Advertisement analysis method, device, storage medium, and electronic device

Abstract

The present invention discloses an advertising analysis method, device, storage medium, and electronic device. The method comprises: obtaining advertising delivery data for each of multiple advertisements delivered for a target product on multiple first platforms and access data for the target product on a second platform, wherein each of the multiple first platforms delivers at least one advertisement from the multiple advertisements; determining the advertising performance index of each advertisement for the target product based on the advertising delivery data, access data, and the platform weight of each of the multiple first platforms; and determining new traffic data for each advertisement based on the access data and the advertising performance index of each advertisement. The present invention solves the technical problem of being unable to obtain the effectiveness of advertising delivery.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular to an advertisement analysis method, device, storage medium, and electronic device. Background Art

[0002] In the existing technology, advertisers can place advertisements through various platforms, or use advertising marketing experts to market advertisements, thereby increasing product sales.

[0003] However, in the prior art, advertisers have no way of knowing the effects of the advertisements they place or market. Summary of the Invention

[0004] Embodiments of the present invention provide an advertisement analysis method, apparatus, storage medium, and electronic device to at least solve the technical problem of being unable to obtain the delivery effect of an advertisement.

[0005] According to one aspect of an embodiment of the present invention, there is provided an advertising analysis method, comprising: obtaining advertising delivery data for each of a plurality of advertisements delivered for a target product on a plurality of first platforms and access data for the target product on a second platform, wherein each of the plurality of first platforms delivers at least one advertisement from the plurality of advertisements; determining an advertising performance index for each of the advertisements for the target product based on the advertising delivery data, the access data and the platform weight of each of the plurality of first platforms; and determining new traffic data for each of the advertisements based on the access data and the advertising performance index of each of the advertisements.

[0006] According to another aspect of an embodiment of the present invention, an advertising analysis device is provided, including: a first acquisition module, used to obtain advertising delivery data of each of a plurality of advertisements delivered for a target product on a plurality of first platforms and access data of the target product on a second platform, wherein each of the plurality of first platforms delivers at least one advertisement from the plurality of advertisements; a first determination module, used to determine an advertising performance index of each of the advertisements for the target product based on the advertising delivery data, the access data and the platform weight of each of the plurality of first platforms; a second determination module, used to determine new traffic data of each of the advertisements based on the access data and the advertising performance index of each of the advertisements.

[0007] As an optional example, the first determination module includes: a determination unit for determining the platform weight of each of the first platforms; a processing unit for normalizing the advertising delivery data of each of the advertisements according to a first time period to obtain a first normalized result; and a calculation unit for multiplying the first normalized result by the platform weight to obtain the advertising performance index of each advertisement in each of the first time period.

[0008] As an optional example, the determination unit includes: an execution sub-unit, used to take each of the first platforms as the current platform, and perform the following operations: obtaining the historical delivery data and historical access data of the current platform within a second time period; normalizing the historical delivery data according to the second time period to obtain a second normalized result; normalizing the target access data of the current platform in the historical access data according to the second time period to obtain a third normalized result; and determining the regression coefficient of the third normalized result and the second normalized result as the platform weight of the current platform.

[0009] As an optional example, the second determination module includes: an execution unit, used to take each of the advertisements as the current advertisement and perform the following operations: comparing the advertising performance index of the current advertisement with the sum of the advertising performance indexes of each of the advertisements within the first time period to obtain the advertising performance index ratio of the current advertisement; and taking the product of the access data within the first time period and the advertising performance index ratio of the current advertisement as the new traffic data for the current advertisement.

[0010] As an optional example, each of the advertisements includes basic push advertisements and additional push advertisements, and the device also includes: a first processing module, used to normalize the advertising delivery data of each of the advertisements according to a first time period, and when the first normalization result is obtained, obtain the normalized result of the basic push advertisement and the normalized result of the additional push advertisement of each of the advertisements respectively; a second processing module, used to calculate the basic new traffic data of the basic promotion advertisements of each of the advertisements and the additional push new traffic data of each of the additional push advertisements of the advertisements based on the normalized result of the basic push advertisements of each of the advertisements and the normalized result of the additional push advertisements; a second acquisition module, used to obtain the basic consumption resource value of the basic push advertisements of each of the advertisements, and the additional push consumption resource value of the additional push advertisements of each of the advertisements; a third determination module, used to determine the basic push advertisement cost of each of the advertisements based on the basic new traffic data and the basic consumption resource value, and determine the additional push advertisement cost of each of the advertisements based on the additional push new traffic data and the additional push consumption resource value.

[0011] As an optional example, the device also includes: a first adjustment module, which is used to increase the proportion of the additional ads of the current advertisement or increase the push volume of the additional ads of the current advertisement when the cost of the additional ads of the current advertisement in each of the advertisements is less than a first threshold.

