified type advertisement are determined when the specified type advertisement is played online, and then the third attribute distribution of the target audience population of the specified type advertisement is determined according to the first attribute distribution and the second attribute distribution.
In one possible design, the determining a third attribute distribution of the target audience population for the specified class of ads according to the first attribute distribution and the at least one set of second attribute distributions includes:
calculating according to the first attribute distribution and each group of attribute distribution in the at least one group of second attribute distribution to obtain at least one group of third attribute distribution of the target audience crowd of the specified type of advertisement;
and selecting one group with the largest variance of the attribute distribution from the at least one group of third attribute distributions.
Based on the above disclosure, a group with the largest variance of the attribute distribution in the third attribute distribution is selected as the third attribute distribution of the target audience population of the specified class advertisement, so that the discrimination of the audience population is improved, and the advertisement is conveniently and accurately delivered.
In one possible design, the determining a third attribute distribution of the target audience population for the specified class of ads according to the first attribute distribution and the at least one set of second attribute distributions includes:
selecting a group of second attribute distributions with the maximum variance of the attribute distributions from the at least one group of second attribute distributions;
and calculating third attribute distribution of target audience population of the specified advertisement according to the first attribute distribution and the selected group of second attribute distributions.
Based on the above disclosure, since a group of second attribute distributions with the largest variance of the attribute distributions is selected, the calculated distribution situation difference of the target audience population of the specified advertisement is more obvious, so as to accurately deliver the advertisement according to the distribution situation of the audience population.
In one possible design, the determining a third attribute distribution of the target audience population for the specified class of ads according to the first attribute distribution and the at least one set of second attribute distributions includes:
calculating fourth attribute distribution of the online audience crowd of the specified class of advertisements according to the at least one group of second attribute distribution;
and calculating the third attribute distribution of the target audience crowd of the specified advertisement according to the first attribute distribution and the fourth attribute distribution.
Based on the disclosed content, the fourth attribute distribution of the on-line audience crowd of the appointed advertisement is calculated according to at least one group of second attribute distribution, then the third attribute distribution of the target audience crowd of the appointed advertisement is calculated according to the first attribute distribution and the fourth attribute distribution, and the third attribute distribution of the target audience crowd of the appointed advertisement is obtained due to the fact that the second attribute distribution of the on-line audience crowd of all the appointed advertisements is comprehensively considered, so that the attribute distribution of the audience crowd of the appointed advertisement can be accurately reflected, and the advertisement can be accurately delivered to the audience crowd when the advertisement is delivered.
In one possible design, the attribute distribution includes: the proportion of the number of audience groups in each age group to the number of all audience groups; or
The attribute distribution includes: the proportion of the number of the audience crowd of each age group corresponding to different genders to the number of all the audience crowd.
In one possible design, taking any one of the at least one set of second attribute distributions as an example, the first attribute distribution is a first age group distribution, and the any one of the second attribute distributions is any one of second age group distributions;
performing an operation according to the first attribute distribution and each of the at least one group of second attribute distributions to obtain at least one group of third attribute distributions of the target audience population of the specified type of advertisement, including:
determining a first age endpoint value and a second age endpoint value from the first age group distribution and the any second age group distribution, wherein the first age endpoint value is the smallest age value in the first age group distribution and the any second age group distribution, and the second age endpoint value is the largest age value in the first age group distribution and the any second age group distribution;
carrying out age section division based on the first age end point value and the second age end point value to obtain an age section corresponding to the target audience crowd, or taking a preset age section as the age section corresponding to the target audience crowd;
and calculating the third age group distribution of the target audience crowd of the specified advertisement according to the first age group distribution of the offline audience crowd, the second age group distribution and the age group corresponding to the target audience crowd.
In a second aspect, the present invention provides an advertisement delivery device, including:
the first determining unit is used for determining first attribute distribution of offline audience population when the specified type of advertisements are played online;
a second determining unit, configured to determine at least one set of second attribute distribution of the online audience population of the specified class of advertisement;
a third determining unit, configured to determine a third attribute distribution of a target audience crowd of the specified class advertisement according to the first attribute distribution and the at least one group of second attribute distributions, so as to deliver the specified class advertisement according to the third attribute distribution;
the attribute distribution comprises age groups or age groups and gender distribution, and the target audience population is preset or determined according to the age groups of the offline audience population and the age groups of the online audience population.
In a possible design, the third determining unit, when configured to determine the third attribute distribution of the target audience segment for the specified class of advertisement according to the first attribute distribution and the at least one group of second attribute distributions, is specifically configured to:
calculating according to the first attribute distribution and each group of attribute distribution in the at least one group of second attribute distribution to obtain at least one group of third attribute distribution of the target audience crowd of the specified type of advertisement;
and selecting one group with the largest variance of the attribute distribution from the at least one group of third attribute distributions.
In a possible design, the third determining unit, when configured to determine the third attribute distribution of the target audience segment for the specified class of advertisement according to the first attribute distribution and the at least one group of second attribute distributions, is specifically configured to:
selecting a group of second attribute distribution with the maximum variance of the attribute distribution from the at least one group of second attribute distribution;
and calculating third attribute distribution of target audience population of the specified advertisement according to the first attribute distribution and the selected group of second attribute distributions.
