KR20110011947A

KR20110011947A - System and method for analysis and statistical processing of internet display advertisement

Info

Publication number: KR20110011947A
Application number: KR1020090069435A
Authority: KR
Inventors: 유광석; 이명석
Original assignee: (주)리서치애드
Priority date: 2009-07-29
Filing date: 2009-07-29
Publication date: 2011-02-09

Abstract

PURPOSE: An internet advertisement analysis and a statistic process system for supplying systematized internet display advertisement-related information is provided to classify the collected advertisement by collecting the exposed advertisement interposed on fixed advertisement slots of internet media. CONSTITUTION: A clipping engine(20) automatically collects exposed advertisements. The clipping engine accumulates basic data and supports an advertisement classification and statistics management system. An advertisement classifying management system classifies the collected clipping advertisement by each level and updates data. The advertisement classifying management system calculates advertisement costs. A user PC(60) searches the updated advertisement statistic data through a website.

Description

System and method for analysis and statistical processing of internet display advertisement}

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to the processing of Internet display advertisements (commonly referred to as "banner advertisements"), and is exposed to the Internet. The present invention relates to an analysis and statistical processing system and method for analyzing an Internet-exposed advertisement that is suitable for extracting and processing information included in an advertisement from an advertisement) and supplying it to a customer who needs the result for a fee.

In general, advertisements that take advantage of the features and benefits of the medium of the Internet allow companies to deliver information to more consumers at a lower cost, and also to quickly and accurately understand the effects of advertising, including customer responses. . Such advertisements are largely divided into an interactive media model that connects companies and consumers and a model that combines display advertising.

The interactive media advertisement analyzes the tastes of consumers by using the interactiveness of the Internet and provides advertisements differentially. This allows companies to increase their effectiveness compared to existing ads targeting unspecified majority.

The impression-type advertisement is a band advertisement in the corner of the screen. Like the road advertisement, the impression-type advertisement is displayed in a place where people are frequently visited and the interested person clicks on it to access the homepage. Used.

However, conventionally, by extracting and processing information included in the advertisement from the display advertisement (display advertisement, commonly referred to as 'banner advertisement') in a fixed advertisement slot on a web site (Web Site) There was no technology that could systematically identify the size and execution status of Internet-exposed advertising expenses by industry, advertiser (company), and media. In addition, there was no system to provide relevant information about Internet-exposed advertisements as a database.

Accordingly, the present invention has been proposed to solve the above-mentioned general problems, and an object of the present invention is to analyze Internet-exposed ads that can be conveniently used by users who need them by organizing information related to Internet-exposed ads. And a statistical processing system and method thereof.

In addition, another object of the present invention is to collect the exposed ads in the fixed advertising slot (Slot) of the Internet (Web Site) through a unique device (Clipping Engine) and then classify and statistical processing the results of the website The present invention provides a system and method for analyzing and statistically displaying Internet-exposed advertisements.

In addition, another object of the present invention is an analysis and statistical processing system of the Internet-exposed ads that can extract and process the information contained in the advertisements from the exposed advertising on the Internet and supply them to customers in need for the results for a fee; To provide that method.

Furthermore, another object of the present invention is to collect image files such as the extension GIF, JPG, SWF, etc. exposed to the exposed position (advertised as 'banner advertisement') placement (advertising space, slot) on the Internet Analysis and statistics of internet-exposed ads that can calculate internet-exposed advertising costs for specific industries, advertisers (businesses), and media by using option information for calculating the amount of advertising applied with correction factors such as the date of publication, media, and page information. It is to provide a processing system and method thereof.

It is still another object of the present invention to provide a system and method for analyzing and statistically displaying Internet-exposed advertisements that can be utilized for identifying and benchmarking Internet-exposed advertisement trends through rapid collection, storage, and provision of complete Internet-exposed advertisement files. There is.

It is still another object of the present invention to provide an analysis and statistical processing system and method for analyzing an Internet-exposed advertisement that can convincingly grasp the size and execution status of advertisement costs through systematic estimation of Internet advertisement costs.

It is still another object of the present invention to provide a system and method for analyzing and statistically displaying Internet-exposed advertisements that can provide internet advertisement data supporting cross media research according to media diversification. have.