[0012] As an optional example, the device also includes: a second adjustment module, which is used to increase the proportion of additional advertisements of the current advertisement or increase the push volume of additional advertisements of the current advertisement when the new traffic data of the current advertisement in each of the advertisements is greater than a second threshold.

[0013] As an optional example, the device also includes: a display module for displaying the new traffic data of each of the advertisements; a third adjustment module for increasing the proportion of the additional advertisements of the target advertisement or increasing the push volume of the additional advertisements of the target advertisement when receiving an instruction to push the target advertisement.

[0014] As an optional example, the device also includes: a fourth determination module, used to determine the object used to operate each of the multiple advertisements, and determine multiple objects; based on the new traffic data and / or new advertising cost of each of the advertisements, determine the new customer contribution value of each of the objects.

[0015] According to another aspect of the embodiments of the present invention, a storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned advertisement analysis method is executed.

[0016] According to another aspect of an embodiment of the present invention, there is provided an electronic device including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the above-mentioned advertisement analysis method through the computer program.

[0017] The present invention can be applied in the process of data visualization of data capabilities. In an embodiment of the present invention, a method is adopted to obtain advertising delivery data of each of multiple advertisements delivered for a target product on multiple first platforms and access data of the target product on a second platform, wherein each of the multiple first platforms delivers at least one advertisement from the multiple advertisements; determine the advertising performance index of each of the advertisements for the target product based on the advertising delivery data, the access data, and the platform weight of each of the multiple first platforms; and determine the new traffic data of each of the advertisements based on the access data and the advertising performance index of each of the advertisements. Since in the above method, after delivering advertisements for the target product on multiple first platforms, the advertising delivery data and the access data of the target product on the second platform can be obtained, and then the advertising delivery data, the access data, and the platform weight of each of the multiple first platforms are used to determine the advertising performance index of each of the advertisements for the target product, and finally determine the new traffic data of each advertisement, thereby achieving the purpose of analyzing the delivery effect of each advertisement, thereby solving the technical problem of being unable to know the delivery effect of the advertisement. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a flow chart of an optional advertising analysis method according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of analysis results of an optional advertisement analysis method according to an embodiment of the present invention;

[0021] Figure 3 is a schematic diagram of advertising proportions according to an optional advertising analysis method according to an embodiment of the present invention;

[0022] Figure 4 is an object hierarchy diagram of an optional advertisement analysis method according to an embodiment of the present invention;

[0023] Figure 5 is a schematic structural diagram of an optional advertisement analysis device according to an embodiment of the present invention;

[0024] Figure 6 is a schematic diagram of an optional electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] According to a first aspect of an embodiment of the present invention, an advertisement analysis method is provided. Optionally, as Figure 1 As shown, the above method includes:

[0028] S102, obtaining advertisement delivery data for each of a plurality of advertisements delivered for a target product on a plurality of first platforms and access data for the target product on a second platform, wherein each of the plurality of first platforms delivers at least one advertisement from the plurality of advertisements;

[0029] S104, determining an advertising performance index of each advertisement for the target product based on the advertisement delivery data, the access data, and the platform weight of each of the plurality of first platforms;

[0030] S106: Determine new traffic data for each advertisement based on the access data and the advertisement performance index of each advertisement.

[0031] Optionally, the first platform and the second platform mentioned in this embodiment are different platforms. The first platform is used to place advertisements corresponding to the target product, and the second platform is a sales platform for the target product, which can display the target product for users to access, purchase, or collect the target product.

[0032] In this embodiment, advertisements related to the target product can be placed on multiple different first platforms. Each first platform can place advertisements according to a placement plan. In this embodiment, the advertising data of advertisements placed on multiple first platforms can be used as advertising placement data. The advertising placement data may include at least one of, but is not limited to, the content, type, number of advertisements placed, placement patterns within a campaign cycle, and placement targets of the advertisements.

[0033] Optionally, in this embodiment, the access data may be at least one of search data, access data, click data, favorite data, and purchase data of the target product on the second platform, but is not limited thereto.

[0034] In this embodiment, the platform weight can be the weight of advertisements on each of the multiple first platforms. The platform weight indicates the proportion of advertisements for the target product. The advertising performance coefficient for each advertisement is determined by combining advertising placement data, visit data, and the platform weight. The new traffic data generated by the advertisement is then determined based on the visit data and the advertising performance coefficient.

[0035] Because in the above method, after advertising for the target product on multiple first platforms, the advertising delivery data and the access data of the target product on the second platform can be obtained, and then the advertising performance index of each advertisement for the target product is determined based on the advertising delivery data, the access data and the platform weight of each first platform in the multiple first platforms, and finally the new traffic data of each advertisement is determined, thereby achieving the purpose of analyzing the delivery effect of each advertisement.