In a possible design, the third determining unit, when configured to determine the third attribute distribution of the target audience segment for the specified class of advertisement according to the first attribute distribution and the at least one group of second attribute distributions, is specifically configured to:
calculating fourth attribute distribution of the online audience crowd of the specified class of advertisements according to the at least one group of second attribute distribution;
and calculating the third attribute distribution of the target audience crowd of the specified advertisement according to the first attribute distribution and the fourth attribute distribution.
In one possible design, the attribute distribution includes: the proportion of the number of audience groups in each age group to the number of all audience groups; or
The attribute distribution includes: the proportion of the number of audience groups of all ages corresponding to different sexes to the number of all audience groups.
In one possible design, taking any one of the at least one set of second attribute distributions as an example, the first attribute distribution is a first age group distribution, and the any one of the second attribute distributions is any one of second age group distributions;
the third determining unit, when configured to perform an operation according to the first attribute distribution and each of the at least one group of second attribute distributions to obtain at least one group of third attribute distributions of target audience population of the specified type of advertisement, is specifically configured to:
determining a first age endpoint value and a second age endpoint value from the first age group distribution and the any second age group distribution, wherein the first age endpoint value is the smallest age value in the first age group distribution and the any second age group distribution, and the second age endpoint value is the largest age value in the first age group distribution and the any second age group distribution;
carrying out age section division based on the first age end point value and the second age end point value to obtain an age section corresponding to the target audience crowd, or taking a preset age section as the age section corresponding to the target audience crowd;
and calculating the third age group distribution of the target audience crowd of the specified advertisement according to the first age group distribution of the offline audience crowd, the selected group of second age group distributions and the age group corresponding to the target audience crowd.
In a third aspect, the present invention provides an advertisement delivery apparatus, including a memory, a processor and a transceiver, which are sequentially connected in communication, wherein the memory is used for storing a computer program, the transceiver is used for sending and receiving a message, and the processor is used for reading the computer program and executing the advertisement delivery method according to the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon instructions which, when run on a computer, perform the advertisement delivery method of the first aspect.
In a fifth aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of advertisement delivery according to the first aspect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic view of an application environment of an advertisement delivery method, an advertisement delivery device and a storage medium provided by the present invention.
Fig. 2 is a flowchart of an advertisement delivery method provided by the present invention.
Fig. 3 is a schematic structural diagram of an advertisement delivery device provided by the present invention.
Fig. 4 is a schematic structural diagram of another advertisement delivery device provided by the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific examples. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. Specific structural and functional details disclosed herein are merely representative for purposes of describing example embodiments of the present invention. The present invention may, however, be embodied in many alternate forms and should not be construed as limited to the embodiments set forth herein.
It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments of the present invention.
It should be understood that, for the term "and/or" as may appear herein, it is merely an associative relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists independently, B exists independently, and A and B exist simultaneously; for the term "/and" as may appear herein, which describes another associative object relationship, it means that two relationships may exist, e.g., a/and B, may mean: a exists independently, and A and B exist independently; in addition, with respect to the character "/" which may appear herein, it generally means that the former and latter associated objects are in an "or" relationship.
It will be understood that when an element is referred to herein as being "connected," "connected," or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may be present. Conversely, if a unit is referred to herein as being "directly adjacent" or "directly coupled" to another unit, it is intended that no intervening units are present. In addition, other words used to describe the relationship between elements should be interpreted in a similar manner (e.g., "between 8230; \8230; between pairs" directly between 8230; \8230; between "," adjacent "pairs" directly adjacent ", etc.).
It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments of the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, numbers, steps, operations, elements, components, and/or groups thereof.
It should also be noted that, in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
It should be understood that specific details are provided in the following description to facilitate a thorough understanding of example embodiments. However, it will be understood by those of ordinary skill in the art that the example embodiments may be practiced without these specific details. For example, systems may be shown in block diagrams in order not to obscure the examples in unnecessary detail. In other instances, well-known processes, structures and techniques may be shown without unnecessary detail in order to avoid obscuring example embodiments.
Examples
In order to achieve a better advertisement putting effect, the embodiment of the application provides an advertisement putting method, an advertisement putting device and a storage medium, and the advertisement putting method, the advertisement putting device and the storage medium can determine the attribute distribution of the designated advertisement in audience population, so that the advertisement can be accurately put in the population when the advertisement is put, and the conversion rate of the advertisement is improved.
First, in order to more intuitively understand the scheme provided by the embodiment of the present application, a system architecture of the advertisement delivery scheme provided by the embodiment of the present application is described below with reference to fig. 1.
Fig. 1 is a schematic application environment diagram of an advertisement delivery method, an advertisement delivery device, and a storage medium according to one or more embodiments of the present application. As shown in fig. 1, the server is in communication connection with at least one third-party server and at least one advertisement machine respectively for data communication or interaction, the server may be a server of an advertisement publisher, and the third-party server may be a server that can count attention of users to various advertisements on line, such as an e-commerce platform, a media platform, and the like. The advertisement machine is provided with an image acquisition device for acquiring a face image of a person entering a designated area (such as an elevator entrance of an office area or a cell) so as to identify the attention of a user to a designated type of advertisement according to the acquired face image, wherein the image acquisition device can be, but not limited to, a webcam, a miniature camera, an Artificial Intelligence (AI) camera, and the like, and the image acquisition device can be integrated with the advertisement machine or independent of the advertisement machine.
