KR101085943B1 - Method and Server apparatus for providing advertizing service - Google Patents

Abstract

This document discloses an advertisement service providing method and server for calculating a customer response index for advertisement exposure and reflecting the same in the advertisement exposure ranking. According to an advertisement service providing method according to an embodiment of the present invention, a customer response is applied by applying a probability that an actual purchase is made on an internet site corresponding to a line item provided as a result of inputting a search word, a penalty according to the time spent on the internet site. The index can be calculated and reflected back in ranking ad impressions. As a result, it increases customer's search reliability and reduces unnecessary competition among advertisers.

Customer response, purchase conversion probability, impression ranking, internet advertising.

Description

Method and server apparatus for providing advertising service {Method and Server apparatus for providing advertizing service}

The present invention relates to internet advertising, and more particularly, to determining exposure ranking of internet advertising.

Today, with the rapid development of communication networks such as the Internet, information retrieval through communication networks is becoming very common. In other words, by using the Internet, Internet users can easily obtain the necessary information anytime, anywhere, and such information retrieval brings a lot of changes throughout our lives.

Accordingly, various models have been developed for billing methods for providing advertisements between a service provider providing a search service to an Internet user and an advertiser who obtains an advertisement effect by providing information about his website to the Internet user through search results. Is being developed.

As an example of a billing method for providing an advertisement, a method of pre-selecting a location where an advertiser's information is to be displayed on a search result providing screen and assuming a predetermined sales amount for each selected location is sold to the advertiser. This allows advertisers who want to display their information in a particular location to give their first-time advertiser the right to display their information for locations that aren't currently showing their information. There is a problem of waiting until the end of the contract period for the information of the advertiser previously displayed in the location.

That is, the above-described method is a billing method in which the advertiser preempts a specific position where the advertiser's information is to be displayed, and includes a disadvantage that other advertisers cannot provide information during the contract period when the information display position is occupied by the advertiser. In addition, even when waiting until the end of the contract period, there is a problem that the information provided by the waiting advertisers can not be guaranteed because it is a sale method on a first-come, first-served basis. In addition, since the sale amount for the display position is determined by the service provider, there is a problem that the advertiser's position is not considered at all on the sale amount.

In order to solve the above problem of the charging method has been proposed a charging method by PPC (Pay Per Click) method. The PPC method calculates the advertising cost by calculating the number of connection connections (valid connections) that a user connects to an advertiser by clicking on information of a specific advertiser included in a search result. According to the size order of the PPC amount (the charge per click), the advertisements of each advertiser are sequentially arranged within a specific area and provided to the user.

In this PPC billing method, advertisers who provide the highest PPC amount are placed at the top within a specific area. Therefore, advertisers use competitively high PPC amount in order to display their information in a relatively good position. As a result, the advertising costs borne by each advertiser must also continuously increase, resulting in an increase in the number of advertisers who give up advertising.

In addition, as described above, it is determined only by the competition of advertisers such as the placement order or location of the advertisement in the specific area of the screen displaying the search result or the highest PPC amount, such as the user requesting the search. There is also a problem that the advertisement can be placed at the top of the search irrelevant to the requested search, in which case the user can be recognized that the search accuracy is low.

The present invention is to solve the above problems, it is a technical problem to provide an advertising service for calculating the customer response index for the advertisement and reflecting it to determine the position or position of Internet advertising.

In addition, the present invention is to provide an advertising service to determine the customer response index by calculating the probability that the actual purchase can be made on the site, that is, the purchase conversion probability among the line items for a specific search term.

In addition, the present invention is to provide an advertising service that determines the customer response index in consideration of the time the user stays on the site of the line item for a specific search term as a technical problem.

According to an aspect of the present invention, there is provided a method of providing an advertisement service, the method comprising: receiving a predetermined search word from a user through the Internet, extracting advertisement items associated with the search word, and an Internet site corresponding to each line item. Acquiring a Customer Reaction Index (CRI) for each line item, which is determined by considering the User Conversion Rate (UCR), which is the probability that a purchase will be made in the UCR, and the customer response index for the extracted line items ( Comparing the CRI), determining the exposure rank of the line items according to the comparison result, and providing each of the line items to the user through the Internet based on the exposure rank.