[0036] As an optional example, determining the advertising performance index of each advertisement for the target product based on the advertising delivery data, the access data, and the platform weight of each of the plurality of first platforms includes:

[0037] determining the platform weight of each of the first platforms;

[0038] Normalizing the advertisement delivery data of each advertisement according to a first time period to obtain a first normalized result;

[0039] The first normalized result is multiplied by the platform weight to obtain the advertising performance index of each advertisement in each of the first time periods.

[0040] Optionally, in this embodiment, a platform weight may correspond to each first platform. In this embodiment, the advertising data of the advertisement on each platform may be normalized according to the first time period to obtain a first normalized result. The product of the first normalized result and the platform weight is used as the advertising performance index. The first time period in this embodiment may be an advertising monitoring period for advertising. For example, it is 1 month. The data within one month is normalized, and the advertising performance index of each advertisement within the 1 month is calculated. Then, the access data of the 1 month and the advertising performance index of each advertisement are used to calculate the new traffic data of each advertisement within the 1 month.

[0041] As an optional example, determining the platform weight of each first platform includes:

[0042] Take each of the first platforms as the current platform and perform the following operations:

[0043] Obtaining historical delivery data of all historical advertisements delivered by the current platform during a second time period and historical access data of historical products corresponding to each historical advertisement during the second time period on the second platform;

[0044] Normalizing the historical delivery data according to the second time period to obtain a second normalized result;

[0045] Normalizing the target access data of the current platform in the historical access data according to the second time period to obtain a third normalization result;

[0046] A regression coefficient of the third normalization result and the second normalization result is determined as the platform weight of the current platform.

[0047] The third normalized result and the second normalized result are calculated using a regression algorithm, and the second normalized result is used as the independent variable and the third normalized result is used as the dependent variable. The regression coefficient obtained by regression analysis is determined as the platform weight of the current platform.

[0048] Optionally, in this embodiment, the platform weight of each of the multiple first platforms can be calculated using historical data. The historical delivery data and historical access data of advertisements delivered using multiple first platforms within the second time period can be obtained. The second time period in this embodiment can be a time interval that occurs before the first time period. The second time period can be a time period of the same or different length as the first time period. The historical data within the second time period may include data of the target product and data of other products. That is, the data used in calculating the platform weight can include data of all advertisements delivered by an advertiser using the first platform, and is not limited to data of advertisements using the target product. For example, the historical delivery data of all advertisements of various products delivered by an advertiser on the first platform last month and the historical access data of various products are obtained to calculate the platform weight of the first platform.

[0049] As an optional example, determining the new traffic data of each advertisement based on the new traffic data of each first platform and the advertisement performance index of each advertisement includes:

[0050] Take each of the ads as the current ad and perform the following operations:

[0051] Comparing the advertisement performance index of the current advertisement with the sum of the advertisement performance indexes of each advertisement in the first time period to obtain an advertisement performance index ratio of the current advertisement;

[0052] The product of the access data in the first time period and the advertisement performance index ratio of the current advertisement is used as the new traffic data of the current advertisement.

[0053] Optionally, in this embodiment, for each advertisement, an advertising performance index ratio is calculated for that advertisement. The advertising performance index ratio for that advertisement is calculated as the ratio of the advertising performance index for that advertisement to the sum of the advertising performance indexes for all advertisements placed for the target product during the first time period. The product of the advertising performance index ratio for that advertisement and the visit data for the target product during the first time period serves as the new traffic data for that advertisement during the first time period. This method can be used to determine the new traffic data for each advertisement for the target product on each first platform during any first time period.

[0054] As an optional example, each of the advertisements includes a first advertisement consisting of a basic push advertisement and a second advertisement consisting of a basic push advertisement and an additional push advertisement, and the method further includes:

[0055] Normalizing the advertising delivery data of each advertisement according to a first time period to obtain a first normalized result, and obtaining a normalized result of the basic push advertisement of each advertisement and a normalized result of the additional push advertisement in the second advertisement;

[0056] Calculate the basic new traffic data of the basic promotion advertisement of each advertisement and the additional new traffic data of the additional push advertisement of each second advertisement according to the normalized result of the basic push advertisement of each advertisement and the normalized result of the additional push advertisement in the second advertisement;

[0057] Obtaining a basic resource consumption value of a basic push advertisement for each of the advertisements, and a resource consumption value of an additional push advertisement for each of the second advertisements;

[0058] The basic push advertising cost of each of the advertisements is determined based on the basic new traffic data and the basic consumed resource value, and the additional push advertising cost of each of the second advertisements is determined based on the additional push new traffic data and the additional push consumed resource value.

