KR101460129B1 - Method and apparatus for surveying efficiency of keyword advertisement - Google Patents

Abstract

A method and apparatus for measuring keyword advertising effectiveness are provided. A method for measuring the efficiency of a keyword advertisement includes the steps of (a) extracting a number of queries and CTR (click through rate) data for a specific period for a plurality of keywords, (b) Classifying the scores into a plurality of grades; and (c) summing the grades corresponding to the grades classified at the specified ratios to provide an index representing the keyword efficiency.

Description

[0001] METHOD AND APPARATUS FOR SURVEYING EFFICIENCY OF KEYWORD ADVERTISEMENT [0002]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and apparatus for measuring the efficiency of advertising, and more particularly, to a method and apparatus for measuring the efficiency of a keyword advertisement.

In keyword search advertising, a commonly used measure of advertising effectiveness is to measure the click-to-exposure effect of a keyword using an index called CTR (Click Through Rate).

However, when the keyword efficiency is measured based on the CTR alone, the keyword efficiency can not be an absolute reference of the index because the CTR varies depending on the number of impressions.

For example, if you have a low number of impressions but a high number of clicks (1 impressions per month, CTR = 100% for 1 click) and a high number of impressions but low clicks (10,000 impressions over a month and 100 clicks And CTR = 1%), there is a large difference in the number of clicks, but a large difference in CTR occurs depending on the number of impressions.

As such, CTR is commonly used as an index of the efficiency of a general keyword advertisement. However, since the CTR varies greatly depending on the number of impressions as in the above example, There is a problem that it is difficult to confirm the efficiency of one keyword.

Therefore, there is a need for a new method that can be used as a reference of keyword efficiency index in measuring the efficiency of keyword advertisement.

SUMMARY OF THE INVENTION The present invention provides a method and apparatus for calculating a keyword efficiency index by assigning keyword scores based on the number of search queries and the CTR.

According to an aspect of the present invention, there is provided a method for measuring the efficiency of a keyword advertisement, the method comprising: (a) determining a number of queries and a click through rate (CTR) (B) classifying the extracted number of queries and CTR into a plurality of classes, and (c) adding scores corresponding to the classified classes to an index indicative of keyword efficiency .

In one aspect of the present invention, the step (b) includes classifying the number of queries into the plurality of classes, when the number of queries is '0', assigning a lowest class among the plurality of classes to the number of queries, In classifying the CTR into the plurality of classes, when the CTR is 0%, the lowest class among the plurality of classes for the CTR is given.

According to an aspect of the present invention, the step (b) may further include: calculating an interval ratio for dividing the number of queries by each grade when classifying the number of queries into n classes, The number of queries is divided into 2 to n sections, and then classified according to each section, and the section ratio is calculated excluding the lowest rank among the n classes.

According to an embodiment of the present invention, in the step (b), the highest number of queries among the queries of the keywords belonging to the respective classes is selected as the reference-last line of the corresponding class.

According to an aspect of the present invention, in the step (b), when the CTR is classified into n classes, a section ratio for dividing the CTR by each grade is calculated, and the calculated section ratio is divided into a total cumulative keyword number To divide the data into 2 ~ n sections, and assign a grade to each section, and the section ratio is calculated excluding the lowest class among the n classes.

In addition, in one aspect of the present invention, the step (b) selects the highest CTR among the CTRs belonging to each of the above-mentioned classes as a criterion of the corresponding class - the last line of the class.

The step (c) includes the steps of: (c-1) assigning a score within a specific range corresponding to each of the classes to the number of the queries and the CTR; (c-2) Calculating a total score by summing the scores assigned to the respective grades at the specific ratios and taking the maximum score of the scores within the specified range as a scale; and (c-3) calculating the total score And converting the score to a score corresponding to the score.

In order to achieve the above object, in an embodiment of the present invention, an apparatus for measuring efficiency of a keyword advertisement extracts a number of queries and CTR (click through rate) data for a plurality of keywords for a specific period of time A classification unit for classifying the extracted number of queries and the CTR into a plurality of classes, and an advertisement efficiency index providing unit for providing a score corresponding to each of the classified grades as an index indicating keyword efficiency, .