Another object of the present invention is to provide a system and method for analyzing and statistically displaying Internet-exposed advertisements that can build an Internet advertising database that meets the needs of market participants and has industrial and academic values.

It is another object of the present invention to provide a system and method for analyzing and statistically analyzing an Internet-exposed advertisement that can analyze the execution status of competitors' Internet advertisements.

It is another object of the present invention to provide a system and method for analyzing and statistically processing Internet-exposed advertisements that can construct and manage a database of Internet advertisements.

It is still another object of the present invention to provide an analysis and statistical processing system and method for analyzing Internet-exposed ads that can organize an analysis and statistics system for internet advertisements.

It is another object of the present invention to provide an analysis and statistical processing system and method for analyzing an Internet-exposed advertisement that can be used as a basis for establishing an internet advertisement and marketing strategy.

FIG. 1 is a block diagram of a system for analyzing and statistically displaying internet-exposed advertisements according to an embodiment of the present invention. FIG. 2 is a detailed block diagram of a clipping engine in FIG. 1.

As shown in the figure, a clipping engine that automatically collects exposure-type advertisements interspersed in the advertisement space of Internet media in real time and removes the media's own advertisement from the collected advertisements, accumulates basic data, and supports an advertisement classification and statistics management system. and; Classify the clipping advertisement collected by the clipping engine in stages to update the data through the website, statistics the classified advertisements in each stage, calculate the unit price, manage raw data, and apply the unit price An advertisement classification management system for analyzing data integrity in the; An advertisement statistics management system for statistically classifying advertisements in the advertisement classification management system, uploading them to respective statistics modules, comparing the actual advertisement execution history through sampling, and regularly updating advertisement data through a website; And a user PC for searching advertisements classified by the advertisement classification management system and advertisement statistics data updated by the advertisement statistics management system through a website, wherein the clipping engine is classified by advertisement media. A URL storage database for classifying and storing URL information; A plurality of window reading units having buttons for viewing the Internet web browser by the number of setting browsers and the setting time; A template extraction unit for extracting a template of an advertisement image from each browser in the plurality of window viewing units; And an image classification storage database for classifying and storing the advertisement image for each field by comparing the URL information in each advertisement image template extracted by the template extractor with the URL information stored in the URL storage database. It is done.

The analysis and statistical processing system of the Internet-exposed advertisement, collects the exposure-type advertisement in the advertising space of the Internet medium in real time, and then analyzes and statistically processes the result and posts the result through a dedicated website or produces a report. And then send the results to customers for a fee, and then display the extension (GIF, JPG, SWF) that is exposed in the placement (advertisement slot) of exposed ads on the Internet (advertised as 'banner ads'). At the same time, it collects the image files containing the information, and the correction information is applied to the information including the advertisement publication date, the medium, and the page information, and the option information for calculating the advertisement amount is utilized. Calculate the cost of advertising, and quickly collect, store, and provide complete Internet-exposed advertising files to identify and display Internet-exposed advertising trends. It characterized in that one to take advantage of the skirts King.

3 is a flowchart illustrating a method for analyzing and statistically displaying an internet-exposed advertisement according to an embodiment of the present invention, FIG. 4 is a detailed flowchart of a clipping step in FIG. 3, and FIG. 5 is a step of secondary classification in FIG. 3. Operation flow chart for the job.

As shown therein, (a) a clipping step of collecting, in real time through a clipping engine, an exposed advertisement interspersed in the advertisement space of the Internet medium; (b) a first classification step of removing media own advertisements from the collected advertisements through the clipping engine and accumulating basic data; (c) a second classification step of classifying the first classified clipping advertisement step by step through an advertisement classification management system and calculating an advertisement price; (d) an analysis step of managing raw data in the advertisement classification management system and analyzing data integrity in an advertisement unit price application process; (e) a statistic step of performing statistics on the classified advertisements through an advertisement statistics management system, uploading them to respective statistics modules, and calculating an advertisement fee; (f) a verification step of comparing the actual advertisement execution history through sampling in the advertisement statistics management system; And (g) reporting the advertisement statistics data and advertisements regularly updated on the website by the advertisement classification management system and the advertisement statistics management system, wherein step (a) (clipping step) is performed. (a1) classifying and storing URL information in a URL storage database for each advertising media field; (a2) viewing the Internet web browser by the number of setting browsers and the setting time in the plurality of window reading units; (a3) extracting a template of an advertisement image from each browser in the plurality of window viewing units; (a4) comparing the URL information in each extracted advertisement image template with the URL information stored in the URL storage database, and classifying and storing the advertisement image for each corresponding field.