The following describes in detail an advertisement delivery method provided in an embodiment of the present application.
The advertisement putting method provided by the embodiment of the application can be applied to a server. For convenience of description, the embodiments of the present application are described with a server as an execution subject, unless otherwise specified.
It is to be understood that the described execution body does not constitute a limitation of the embodiments of the present application.
As shown in fig. 2, which is a flowchart of an advertisement delivery method provided in an embodiment of the present application, the advertisement delivery method may include the following steps:
step S201, determining first attribute distribution of offline audience population when the specified type of advertisement is played online.
The specified advertisements can be one of the advertisements played on the advertisement player, such as travel advertisements, education and training advertisements, catering and food advertisements, and the like. The audience demographics may refer to those who are interested in the specified advertisement. The attribute distribution may be based on age group classification, or may be based on age group classification of different genders.
When the attribute distribution is divided based on the age groups, the attribute distribution may be a ratio of the number of audience population in each age group to the number of all audience population, or may be a distribution curve of the audience population in each age group. When the attribute distribution is divided based on age groups of different genders, the attribute distribution may be a ratio of the number of audience people corresponding to each age group of different genders to the number of all audience people, or may be a distribution curve of the number of audience people corresponding to each age group of different genders.
Taking the example that the attribute distribution is the proportion of the number of audience groups in each age group to the number of all audience groups, assuming that the attribute distribution is divided into one age group under 20 years old, one age group under 20-45 years old, and one age group over 46 years old, the attribute distribution may be the proportion of the number of audience groups to the number of all audience groups under the lines of each age group under 20 years old, 20-45 years old, and over 46 years old.
Aiming at a specified type of advertisement, the number of offline audience groups below 20 years old is 200, the number of offline audience groups below 20-45 years old is 300, and the number of offline audience groups above 46 years old is 500, so that the proportion of the number of offline audience groups in the age range below 20 years old to the number of all audience groups is 20%, the proportion of offline audience groups in the age range between 20-45 years old to the number of all audience groups is 30%, and the proportion of offline audience groups above 46 years old to the number of all audience groups is 50%. Namely, when the specified advertisement is played online, the first attribute distribution of the offline audience population is that the offline audience population under 20 years old accounts for 20%, the offline audience population between 20 and 45 years old accounts for 30%, and the offline audience population above 46 years old accounts for 50%.
Assuming that the attribute distribution is a ratio of the number of audience population of each age group corresponding to different genders to the number of all audience population, assuming that males aged 20 to 30, males aged 31 to 40, females aged 20 to 30 and females aged 31 to 40 are divided into different populations, the attribute distribution may be a ratio of the number of audience population under the line of males aged 20 to 30, males aged 31 to 40, females aged 20 to 30 and females aged 31 to 40 to the number of all audience population.
Aiming at a specified type of advertisement, the offline male audience of 20-30 years old is 100 people, the offline male audience of 31-40 years old is 300 people, the offline female audience of 20-30 years old is 250 people, and the offline female audience of 31-40 years old is 350 people, then the first attribute distribution of the offline audience population when the specified type of advertisement is played online is that the offline male audience percentage of 20-30 years old is 10%, the offline male audience percentage of 31-40 years old is 30%, the offline female audience percentage of 20-30 years old is 25%, and the offline female audience percentage of 31-40 years old is 35%.
In the embodiment of the application, the first attribute distribution of the offline audience population when the specified type of advertisement is played online can be obtained by analyzing at an advertiser end, or can be obtained by analyzing by a server end according to data uploaded by the advertiser.
For example, the first attribute distribution of the online audience population when the specified type of advertisement is played online is obtained by analyzing at the advertiser end. The advertising machine can be used for deploying human AI computing service, acquiring a face image of a user in an advertising region through image acquisition equipment, identifying whether the user pays attention to the advertisement or not according to the face orientation, and identifying the gender, age and the like of the user through the AI computing service. Meanwhile, the advertising machine can also divide users who pay attention to the specified advertisements according to the ages of the users to obtain all the age groups of the offline audience population, and count the proportion of the offline audience population paying attention to the specified advertisements in all the offline audience population, namely the first attribute distribution of the offline audience population.
If the first attribute distribution of the offline audience population is obtained by analyzing at the server when the specified type of advertisement is played online, the advertisement player can upload the obtained user face image to the server after obtaining the user face image, and the user face image is obtained by analyzing at the server. The specific process is consistent with the process of analysis at the advertiser end, and is not described in the embodiment of the application again.