In one aspect of the present invention, when classifying the number of queries into the plurality of classes, the classifying unit assigns a lowest class among a plurality of classes to the number of queries when the number of queries is '0' Is classified into the plurality of classes, when the CTR is 0%, the lowest class among the plurality of classes for the CTR is given.

According to an aspect of the present invention, when classifying the number of queries into n classes, the classifying unit may calculate an interval ratio for dividing the number of queries by each class, And dividing the result into 2 ~ n sections, and assigning grades to the respective sections, and the section ratio is calculated excluding the lowest class among the n classes.

In one aspect of the present invention, the classifying unit selects the highest number of queries among the number of queries of the keywords belonging to the respective classes as a reference-last line of the class.

In addition, in one aspect of the present invention, when classifying the CTR into n classes, the classifying unit calculates an interval ratio for dividing the CTR by each class, and the calculated interval ratio is applied to the total number of cumulative keywords And dividing the data into 2 ~ n sections and assigning grades to each section, and the section ratio is calculated excluding the lowest class among the n classes.

Further, in one aspect of the present invention, the classifying section selects the highest CTR among the CTRs belonging to the respective classes as the reference-last line of the corresponding class.

In one aspect of the present invention, the advertisement efficiency index providing unit assigns scores within a specific range corresponding to the respective grades to each rank of the number of queries and CTR, and assigns the score assigned to each rank to the specific ratio And calculates a total score of the maximum score among the scores within the specified range as a perfect score and converts the calculated total score into a score corresponding to the indicator.

According to an embodiment of the present invention, efficiency of a search word related to an industry or a brand operated by an advertiser or a keyword already purchased can be objectively recognized.

In addition, since it is possible to measure the objective efficiency of the keyword, it is possible to easily select the keyword with high relevance to the advertiser's interest field and high advertisement efficiency.

In addition, by registering a keyword having high efficiency in keyword advertisement, the advertisement effect can be increased.

It should be understood that the effects of the present invention are not limited to the above effects and include all effects that can be deduced from the detailed description of the present invention or the configuration of the invention described in the claims.

1 is a block diagram illustrating a configuration of an apparatus for measuring keyword advertisement efficiency according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating a process of measuring the keyword advertisement efficiency by the advertisement efficiency measuring apparatus 100 according to an embodiment of the present invention.
FIG. 3 is an index showing advertisement efficiency according to an embodiment of the present invention.
4 is a diagram illustrating a classification of the number of queries according to an exemplary embodiment of the present invention.
5 is a diagram illustrating CTR classification according to an embodiment of the present invention.
FIG. 6 is a diagram illustrating classification results of the number of queries and the CTR according to an embodiment of the present invention.
FIG. 7 is a diagram showing a result of a comprehensive score according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when a part is referred to as being "connected" to another part, it includes not only "directly connected" but also "indirectly connected" . Also, when an element is referred to as "comprising ", it means that it can include other elements, not excluding other elements unless specifically stated otherwise.

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

1 is a block diagram illustrating a configuration of an apparatus for measuring keyword advertisement efficiency according to an embodiment of the present invention.

(Hereinafter, referred to as an 'advertising efficiency measuring apparatus') 100 according to an embodiment of the present invention includes an extracting unit 110, a classifying unit 120, and an advertisement efficiency indicator providing unit 130 and a keyword receiving unit 140.

Describing each component, the extracting unit 110 may extract the number of queries and CTR data for a specific period (for example, one month) for all the keywords.

Meanwhile, the classifying unit 120 may classify the number of queries and the CTR into a plurality of n classes (for example, 10 classes) based on the number of queries extracted from the extracting unit 110 and the CTR data.

Hereinafter, the number of queries and the number of classes (n) for classifying the number of queries and CTRs are limited to the above embodiments It is not.

1. Number of queries Classification

When the total number of queries extracted from the extracting unit 110 is divided into n classes, the classifying unit 120 classifies the 'total number of queries into a plurality of classes' ), And the total number of queries can be divided into 2 to n intervals by applying the ratio of the calculated number of queries, and grades can be assigned to the respective intervals.