In the step (a), it is characterized by clipping an image file including the extension GIF, JPG, SWF exposed from the banner advertisement on the Internet.

The method of removing the media company's advertisement in step (b) is characterized in that it is removed after tracking and classifying by advertisement file name.

The basic data in the step (b) is characterized in that it includes the advertisement file option information to which the correction coefficient for the information including the advertisement publication date, media, page information.

In the step (c), the step-by-step classification method includes: (c1) classifying a subject according to the advertisement execution subject of the clipping advertisement, and (c2) determining a specification of the advertisement classified as a corporate (paid) advertisement by the subject classification. Standard classification step, (c3) advertisers / items / campaign classification step to classify the advertisements with the determined standard by advertiser, item (brand), and (c4) the classification work up to step (c3) And a copy input step of inputting all the texts displayed on the advertisement for the finished advertisement.

In the step (c1), it is characterized by categorizing by company advertisement, affiliate advertisement, media company advertisement, small and medium advertisement, held advertisement.

In the step (c2), it is characterized by managing for each medium / slot and updating according to the change.

The advertising unit price in the step (c) is characterized in that it is applied to the monitoring at all times through the media, media lab network.

In the step (c), the method of calculating the advertisement cost is calculated based on the 'date of advertisement X X unit price X correction coefficient', and the correction coefficient is characterized in that it includes media, page information, and the like.

In the step (d), the industry code for managing raw data, the industry management item for managing the generation, consolidation, and adjustment of industry type / industry / small category items, and the media for changing, adding, and excluding media information. And a management item for managing the adjustment of the advertiser creation, deletion and integration.

The verification in step (f) is characterized by verifying the criteria through Naver, including the next quarterly disclosure data, and through the media lab, agency monitoring on a non-periodical basis.

Analysis and statistical processing system and method of internet exposure advertisement according to the present invention has the following effects.

1. You can organize and use information related to Internet-exposed advertising.

2. After collecting the exposed advertisements on the fixed advertisement slot of the web site through the clipping engine, the classified and statistical processes may be provided and the results may be provided through the website.

3. The advertisement information can be extracted and processed from banner advertisements on the Internet and supplied to the member companies for a fee.

4. Clipping of image files such as GIF, JPG, SWF, etc. exposed from banner advertisements on the Internet, and accumulating advertisement file option information applying correction factors such as advertisement publication date, media, and page information, The advertisement cost of the banner advertisement can be calculated.

5. It can be used for trend identification and benchmarking through rapid collection and provision of complete internet advertisement files.

6. Through systematic estimation of Internet advertising expenses, the scale and execution status of advertising expenses can be convincingly understood.

7. Can provide internet advertising data to support cross media research as media diversifies.

8. Build an Internet advertising database that meets the needs of market participants and has industrial and academic value.

9. Analyze the execution status of competitors' Internet advertisements.

10. Can build and manage a database of Internet advertisements.

11. Systematize the analysis and statistics system of Internet advertising.

12. Can be used as a basis for establishing Internet advertising and marketing strategies.

An exemplary embodiment of the analysis and statistical processing system and method for analyzing Internet-exposed advertisements according to the present invention configured as described above will be described in detail with reference to the accompanying drawings. In the following description of the present invention, detailed descriptions of well-known functions or configurations will be omitted if it is determined that the detailed description of the present invention may unnecessarily obscure the subject matter of the present invention. In addition, terms to be described below are terms defined in consideration of functions in the present invention, which may vary according to intention or precedent of a user or an operator, and thus, the meaning of each term should be interpreted based on the contents throughout the present specification. will be.

1 is a block diagram of an analysis and statistical processing system of an Internet exposed advertisement according to an embodiment of the present invention.

As shown in FIG. 1, the system for analyzing and statistically analyzing internet advertisements according to an exemplary embodiment of the present invention includes an internet advertisement medium 10, a clipping engine 20, an advertisement classification and statistics management system 30, and advertisement statistics. The data 40, the advertisement 50, and the user PC 60 are configured.