In the embodiment of the application, when the advertising machine identifies whether the user pays attention to the advertisement, the time stamp of the user starting paying attention to the specified advertisement and the time stamp of stopping paying attention to the specified advertisement can be recorded, so that the time length of each offline audience paying attention to the specified advertisement is obtained, when the first attribute distribution of offline audience population is determined when the specified advertisement is played online, the average time length of each offline audience population (within a certain time) paying attention to the specified advertisement in each age group can be used as the first attribute distribution of the offline audience population when the specified advertisement is played online.
For example, the average time of the offline audience population under 20 years old to one age group, the average time of the offline audience population under 20 years old to the specified advertisement in one day is 2 minutes, the average time of the offline audience population under 46 years old to the specified advertisement in one day is 1 minute, the ratio of the average duration of the offline audience crowd below 20 years old paying attention to the specified advertisement to the average duration of the offline audience crowd paying attention to the specified advertisement in all age periods is 40%, the ratio of the average duration of the offline audience crowd paying attention to the specified advertisement in 20-45 years old paying attention to the specified advertisement to the average duration of the offline audience crowd paying attention to the specified advertisement in all age periods is 40%, and the ratio of the average duration of the offline audience crowd above 46 years old paying attention to the specified advertisement to the average duration of the offline audience crowd paying attention to the specified advertisement in all age periods is 20%. Therefore, when the specified advertisement is played online, the first attribute distribution of the offline audience population is that the offline audience population percentage below 20 years old is 40%, the offline audience population percentage between 20 and 45 years old is 40%, and the offline audience population percentage above 46 years old is 20%.
Step S202, at least one group of second attribute distribution of the online audience population of the specified advertisement class is determined.
The server is in communication connection with a third-party server, the third-party server can be an e-commerce platform, a media platform and the like, and the third-party server can perform statistical division on the gender and the age of the online users according to user information logged in by the users, so that online audience groups are divided into a plurality of groups. The third-party server can also identify whether the audiences of the specified advertisements are the audiences according to the online browsing records of the commodities, the news and the advertisements, the online purchasing records and the like of the user, so that the proportion of the audiences of all groups to all online audiences is calculated, and a group of second attribute distribution of the online audiences of the specified advertisements is obtained.
In this embodiment, the number of the third-party servers may be one or more, so that the server side may obtain at least one set of second attribute distribution sent by the third-party server.
And S203, determining a third attribute distribution of the target audience crowd of the specified advertisement class according to the first attribute distribution and at least one group of second attribute distributions.
The online audience and the offline audience can both reflect the distribution situation of the advertisement audience to a certain extent, and if the online audience or the offline audience is analyzed singly, the analyzed attribute distribution of the audience crowd can not accurately reflect the distribution situation of the audience of the specified advertisement. Therefore, after the first attribute distribution of the offline audience crowd and the at least one group of second attribute distribution of the online audience crowd of the specified type advertisement are determined when the specified type advertisement is played online, the first attribute distribution of the offline audience crowd and the second attribute distribution of the online audience crowd are combined to be comprehensively considered, and the target audience distribution condition of the specified type advertisement is determined. That is, a third attribute distribution of the target audience population for the specified class of advertisement is determined based on the first attribute distribution and the at least one set of second attribute distributions.
In the embodiment of the present application, the third attribute distribution of the target audience population of the specified advertisement class may be determined in the following manners.
The first method is as follows:
firstly, operation is carried out according to the first attribute distribution and each group of attribute distribution in at least one group of second attribute distribution, and at least one group of third attribute distribution of target audience crowd of specified advertisements is obtained. And then selecting one group with the maximum variance of the attribute distribution from at least one group of third attribute distributions, wherein the selected group of third attribute distributions are the third attribute distributions of the target audience population of the specified class advertisement.
The group with the largest variance of the attribute distribution in the third attribute distribution means that the variance of the ratio of the number of audience people of each age group to the number of all audience people is the largest in the target audience people corresponding to the group of the third attribute distribution, or the ratio variance of the number of audience people of each age group corresponding to different genders to the number of all audience people is the largest. For example, the age groups of the audience population in the target audience population corresponding to a third attribute distribution are divided into 20-30 years, 31-40 years and 41-50 years, the ratio of the number of the audience population in the age groups of 20-30 years to the number of all the audience populations is s1, the ratio of the number of the audience population in the age groups of 31-40 years to the number of all the audience populations is s2, and the ratio of the number of the audience population in the age groups of 41-50 years to the number of all the audience populations is s3, so that the variance of the attribute distribution in the third attribute distribution is the variance of the three numbers s1, s2 and s 3.
The variance of the attribute distribution in the third attribute distribution is selected as the group with the maximum variance of the attribute distribution, and the third attribute distribution is used as the third attribute distribution of the target audience population of the specified advertisement, namely the audience population number of each age group has the largest proportion difference, so that the audience population distinguishing degree is improved, and the advertisement can be accurately put.
Taking any second attribute distribution in the at least one group of second attribute distributions as an example, it is assumed that the first attribute distribution is a first age group distribution, and any second attribute distribution is any second age group distribution, that is, the first attribute distribution and the second attribute distribution both refer to the ratio of the number of audience population in each age group to the number of all audience population.