Ad service providing server apparatus according to another aspect of the present invention for achieving the above object is an input unit for receiving a predetermined search word from the user via the Internet, a line item extraction unit for extracting one or more line items associated with the search word, each advertisement The UCR decision unit calculates a user conversion rate (UCR), which is a probability that a purchase is made on an internet site corresponding to an item, and determines a penalty value that reflects a case where the time spent on each site of each line item is short. A penalty determination unit, an index determination unit for determining a customer response index (CRI) in consideration of the purchase conversion probability (UCR) and the penalty value, and a comparison of the customer response index (CRI) determined for each line item A ranking unit for determining the exposure rank of the line items and each of the line items through the Internet based on the exposure rank And a result display section provided to the user.

According to the present invention, there is an effect of efficiently determining the exposure ranking by considering the response of the user, that is, the customer, in determining the exposure ranking associated with the display position of the Internet advertisement.

In addition, according to the present invention, it is possible to avoid unnecessary competition for advertisers to determine the exposure ranking, there is an effect that can calculate a reasonable advertising cost for advertisers.

In addition, according to the present invention, as the impression ranking is determined in consideration of the purchase conversion probability that the user will actually purchase in the line item related to the search word input by the user, There is a reduction effect, thereby increasing the user's search reliability and satisfaction.

In addition, according to the present invention, as the user determines the exposure ranking in consideration of the dwell time when the user visits the site corresponding to the line item, an appropriate keyword purchase and It is effective in inducing site management.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

One embodiment of the present invention can provide a variety of advertising services through the analysis of the behavior pattern of the user after providing the line item. The advertisement service may include various services such as ranking of an associated advertisement with respect to a specific search word and determining a bill of an advertiser providing the associated advertisement.

In addition, the analysis of the behavioral pattern of the user after providing the line item may include an analysis of the probability of purchase conversion obtained through the analysis of which advertisement the user clicks on, and the analysis of the residence time of the user clicking on the advertisement site. .

Hereinafter, as an example of a method of providing an advertisement service, a method of determining an advertisement location by using factors (for example, purchase conversion probability or distribution of residence time of an advertisement site) obtained through analysis of a behavior pattern of a user after the line item is provided. It will be described, but the present invention is not limited thereto.

1 is an exemplary flowchart of a method of providing an advertisement service according to an embodiment of the present invention.

According to the present exemplary embodiment, unlike the ranking or position of the advertisement is determined by the competition method of the conventional advertisers, the actual user, that is, the response of the customer to the exposure of the advertisement, reflects the response of the line item provided by the customer as a search result. By calculating and considering the probability of the actual purchase of the customer on the page, it is possible to increase the reliability of the search and to avoid unnecessary price competition among advertisers by determining the exposure position or position of the advertisement.

Referring to FIG. 1, first, a predetermined search word is input from a user through the Internet in step S100. In addition, the advertisement items associated with the search word input in step S110 are extracted, and the customer response index (CRI) for each line item is compared in operation S120. The customer response index (CRI) according to this embodiment is indexed to take into account the user's, or customer's, response to ad impressions on the Internet. It may be determined in consideration of the probability that a purchase is made and / or the time a customer stays on the corresponding Internet page. How to determine this will be described in more detail below. In operation S130, the exposure order of the line items is determined based on the comparison result of the customer response index CRI, and the line items arranged according to the exposure order determined in operation S140 are provided through the Internet.

2 is an exemplary structural diagram of an advertisement service providing server according to an embodiment of the present invention.

2, the advertisement service providing server 10 according to the present embodiment may include an input unit 100, a line item extracting unit 105, a UCR determination unit 110, a penalty determination unit 120, The index determiner 130, the rank determiner 140, the result display unit 150, and the database 160 are included.