At this time, when the number of queries is '0', the classifying unit 120 may assign the lowest rank among n classes.

For example, when the total number of queries is divided into 10 classes, the classifying unit 120 regards the total number of cumulative queries as 100%, divides the total number of classes into 9 classes (grades 2 to 10) % / 9 = 11.11%), which can be multiplied by each of the nine ratings to divide the interval for each result.

For reference, when calculating the ratio of the number of queries, the reason why 10 classes are divided by 9 is because the number of queries is '0', which is the lowest grade.

That is, the interval to which the second class is assigned corresponds to 11.11% X 1 = 11.11% of the total cumulative number of queries, and the interval to which the third class is assigned corresponds to 11.11% X 2 = 22.22% to be.

In addition, the interval to which grade 4 is assigned corresponds to 11.11% X 3 = 33.33% of the total number of queries. . The interval to which the 10 grade is assigned can be a section corresponding to 11.11% X 9 = 99.99% (100%) of the total number of cumulative queries.

At this time, the highest number of queries among the queries of the keywords belonging to each class may be the reference (unknown route) of the corresponding class.

A detailed description thereof will be given later with reference to Fig.

2. CTR Classification

In addition, when the CTR extracted from the extracting unit 110 is divided into n classes, the classifying unit 120 may calculate the 'interval ratio for dividing the total CTR by each class' (hereinafter referred to as CTR interval ratio) , The total number of cumulative keywords is divided into 2 to n sections by applying the calculated CTR section ratio, and grades can be assigned to each section.

At this time, when the CTR is '0', the classifying unit 120 can assign the lowest rank among n classes.

For reference, the reason for using the 'cumulative keyword count' in classifying the CTR class is to distribute the number of keywords belonging to each CTR class evenly to obtain the dense CTR data.

For example, if a keyword with the highest CTR is ranked at 10, and the score is uniformly divided according to the CTR value, if a large number of keywords are concentrated in the CTR range of a specific numerical value, Because.

For example, in the case where the classification unit 120 divides the CTR class into 10 classes, the classification unit 120 regards the total number of cumulative keywords as 100%, divides the classification into 9 classes (grades 2 to 10) The ratio (100% / 9 = 11.11%) can be calculated, which can be multiplied by each of the nine ratings to divide the interval for each result.

For reference, the reason for dividing 10 grades by 9 in calculating CTR section ratio is that the CTR of '0%' is already the lowest grade.

In other words, as in the case of the query number classification, the section to which the second grade is assigned corresponds to 11.11% X 1 = 11.11% of the total cumulative keyword count. In the section where the third grade is given, 11.11% X 2 = 22.22%.

In addition, the section to which the 4th grade is assigned corresponds to 11.11% X 3 = 33.33% of the total cumulative keyword number, and ... . 10 grades are assigned to 11.11% X 9 = 99.99% of the total number of cumulative keywords.

At this time, the highest CTR among the CTRs of the keywords belonging to each class may be the reference (unknown route) of the corresponding class.

A detailed description thereof will be given later with reference to Fig.

On the other hand, the advertisement efficiency index providing unit 130 calculates the number of queries classified into 10 grades and the score corresponding to each grade of the CTR, for example, 1 for 1, 2 for 2, 3 for 3 .10 grades can be assigned a score corresponding to each grade like 10 points.

Here, the scope of the score given by the advertisement efficiency index provider 130 for each rank is not limited to the above embodiment, and scores within various ranges may be assigned to each rank.

In addition, the advertisement efficiency index provider 130 sums the number of queries and the score assigned to each rank of the CTR into a specific ratio (for example, 50%) as described above, 1 point to 10 points) of the maximum score (10 points) can be calculated.

At this time, when the scores given to each grade of the number of queries and the CTR are added to a specific ratio (for example, 50%), the decimal point can be rounded and reflected.

Here, the specific rate at which the advertisement efficiency index providing unit 130 adds the number of the queries and the scores given to the respective grades of the CTR is not limited to the embodiment (50%), but may be added at various ratios.

