CN115907868A - Advertisement delivery analysis method and device - Google Patents
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Abstract
The embodiment of the invention discloses an advertisement putting analysis method and device, comprising the following steps: receiving delivery information, extracting advertisement elements in the target advertisement, and matching a target group based on the advertisement elements, wherein the target group comprises group age and gender; screening matched target releasing platforms from a plurality of releasing platforms to be selected based on a target group; respectively acquiring advertisement data of each target delivery platform, wherein the advertisement data comprises popular advertisement types, advertisement exposure rates and advertisement conversion rates; and calculating the delivery priority of the target delivery platform based on the advertisement data. The embodiment matches the target group by extracting the advertisement elements in the target advertisement, screens a proper target delivery platform based on the target group, further calculates the priority of the target delivery platform according to the advertisement data, and further selects one or more target delivery platforms from the screened target delivery platforms according to the priority to deliver, thereby realizing benefit maximization.
Description
Technical Field
The invention relates to the technical field of computer analysis, in particular to an advertisement putting analysis method and device.
Background
From the history of human development, advertising is an ubiquitous, untimely and unprecedented activity in human society. The mass propagation media enable the human advertisement propagation to generate qualitative changes again. Because of various advertisement media, different advertisement modes, long advertisement mechanisms and various and complicated advertisement extension, the most common outdoor advertisement types can be roughly divided into electronic types and non-electronic types, such as signboards, posters, neon lamps, outdoor lamp boxes, hot air balloons, large-screen electronic displays, electronic screens on vending machines and the like. The purpose of the merchant selecting the medium to put the advertisement is to attract the attention of a large number of people and improve the popularity of the brand, so that the sales volume is improved, and the merchant needs to obtain the related information data of the attention for the put advertisement.
At present, the effect of merchants on delivered advertisements is usually statistics of return rate of delivered advertisements, but there is no automatic analysis and prediction on the delivered advertisements, so that a better delivery platform cannot be screened before the delivered advertisements are not delivered.
Disclosure of Invention
Aiming at the defects, the embodiment of the invention discloses an advertisement putting analysis method and device, which can analyze initial optimal selection of each large putting platform before advertisement putting.
The first aspect of the embodiment of the invention discloses an advertisement putting analysis method, which comprises the following steps:
receiving delivery information, wherein the delivery information comprises a target advertisement and a delivery platform to be selected;
extracting advertisement elements in a target advertisement, and matching a target group based on the advertisement elements, wherein the target group comprises group age and gender;
screening matched target releasing platforms from a plurality of releasing platforms to be selected based on a target group;
respectively acquiring advertisement data of each target delivery platform, wherein the advertisement data comprises popular advertisement types, advertisement exposure rates and advertisement conversion rates;
and calculating the delivery priority of the target delivery platform based on the advertisement data.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the generating of the delivery information through a delivery information writing interface includes:
responding to a release information compiling instruction received by a user, and skipping to an information editing interface, wherein the information editing interface is used for displaying an information compiling frame, a list of advertisements to be released and a release platform;
receiving an advertisement selection instruction of a user, selecting a target advertisement from a list of advertisements to be launched and selecting a plurality of launching platforms to be selected from the launching platforms;
and generating delivery information based on the advertisement selection instruction.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the advertisement element includes a keyword, an advertisement type, an advertisement item attribute, and an applicable group; the adapting a target group based on advertisement elements includes:
acquiring a group subset respectively conforming to the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups based on all element types contained in the advertisement elements;
and calculating the intersection between a plurality of population subsets, and defining the intersection as a target population.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the advertisement element includes a keyword, an advertisement type, an advertisement item attribute, and an applicable group; the adapting a target group based on advertisement elements comprises:
calculating similarity between advertisement instances in an advertisement database and a target advertisement based on the advertisement elements;
acquiring a consumption group corresponding to the advertisement instance with the similarity higher than a threshold value;