Calculating according to the first age group distribution and each group of age group distribution in the at least one group of second age group distribution to obtain at least one group of third age group distribution of target audience crowd of the specified class advertisement, and the following process can be included:
step S301, determining a first age endpoint value and a second age endpoint value according to the first age group distribution and any second age group distribution.
Wherein the first age endpoint value is the smallest age value in the first age group distribution and any second age group distribution, and the second age endpoint value is the largest age value in the first age group distribution and any second age group distribution.
For example, a first age group distribution includes a ratio of the number of offline audience segments to the number of all offline audience segments between ages 20-30 and 31-40, and a second age group distribution includes a ratio of the number of online audience segments to the number of all online audience segments between ages 25-35 and 36-45. The first age endpoint includes 20, 25, 31 and 36 years and the second age endpoint includes 30, 35, 40 and 45 years.
And S302, dividing the age group based on the first age endpoint value and the second age endpoint value to obtain the age group corresponding to the target audience crowd.
When the age groups are divided, the shortest age group can be used as a target for dividing according to the first age endpoint value and the second age endpoint value, and the age group corresponding to the target audience crowd is obtained.
Still based on the example in step S301 above, the first age endpoint values include 20, 25, 31, and 36 years, and the second age endpoint values include 30, 35, 40, and 45 years, then when dividing, the 20-25 years can be divided into one age group, the 26-30 years can be divided into one age group, the 31-35 years can be divided into one age group, the 36-40 years can be divided into one age group, and the 41-45 years can be divided into one age group. I.e., the age groups corresponding to the target audience population are 20-25 years old, 26-30 years old, 31-35 years old, 36-40 years old, and 41-45 years old.
For convenience of description, in the embodiments of the present application, 20 to 25 years are referred to as age group P1, 26 to 30 years are referred to as age group P2, 31 to 35 years are referred to as age group P3, 36 to 40 years are referred to as age group P4, and 41 to 45 years are referred to as age group P5.
In the embodiment of the application, the age groups are divided based on the first age endpoint value and the second age endpoint value to obtain the age groups corresponding to the target audience crowd. It is understood that, in other embodiments, the age groups corresponding to the target audience groups may be divided in other manners, for example, the age groups may be preset and the preset age groups may be used as the age groups corresponding to the target audience groups.
Step S303, calculating the third age group distribution of the target audience crowd of the specified advertisement according to the first age group distribution of the offline audience crowd, the selected group of second age group distributions and the age group corresponding to the target audience crowd.
Specifically, the age distributions of all age groups in the target audience population can be calculated according to the age groups distributed in the first age group and the corresponding age distributions (the proportion of the number of the audience populations in the age groups to the number of all the audience populations), the age groups distributed in the second age group and the corresponding age distributions, and the age groups corresponding to the target audience populations, so that the third age group distribution of the target audience population of the specified type of advertisement is obtained.
More specifically, if there is an overlap between the age group corresponding to the target audience population and the age groups of the first age group distribution and the second age group distribution, the age distribution of the age group is calculated according to the age group of the first age group distribution and the second age group distribution that overlap with each other and the corresponding age distribution, and the age group.
The age distribution for the one age group may be expressed as: g = g 1/(e 1-s1+ 1) × (m 2-m1+ 1) × q1+ g 2/(e 2-s2+ 1) × (m 2-m1+ 1) × q2, wherein e1, s1, g1 and q1 are the maximum age, the minimum age, the corresponding age distribution and the corresponding weight of the age segment in which one of the first and second age segment distributions overlaps with the one age segment in this order, e2, s2, g2 and q2 are the maximum age, the minimum age, the corresponding age distribution and the corresponding weight of the age segment in which the other of the first and second age segment distributions overlaps with the one age segment in this order, and m1 and m2 are the minimum age and the maximum age of the one age segment in this order.
If one age group corresponding to the target audience crowd only overlaps with the age group of the first age group distribution, the age distribution of the age group is calculated according to the age group overlapping with the target audience crowd in the first age group distribution and the corresponding age distribution, and the age group. If one age group corresponding to the target audience crowd only overlaps with the age group of the second age group distribution, the age distribution of the age group is calculated according to the age group overlapping with the target audience crowd in the second age group distribution and the corresponding age distribution thereof, and the age group. The age distribution for the one age group may be expressed as: g = g 3/(e 3-s3+ 1) × (m 2-m1+ 1), where s3, e3, g3 are the maximum age, the minimum age and the corresponding age distribution of the age groups overlapping with the one age group in the first age group distribution or the second age group distribution in this order, and m1 and m2 are the minimum age and the maximum age in this order.
Still based on the example in step S302, assume that the age distribution of the specified type advertisement in the first age group distribution is 20% in the age group of 20-30 years, the age distribution of the specified type advertisement in the first age group distribution is 40% in the age group of 31-40 years, the age distribution of the specified type advertisement in the second age group distribution is 30% in the age group of 25-35 years, the age distribution of the specified type advertisement in the second age group distribution is 50% in the age group of 36-35 years, and q1 and q2 are both 0.5.