In addition, the advertisement efficiency index providing unit 130 calculates a total score, which is the maximum score (10 points) among the scores within a specific range (for example, 1 point to 10 points) For example, 1 to 5 points).

When the specific keyword is received from the keyword receiving unit 140 to be described later, the advertisement efficiency index providing unit 130 may search for an index indicating the advertisement efficiency of the keyword and provide the index to a user terminal (not shown).

Meanwhile, the keyword receiving unit 140 may receive a keyword as an efficiency measurement target from a user terminal (not shown), and may transmit the received keyword to the advertisement efficiency indicator providing unit 130.

FIG. 2 is a flowchart illustrating a process of measuring the keyword advertisement efficiency by the advertisement efficiency measuring apparatus 100 according to an embodiment of the present invention.

First, the advertisement efficiency measuring apparatus 100 extracts the number of queries and the CTR data for a specific period (for example, one month) of all keywords (S201).

After S201, the advertisement efficiency measuring apparatus 100 classifies the number of queries and the CTR into a plurality of classes (e.g., 10 classes) (S202)

Here, the content of the advertisement efficiency measuring apparatus 100 for classifying the number of queries and the CTR into a plurality of grades has been described with reference to FIG. 1, and will be omitted.

After S202, the advertisement efficiency measuring apparatus 100 gives a score to each grade of the number of queries classified into a plurality of grades and the CTR in S202 (S203).

After S203, the advertisement efficiency measuring apparatus 100 adds the number of queries and the score given to each rating of the CTR to a specific ratio (for example, 50%). At this time, the decimal point can be rounded and reflected (S204).

After S204, the advertisement efficiency measuring apparatus 100 calculates a total score, which is the maximum score (10 points) out of the scores within a specific range (for example, 1 point to 10 points) For example, 1 to 5 points) (S205).

After S205, the advertisement efficiency measuring apparatus 100 searches the index indicating the advertisement efficiency for the keyword, and provides it to the user terminal (not shown) when receiving the keyword as the advertisement efficiency measurement target from the user terminal (not shown) ).

FIG. 3 is an index showing advertisement efficiency according to an embodiment of the present invention.

In FIG. 3, the total score is a sum of the number of queries and the score given to each grade of CTR as a specific ratio (50%), which is rounded by 50% of the number of queries and 50% Is a score obtained by converting the total score into an index indicating the efficiency of the advertisement.

Therefore, the present invention can provide an index as shown in FIG. 3, so that the efficiency of a search word related to an industry or a brand operated by an advertiser or a keyword already purchased can be objectively detected and the objective efficiency of the keyword can be measured, It is possible to easily select keywords having a high degree of relevance and high advertising efficiency.

4 is a diagram illustrating a classification of the number of queries according to an exemplary embodiment of the present invention.

FIG. 4 shows a result of simulating actual data according to the number-of-queries classification method of the present invention. In FIG. 4, a keyword (470, 025) having a query count of 1 ) Were classified into 10 classes based on the number of cumulative queries.

Here, 'cumulative number of queries' indicates that the number of search queries and the number of keywords exposed by the number of search queries are accumulated according to the number of search queries.

In addition, 'Cumulative number of queries' shows the ratio of each cumulative number of queries when the total number of cumulative queries is 100%. The ratio of the number of queries to the total number of queries (11.11% ), The cumulative number of queries is 11.11%, 22.22%, 33.33% ... , 88.88%, and 99.99 (100)% are classified into each grade.

As shown in FIG. 4, the number of accumulated queries for a specific period of the entire keyword (2,604,651) is 275,694,455, and data having a query number of '0' is not retrieved. .

As described above with reference to FIG. 1, when the number of queries is classified into 10 classes, the ratio of the number of queries is 100% / 9 = 11.11% 1 = 11.11%, and the third grade is the interval corresponding to 11.11% X 2 = 22.22% of the total number of cumulative queries.

At this time, the highest number of queries among the queries of the keywords belonging to each class can be the reference (last line) of the corresponding class.

Therefore, in the interval where the second rank is assigned, the interval in which the cumulative number of queries is 11.11% of the total number of queries 275,694,455, that is, the interval in which the cumulative number of queries is 30,575,315, The number of the reference queries of the second grade is 106 since the number can be a reference of the second rank (the last line).