respectively obtaining group subsets which accord with the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups;
and calculating the intersection between the plurality of population subsets and the consumption population, and defining the intersection as a target population.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the screening a matched target delivery platform from a plurality of delivery platforms to be selected based on a target group includes:
respectively acquiring an active group and an advertisement type of each to-be-selected delivery platform;
matching the advertisement type with a target advertisement corresponding to a target platform to be selected as a target platform to be selected;
and respectively calculating the evaluation indexes of the target platforms to be selected based on the matching degrees of the active groups and the target groups of the target platforms to be selected, and rejecting the target platforms to be selected with the evaluation indexes lower than a preset value.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the performing the target delivery platform that is screened and matched from a plurality of delivery platforms to be selected based on a target group further includes:
acquiring the consumption amount in the target delivery platform, and grading different consumption amounts;
collecting all active platforms of a group corresponding to the highest-level consumption amount;
and screening out a target active platform based on the active platform and adding the target active platform into a set of target delivery platforms.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the calculating a delivery priority of a target delivery platform based on the advertisement data includes:
calculating the similarity between the hot advertisement type of each target delivery platform and the target advertisement;
acquiring weight proportions respectively corresponding to the popular advertisement type, the advertisement exposure rate and the advertisement conversion rate of a target delivery platform;
respectively calculating the product of the similarity, the advertisement exposure rate, the advertisement conversion rate and the corresponding weight proportion as the priority evaluation score of each target delivery platform;
and according to the priority evaluation score, attributing the target launching platform to a corresponding priority division range so as to obtain the launching priority of the target launching platform.
A second aspect of the embodiments of the present invention discloses an advertisement placement analysis apparatus, which includes:
an information receiving module: the system comprises a receiving module, a processing module and a display module, wherein the receiving module is used for receiving release information which comprises a target advertisement and a release platform to be selected;
an element extraction module: the advertisement element extraction module is used for extracting advertisement elements in a target advertisement and matching a target group based on the advertisement elements, wherein the target group comprises a group age and a gender;
a platform matching module: the target releasing platform is used for screening matched target releasing platforms from a plurality of releasing platforms to be selected based on a target group;
a data acquisition module: the system comprises a target delivery platform, a database and a server, wherein the target delivery platform is used for receiving target advertisement data of each target delivery platform;
and (3) putting a screening module: for calculating a delivery priority for a targeted delivery platform based on the advertisement data.
As an optional implementation manner, in a second aspect of the embodiment of the present invention, the generating of the placement information through a placement information writing interface includes:
responding to a releasing information writing instruction received by a user, and jumping to an information editing interface, wherein the information editing interface is used for displaying an information writing frame, a list of advertisements to be released and a releasing platform;
receiving an advertisement selection instruction of a user, selecting a target advertisement from a list of advertisements to be launched and selecting a plurality of launching platforms to be selected from the launching platforms;
and generating delivery information based on the advertisement selection instruction.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the advertisement element includes a keyword, an advertisement type, an advertisement item attribute, and an applicable group; the adapting a target group based on advertisement elements includes:
acquiring a group subset respectively conforming to the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups based on all element types contained in the advertisement elements;
and calculating the intersection between a plurality of population subsets, and defining the intersection as a target population.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the advertisement element includes a keyword, an advertisement type, an advertisement item attribute, and an applicable group; the adapting a target group based on advertisement elements includes:
calculating similarity between advertisement instances in an advertisement database and a target advertisement based on the advertisement elements;
acquiring a consumption group corresponding to the advertisement instance with the similarity higher than a threshold value;
respectively acquiring group subsets which accord with the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups;
and calculating the intersection between the plurality of population subsets and the consumption population, and defining the intersection as a target population.