The input unit 100 according to the present embodiment receives a predetermined search word from a user through the Internet. When a user wants to search for specific information through a communication network, a user may input a search word corresponding to a keyword of information to be obtained and display a advertisement item extracted by the advertisement service providing server 10. Here, the terminal includes a computer, a terminal having a predetermined memory and arithmetic capability, such as a personal digital assistant (PDA), a mobile phone, a smart phone, an electronic dictionary, an MP3 player, and the like.

The advertisement item extractor 105 according to the present embodiment extracts advertisement items associated with a search word input through the input unit 100 using a search engine. The search engine may mean a program or a search server for searching for information corresponding to a predetermined search word input by a user through a search means. For example, a web server at a particular site may be an example.

In response to a user's search request, the search engine may provide brief information about the advertiser (eg, a specific advertisement item) that may provide information requested by the user. The brief information about the advertiser may also include link information for moving to a site operated by the advertiser. The search engine may provide the user with the information desired by the user through various search methods such as a search method by inputting a search word and a category search method by information topic. Meanwhile, the search engine may be configured separately from the advertisement service providing server 10 or may be integrated into one.

The UCR determination unit 110 according to the present embodiment calculates a user conversion rate (UCR) for each of one or more advertisement items associated with a predetermined search word. The probability of purchase conversion (UCR) according to the present embodiment may be generated for the line item clicked by the user as a probability that the user will make a purchase conversion in a specific site. For example, the total number of advertisement items clicked by the user among the extracted advertisement items for the search word may be calculated and calculated using the inverse of the value.

search word Click order One 2 3 Line item1 click Line item 2 click Line item 3 Line item 4 click Line item 5

Table 1 shows whether the user clicks on the item 1 to item 5 extracted for the search word. For example, in this case, the probability of purchase conversion (UCR) for the clicked line items according to the present embodiment is 1 /, which is the inverse of 3, that is, the total number of line items clicked by the user among the line items extracted for the search term. Can be three.

And the penalty determination unit 120 according to the present embodiment determines the penalty value reflecting the case where the time spent in the corresponding site of each line item is short. In this case, the residence time may be defined as a time from opening a page of a specific Internet site to closing a page of the page, or may be defined as a time from opening a page of a specific Internet site to opening a page of another Internet site. In the latter case, it is desirable to collect and use a sample of visitors who stay for a certain period of time since there is no subsequent open Internet page, so that the residence time can be infinitely long.

The index determination unit 130 according to the present exemplary embodiment may calculate the customer response index (Ur) in consideration of the purchase conversion probability (UCR) calculated by the UCR determination unit 110 and / or the penalty value calculated by the penalty determination unit 120. CRI). In addition, the ranking determiner 140 according to the present embodiment compares the customer response index (CRI) determined for each line item, and determines the exposure rank of the line items.

The result display unit 150 according to the present exemplary embodiment provides each advertisement item to a user who has requested a search for a search word through the Internet based on the exposure ranking determined by the ranking determiner 140.

The database 160 according to the present embodiment may store an advertisement item associated with a predetermined search word, price information on the advertisement item, and various variables used to derive the customer response index according to the present embodiment.

3 is an exemplary flowchart of a method for determining a customer response index (CRI) according to an embodiment of the present invention.

According to the present embodiment, in determining the customer response index (CRI), the above-described purchase conversion probability (UCR) is calculated and taken into consideration, as well as the total number of line items (listing number) provided to the query related line item (listing number) and the customer. Various methods may be applied to determine the Customer Response Index (CRI), taking into account various factors such as ratings and / or length of stay on the Internet site.

First, in operation S300, a purchase conversion probability (UCR) is calculated for each of one or more advertisement items associated with a predetermined search word. As described above, the probability of purchase conversion (UCR) is a probability that a user converts a purchase on a specific site, and calculates the total number of line items clicked by the user among the line items extracted for the search term. It can be calculated as the inverse of the value.