[0059] Optionally, in this embodiment, the basic push advertisements may be advertisements placed for the target product on the first platform, for example, 30 basic push advertisements are placed on the first platform. And the additional push advertisements may be additional push advertisements for the basic push advertisements through the additional push means provided by the first platform on the basis of the basic push advertisements. For example, within a month, 30 basic push advertisements are placed in the first week. Then, in the second week, additional push investment is increased for 10 of the basic push advertisements, and additional push is carried out on the first platform, and each basic push advertisement is additionally pushed 2 times. Then, in the second week, there are a total of 20 (10×2) additional push advertisements. No advertisements are placed in the third and fourth weeks. Then, within this month, there are a total of 30 basic push advertisements, of which 10 basic push advertisements are additionally pushed, and the number of additional pushes is 2 times, so the total number of additional push advertisements is 20.

[0060] In this embodiment, the new traffic data of each basic push advertisement and the new traffic data of each additional push advertisement can be calculated separately, and then the basic push advertisement cost of the basic push advertisement and the additional push advertisement cost of the additional push advertisement can be calculated according to the basic consumption resource value of the basic push advertisement and the additional consumption resource value of the additional push advertisement.

[0061] As an optional example, the above method further includes:

[0062] When the additional advertisement cost of the current advertisement in each of the advertisements is less than a first threshold, the proportion of the additional advertisements of the current advertisement is increased or the push amount of the additional advertisements of the current advertisement is increased.

[0063] Optionally, in this embodiment, the push status of the advertisement can be monitored. If the additional push advertisement cost is less than the first threshold, it can be determined that the new user acquisition cost of the additional push advertisement is low, and the additional push advertisement can be continued.

[0064] As an optional example, the above method further includes:

[0065] When the new traffic data for the current ad in each of the ads exceeds a second threshold, the proportion of additional ads for the current ad is increased or the push volume of the additional ads for the current ad is increased. Increasing the proportion of additional ads means pushing more basic push ads; increasing the push volume of additional ads means increasing the number of additional pushes for a given basic push ad.

[0066] Optionally, in this embodiment, the push status of the advertisement can be monitored. If the new user traffic data of the advertisement is greater than a second threshold, it can be determined that the advertisement has a strong ability to attract new users, and the advertisement can be pushed again. If the advertisement has already been pushed again, it can be pushed again, that is, the number of pushes for the advertisement can be increased.

[0067] As an optional example, the above method further includes:

[0068] Display the new traffic data of each advertisement;

[0069] When an instruction to push additional advertisements for a target advertisement is received, the proportion of the additional advertisements for the target advertisement is increased or the push amount of the additional advertisements for the target advertisement is increased.

[0070] Optionally, in this embodiment, it is also possible to determine which advertisements to push based on the user's instructions, and to determine the amount of the advertisements to push, the time of pushing, etc.

[0071] As an optional example, the above method further includes:

[0072] determining an object for operating each of the plurality of advertisements, to determine a plurality of objects;

[0073] The new customer acquisition contribution value of each of the objects is determined based on the new customer acquisition traffic data and / or new customer acquisition advertising cost of each of the advertisements.

[0074] Optionally, the objects in this embodiment can be objects that place or operate advertisements. For example, an advertiser can place advertisements themselves as an object, for example, through an official account on a first platform. Alternatively, the advertiser can entrust a third party to place advertisements on the first platform. The third party can specifically be a social influencer on a social media platform. Multiple objects can include advertisers and third parties. After multiple objects place advertisements, the new user acquisition contribution value of each object can be determined.

[0075] This is explained with examples. In order to perform a quality analysis on the advertisements placed for the target product, the advertisement placement data of each advertisement of the target product is obtained. For the target product, the enterprise has invested in advertisements. The advertisement format is not limited in this embodiment. For example, it can be a variety of content such as text, multimedia data, and can be in various forms such as posts, pictures, videos, and articles.

[0076] Obtain advertising data for each ad, specifically monitoring its performance. This data is then used to analyze each ad's marketing conversion performance and to record marketing actions taken for each ad in real time. Marketing actions here refer to additional promotions for the ad. Advertising data includes performance data such as post engagement and clickthrough rates.

[0077] The advertising delivery data of the advertisement is filtered and anomaly diagnosis and identification is performed on the advertising delivery data, that is, invalid data / abnormal data is identified and calculated, and the identified invalid data / abnormal data is filtered accordingly to obtain the real advertising delivery data.

[0078] For example, the interactive data of advertisements obtained from various social media platforms (first platform) needs to be de-watered, that is, the water army data is identified and then filtered to obtain real interactive data.

[0079] Based on real advertising data, calculate the new traffic of each ad:

[0080] (1) Obtaining the platform weight of each social media platform

[0081] Since different social media platforms have different corresponding user scales, the scales of data indicators such as interaction volume and click volume will also vary. Therefore, it is necessary to uniformly quantify and decompose the platform weights corresponding to each social media platform.