As an optional implementation manner, in a second aspect of the embodiment of the present invention, the screening a matched target delivery platform from a plurality of delivery platforms to be selected based on a target group includes:
respectively acquiring an active group and an advertisement type of each to-be-selected delivery platform;
matching the advertisement type with a target advertisement corresponding to a target platform to be selected as a target platform to be selected;
and respectively calculating the evaluation indexes of the target platforms to be selected based on the matching degrees of the active groups and the target groups of the target platforms to be selected, and eliminating the target platforms to be selected with the evaluation indexes lower than a preset value.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the performing the target delivery platform that is selected and matched from a plurality of delivery platforms to be selected based on the target group further includes:
acquiring the consumption amount in the target putting platform, and grading different consumption amounts;
collecting all active platforms of a group corresponding to the highest consumption amount;
and screening out a target active platform based on the active platform and adding the target active platform into a set of target delivery platforms.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the calculating a delivery priority of a target delivery platform based on the advertisement data includes:
calculating the similarity between the hot advertisement type of each target delivery platform and the target advertisement;
acquiring weight proportions respectively corresponding to the popular advertisement type, the advertisement exposure rate and the advertisement conversion rate of a target delivery platform;
respectively calculating the product of the similarity, the advertisement exposure rate, the advertisement conversion rate and the corresponding weight proportion as a priority evaluation score of each target delivery platform;
and according to the priority evaluation score, attributing the target releasing platform to a corresponding priority division range so as to obtain the releasing priority of the target releasing platform.
A third aspect of an embodiment of the present invention discloses an electronic device, including: a memory storing executable program code; a processor coupled with the memory; the processor calls the executable program code stored in the memory for executing the advertisement delivery analysis method disclosed in the first aspect of the embodiment of the present invention.
A fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program, where the computer program causes a computer to execute the advertisement placement analysis method disclosed in the first aspect of the present invention.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, the advertisement elements in the target advertisement are extracted to match the target group, then the appropriate target delivery platform is screened based on the target group, the priority of the target delivery platform is further calculated according to the advertisement data, and a merchant can further select one or more target delivery platforms from the screened target delivery platforms according to the priority to deliver, so that the benefit maximization is realized.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flowchart of an advertisement delivery analysis method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating another advertisement placement analysis method disclosed in the embodiments of the present invention;
fig. 3 is a schematic flowchart of another advertisement delivery analysis method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an advertisement delivery analysis apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first", "second", "third", "fourth", and the like in the description and the claims of the present invention are used for distinguishing different objects, and are not used for describing a specific order. The terms "comprises," "comprising," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiment of the invention discloses an advertisement putting analysis method, an advertisement putting analysis device, electronic equipment and a storage medium.
Example one
Referring to fig. 1, fig. 1 is a schematic flowchart of an advertisement delivery analysis method according to an embodiment of the present invention. The execution main body of the method described in the embodiment of the present invention is an execution main body composed of software or/and hardware, and the execution main body can receive related information in a wired or/and wireless manner and can send a certain instruction. Of course, it may also have certain processing and storage functions. The execution body may control a plurality of devices, such as a remote physical server or a cloud server and related software, or may be a local host or a server and related software for performing related operations on a device installed somewhere. In some scenarios, multiple storage devices may also be controlled, which may be co-located with the device or located in a different location. As shown in fig. 1, the advertisement placement analysis method includes the following steps:
101. and receiving delivery information, wherein the delivery information comprises a target advertisement and a delivery platform to be selected.
In an embodiment, the placement information may be generated by a merchant inputting a corresponding instruction through a specific platform and an application program, and the placement information includes a target advertisement and a placement platform to be selected, where the target advertisement is an advertisement that the merchant wants to prepare for placement through some placement platforms to achieve revenue, and the target advertisement may be one or multiple advertisements. In the case of multiple targeted advertisements, each targeted advertisement is analyzed separately. The description of the embodiments is described in terms of a targeted advertisement. The selected delivery platform is an intention advertisement delivery platform of a merchant, and generally, the advertisement delivery platforms are various, such as different self-media platforms, different public numbers, different search platforms, different application programs and different offline display channels. The selected delivery platforms are the platforms to be selected, that is, the merchants screen a part of the platforms from a plurality of advertisement delivery platforms after the first round of screening, usually according to the own wishes and the forecast of the past income experiences of the merchants, and the screened platforms are used as the delivery platforms to be selected to enter the next round of analysis.
102. Extracting advertisement elements in the target advertisement, and matching a target group based on the advertisement elements, wherein the target group comprises group age and gender.