In addition to the purchase conversion probability (UCR), the average purchase conversion probability (AVG_UCR) may be calculated for the users who visited the corresponding site in step S310. The purchase conversion probability (UCR) may be calculated by further considering the total number of line items provided to the user for the predetermined search word for each user. For example, a case in which User 1 and User 2 visits an Internet page corresponding to a specific line item will be described.

User 1:
search word Click order One 2 3 Line item1 click Line item 2 Line item 3 click Line item 4 click Line item 5

User 2:
search word Click order One 2 3 Line item1 click Line item 2 Line item 3 click

Table 2 shows whether User 1 clicks on line items 1 to 5 extracted for a query, and Table 3 shows User 2 clicks on line items 1 to 3 extracted for a query. have. For example, in this case, the average purchase conversion probability AVG_UCR for the clicked line items according to the present embodiment is as follows. Line item 1 and line item 3 are about 0.417 (= (1/3 + 1/2) / 2), and line item 4 is 0.333 (= 1/3).

In this case, the total conversion number (listing number) provided to the user for the predetermined search word may be further applied to the purchase conversion probability (UCR). The greater the total number of line items, the lower the likelihood that a particular item is selected. Therefore, more weight is given to clicks generated when there are more line items. For example, in the above case, the total number of line items provided to user 1 is 5 and the total number of line items provided to user 2 is 3. In this case, the average purchase conversion probability AVG_UCR for the clicked line items according to the present embodiment is as follows. About 0.396 (= ((1/3) * 5 + (1/2) * 3) / (5 + 3)) for line item 1 and line item 3, and 0.333 (= 1/3 for line item 4) )

On the other hand, the customer rating determined for each user may be further applied to the purchase conversion probability (UCR).

For example, each customer can be graded using the customer's query set, past purchase history, and sales contribution, and reflected in the UCR decision. For example, assume that the customer rating given to user 1 is 0.9 and the customer rating given to user 2 is 0.7. In this case, the average purchase conversion probability AVG_UCR for the clicked line items according to the present embodiment is as follows. About 0.406 (= ((1/3) * 0.9 + (1/2) * 0.7) / (1 * 0.9 + 1 * 0.7)) for line item 1 and line item 3, and 0.3 (for line item 4 = (1/3) * 0.9).

Of course, it may be calculated in consideration of the total number of line items provided to the user for the predetermined search word for each user and the customer grade determined for each user. In this case, the average purchase conversion probability AVG_UCR for the clicked line items according to the present embodiment is as follows. Line item 1 and line item 3 are approximately 0.386 (= ((1/3) * 5 * 0.9 + (1/2) * 3 * 0.7) / (5 * 0.9 + 3 * 0.7)), and line item 4 In this case, 0.3 (= 1/3 * 0.9).

In operation S320, the normalized purchase conversion probability STD_UCR may be calculated using the purchase conversion probability UCR and the average purchase conversion probability AVG_UCR. This is to compare the high and low effects according to the relative purchase conversion probability (UCR) value of each advertisement list for the search term.

On the other hand, in deciding on purchase conversion probability (UCR), average conversion probability (AVG_UCR), and normalized purchase conversion probability (STD_UCR), we added the temporal notion to view recent clicks at a higher rate than past clicks. In some embodiments, the CRI may be determined according to an embodiment.

For example, the weight of time may be reflected in the UCR using a function such as Equation 1 below.

σ: sample period

τ: reporting period

UCR: user conversion rate

In operation S330, the penalty value reflecting the case where the time spent in the corresponding site of each line item is short is determined.

Here, the penalty value may be determined by referring to the ratio of users within a minimum residence time to users staying within a certain residence time on the corresponding site for each line item. For example, by calculating an error rate (P_short), which is the ratio of users within a minimum residence time to users staying within a certain time spent on the site, and calculates an average error rate (P_avg_short) for line items for the search term. The ratio may be determined by referring to the ratio of the false visit rate P_short to the average false visit rate P_avg_short. In other words, if the ratio of the false visit rate (P_short) to the average visit rate (P_avg_short) is large, it means that the short time visit rate is large among all visits, so that the search quality is low and the penalty value is determined according to the high and low values. Can be.