The age distribution of the designated class advertisement in the target audience crowd is 20%/(30-20 + 1) × (25-20 + 1) =10.9% in an age segment P1 (20-25 years old), the age distribution of the designated class advertisement in the target audience crowd is 20%/(30-20 + 1) × (30-26 + 1) × 0.5+ 30%/(35-25 + 1) × (30-26 + 1) × (0.5) =11.4% in an age segment P2 (26-30 years old), and the age distribution of the designated class advertisement in the target audience crowd is 50%/(45-36 + 1) × (45-41 + 1) =25%. Similarly, the age distribution of the age groups P3 (31-35) and P4 (36-40) of the ad in the designated class in the target audience population can be calculated. The age distributions of age groups P1, P2, P3, P4 and P5 of the ad of the specified class in the target audience population together constitute a third age group distribution of the target audience population of the ad of the specified class.
The second method comprises the following steps:
firstly, a group of second attribute distributions with the maximum variance of the attribute distributions is selected from at least one group of second attribute distributions. And then calculating a third attribute distribution of the target audience crowd of the specified class of advertisement according to the first attribute distribution and the selected group of second attribute distributions.
The third method comprises the following steps:
the method comprises the steps of firstly calculating fourth attribute distribution of online audience crowd of specified advertisements according to at least one group of second attribute distribution, and then calculating third attribute distribution of target audience crowd of the specified advertisements according to the first attribute distribution and the fourth attribute distribution.
In the embodiment of the present application, the principle of calculating the third attribute distribution of the target audience population of the specified type of advertisement according to the first attribute distribution and the selected group of second attribute distributions is consistent with the calculation principle in the first mode, and details are not repeated here.
After determining the third attribute distribution of the target audience population of the specified advertisement class, the server may deliver the specified advertisement class according to the third attribute distribution. For example, the server can send the third attribute distribution to the advertisement machine, then find out one or more age groups with the highest proportion of the audience population quantity to all the audience population quantities from the advertisement machine according to the third attribute distribution, and deliver the specified advertisement according to the trip peak time of the population of the found age groups, so that the specified advertisement is delivered to the population with the largest specified advertisement audience, the accurate delivery of the advertisement is realized, a better delivery effect is achieved, and the conversion rate of the delivered advertisement is improved. The travel peak time of the crowd can be determined according to the historical time stamp of the advertisement paid attention to by the user.
Therefore, by the advertisement delivery method in the steps S201 to S203, the first attribute distribution of the offline audience population of the specified type of advertisement is determined and the second attribute distribution of the online audience population of the specified type of advertisement is obtained when the specified type of advertisement is played online, and then the third attribute distribution of the target audience population of the specified type of advertisement is determined according to the first attribute distribution and the second attribute distribution. Secondly, when determining the third attribute distribution of the target audience crowd of the specified type of advertisement, if the second attribute distribution is at least one group, calculating according to the first attribute distribution and each group of attribute distribution in the at least one group of second attribute distribution to obtain at least one group of third attribute distribution of the target audience crowd of the specified type of advertisement, and then selecting one group with the maximum variance of the attribute distribution from the at least one group of third attribute distribution as the third attribute distribution of the target audience crowd of the specified type of advertisement. Or selecting one group of second attribute distribution with the maximum variance of the attribute distribution from at least one group of second attribute distribution, and then calculating the third attribute distribution of the target audience population of the specified advertisement class according to the first attribute distribution and the selected group of second attribute distribution. Therefore, the third attribute distribution is obtained, namely the attribute distribution difference is large, namely the proportion difference of the audience population number of each age group is the largest, so that the audience population discrimination is improved, and the advertisement is conveniently and accurately put. In addition, the AI computing service is deployed at the end of the advertisement player, so that the audience population can be accurately divided according to the collected face images, and the trip peak of each population can be determined according to the timestamp, so that the specified advertisement can be delivered to the population with the most specified advertisement audiences according to the trip peak, and the accurate delivery of the advertisement is realized.
In a second aspect, please refer to fig. 3, an embodiment of the present application provides an advertisement delivery apparatus, including:
the first determining unit is used for determining first attribute distribution of offline audience population when the specified type of advertisements are played online;
a second determining unit, configured to determine at least one set of second attribute distribution of the online audience population of the specified class of advertisement;
a third determining unit, configured to determine a third attribute distribution of a target audience population of the specified advertisement class according to the first attribute distribution and the at least one group of second attribute distributions, so as to deliver the specified advertisement class according to the third attribute distribution;
wherein, attribute distribution includes the distribution of age bracket or age bracket and gender, target audience crowd is predetermined, or according to off-line audience crowd's age bracket with on-line audience crowd's age bracket confirms.
In a possible design, the third determining unit, when configured to determine the third attribute distribution of the target audience segment for the specified class of advertisement according to the first attribute distribution and the at least one group of second attribute distributions, is specifically configured to:
calculating according to the first attribute distribution and each group of attribute distribution in the at least one group of second attribute distribution to obtain at least one group of third attribute distribution of the target audience crowd of the specified type of advertisement;
and selecting one group with the largest variance of the attribute distribution from the at least one group of third attribute distributions.