[0082] The calculation method of the platform weight corresponding to each social media platform can be as follows:

[0083] Obtain advertisers' historical advertising data on various social media platforms, normalize it, and process it using a regression algorithm to obtain the platform weight corresponding to each social media platform.

[0084] For example, historical performance data for a company's (advertiser's) advertising on various social media platforms over the past year (this period can be adjusted to three, six, or other months depending on the specific situation) can be collected: pull data (basic push advertising performance data), push data (add-on advertising performance data), and TP data (e-commerce search UV data) for the products targeted by each company's advertisements over the past year. E-commerce search UV data (e-commerce search data) includes data on the number of unique visitors searching for products on e-commerce platforms (secondary platforms).

[0085] 1) Normalize push and pull data by platform. The unit of measurement is day (byday). If there are multiple records from the same platform on the same day, they will be merged. The total data for the past year is calculated and normalized to obtain the normalized results.

[0086] 2) Normalize the tp data to obtain the normalized result.

[0087] 3) Using the normalized results of push and pull data as x and the normalized results of TP data as y, a regression algorithm is used to calculate the data for each social media platform. A linear regression algorithm can be used. The regression coefficient obtained by the regression algorithm is the platform weight corresponding to each social media platform.

[0088] Among them, pull data refers to the social performance data of basic push posts of advertising type published by objects on social media platforms, which can specifically be the social interaction volume of basic push posts.

[0089] Push data: refers to the amount of social interaction on additional push posts based on basic push posts on various social media platforms.

[0090] (2) Split the real advertising data and calculate the performance index of each advertisement.

[0091] Divided by platform, daily ad interaction data for each platform is obtained from actual ad delivery data during the monitoring period; data details: Platform - Day - Single Post (Basic Push Post / Additional Push Post) - Post Interaction Volume.

[0092] For example, if the monitoring period for real advertising data is one month (i.e., each ad has been running for one month), we can obtain the daily post interaction data (de-duplicated) for each ad post from each platform during that month. Based on the de-duplicated post interaction data, we first normalize the data by platform, and then multiply the normalized result by the platform weight to obtain the daily advertising performance index (PI) for each post.

[0093] (3) Based on the single post performance index pi, calculate the new traffic of a single post.

[0094] Obtain search UV data from the e-commerce platform and decompose it to obtain the total daily new traffic data of the e-commerce platform (that is, remove the natural traffic data from the search UV data, where natural traffic data refers to the natural search traffic that products will have on the e-commerce platform even without any marketing activities).

[0095] Every day, based on the pi value of each post, the total new traffic data of the day is broken down to obtain the single-post new traffic corresponding to each post.

[0096] The calculation method is:

[0097] The amount of new users attracted by a single post = the total daily traffic of the e-commerce platform × (the PI of the single post on that day / the sum of the PIs of all single posts on that day)

[0098] If you need to count the single-post new user acquisition data for the entire monitoring period, then sum up the single-post new user acquisition traffic for each day in the monitoring period to get the total single-post new user acquisition traffic for the monitoring period (1 month).

[0099] Get the cost of acquiring new users per post based on the traffic and spending data of each post

[0100] Obtain the company's spending data on each post, and use the spending on each post / total new traffic of the post to obtain the new user acquisition cost (unit cost) of a single post.

[0101] Distinguish between pull ads and push ads, and calculate the cost of acquiring new users for each post separately. This is because push ads increase the investment in pull ads.

[0102] Adjust the delivery strategy (additional push strategy) of single-post marketing operations based on advertising delivery data, single-post new traffic, and single-post new cost.

[0103] The data from the above steps, such as advertising data, traffic per post, and cost per post, can be aggregated and presented in reports. For example, a dashboard can be constructed to present data reports, with filter controls. Based on the corresponding filter control operation information, advertising data, traffic per post, and cost per post can be categorized and presented in a dashboard format.

[0104] The filter item controls may include: platform, whether to add a push, object level (described in the next step), and other filtering dimensions.

[0105] Category presentation can be: data display items of post-related details.

[0106] For example, Figure 2 As shown, Figure 2 2 is a schematic diagram of a method for selectively viewing advertisement-related data. By selecting a data display item 202, such as whether to add a promotion, platform 1 or platform 2, or the level, corresponding data 204 can be selected for viewing. Figure 2 For example only, the display items of this embodiment may also include, but are not limited to, time, change trend, number of additional pushes, number of collaborations, amount of interaction, etc., and an analysis button may also be set to view the analysis results of the data. Figure 3 This is a diagram showing the percentage of ads on each of the top platforms. You can view the new traffic generated by ads on each platform.