First, the internet advertising medium 10 includes all domestic internet websites in which advertising sales occur regularly.

The clipping engine 20 automatically collects banner advertisements interspersed in the advertisement space of the Internet media in real time, and accumulates basic data by removing media own advertisements from the collected advertisements. The advertisement classification and statistics management system 30 Support.

FIG. 2 is a detailed block diagram of the clipping engine in FIG. 1.

Thus, the clipping engine 20 may be configured of a URL storage database 21, a plurality of window viewing units 22, a template extraction unit 23, and an image classification storage database 24.

The URL storage database 21 classifies and stores URL information for each advertising medium field.

The multiple window reading unit 22 includes a button for reading the Internet web browser by the number of setting browsers and the setting time, and transmits the reading result to the template extracting unit 23.

The template extracting unit 23 extracts a template of an advertisement image from each browser in the plurality of window viewing units 22 and delivers the template of the advertisement image to the image classification storage database 24.

The image classification storage database 24 compares the URL information in each advertisement image template extracted by the template extraction unit 23 with the URL information stored in the URL storage database 21, and classifies and stores the advertisement images for respective fields. .

Through this, the present invention collects the exposure-type advertisements included in the advertisement space of the Internet media in real time, analyzes and processes the statistics and posts the results through a dedicated website or transmits the generated report to the customers and sends the result to the customers. Collects image files including GIF, JPG, and SWF, which are extensions exposed to the placement (advertising space, slot) of exposed ads on the Internet (advertised as 'banner ads') on the Internet, At the same time, by applying the correction factor to the information including the advertisement publication date, media, and page information, the option information for calculating the advertising amount is utilized to calculate the Internet exposure advertising costs of a specific sector, advertiser (company), and media. Rapid collection, storage, and provision of Internet-exposed advertising files can be used to identify and benchmark Internet-exposed advertising trends.

Meanwhile, a method for selecting a medium for collecting banner advertisements in the clipping engine 20 is as follows.

As a first step, the medium is selected and input according to the ranking of websites according to the Internet usage status. At this time, the media is selected in consideration of the metric corporation and Korean click overlapping the ranking of the website.

As a second step, select and add specialized sites for each industry. In this case, refer to Internet connection amount and industry / user awareness.

As a third step, input after a decision by the advisory panel (regular review).

As a fourth step, the selection medium is added and excluded. In this case, if the necessity is recognized according to the request of the company, it is immediately reflected and the selection media is added and excluded through regular deliberation by the advisory group.

The advertisement classification management system in the advertisement classification and statistics management system 30 classifies the clipping advertisement (banner advertisement) collected by the clipping engine 20 step by step to update data through a website and classifies the step by step. It calculates the advertising cost, calculates the advertising price, manages raw data, and analyzes the data integrity in the process of applying the advertising price. In this case, it is preferable to apply the advertising unit price by constantly monitoring through each medium and media lab network.

The advertisement statistics management system in the advertisement classification and statistics management system 30 statistics the classified advertisements in the advertisement classification management system, uploads them to their respective statistics modules, and compares them with actual advertisement execution details through sampling.

The advertisement classification and statistics management system 30 regularly updates the advertisement statistics data 40 and the advertisement 50 through the website.

The user PC 60 reports the advertisement statistics data 40 and the advertisement 50 through the website.

3 is a flowchart illustrating a method of analyzing and statistically displaying an Internet-exposed advertisement according to an embodiment of the present invention.

As shown in FIG. 3, the method of analyzing and statistically processing internet-exposed advertisements according to an embodiment of the present invention includes a clipping step S10, a first classification step S20, and a second classification step S30. ), An analysis step (S40), statistics (Statistics) step (S50), verification step (S60), and reporting (Reporting) step (S70).

First, in the clipping step S10, the exposure type advertisement interposed on an advertisement slot of an internet medium is automatically collected in real time through the clipping engine 20.

In this case, the clipping engine 20 measures display-type Internet advertisements (banner advertisements) excluding sponsorship, email, text, and video player advertisements, and the extension GIF, JPG, SWF, etc. exposed from banner advertisements on the Internet. By clipping the image file, we collect banner advertisements.

The clipping engine 20 accumulates the advertisement file option information for applying the correction coefficient such as the advertisement publication date, the medium, the ground information, and the like while clipping the advertisement file.