Alternatively, the penalty value may be determined by referring to an average residence time (mean_sitedt) for users who stay within a certain residence time on the corresponding site for each line item. For example, the average residence time (mean_sitedt) of each site for a specific keyword search term is calculated, and the average residence time (avg_mean_sitedt) of all the sites for the search term is calculated, and all sites for the search term are calculated. It may also be determined by referring to the ratio of the average residence time (mean_sitedt) for each site to the average value (avg_mean_sitedt) of the average residence time. That is, if the ratio of the average stay time (mean_sitedt) for each site to the average value of the average stay time (avg_mean_sitedt) for all sites for the search term is large, it means that the visit time of the corresponding Internet site for the search term is relatively long. Therefore, the search quality can be regarded as relatively high and the penalty value can be determined according to the height of the value. On the contrary, if the ratio is small, the visit time of the corresponding site is relatively short, and thus the search quality is relatively low.

In addition to the two exemplary methods of determining the penalty value described above, it would be obvious that both may apply if the visitor reflects a short time spent on the corresponding Internet page of the line item.

In step S340, the final customer response index (CRI) is determined in consideration of the above-described purchase conversion probability (UCR) or penalty value related to the residence time. Of course, the final customer response index (CRI) can also be determined by considering both the probability of purchase conversion (UCR) and the penalty value associated with residence time. When considering the purchase conversion probability (UCR) and the penalty value together, it may be determined by weighting each. For example, different weights of probabilities of purchase conversion (UCR) and penalty values may be applied to give a different amount of contribution to the determination of customer response (CRI).

The customer response index (CRI) determined according to the present embodiment is reflected in determining the exposure ranking on the Internet when providing line items for a predetermined search word, so that the customer response index (CRI) can directly or indirectly reflect the actual customer response to the search result. In addition, this is expected to increase the reliability of the search for the customer, while being given an objective criterion for the ranking of the advertisement exposure, it is expected to have an effect that can prevent the unnecessary competition of the advertiser and the damage of the price increase.

In addition, the above-described purchase conversion probability (UCR), penalty value, customer response index (CRI), etc. may be applied to determine the exposure position when the Internet advertisement is applied according to the above-described embodiments, as well as the time at which the advertisement is exposed, the advertiser May be used to determine various factors related to Internet advertising, such as determining the advertising bills that will be paid.

The above-described advertising service providing method may be implemented in the form of program instructions that can be executed by various computer means and recorded in a computer-readable recording medium. In this case, the computer-readable recording medium may include program instructions, data files, data structures, and the like, alone or in combination. On the other hand, the program instructions recorded on the recording medium may be those specially designed and configured for the present invention or may be available to those skilled in the art of computer software.

Computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs, DVDs, and magnetic disks such as floppy disks. Magnetic-Optical Media, and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. The recording medium may be a transmission medium such as an optical or metal wire, a waveguide, or the like including a carrier wave for transmitting a signal specifying a program command, a data structure, or the like.

In addition, program instructions include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

On the other hand, those skilled in the art will understand that the present invention described above can be implemented in other specific forms without changing the technical spirit or essential features.

Therefore, it is to be understood that the embodiments described above are exemplary in all respects and not restrictive. The scope of the present invention is shown by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention. do.

1 is an exemplary flowchart of a method of providing an advertisement service according to an embodiment of the present invention.

2 is an exemplary structural diagram of an advertisement service providing server according to an embodiment of the present invention.

3 is an exemplary flow diagram of a method for determining a customer response index (CRI) in accordance with an embodiment of the present invention.