Each target advertisement necessarily comprises a plurality of advertisement elements, such as an advertisement file and an advertisement picture, wherein the advertisement file comprises keywords or keywords, product attributes corresponding to the advertisement can be known through the keywords or the keywords, a target group corresponding to the product can be further known according to big data, and the advertisement picture is usually a picture corresponding to the advertisement product. For example, the product is a female skin care product, firstly, the target group is female, secondly, the user use group which can be described by the advertising copy can further divide females in the corresponding age range from the female group, or the advertising copy does not describe the user use group, but the use group and the use age can be judged according to the attribute and the type of the product. Or, the delivery information may also directly include product information, and the product information may directly describe the user group.
103. And screening matched target releasing platforms from a plurality of releasing platforms to be selected based on the target group.
In the previous step, the target group corresponding to the target advertisement is obtained, and a delivery platform for which the registered users are more attributes corresponding to the target group can be selected for the target group. For example, a makeup advertisement may be selected as a makeup platform, a makeup teaching platform, and the like, while a platform such as a sports platform, which is a platform for few or even few users without female users, may be discarded accordingly, and in this step, the selected platform is a target delivery platform.
104. And respectively acquiring advertisement data of each target delivery platform, wherein the advertisement data comprises popular advertisement types, advertisement exposure rates and advertisement conversion rates.
The popular advertisement type is that at a certain delivery platform, which type of advertisement is more popular, the click rate of more playing amount is increased, or the user acceptance is higher. The advertisement exposure rate is also the total amount of promotion, including platform promotion, platform user forwarding, etc. The advertisement conversion rate is that the platform user clicks on the playing advertisement, clicks on the advertisement link and successfully purchases the product.
105. And calculating the delivery priority of the target delivery platform based on the advertisement data.
In the embodiment, a ranking is performed on all target delivery platforms, and in the selected target delivery platforms, advertisement data is further calculated for each target delivery platform, that is, the delivery ranking of the target delivery platforms is calculated according to the advertisement data, and the delivery ranking rank is determined according to the delivery priority, wherein the higher the delivery priority, the higher the delivery ranking name is, the higher the delivery priority, for example, the delivery priority of the platform a is the first rank, and the delivery priority of the platform B is the second rank, the delivery ranking of the platform a is to be ranked in front of the platform B. For example, the release priority of the platform C is the first level, that is, the platforms a and C are both release priorities corresponding to the first level, and the platforms a and C are ranked the same and are all ranked in front of the platform B. If the target delivery platform has only platform a, platform B and platform C as examples, and only two platforms are selected as the final delivery platform, then platform a and platform C are preferably selected.
Example two
Fig. 2 is a schematic flow chart illustrating an advertisement delivery analysis method according to an embodiment of the present invention, please refer to fig. 2, where the advertisement delivery analysis method includes:
201. and receiving delivery information, wherein the delivery information comprises a target advertisement and a delivery platform to be selected.
In an embodiment, the launch information is generated through a launch information write interface, and includes: responding to a releasing information writing instruction received by a user, and jumping to an information editing interface, wherein the information editing interface is used for displaying an information writing frame, a list of advertisements to be released and a releasing platform; receiving an advertisement selection instruction of a user, selecting a target advertisement from a list of advertisements to be launched and selecting a plurality of launching platforms to be selected from the launching platforms;
and generating delivery information based on the advertisement selection instruction.
202. And extracting advertisement elements in the target advertisement.
The advertisement elements comprise keywords, advertisement types, advertisement article attributes and applicable groups. Matching a target population based on the advertising elements, the target population including a population age and a gender. In the embodiment, a plurality of advertisement elements contained in the target advertisement are extracted, the characteristic information related to the target advertisement can be obtained, and then the advertisement can be analyzed in a targeted manner, so that the subsequent selection of a delivery platform is facilitated.
203. And acquiring a group subset respectively conforming to the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups based on all element types contained in the advertisement elements.
204. And calculating the intersection between a plurality of population subsets, and defining the intersection as a target population.