4 is a detailed flowchart of the clipping step in FIG. 3.

Thus, (a1) the URL information is classified and stored in the URL storage database for each advertising medium field (S11).

In addition, (a2) the plurality of window reading unit 22 browses the Internet web browser by the number of setting browsers and the setting time (S22).

In addition, (a3) the template extraction unit 23 extracts the template of the advertisement image from each browser in the plurality of window viewing unit 22 (S23).

In addition, (a4) the URL information in each extracted advertisement image template and the URL information stored in the URL storage database 24 are compared, and the advertisement image is classified and stored for each corresponding field (S24).

Next, in the first classification step S20, media own advertisements are removed from the advertisements collected through the clipping engine 20, and the basic data is accumulated.

Here, the method of removing the media company advertisement may be classified after being classified by advertisement file name and then removed. Preferably, the basic data includes advertisement file option information to which a correction coefficient such as advertisement publication date, medium, and page information is applied.

Next, in the second classification step (S30), the banner advertisement classified into the first category is classified step by step through the advertisement classification management system and the advertisement unit price is calculated.

Here, the step-by-step classification method, as shown in Figure 5, subject classification step (S31), standard classification step (S32), advertiser / item (brand) / campaign classification step (S33), copy (Copy) input step ( S34).

The subject classification step S31 is classified according to the advertisement execution subject of the clipping advertisement. In this case, the advertisement execution subject may include a corporate advertisement, affiliate advertisement, media company advertisement, pending advertisement.

The subject classification step (S31) is for the purpose of distinguishing the corporate (paid) advertising, advertising other than the corporate advertising is separately managed after, and the company's own media is filtered in the primary classification step (S20).

In the specification classification step S32, the specification of the advertisement classified as a corporate (paid) advertisement is determined by the subject classification step S31. And manage by media / advertising slot (Slot) and update according to the change.

The advertisement has media and page information during clipping. In this case, the standard classification is used as basic information for calculating the advertising amount, and in the case of a new standard, the standard registration operation is performed at the same time.

The advertiser / item (brand) / campaign classification step (S33) classifies the determined advertisements by advertiser and item (brand) and bundles them in campaign units. In this case, new advertisers, items (brands) and campaigns are registered, and when registering new items (brands), the advertisement type codes are assigned according to the items, and individual advertisements are controlled in campaign units through campaign registration.

That is, the advertiser / item (brand) / campaign classification step (S33) manages the accurate registration and duplication of the advertiser, the item (brand).

The copy input step S34 inputs all the texts displayed on the advertisements for the classified advertisements from the step S31 to the step S33. It has a variety of applications through advertisement copy search.

Next, the analysis step (S40) in Figure 3 manages the raw data (Raw Data) in the advertisement classification management system and analyzes the data integrity in the advertising unit price application process.

Here, the item for managing the raw data (Raw Data), as shown in Figure 6, the item (brand) management items, industry management items, including campaign management items, advertising standards management items, advertising space (Slot) Media management items including management items, advertiser management items, and the like.

In this case, the industry management item manages the industry code, industry type large / medium / small category items, integration and adjustment. For example, it now consists of 21 major, 187 middle, and 1128 subclasses.

The item (brand) management item manages item (brand) creation, deletion, consolidation, and industry code granting, and the campaign management item manages adjustment such as campaign generation, deletion, and consolidation. The item (brand) management and campaign management items manage the duplication and mistake creation.

The media management item manages media information change, addition and exclusion.

The advertisement specification management item monitors the media lab or the media to quickly apply the changes of the advertisement standard and the unit price, and the advertisement surface management item monitors the media lab or the medium to quickly apply the change of the advertisement page link information. .

The advertiser management item manages coordination of advertiser creation, deletion, integration, and the like, and manages duplication and misleading generation.

Next, the statistical step (S50) in Figure 3 is the statistics for the classified ads through the advertising statistics management system and uploaded to each of its own statistical module to calculate the advertising costs.

At this time, the method of calculating the advertising cost is calculated by the formula of 'advertisement date ㅧ daily unit price ㅧ correction coefficient', and after correcting the daily advertising amount. In this case, the advertisement cost correction option includes a media correction option, a ground correction option, an account correction option, an inflation rate, and the like. In this case, the media correction option applies a differential based on the PV contrast for each medium, and the ground correction option applies a differential based on the PV contrast for each ground. The structural correction option applies the number and frequency of exposure advertisements to the number of accounts for each page. Here, it is preferable to apply the advertising unit price by constantly monitoring through each medium and media lab network.