[0107] Additional promotion strategy 1: You can set a benchmark value based on the cost of attracting new users per post. When the cost is lower than the benchmark value of the cost of attracting new users per post, you can adopt an additional promotion strategy for the post.

[0108] Additional push strategy 2: You can set a benchmark value for attracting new traffic for a single post, and adopt an additional push strategy for posts with new traffic higher than the benchmark value.

[0109] Additional push strategy three: Click on the details in the dashboard to get a trend analysis chart for a single post: new traffic and unit cost; based on this trend analysis chart, you can decide whether to push additional posts and whether to increase the number of pushes for posts with good trends.

[0110] Obtain historical social performance data and marketing performance data for each object, and conduct object delivery monitoring and analysis

[0111] (1) Obtain historical social performance data of the subject

[0112] Determine the subject's contribution to sales conversions based on the subject's historical social performance data.

[0113] For each social media platform, historical social performance data of the object is obtained on the social media platform, and the level of the object is determined based on the historical social performance data.

[0114] Specifically, objects on various social media platforms can be divided into "super head, head, shoulders, waist, tail" and other levels according to influence evaluation indicators (number of fans, number of levels, activity level, etc., which can be directly obtained from social media platforms). When used for subsequent data analysis, the contribution of objects of different levels to sales conversion can be reflected.

[0115] (2) Based on the single post performance data obtained in the above steps, correlation analysis is performed to obtain the marketing performance data of the object.

[0116] Posts are associated with objects. By aggregating the new traffic and unit cost data of a single post to the corresponding object, you can obtain the marketing performance data (new traffic, expenditure, unit new customer acquisition cost) of objects at all levels, as well as information such as the number of collaborations with the statistical object.

[0117] Aggregate and present historical social and marketing performance data for an individual. For example, you can create a dashboard for presenting data reports, with filter controls. Based on the corresponding filter control operations, you can categorize the individual's marketing performance data and present it in a dashboard format.

[0118] The filter item control can have filtering dimensions such as platform and object level.

[0119] The classification presentation may be: a data display item of the object marketing performance details.

[0120] Figure 4 This is a diagram of objects at different levels. Through analysis, we can determine the objects with the best advertising effects.

[0121] Adjust the target selection delivery strategy based on the target’s marketing performance data

[0122] According to the data information in the dashboard, the delivery strategy of the object selection can be carried out

[0123] (1) Decision on the object magnitude: Based on the marketing performance data corresponding to the object magnitude, the magnitude decision for subsequent object selection can be made.

[0124] For example, if subsequent marketing efforts focus more on attracting new users, select the top subjects. If subsequent marketing efforts focus more on increasing the cost of acquiring new users, select the shoulder subjects based on the dashboard information. The top subjects refer to the top subjects in the dashboard ranking results. The shoulder subjects refer to the subjects that fall below the top subjects.

[0125] (2) Determine the decision for a specific object: Based on the selection of the object magnitude in (1), filter the objects of the corresponding magnitude in the dashboard and view the marketing performance data.

[0126] The specific decision-making basis can be: determine the specific object based on the number of cooperation with a certain object, the new traffic, and the unit new cost.

[0127] Number of collaborations: reflects the historical collaborations of the object.

[0128] Attract new traffic: The object’s contribution to attracting new customers to the brand, focusing on the object’s contribution to the value of the product.

[0129] Unit new customer acquisition cost: The unit new customer acquisition cost of the target for the brand, reflecting the cost the target needs to pay for bringing in a single piece of traffic. The lower the value, the better.

[0130] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0131] According to another aspect of the embodiment of the present application, an advertisement analysis device is also provided. Figure 5 As shown, including:

[0132] A first acquisition module 502 is configured to acquire advertisement delivery data for each of a plurality of advertisements delivered for a target product on a plurality of first platforms and access data for the target product on a second platform, wherein each of the plurality of first platforms delivers at least one advertisement from the plurality of advertisements;

[0133] A first determination module 504 is configured to determine an advertising performance index of each advertisement for a target product based on the advertisement delivery data, the access data, and the platform weight of each of the plurality of first platforms;

[0134] The second determination module 506 is used to determine the new traffic data of each advertisement based on the access data and the advertisement performance index of each advertisement.

[0135] Optionally, the first platform and the second platform mentioned in this embodiment are different platforms. The first platform is used to place advertisements corresponding to the target product, and the second platform is a sales platform for the target product, which can display the target product for users to access, purchase, or collect the target product.

[0136] In this embodiment, advertisements related to the target product can be placed on multiple different first platforms. Each first platform can place advertisements according to a placement plan. In this embodiment, the advertising data of advertisements placed on multiple first platforms can be used as advertising placement data. The advertising placement data may include at least one of, but is not limited to, the content, type, number of advertisements placed, placement patterns within a campaign cycle, and placement targets of the advertisements.