The embodiment respectively acquires a, b, c and d, wherein the group subset conforming to the keywords in the advertisement elements is a, the group subset conforming to the advertisement types is b, the group subset c of the attributes of the advertisement articles and the group subset of the applicable groups are d. And then the intersection of a, b, c and d is obtained. Illustratively, the advertisement product is facial cleanser, the function is powerful cleaning, the advertisement literature is applicable to women, the group subset for respectively acquiring the keywords is a group with powerful cleaning requirements, the group subset for the advertisement type is a human group, the group subset for acquiring the attributes of the advertisement articles is a group needing face cleaning, the acquired applicable group is a female group, and the acquired target group is a female group with the powerful cleaning requirements for faces. The above are merely examples, and in other examples, advertisement types, keywords, advertisement item attributes, etc. may each correspond to different content.
Embodiments match target populations based on the advertising elements, which may include population age and gender, and may also include others, such as demand for product functionality, and the like.
205. And respectively acquiring the active group and the advertisement type of each to-be-selected delivery platform.
Different to-be-selected delivery platforms have different active users due to different operation purposes, strategies and the like, and advertisements can be delivered in a targeted manner according to the active user groups of each to-be-selected delivery platform.
206. And matching the advertisement type with the target advertisement corresponding to the target platform to be selected.
207. And respectively calculating the evaluation indexes of the target platforms to be selected based on the matching degrees of the active groups and the target groups of the target platforms to be selected, and rejecting the target platforms to be selected with the evaluation indexes lower than a preset value.
In an embodiment, for example, the target population obtained is a 20-30 year old female population, and the active population of a delivery platform is a middle-aged and old male, the target population is obviously not met, and generally, such delivery platforms are not used as candidate target platforms. For another example, the candidate target platform with the active population of 20-25 year-old female population, the candidate target platform with the active population of 25-40 year-old female population and the candidate target platform with the active population of 22-32 year-old female population are provided, and of the three candidate target platforms, the candidate target platform of 22-32 year-old female population is higher in matching degree and therefore higher in evaluation index.
208. And respectively acquiring advertisement data of each target delivery platform, wherein the advertisement data comprises popular advertisement types, advertisement exposure rates and advertisement conversion rates.
209. And calculating the delivery priority of the target delivery platform based on the advertisement data.
According to the embodiment, the method and the device for selecting the target delivery platform are used for carrying out weighted summation calculation according to different types in the advertisement data to obtain the delivery priority, and selecting the target delivery platform according to the high level of the delivery priority.
EXAMPLE III
Fig. 3 is a schematic flow chart of another advertisement placement analysis method disclosed in the embodiment of the present application, and referring to fig. 3, the advertisement placement analysis method includes:
301. and receiving delivery information, wherein the delivery information comprises a target advertisement and a delivery platform to be selected.
302. Extracting advertisement elements in the target advertisement, and matching a target group based on the advertisement elements, wherein the target group comprises group age and gender.
The advertisement elements of an embodiment include keywords, advertisement type, advertisement item attributes, applicable groups. In this step, adapting the target group based on the advertisement element includes: calculating similarity between advertisement instances in an advertisement database and a target advertisement based on the advertisement elements; acquiring a consumption group corresponding to the advertisement instance with the similarity higher than a threshold value; respectively acquiring group subsets which accord with the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups; and calculating the intersection between the plurality of population subsets and the consumption population, and defining the intersection as a target population.
303. And screening matched target releasing platforms from a plurality of releasing platforms to be selected based on the target group.
304. And acquiring the consumption amount in the target putting platform, and grading different consumption amounts.
305. And collecting all active platforms of the group corresponding to the highest consumption amount.
306. And screening out a target active platform based on the active platform and adding the target active platform into a set of target delivery platforms.