Accurate advertisement specifications and unit price information have the greatest influence on the reliability of the data. Therefore, it is necessary to quickly reflect changes in specifications and unit prices through the change of advertising products in the media.

The method of collecting information about advertisement page, specification and unit price is as follows.

As a first step, information on the website is collected. At this time, the media website providing information is collected.

As a second step, information is collected through the medium. In this step, when there is a modification of the information provided by the website or no information provided through the website, information is collected through the medium.

As a third step, the actual selling price information is collected through the media lab.

As a fourth step, integrate and coordinate collection / investigation information. At this time, regular investigation and change monitoring are performed in parallel.

Next, the verification step (S60) in Figure 3 is verified by comparing with the actual advertisement execution history through the sampling in the advertising statistics management system. In this case, the verification method is preferably verified by Naver, the next quarterly disclosure data, and regularly verified through media labs and agency monitoring.

Then, the reporting step (S70) reports the advertisement statistics data and advertisements regularly updated on the website by the advertisement classification management system and the advertisement statistics management system.

7 is a diagram illustrating a step-by-step operation of real-time automatic clipping.

The clipping engine 20 may operate according to the number of visits by media, advertisement surface, and number of accounts.

In the clipping engine 20, an operation for automatically clipping an exposed advertisement in real time through an internet medium is largely set as an option setting step (step 1), driving and checking step (step 2), and finishing and verification step (step 3). Can be divided.

Here, the option setting step (step 1) includes a driving option for each medium, a driving option for each ground, a driving option for an account, and a driving option for each advertisement characteristic.

The operation and inspection step (step 2) includes engine operation by medium / ground, checking of normal operation of option information, engine operation state checking, and mechanical primary classification.

The closing and verification step (step 3) includes daily / weekly / monthly service deadline, media / ground run deadline, operation result variation check, and linking to classification work.

8 is a diagram illustrating the operation of each step for class classification.

In the sector classification, the process of integrating the online and offline advertising sector classification systems, reorganizing the online industry classification system (step 1), analyzing the offline industry classification system (step 2), and Integrate / Offline Scenario Integration (Step 3) and Add Changes (Step 4).

At this time, in the re-establishment of the online industry classification system (step 1), reference is made to Korean Standard Industry Classification, Internet Marketing Association Recommendation. The offline industry classification system analysis step (step 2) refers to the 'KOBACO' advertising industry classification code. In the on / offline sector classification system integration step (step 3), the deliberation of new businesses, integration work, and advisory faculty will be considered. Lastly, in the step of reflecting additional changes (step 4), additional changes are reflected through regular deliberations of advisory professors, and regular opinions are exchanged with the offline side.

9 is a diagram illustrating items of a measurement index, a classification index, and a publication index.

Referring to FIG. 9, the measurement index technically extracts extractable elements from a clipped advertisement, and includes items such as a medium, a page, a specification, a copy, an advertisement publication start date, an advertisement publication end date, and the like.

The classification index is to analyze and classify in stages according to its own setting criteria based on information extracted from a clipped advertisement, and items such as advertisement characteristics, advertisement specifications, advertisers, brands (items), campaigns, and industries It includes.

The reporting index quantifies the classified advertisement information and displays the classified information according to the posted item. The reporting index includes items such as an industry type, an advertiser, a brand (item), a campaign, a medium, a page, an advertisement fee, an advertisement, a copy, and the like. .

10 is a view showing each step operation for calculating the advertising amount.

The method of calculating the amount of advertisement includes collecting and updating the advertisement specification / unit price information (step 1), calculating a correction coefficient (step 2), calculating an advertisement amount (step 3), checking and correcting step (step 4), and the like. .

Here, in the collecting and updating the advertisement specification / unit price information (step 1), the advertisement specification / unit price information is collected and updated by monitoring through the media and the media lab network. In the calculating of the correction factor (step 2), the media, page view, advertisement operation characteristics, and the like are taken into consideration. In the advertisement amount calculation step (step 3), it operates in conjunction with the measurement data of the clipping engine. In the checking and correcting step (step 4), the monitoring and correction are performed by monitoring the change in the media advertising unit price.