That is, keywords exposed from 1 to 106 times during a specific period can be classified into 2 classes.

In the same way, in the interval in which the third grade is assigned, the interval in which the cumulative number of queries is 22.22% of the total number of queries 275,694,455, that is, the interval in which the cumulative number of queries is 61,211,715, Since the number of high queries can be the third rank (last line), the number of the third query is 418.

That is, keywords exposed from 107 to 418 times during a specific period can be classified into 3 classes.

In this way, the number of queries can be classified as shown in FIG.

5 is a diagram illustrating CTR classification according to an embodiment of the present invention.

FIG. 5 is a graph showing a result of simulating real data according to the CTR classification method of the present invention. As shown in FIG. 5, the number of keywords with a CTR of 0% (1,700,783) to a keyword with a CTR of 3.5 And classified into 10 grades.

Here, 'cumulative keyword number' indicates that the number of keywords having the CTR and the corresponding CTR is accumulated according to the CTR.

In addition, 'cumulative keyword number ratio' indicates the ratio of the number of cumulative keywords when the total number of cumulative keywords is taken as 100%, and it is calculated according to the CTR section ratio (11.11%), which is a section ratio for dividing the total CTR by each grade The cumulative number of keywords was 11.11%, 22.22% 33.33% ... , 88.88%, and 99.99 (100)% are classified into each grade.

As shown in FIG. 5, the number of cumulative keywords is 903,660 for a specific period of the entire keywords (2,604,443), and the data having a CTR of '0' is given the lowest rank among the 10 classes.

As described above with reference to FIG. 1, when the number of CTRs is classified into 10 classes, the CTR section ratio is 100% / 9 = 11.11%. Accordingly, 11.11% of underwater 11.1% of the total number of cumulative keywords, and X 3 = 11.11% of the total number of cumulative keywords is equivalent to 22.22%.

At this time, the highest CTR among the CTRs of the keywords belonging to each class can be the reference (last line) of the corresponding class.

Accordingly, the interval in which the second grade is assigned is a section in which the cumulative number of keywords counts is 11.11% of the total cumulative keyword counts of 903,660, that is, the cumulative keyword count is 93,842, and the highest CTR among the CTRs belonging to the second- Since this can be the criterion of the second class (the last line), the standard CTR of the second class becomes 0.008.

That is, keywords with a CTR of 0.001 to 0.008 over a certain period of time can be classified as two classes.

In the same way, in the interval in which the third grade is assigned, the interval in which the cumulative number of keywords in the total number of cumulative keywords is 903,660 is 22.22%, that is, the cumulative number of keywords is 193,864, and the third among the CTRs Since a high CTR may be a criterion of a third class (the last line), the reference CTR of the third class is 0.019.

That is, keywords with a CTR of 0.009 to 0.019 over a certain period of time can be classified as grade 3.

In this way, the CTR class can be classified as shown in FIG.

FIG. 6 is a diagram illustrating classification results of the number of queries and the CTR according to an embodiment of the present invention.

As shown in FIG. 6, the number of queries and the CTR are classified into 10 classes, and the number of queries per each class, the range of CTR, and the number and ratio of keywords in the range can be grasped.

For reference, 1 to 10 points may be assigned to each grade.

For example, 1 point for grade 1, 2 points for grade 2 ... .9 grade can be awarded 9 points, and grade 10 can be awarded 10 points respectively.

FIG. 7 is a diagram showing a result of a comprehensive score according to an embodiment of the present invention.

Based on the results shown in FIG. 4 to FIG. 6, the number of queries was 50% and the CTR score was 50%.

For the sake of summarizing 50% of the query number and 50% of the CTR score, rounding is applied when calculating the number of queries or the CTR score is a real number.

It will be understood by those skilled in the art that the foregoing description of the present invention is for illustrative purposes only and that those of ordinary skill in the art can readily understand that various changes and modifications may be made without departing from the spirit or essential characteristics of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the present invention is defined by the appended claims, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included within the scope of the present invention.