The embodiment firstly counts the consumption amount of a user group of different target delivery platforms, for example, a target delivery platform a, the corresponding consumption amount of a user A is A1, the consumption amount of a user B is B1, the consumption amount is the total consumption of the target delivery platform till now, different consumption amount ranges are set in advance, for example, 0-5000,5000-10000,10000-30000 and the like, and then the consumption amount of each user on the target delivery platform is classified. Illustratively, a target delivery platform 1, a target delivery platform 2 and a target delivery platform 3 are shared, wherein a group of the highest consumption amount in the target delivery platform 1 has a, b and c, a group of the highest consumption amount in the target delivery platform 2 has d and e, and a group of the highest consumption amount in the target delivery platform 3 has f, and all active platforms of a, b, c, d, e and f are obtained respectively, for example, if a user is not only active in the target delivery platform 1, but also active in a non-target delivery platform 4, the non-target delivery platform is also added to the target delivery platform.
307. Respectively acquiring advertisement data of each target delivery platform, wherein the advertisement data comprises popular advertisement types, advertisement exposure rates and advertisement conversion rates;
308. and calculating the delivery priority of the target delivery platform based on the advertisement data.
In the step, the method for calculating the delivery priority specifically comprises the steps of calculating the similarity between the hot advertisement type of each target delivery platform and the target advertisement; acquiring weight proportions respectively corresponding to the hot advertisement type, the advertisement exposure rate and the advertisement conversion rate of a target delivery platform; respectively calculating the product of the similarity, the advertisement exposure rate, the advertisement conversion rate and the corresponding weight proportion as the priority evaluation score of each target delivery platform; and according to the priority evaluation score, attributing the target releasing platform to a corresponding priority division range so as to obtain the releasing priority of the target releasing platform.
Example four
Referring to fig. 4, fig. 4 is a schematic structural diagram of an advertisement delivery analysis apparatus according to an embodiment of the present invention. As shown in fig. 4, the advertisement placement analysis means may include: the system comprises an information receiving module 401, an element extracting module 402, a platform matching module 403, a data obtaining module 404 and a delivery screening module 405, wherein the information receiving module 401 is used for receiving delivery information, and the delivery information comprises a target advertisement and a delivery platform to be selected; an element extraction module 402, configured to extract advertisement elements in a target advertisement, and match a target group based on the advertisement elements, where the target group includes a group age and a gender; the platform matching module 403 is used for screening matched target releasing platforms from a plurality of releasing platforms to be selected based on a target group; the data acquisition module 404 is configured to acquire advertisement data of each target delivery platform, where the advertisement data includes a popular advertisement type, an advertisement exposure rate, and an advertisement conversion rate; and the delivery screening module 405 is configured to calculate a delivery priority of the target delivery platform based on the advertisement data.
In an embodiment, in the information receiving module 401, the generating of the delivery information through a delivery information writing interface includes: responding to a releasing information writing instruction received by a user, and jumping to an information editing interface, wherein the information editing interface is used for displaying an information writing frame, a list of advertisements to be released and a releasing platform; receiving an advertisement selection instruction of a user, selecting a target advertisement from a list of advertisements to be launched and selecting a plurality of launching platforms to be selected from the launching platforms; and generating delivery information based on the advertisement selection instruction.
The advertisement elements of an embodiment include keywords, advertisement type, advertisement item attributes, applicable groups. In the element extracting module 402, the adapting the target group based on the advertisement element includes: acquiring a group subset respectively conforming to the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups based on all element types contained in the advertisement elements; and calculating the intersection between a plurality of population subsets, and defining the intersection as a target population. In another example, adapting the target population based on the advertisement element may further include: calculating similarity between advertisement instances in an advertisement database and a target advertisement based on the advertisement elements; acquiring a consumption group corresponding to the advertisement instance with the similarity higher than a threshold value; respectively acquiring group subsets which accord with the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups; and calculating the intersection between the plurality of population subsets and the consumption population, and defining the intersection as a target population.
In the platform matching module 403, the screening of matched target delivery platforms from a plurality of delivery platforms to be selected based on a target group includes: respectively acquiring an active group and an advertisement type of each to-be-selected delivery platform; matching the advertisement type with a target advertisement corresponding to a target platform to be selected as a target platform to be selected; and respectively calculating the evaluation indexes of the target platforms to be selected based on the matching degrees of the active groups and the target groups of the target platforms to be selected, and rejecting the target platforms to be selected with the evaluation indexes lower than a preset value. On the basis, the target releasing platform which is screened and matched from a plurality of releasing platforms to be selected based on the target group is executed, and the method further comprises the following steps: acquiring the consumption amount in the target putting platform, and grading different consumption amounts; collecting all active platforms of a group corresponding to the highest consumption amount; and screening out a target active platform based on the active platform and adding the target active platform into a set of target delivery platforms.