[0137] Optionally, in this embodiment, the access data may be at least one of search data, access data, click data, favorite data, and purchase data of the target product on the second platform, but is not limited thereto.

[0138] In this embodiment, the platform weight can be the weight of advertisements on each of the multiple first platforms. The platform weight indicates the proportion of advertisements for the target product. The advertising performance coefficient for each advertisement is determined by combining advertising placement data, visit data, and the platform weight. The new traffic data generated by the advertisement is then determined based on the visit data and the advertising performance coefficient.

[0139] Because in the above method, after advertising for the target product on multiple first platforms, the advertising delivery data and the access data of the target product on the second platform can be obtained, and then the advertising performance index of each advertisement for the target product is determined based on the advertising delivery data, the access data and the platform weight of each first platform in the multiple first platforms, and finally the new traffic data of each advertisement is determined, thereby achieving the purpose of analyzing the delivery effect of each advertisement.

[0140] For other examples of this embodiment, please refer to the above examples and will not be repeated here.

[0141] Figure 6 is a structural block diagram of an optional electronic device according to an embodiment of the present application, such as Figure 6 As shown, it includes a processor 602, a communication interface 604, a memory 606 and a communication bus 608, wherein the processor 602, the communication interface 604 and the memory 606 communicate with each other through the communication bus 608, wherein,

[0142] Memory 606, for storing computer programs;

[0143] The processor 602 is configured to implement the following steps when executing the computer program stored in the memory 606:

[0144] Obtaining advertisement delivery data for each of a plurality of advertisements delivered for a target product on a plurality of first platforms and access data for the target product on a second platform, wherein each of the plurality of first platforms delivers at least one advertisement from the plurality of advertisements;

[0145] determining an advertising performance index for each advertisement for a target product based on the advertising delivery data, the access data, and the platform weight of each of the plurality of first platforms;

[0146] Based on the visit data and the advertising performance index of each advertisement, the new traffic data of each advertisement is determined.

[0147] Optionally, in this embodiment, the communication bus may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 The use of only one thick line in the figure does not mean that there is only one bus or only one type of bus. The communication interface is used for communication between the above electronic devices and other devices.

[0148] The memory may include RAM, or may include non-volatile memory, such as at least one disk memory. Alternatively, the memory may also be at least one storage device located away from the aforementioned processor.

[0149] As an example, the memory 606 may include, but is not limited to, the first acquisition module 502, the first determination module 504, and the second determination module 506 in the advertisement analysis device. Furthermore, it may also include, but is not limited to, other modules and units in the request processing device, which will not be described in detail in this example.

[0150] The above-mentioned processor can be a general-purpose processor, including but not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; it can also be DSP (Digital Signal Processing), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0151] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0152] It can be understood by those skilled in the art that Figure 6 The structure shown is for illustration only. The device for implementing the above-mentioned advertising analysis method may be a terminal device, which may be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, MID), a PAD, and other terminal devices. Figure 6 It does not limit the structure of the above electronic device. For example, the electronic device may also include Figure 6 More or fewer components (such as network interfaces, display devices, etc.) shown in, or with Figure 6 Different configurations shown.

[0153] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, which can include: a flash drive, ROM, RAM, a magnetic disk or an optical disk, etc.

[0154] According to another aspect of the embodiments of the present invention, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned advertising analysis method are executed.

[0155] Optionally, in this embodiment, a person of ordinary skill in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing the hardware related to the terminal device through a program, and the program may be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0156] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0157] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above-mentioned computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes a number of instructions for causing one or more computer devices (such as personal computers, servers, or network devices) to execute all or part of the steps of the methods described in various embodiments of the present invention.

[0158] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0159] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0160] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0161] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0162] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. An advertising analysis method, characterized in that: include: Obtaining advertisement delivery data for each of a plurality of advertisements delivered for a target product on a plurality of first platforms and access data for the target product on a second platform, wherein each of the plurality of first platforms delivers at least one advertisement from the plurality of advertisements; determining an advertising performance index of each of the advertisements for the target product based on the advertisement delivery data, the access data, and a platform weight of each of the plurality of first platforms; Determining new traffic data for each of the advertisements based on the access data and the advertisement performance index of each of the advertisements; Wherein, determining the advertising performance index of each advertisement for the target product based on the advertising delivery data, the access data, and the platform weight of each of the plurality of first platforms includes: determining the platform weight of each of the first platforms; normalizing the advertising delivery data of each advertisement according to a first time period to obtain a first normalized result; and multiplying the first normalized result by the platform weight to obtain the advertising performance index of each advertisement in each of the first time periods; Determining the platform weight of each of the first platforms includes: taking each of the first platforms as a current platform, performing the following operations: obtaining historical delivery data and historical access data of the current platform within a second time period; normalizing the historical delivery data according to the second time period to obtain a second normalized result; normalizing the target access data of the current platform in the historical access data according to the second time period to obtain a third normalized result; and determining the regression coefficient of the third normalized result and the second normalized result as the platform weight of the current platform; Among them, the determining of the new traffic data of each of the first platforms and the advertising performance index of each of the advertisements includes: taking each of the advertisements as the current advertisement, and performing the following operations: comparing the advertising performance index of the current advertisement with the sum of the advertising performance indexes of each of the advertisements in the first time period to obtain the advertising performance index ratio of the current advertisement; and taking the product of the access data in the first time period and the advertising performance index ratio of the current advertisement as the new traffic data of the current advertisement.