In a possible design, the third determining unit, when configured to determine the third attribute distribution of the target audience segment for the specified class of advertisement according to the first attribute distribution and the at least one group of second attribute distributions, is specifically configured to:
selecting a group of second attribute distributions with the maximum variance of the attribute distributions from the at least one group of second attribute distributions;
and calculating third attribute distribution of target audience population of the specified advertisement according to the first attribute distribution and the selected group of second attribute distributions.
In a possible design, the third determining unit, when configured to determine the third attribute distribution of the target audience segment for the specified class of advertisement according to the first attribute distribution and the at least one group of second attribute distributions, is specifically configured to:
calculating fourth attribute distribution of the online audience population of the specified type of advertisement according to the at least one group of second attribute distribution;
and calculating the third attribute distribution of the target audience crowd of the specified advertisement according to the first attribute distribution and the fourth attribute distribution.
In one possible design, the attribute distribution includes: the proportion of the number of audience groups in each age group to the number of all audience groups; or
The attribute distribution includes: the proportion of the number of the audience crowd of each age group corresponding to different genders to the number of all the audience crowd.
In one possible design, taking any one of the at least one set of second attribute distributions as an example, the first attribute distribution is a first age group distribution, and the any one of the second attribute distributions is any one of second age group distributions;
the third determining unit, when being configured to perform an operation according to the first attribute distribution and each of the at least one group of second attribute distributions to obtain at least one group of third attribute distributions of the target audience population of the specified type of advertisement, is specifically configured to:
determining a first age endpoint value and a second age endpoint value from the first age group distribution and the any second age group distribution, wherein the first age endpoint value is the smallest age value in the first age group distribution and the any second age group distribution, and the second age endpoint value is the largest age value in the first age group distribution and the any second age group distribution;
carrying out age section division based on the first age end point value and the second age end point value to obtain an age section corresponding to the target audience crowd, or taking a preset age section as the age section corresponding to the target audience crowd;
and calculating the third age bracket distribution of the target audience crowd of the specified advertisement according to the first age bracket distribution of the offline audience crowd, the selected group of second age bracket distribution and the age bracket corresponding to the target audience crowd.
For the working process, the working details, and the technical effects of the apparatus provided in the second aspect of this embodiment, reference may be made to the first aspect of this embodiment, which are not described herein again.
As shown in fig. 4, a third aspect of the embodiment of the present application provides an advertisement delivery apparatus, including a memory, a processor, and a transceiver, which are sequentially connected in a communication manner, where the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the advertisement delivery method according to the first aspect of the embodiment.
For specific examples, the Memory may include, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Flash Memory (Flash Memory), a first-in first-out Memory (FIFO), a first-in last-out Memory (FILO), and/or the like; the processor may not be limited to a microprocessor of model STM32F105 series, an ARM (Advanced RISC Machines), an X86 architecture processor, or an NPU (neutral-network processing unit) integrated processor; the transceiver may be, but is not limited to, a WiFi (wireless fidelity) wireless transceiver, a bluetooth wireless transceiver, a General Packet Radio Service (GPRS) wireless transceiver, a ZigBee wireless transceiver (a low power local area network protocol based on ieee802.15.4 standard), a 3G transceiver, a 4G transceiver, and/or a 5G transceiver, etc.
For the working process, the working details, and the technical effects of the apparatus provided in the third aspect of this embodiment, reference may be made to the first aspect of the embodiment, which is not described herein again.
A fourth aspect of the present embodiment provides a computer-readable storage medium storing instructions including the instructions of the advertisement delivery method according to the first aspect of the present embodiment, that is, the computer-readable storage medium stores instructions that, when executed on a computer, perform the advertisement delivery method according to the first aspect. The computer-readable storage medium refers to a carrier for storing data, and may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash Memory, a flash disk and/or a Memory Stick (Memory Stick), etc., and the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.
For a working process, working details, and technical effects of the computer-readable storage medium provided in the fourth aspect of this embodiment, reference may be made to the first aspect of the embodiment, which is not described herein again.
A fifth aspect of the present embodiments provides a computer program product comprising instructions which, when run on a computer, wherein the computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus, cause the computer to perform the advertisement delivery method according to the first aspect of the embodiments.
The embodiments described above are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on the understanding, the above technical solutions may be embodied in the form of software products, which may be stored in computer-readable storage media, such as ROM/RAM, magnetic disk, optical disk, etc., and include instructions for causing a warehouse code combining apparatus to execute the methods according to the embodiments or some parts of the embodiments.
The invention is not limited to the above alternative embodiments, and any other various forms of products can be obtained by anyone in the light of the present invention, but any changes in shape or structure thereof, which fall within the scope of the present invention as defined in the claims, fall within the scope of the present invention.