11 is a view showing a content screen of a website for report output.

As shown in FIG. 11, the content screen of the website for outputting the report includes items such as period, classification, selection items, and trends. The period items are divided into daily, weekly, and monthly, and the classification items are classified into medium, industry, advertiser, and brand.

The selection item of the medium includes media selection, media industry classification, advertiser, brand, publication surface, and the like. The selection item of the industry is composed of industry classification, industry classification, media selection, media industry classification, advertiser, brand, media, publication surface and the like. The advertiser's selection items include advertiser selection, competitive advertiser selection, media selection, media industry classification, brand, campaign, media, publication page, and quarter. In addition, the selection item of the brand is composed of brand selection, competitive brand selection, media selection, media industry classification, advertiser, campaign, media, publication page, semi-annual.

12 is a diagram illustrating a content screen of a website for advertising statistics and advertisement search.

First, the content screen of the website for advertising statistics is classified into industry statistics, company statistics, brand statistics, media statistics, and there are selection items such as industry classification, industry classification, company selection, brand selection, and media selection. Period items such as, weekly and monthly are organized.

The content screen of the website for the advertisement search has period items such as daily, weekly, and monthly, and it is classified into industry category, industry category, company selection, brand selection, media selection, main advertisement selection, copy input, horizontal advertisement, and vertical length. It consists of selection items such as advertisement, square advertisement, floating advertisement.

Although the above has been described as being limited to the preferred embodiment of the present invention, the present invention is not limited thereto and various changes, modifications, and equivalents may be used. Therefore, the present invention can be applied by appropriately modifying the above embodiments, it will be obvious that such application also belongs to the scope of the present invention based on the technical idea described in the claims below.

FIG. 2 is a detailed block diagram of the clipping engine in FIG. 1.

3 is a flowchart illustrating a method for analyzing and statistically displaying an internet-exposed advertisement according to an embodiment of the present invention.

4 is a detailed flowchart of the clipping step in FIG. 3.

FIG. 5 is an operation flowchart for the step-by-step operation of the secondary classification in FIG. 3.

FIG. 6 is a table showing items for managing raw data in the analysis step of FIG. 3.

11 is a view showing a content screen of a website for report output.

Explanation of symbols on the main parts of the drawings

10: Internet advertising media

20: clipping engine

21: URL storage database

22: multiple window reading unit

23: template extraction unit

24; Image classification storage database

30: Ad classification and statistics management system

40: Advertising statistics data

50: advertisement

60: user PC

Claims

A clipping engine that automatically collects exposed advertisements interspersed in advertisement spaces of Internet media in real time and removes the media company's advertisements from among the advertisements collected, and accumulates basic data, and supports an advertisement classification and statistics management system;

Classify the clipping advertisement collected by the clipping engine in stages to update the data through the website, statistics the classified advertisements in each stage, calculate the unit price, manage raw data, and apply the unit price An advertisement classification management system for analyzing data integrity in the;

An advertisement statistics management system for statistically classifying advertisements in the advertisement classification management system, uploading them to respective statistics modules, comparing the actual advertisement execution history through sampling, and regularly updating advertisement data through a website; And

A user PC for searching advertisements classified by the advertisement classification management system and advertisement statistics data updated by the advertisement statistics management system through a website;

It is configured to include, the clipping engine,

A URL storage database for classifying and storing URL information for each advertising media field;

A plurality of window reading units having buttons for viewing the Internet web browser by the number of setting browsers and the setting time;

A template extraction unit for extracting a template of an advertisement image from each browser in the plurality of window viewing units;

An image classification storage database for classifying and storing the advertisement image for each field by comparing the URL information in each advertisement image template extracted by the template extractor with the URL information stored in the URL storage database;

Analysis and statistical processing system of Internet exposed advertising, characterized in that configured to include.

The method according to claim 1,

The analysis and statistical processing system of the internet exposure ads,

It collects and displays real-time exposed advertisements on the advertising media of internet media, analyzes and statistics, publishes the results through a dedicated website, or sends the produced report to customers for paying the results to customers. And collect image files including GIF, JPG, and SWF, which are extensions exposed to the placement (advertising space, slot) of exposed ads on the Internet (advertised as 'banner ads'), A correction factor is applied to the information including the media and the page information, and the option information for calculating the advertising amount is used to calculate the Internet exposure advertising costs of the specific industry, advertiser (company), and the media. Fast collection, storage, and delivery of the Internet's exposed advertising trends and benchmarking Exposure ad analysis and statistical systems.