In the placement screening module 405 of an embodiment, calculating the placement priority of the target placement platform based on the advertisement data includes: calculating the similarity between the hot advertisement type of each target delivery platform and the target advertisement; acquiring weight proportions respectively corresponding to the hot advertisement type, the advertisement exposure rate and the advertisement conversion rate of a target delivery platform; respectively calculating the product of the similarity, the advertisement exposure rate, the advertisement conversion rate and the corresponding weight proportion as the priority evaluation score of each target delivery platform; and according to the priority evaluation score, attributing the target launching platform to a corresponding priority division range so as to obtain the launching priority of the target launching platform.
EXAMPLE five
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure. The electronic device may be a computer, a server, or the like, and may also be an intelligent device such as a mobile phone, a tablet computer, a monitoring terminal, or the like, and an image acquisition device having a processing function. As shown in fig. 5, the electronic device may include:
a memory 501 in which executable program code is stored;
a processor 502 coupled to a memory 501;
the processor 502 calls the executable program code stored in the memory 501 to execute part or all of the steps in the advertisement delivery analysis method in the first embodiment.
The embodiment of the invention discloses a computer-readable storage medium which stores a computer program, wherein the computer program enables a computer to execute part or all of the steps in the advertisement delivery analysis method in the first embodiment.
The embodiment of the invention also discloses a computer program product, wherein when the computer program product runs on a computer, the computer is enabled to execute part or all of the steps in the advertisement putting analysis method in the first embodiment.
The embodiment of the invention also discloses an application publishing platform, wherein the application publishing platform is used for publishing the computer program product, and when the computer program product runs on a computer, the computer is enabled to execute part or all of the steps in the advertisement putting analysis method in the first embodiment.
In various embodiments of the present invention, it should be understood that the sequence numbers of the processes do not mean the execution sequence necessarily in order, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
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 multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated units, if implemented as software functional units and sold or used as a stand-alone product, may be stored in a computer accessible memory. Based on such understanding, the technical solution of the present invention, which is a part of or contributes to the prior art in essence, or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several requests for causing a computer device (which may be a personal computer, a server, a network device, or the like, and may specifically be a processor in the computer device) to execute part or all of the steps of the method according to the embodiments of the present invention.
In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a from which B can be determined. It should also be understood, however, that determining B from a does not mean determining B from a alone, but may also be determined from a and/or other information.
Those of ordinary skill in the art will appreciate that some or all of the steps of the methods of the embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, including Read-Only Memory (ROM), random Access Memory (RAM), programmable Read-Only Memory (PROM), erasable Programmable Read-Only Memory (EPROM), one-time Programmable Read-Only Memory (OTPROM), electrically Erasable Programmable Read-Only Memory (EEPROM), compact Disc Read-Only (CD-ROM) or other Memory capable of storing data, magnetic tape, or any other medium capable of carrying computer data.
The advertisement delivery analysis method, the advertisement delivery analysis device, the electronic device and the storage medium disclosed in the embodiments of the present invention are described in detail above, and a specific example is applied in the description to explain the principle and the implementation of the present invention, and the description of the above embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. An advertisement placement analysis method, comprising:
receiving delivery information, wherein the delivery information comprises a target advertisement and a delivery platform to be selected;
extracting advertisement elements in a target advertisement, and matching a target group based on the advertisement elements, wherein the target group comprises group age and gender;
screening matched target releasing platforms from a plurality of releasing platforms to be selected based on a target group;
respectively acquiring advertisement data of each target delivery platform, wherein the advertisement data comprises popular advertisement types, advertisement exposure rates and advertisement conversion rates;
and calculating the delivery priority of the target delivery platform based on the advertisement data.