100: Ad efficiency measuring device
110:
120:
130: Advertisement efficiency index provisioning
140:

Claims (14)

A method for measuring the efficiency of a keyword advertisement,
(a) extracting a number of queries and click through rate (CTR) data for a plurality of keywords over a specific period;
(b) classifying the extracted number of queries and CTR into a plurality of classes; And
(c) summing scores corresponding to the classified grades at a specific ratio and providing the scores as an index representing keyword efficiency;
Lt; / RTI >
In the step (b), when classifying the number of queries into the plurality of classes, when the number of queries is '0', the lowest class among the plurality of classes for the number of queries is assigned,
And classifying the CTR into the plurality of classes, if the CTR is 0%, assigning the lowest class among the plurality of classes to the CTR.
delete The method according to claim 1,
Wherein the step (b) comprises the steps of: calculating an interval ratio for dividing the number of queries by each grade when classifying the number of queries into n classes; applying the calculated interval ratio to the total number of cumulative queries to obtain 2 to n Wherein the segment rate is calculated by excluding the lowest rank among the n classes of segments.
The method of claim 3,
Wherein the step (b) selects the highest number of queries among the queries belonging to the respective classes as the reference-final route of the corresponding class.
The method according to claim 1,
In the step (b), when the CTR is classified into n classes, an interval ratio for dividing the CTR by each class is calculated, and the calculated interval ratio is applied to the total number of cumulative keywords to form 2 to n intervals Wherein the ratio is calculated by excluding the lowest rank among the n classes.
6. The method of claim 5,
Wherein the step (b) selects the CTR having the highest CTR among the CTRs belonging to the respective grades as the reference - the last line of the corresponding grade.
The method according to claim 1,
The step (c)
(c-1) assigning a score within a specific range corresponding to each class for each class of the number of queries and the CTR;
(c-2) calculating a total score by summing the scores assigned to the respective grades at the specific ratios, and calculating a maximum score among the scores within the specified range; And
(c-3) converting the calculated total score into a score corresponding to the indicator;
Wherein the keyword advertising effectiveness measure comprises:
An apparatus for measuring the efficiency of a keyword advertisement,
An extracting unit for extracting a number of queries and click through rate (CTR) data for a plurality of keywords over a specific period;
A classifying unit for classifying the extracted number of queries and CTR into a plurality of classes;
An advertisement efficiency index providing unit for summing the scores corresponding to the classified grades at a specific ratio and providing the sum as an index indicating keyword efficiency;
Lt; / RTI >
Wherein the classification unit classifies the number of queries into the plurality of classes by assigning a lowest class among a plurality of classes to the number of queries when the number of queries is'
And assigns the lowest rank among the plurality of classes to the CTR when the CTR is 0% in classifying the CTR into the plurality of classes.
delete 9. The method of claim 8,
The classifying unit may calculate an interval ratio for dividing the number of queries by each class when the number of queries is classified into n classes, and apply the calculated interval ratio to the total number of cumulative queries to form 2 to n intervals Wherein the ratio is calculated for each of the n sections except for the lowest rank among the n classes.
11. The method of claim 10,
Wherein the classification unit selects the highest number of queries among the queries of the keywords belonging to the respective classes as the reference-final route of the corresponding class.
9. The method of claim 8,
When the CTR is classified into n classes, the classification unit calculates an interval ratio for dividing the CTR by each class, divides the calculated interval ratio into 2 to n intervals by applying the calculated interval ratio to the total number of cumulative keywords Wherein the rating is calculated for each section, and the section ratio is calculated excluding the lowest rank among the n classes.
13. The method of claim 12,
Wherein the classifying unit selects the highest CTR among the CTRs belonging to the respective classes as a reference - a last line of the corresponding class.
9. The method of claim 8,
Wherein the advertisement efficiency index providing unit assigns a score within a specific range corresponding to each of the classes to the number of the queries and the CTR,
Calculating a total score by summing the scores assigned to the respective grades at the specified ratio and taking the maximum score among the scores within the specified range as a scale,
And the calculated total score is converted into a score corresponding to the indicator.

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