Claims (6)
1. An advertisement delivery method, comprising:
determining first attribute distribution of an offline audience crowd when the specified type of advertisement is played online;
determining at least one second set of attribute distributions for an online audience population for the specified class of advertisements;
determining a third attribute distribution of the target audience crowd of the specified advertisement class according to the first attribute distribution and the at least one group of second attribute distributions, so as to deliver the specified advertisement class according to the third attribute distribution;
the attribute distribution comprises an age group or distribution of the age group and gender, and the target audience population is preset or determined according to the age group of the offline audience population and the age group of the online audience population;
determining a third attribute distribution of a target audience population for the specified class of advertisements based on the first attribute distribution and the at least one set of second attribute distributions, comprising:
calculating according to the first attribute distribution and each group of attribute distribution in the at least one group of second attribute distribution to obtain at least one group of third attribute distribution of the target audience crowd of the specified type of advertisement;
selecting one group with the maximum variance of the attribute distribution from the at least one group of third attribute distributions;
the attribute distribution includes: the proportion of the number of audience groups in each age group to the number of all audience groups; or
The attribute distribution includes: the proportion of the number of audience people of different genders in all age groups to the number of all audience people;
taking any one second attribute distribution in the at least one group of second attribute distributions as an example, the first attribute distribution is a first age group distribution, and the any one second attribute distribution is any one second age group distribution;
calculating according to the first attribute distribution and each group of attribute distribution in the at least one group of second attribute distribution to obtain at least one group of third attribute distribution of the target audience crowd of the specified type of advertisement, wherein the method comprises the following steps:
determining a first age endpoint value and a second age endpoint value from the first age group distribution and the any second age group distribution, wherein the first age endpoint value is the smallest age value in the first age group distribution and the any second age group distribution, and the second age endpoint value is the largest age value in the first age group distribution and the any second age group distribution;
carrying out age section division based on the first age end point value and the second age end point value to obtain an age section corresponding to the target audience crowd, or taking a preset age section as the age section corresponding to the target audience crowd;
and calculating the third age group distribution of the target audience crowd of the specified advertisement according to the first age group distribution of the offline audience crowd, the second age group distribution and the age group corresponding to the target audience crowd.
2. The method of claim 1, wherein determining a third attribute distribution for a target audience population for the specified class of ads based on the first attribute distribution and the at least one set of second attribute distributions comprises:
selecting a group of second attribute distributions with the maximum variance of the attribute distributions from the at least one group of second attribute distributions;
and calculating the third attribute distribution of the target audience crowd of the specified advertisement according to the first attribute distribution and the selected group of second attribute distributions.
3. The method of claim 1, wherein determining a third attribute distribution for a target audience population for the specified class of ads based on the first attribute distribution and the at least one second attribute distribution comprises:
calculating fourth attribute distribution of the online audience crowd of the specified class of advertisements according to the at least one group of second attribute distribution;
and calculating the third attribute distribution of the target audience crowd of the specified advertisement according to the first attribute distribution and the fourth attribute distribution.
4. An advertisement delivery device, comprising:
the first determining unit is used for determining first attribute distribution of offline audience population when the specified type of advertisements are played online;
a second determining unit, configured to determine at least one set of second attribute distribution of the online audience population of the specified class of advertisement;
a third determining unit, configured to determine a third attribute distribution of a target audience crowd of the specified class advertisement according to the first attribute distribution and the at least one group of second attribute distributions, so as to deliver the specified class advertisement according to the third attribute distribution;
the attribute distribution comprises age groups or distribution of age groups and gender, and the target audience population is preset or determined according to the age groups of the offline audience population and the age groups of the online audience population;
when the third determining unit is configured to determine the third attribute distribution of the target audience population of the specified advertisement class according to the first attribute distribution and the at least one group of second attribute distributions, the third determining unit is specifically configured to:
calculating according to the first attribute distribution and each group of attribute distribution in the at least one group of second attribute distribution to obtain at least one group of third attribute distribution of the target audience crowd of the specified type of advertisement;
selecting one group with the largest variance of the attribute distribution from the at least one group of third attribute distributions;
the attribute distribution includes: the proportion of the number of audience groups in each age group to the number of all audience groups; or
The attribute distribution includes: the proportion of the number of the audience population of each age group corresponding to different genders to the number of all the audience populations;
taking any one second attribute distribution in the at least one group of second attribute distributions as an example, the first attribute distribution is a first age group distribution, and the any one second attribute distribution is any one second age group distribution;
the third determining unit, when configured to perform an operation according to the first attribute distribution and each of the at least one group of second attribute distributions to obtain at least one group of third attribute distributions of target audience population of the specified type of advertisement, is specifically configured to:
determining a first age end point value and a second age end point value according to the first age group distribution and the any second age group distribution, wherein the first age end point value is a minimum age value in the first age group distribution and the any second age group distribution, and the second age end point value is a maximum age value in the first age group distribution and the any second age group distribution;
dividing the age group based on the first age endpoint value and the second age endpoint value to obtain the age group corresponding to the target audience crowd, or taking a preset age group as the age group corresponding to the target audience crowd;
and calculating the third age group distribution of the target audience crowd of the specified advertisement according to the first age group distribution of the offline audience crowd, the selected group of second age group distributions and the age group corresponding to the target audience crowd.
5. An advertisement delivery device, comprising a memory, a processor and a transceiver which are connected in communication in sequence, wherein the memory is used for storing a computer program, the transceiver is used for sending and receiving messages, and the processor is used for reading the computer program and executing the advertisement delivery method according to any one of claims 1 to 3.
6. A computer-readable storage medium having stored thereon instructions for performing, when running on a computer, the method of advertisement delivery according to any one of claims 1-3.
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