2. The method according to claim 1, characterized in that Each of the advertisements includes a first advertisement consisting of a basic push advertisement and a second advertisement consisting of a basic push advertisement and an additional push advertisement. The method further includes: Normalizing the advertising delivery data of each advertisement according to a first time period to obtain a first normalized result, and obtaining a normalized result of the basic push advertisement of each advertisement and a normalized result of the additional push advertisement in the second advertisement; Calculate the basic new traffic data of the basic promotion advertisement of each advertisement and the additional new traffic data of the additional push advertisement of each second advertisement according to the normalized result of the basic push advertisement of each advertisement and the normalized result of the additional push advertisement; Obtaining a basic resource consumption value of a basic push advertisement for each of the advertisements, and a resource consumption value of an additional push advertisement for each of the second advertisements; The basic push advertising cost of each of the advertisements is determined based on the basic new traffic data and the basic consumed resource value, and the additional push advertising cost of each of the second advertisements is determined based on the additional push new traffic data and the additional push consumed resource value.

3. The method according to claim 2, characterized in that The method further comprises: When the additional advertisement cost of the current advertisement in each of the advertisements is less than a first threshold, the proportion of the additional advertisements of the current advertisement is increased or the push amount of the additional advertisements of the current advertisement is increased.

4. The method according to claim 1, wherein The method further comprises: When the new traffic data of the current advertisement in each of the advertisements is greater than the second threshold, the proportion of the additional advertisements of the current advertisement is increased or the push amount of the additional advertisements of the current advertisement is increased.

5. The method according to claim 1, wherein The method further comprises: Display the new traffic data of each advertisement; When an instruction to push additional advertisements for a target advertisement is received, the proportion of the additional advertisements for the target advertisement is increased or the push amount of the additional advertisements for the target advertisement is increased.

6. The method according to any one of claims 1 to 5, characterized in that The method further comprises: determining an object for operating each of the plurality of advertisements, to determine a plurality of objects; The new customer acquisition contribution value of each of the objects is determined based on the new customer acquisition traffic data and / or new customer acquisition advertising cost of each of the advertisements.

7. An advertising analysis device, characterized in that: include: a first acquisition module, configured to acquire advertisement delivery data for each of a plurality of advertisements delivered for a target product on a plurality of first platforms and access data for the target product on a second platform, wherein each of the plurality of first platforms delivers at least one advertisement from the plurality of advertisements; a first determining module, configured to determine an advertising performance index of each of the advertisements for the target product based on the advertisement delivery data, the access data, and a platform weight of each of the plurality of first platforms; A second determining module is configured to determine new traffic data of each advertisement based on the access data and the advertisement performance index of each advertisement; Wherein, determining the advertising performance index of each advertisement for the target product based on the advertising delivery data, the access data, and the platform weight of each of the plurality of first platforms includes: determining the platform weight of each of the first platforms; normalizing the advertising delivery data of each advertisement according to a first time period to obtain a first normalized result; and multiplying the first normalized result by the platform weight to obtain the advertising performance index of each advertisement in each of the first time periods; Determining the platform weight of each of the first platforms includes: taking each of the first platforms as a current platform, performing the following operations: obtaining historical delivery data and historical access data of the current platform within a second time period; normalizing the historical delivery data according to the second time period to obtain a second normalized result; normalizing the target access data of the current platform in the historical access data according to the second time period to obtain a third normalized result; and determining the regression coefficient of the third normalized result and the second normalized result as the platform weight of the current platform; Among them, the determining of the new traffic data of each of the first platforms and the advertising performance index of each of the advertisements includes: taking each of the advertisements as the current advertisement, and performing the following operations: comparing the advertising performance index of the current advertisement with the sum of the advertising performance indexes of each of the advertisements in the first time period to obtain the advertising performance index ratio of the current advertisement; and taking the product of the access data in the first time period and the advertising performance index ratio of the current advertisement as the new traffic data of the current advertisement.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

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