<Description of the code for the main configuration of the drawings>

10: advertisement service providing server 100: input unit

105: line item extraction unit 110: UCR determination unit

120: penalty determination unit 130: index determination unit

140: ranking unit 150: result display unit

160: database

Claims (18)

Receiving a predetermined search word from a user through the Internet; Extracting line items associated with the search term; Acquiring a Customer Reaction Index (CRI) determined for each line item in consideration of a user conversion rate (UCR), which is a probability of making a purchase on an Internet site corresponding to each line item; Comparing a customer response index (CRI) for the extracted line items; Determining an exposure rank of line items according to the comparison result; And Providing each of the line items to the user through the Internet based on the exposure ranking, The customer response index (CRI) The method of claim 1, wherein the penalty value reflecting the case where the time spent on the corresponding site of each line item is less than the predetermined time is further considered. The method of claim 1, The purchase conversion probability (UCR) is generated for the line item clicked by the user among the line items for the search word, characterized in that calculated using the inverse of the number of clicked line items. 3. The method of claim 2, An average purchase conversion probability (AVG_UCR) for each line item is calculated using the average value of the purchase conversion probability values calculated for a plurality of users who visit the corresponding site for each line item for the search term, and the purchase conversion probability Calculate the normalized purchase conversion probability (STD_UCR) by using (UCR) and the average purchase conversion probability (AVG_UCR), and determine that the customer response index (CRI) is determined in consideration of the normalized purchase conversion probability (STD_UCR). Characterized in that, advertising service providing method. 3. The method of claim 2, The purchase conversion probability (UCR) is calculated by further considering the total number of line items provided to the user for the predetermined search word for each user, advertising service providing method. The method according to claim 3 or 4, The purchase conversion probability (UCR) is calculated by further considering the customer rating determined for each user, advertising service providing method. The method of claim 5, The method of claim 1, wherein the user's recent click in the purchase conversion probability (UCR) is reflected at a greater rate than the user's click in the past. delete The method of claim 1, The penalty value is determined by referring to the ratio of users within a minimum residence time for users staying within a certain residence time on a corresponding site for each line item. The method of claim 1, The penalty value is determined by referring to an average residence time (mean_sitedt) for users who stay within a certain time of stay on a corresponding site for each line item. An input unit for receiving a predetermined search word from a user through the Internet; A line item extracting unit extracting one or more line items associated with the search word; A UCR determination unit for calculating a user conversion rate (UCR), which is a probability of making a purchase in an internet site corresponding to each line item; A penalty determination unit that determines a penalty value reflecting a case where the time spent on each site of each line item is less than a predetermined time; An index determination unit for determining a customer response index (CRI) in consideration of the purchase conversion probability (UCR) and the penalty value; A ranking unit configured to determine the exposure ranking of the line items by comparing the customer response index (CRI) determined for each line item; And And a result display unit for providing each of the line items to the user through the Internet based on the exposure ranking. The method of claim 10, The purchase conversion probability (UCR) is generated for the line item clicked by the user among the line items for the search term, and is calculated using the inverse of the number of clicked line items, ad service providing server device . The method of claim 11, An average purchase conversion probability (AVG_UCR) for each line item is calculated using the average value of the purchase conversion probability values calculated for a plurality of users who visit the corresponding site for each line item for the search term, and the purchase conversion probability Calculate the normalized purchase conversion probability (STD_UCR) by using (UCR) and the average purchase conversion probability (AVG_UCR), and determine that the customer response index (CRI) is determined in consideration of the normalized purchase conversion probability (STD_UCR). Characterized in that the advertisement service providing server device. The method of claim 11, The purchase conversion probability (UCR) is calculated by further considering the total number of line items provided to the user for the predetermined search word for each user, advertising service providing server device. The method according to claim 12 or 13, The purchase conversion probability (UCR) is calculated in consideration of the customer rating determined for each user, characterized in that the advertisement service providing server device. The method of claim 14, Advertisement service providing server device, characterized in that the recent click on the user's click is determined in the purchase conversion probability (UCR) is greater than the user's click occurred in the past. delete The method of claim 10, The penalty value is determined by referring to the ratio of the users within the minimum residence time for users staying within the site for a predetermined time period for each line item, advertising service providing server device. The method of claim 10, The penalty value is determined by referring to the average residence time (mean_sitedt) for users staying within a certain residence time on the corresponding site for each line item.

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