In the Internet exposure analysis and statistics method,

(a) a clipping step of collecting, in real time through a clipping engine, an exposed advertisement displayed on an advertisement sheet of an internet medium;

(b) a first classification step of removing media own advertisements from the collected advertisements through the clipping engine and accumulating basic data;

(c) a second classification step of classifying the first classified clipping advertisement step by step through an advertisement classification management system and calculating an advertisement price;

(d) an analysis step of managing raw data in the advertisement classification management system and analyzing data integrity in an advertisement unit price application process;

(e) a statistic step of performing statistics on the classified advertisements through an advertisement statistics management system, uploading them to respective statistics modules, and calculating an advertisement fee;

(f) a verification step of comparing the actual advertisement execution history through sampling in the advertisement statistics management system; And

(g) reporting advertisement statistics data and advertisements regularly updated on the website by the advertisement classification management system and the advertisement statistics management system;

Including, and the step (a) (clipping step),

(a1) classifying and storing URL information for each advertising media field in a URL storage database;

(a2) viewing the Internet web browser by the number of browsers set by the number of browsers and the set time in the plurality of window reading units;

(a3) extracting a template of an advertisement image from each browser in the plurality of window viewing units;

(a4) classifying and storing the advertisement image for each field by comparing URL information in each extracted advertisement image template with URL information stored in the URL storage database;

Analysis and statistical processing method of the Internet-exposed advertisement, characterized in that performed.

The method of claim 3, wherein in step (a),

A method for analyzing and statistically displaying an Internet-exposed advertisement comprising clipping an image file including an extension GIF, JPG, and SWF exposed from a banner advertisement on the Internet.

The method of claim 3, wherein

In the step (b), the method of removing the media company advertisement,

Analysis and statistical processing method of Internet-exposed ads, characterized in that the removal by tracking and classifying by the advertisement file name.

The method of claim 3, wherein the basic data in step (b),

A method for analyzing and statistically displaying an Internet-exposed advertisement comprising advertisement file option information applying a correction factor to information including an advertisement publication date, media, and page information.

The method of claim 3, wherein the step of classifying in step (c),

(c1) a subject classification step of classifying according to the advertisement execution subject of the clipping advertisement;

(c2) a specification classification step of determining a specification of advertisement classified as a corporate (paid) advertisement by the subject classification;

(c3) classifying advertisers / items / campaigns by classifying the determined advertisements by advertisers and items (brands) and then grouping them in campaign units; And

(c4) a copy input step of inputting all the texts displayed on the advertisements for the advertisements classified by the step (c3); analysis and statistics of the Internet-exposed advertisements Treatment method.

The method of claim 7, wherein in step (c1),

Method for analyzing and statistically displaying Internet-exposed advertisements, which are classified by corporate advertisement, affiliate advertisement, media company advertisement, and held advertisement.

The method of claim 7, wherein in step (c2),

Method for analyzing and statistically displaying Internet-exposed advertisements, which are managed by media / slot and updated according to changes.

The method of claim 3, wherein the advertising unit price in step (c),

Method for analyzing and statistically displaying Internet-exposed advertisements, which are always monitored and applied through each media and media lab network.

The method of claim 3, wherein in the step (c),

Calculated based on the 'date of advertisement X price unit X'

The correction coefficient is an analysis method and statistical processing method of the Internet exposure advertising, characterized in that it comprises a medium, page information.

The method of claim 3, wherein

Managing raw data (Raw Data) in the step (d),

An industry management item for managing an industry code, industry type / middle / small classification item generation, integration, and coordination;

A media management item for managing change, addition, and exclusion of media information; And

Advertiser management items to manage the adjustment of the advertiser creation, deletion and integration; Internet and display ads analysis and statistical processing method comprising a.

The method of claim 3, wherein the verification in the step (f),

NAVER, based on data including next quarterly disclosure,

Method for analyzing and statistically displaying Internet-exposed advertisements, which are regularly verified through media labs and agency monitoring.