2. The advertisement placement analysis method according to claim 1, wherein the placement information is generated through a placement information writing interface, and includes:
responding to a release information compiling instruction received by a user, and skipping to an information editing interface, wherein the information editing interface is used for displaying an information compiling frame, a list of advertisements to be released and a release platform;
receiving an advertisement selection instruction of a user, selecting a target advertisement from a list of advertisements to be launched and selecting a plurality of launching platforms to be selected from the launching platforms;
and generating delivery information based on the advertisement selection instruction.
3. The advertisement placement analysis method according to claim 1, wherein the advertisement elements include keywords, advertisement types, advertisement item attributes, applicable groups; the adapting a target group based on advertisement elements includes:
acquiring a group subset respectively conforming to the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups based on all element types contained in the advertisement elements;
and calculating the intersection between a plurality of population subsets, and defining the intersection as a target population.
4. The advertisement placement analysis method according to claim 1, wherein the advertisement elements include keywords, advertisement types, advertisement item attributes, applicable groups; the adapting a target group based on advertisement elements includes:
calculating similarity between advertisement instances in an advertisement database and a target advertisement based on the advertisement elements;
acquiring a consumption group corresponding to the advertisement instance with the similarity higher than a threshold value;
respectively acquiring group subsets which accord with the keywords, the advertisement types, the attributes of the advertisement articles and the applicable groups;
and calculating the intersection between the plurality of population subsets and the consumption population, and defining the intersection as a target population.
5. The advertisement placement analysis method according to claim 3 or 4, wherein the screening of matching target placement platforms from a plurality of candidate placement platforms based on target groups comprises:
respectively acquiring an active group and an advertisement type of each to-be-selected delivery platform;
matching the advertisement type with a target advertisement corresponding to a target platform to be selected as a target platform to be selected;
and respectively calculating the evaluation indexes of the target platforms to be selected based on the matching degrees of the active groups and the target groups of the target platforms to be selected, and eliminating the target platforms to be selected with the evaluation indexes lower than a preset value.
6. The advertisement delivery analysis method according to claim 5, wherein the target delivery platform that is selected and matched from a plurality of target delivery platforms based on the target group is executed, and further comprising:
acquiring the consumption amount in the target delivery platform, and grading different consumption amounts;
collecting all active platforms of a group corresponding to the highest consumption amount;
and screening out a target active platform based on the active platform and adding the target active platform into a set of target delivery platforms.
7. The advertisement placement analysis method according to claim 1, wherein the calculating of placement priorities of targeted placement platforms based on the advertisement data comprises:
calculating the similarity between the hot advertisement type of each target delivery platform and the target advertisement;
acquiring weight proportions respectively corresponding to the hot advertisement type, the advertisement exposure rate and the advertisement conversion rate of a target delivery platform;
respectively calculating the product of the similarity, the advertisement exposure rate, the advertisement conversion rate and the corresponding weight proportion as the priority evaluation score of each target delivery platform;
and according to the priority evaluation score, attributing the target launching platform to a corresponding priority division range so as to obtain the launching priority of the target launching platform.
8. An advertisement placement analysis device, comprising:
an information receiving module: the system comprises a receiving module, a selecting module and a display module, wherein the receiving module is used for receiving delivery information which comprises a target advertisement and a delivery platform to be selected;
an element extraction module: the advertisement element extraction module is used for extracting advertisement elements in the target advertisement and matching a target group based on the advertisement elements, wherein the target group comprises group age and gender;
a platform matching module: the target releasing platform is used for screening matched target releasing platforms from a plurality of releasing platforms to be selected based on a target group;
a data acquisition module: the system comprises a target delivery platform, a database and a server, wherein the target delivery platform is used for receiving target advertisement data of each target delivery platform;
and (3) putting a screening module: and the delivery priority of the target delivery platform is calculated based on the advertisement data.
9. An electronic device, comprising: a memory storing executable program code; a processor coupled with the memory; the processor calls the executable program code stored in the memory for executing the ad placement analysis method of any of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the advertisement placement analysis method according to any one of claims 1 to 7.
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