JP6347532B1 - Evaluation apparatus, evaluation method, and evaluation program - Google Patents

Abstract

An evaluation apparatus, an evaluation method, and an evaluation program for evaluating a website based on the number and ratio of high-quality, high-engagement users who browse the website are provided. An apparatus 1 that evaluates a website based on the number or percentage of high-engagement users includes a communication unit 2, a storage unit 3, and a control unit 4, and includes websites 11, 12,. Connected. The storage unit 3 includes an access status DB 31, a high engagement user DB 32 that stores high engagement users of each website, and a website evaluation DB 33 that stores evaluation values of each website. The control unit 4 includes an access status acquisition unit 41, a reading rate calculation unit 42 when browsing a website, a browsing time calculation unit 43, a reading rate correction unit 44, and a user extraction unit 45 that extracts high engagement users. And an evaluation unit 46 for calculating a deviation value of each Web site. [Selection] Figure 1

Description

  The present disclosure relates to an evaluation apparatus, an evaluation method, and an evaluation program for evaluating a website based on the number and ratio of high-quality users browsing the website.

  In order to optimize the website, an analysis of access to the website is known (for example, refer to Patent Document 1). The access analysis is based on data such as the number of visitors to each website included in the website and the presence / absence of a specific action by each website visitor. A method of improvement.

  For example, according to the access analysis method described in Patent Literature 1, transmission / reception data between a client terminal and a Web server is monitored, and based on the monitoring result, at least information on the client terminal, access status, and request destination information are included. Record the transmission / reception status information in the storage means, and when an analysis request is issued from the client terminal of the analysis request source, obtain the information stored in the storage means, analyze the access of the client terminal to the Web server, An access analysis method for outputting an analysis result to a client terminal that is an analysis request source via a Web server is disclosed.

JP 2000-31124 A

  However, the degree of interest of a user accessing a website varies, and a website that many users access but does not attract strong interest, or a web that attracts strong interest in a certain user group. There are sites. Depending on the degree of interest in the website, the attention to the banner advertisement displayed on the website may be different. There has been a demand for a method that can digitize the degree of interest of a user accessing a website and objectively compare it with other websites.

  Therefore, in the present disclosure, an evaluation apparatus, an evaluation method, and an evaluation program for evaluating a website will be described based on the number and ratio of high-quality users (high engagement users) who browse the website.

  An evaluation apparatus according to an aspect of the present disclosure includes an access status acquisition unit that acquires a user's access status to a Web site, a read rate calculation unit that calculates a read rate for each access to the user's Web site, and a predetermined period A user extraction unit that extracts high-engagement users whose reading rate sum is equal to or greater than a threshold; and an evaluation unit that calculates an evaluation value of a website based on the number and / or percentage of high-engagement users.

  An evaluation method according to an aspect of the present disclosure includes an access status acquisition step in which an access status acquisition unit acquires a user's access status to a website, and a read rate calculation unit that determines the read rate for each access to the user's Web site. A user-extracting step for calculating a high-engagement user, and a user-extracting step for extracting a high-engagement user whose sum of read-out rates in a predetermined period is equal to or greater than a threshold by a user extracting unit; And an evaluation step for calculating an evaluation value of the website.

  An evaluation program according to an aspect of the present disclosure includes an access status acquisition step for acquiring a user's access status to the website, a read rate calculation step for calculating a read rate for each access to the user's website, and a predetermined A user extraction step for extracting high-engagement users whose sum of reading rates in a period is equal to or greater than a threshold value and an evaluation step for calculating an evaluation value of a website based on the number and / or ratio of high-engagement users are executed on an electronic computer. Let

  According to the present disclosure, since a website is evaluated based on the number and ratio of high-engagement users, the degree of interest of users accessing the website can be quantified, and each website can be objectively viewed. Can be compared.

It is a block diagram showing an evaluation device concerning one embodiment of this indication. It is a figure which shows the example of the access condition for every Web site stored in access condition DB31 of FIG. It is a figure which shows the example of the high engagement user for every Web site stored in high engagement user DB32 of FIG. It is a figure which shows the example of the evaluation value for every Web site stored in Web site evaluation DB33 of FIG. It is a schematic diagram which shows the example of a display of the website for demonstrating the reading rate of FIG. It is a graph which shows the example of the relationship between the average value of the browsing time of FIG. 2, and the sum total of a reading completion rate. It is a schematic diagram which shows the example of the calculation means of the reading rate correction value of FIG. It is a flowchart which shows the evaluation method by the evaluation apparatus 1 of FIG.

  An embodiment of the present disclosure will be described with reference to the drawings. Note that the embodiments described below do not unduly limit the content of the present disclosure described in the claims. In addition, all the components shown in the embodiments are not necessarily essential components of the present disclosure.

  Hereinafter, as an example, an evaluation apparatus, an evaluation method, and an evaluation program for evaluating a website based on the number and ratio of high-quality users (high engagement users) who browse the website will be described. Here, a high-quality user is a user who has a high degree of interest in the website to be browsed, and when such a user browses the website, an attitude change (behavior change) can be expected. As a high-engagement user, the website is evaluated based on the number and ratio.

<Configuration>
FIG. 1 is a block diagram illustrating an evaluation apparatus 1 according to an embodiment of the present disclosure. The evaluation device 1 is a device that evaluates a website based on, for example, the number or percentage of high-engagement users, and is connected to the websites 11, 12,... Via the network NW. The network NW is configured by the Internet, a WAN (Wide Area Network), or the like. The evaluation device 1 includes a communication unit 2, a storage unit 3, and a control unit 4.

  The communication unit 2 is a communication interface for communicating with the websites 11, 12,..., And performs communication according to a communication protocol such as TCP / IP (Transmission Control Protocol / Internet Protocol).

  The storage unit 3 stores programs for executing various control processes and functions in the control unit 4, input data, and the like, and includes a RAM (Random Access Memory), a ROM (Read Only Memory), and the like. The

  In addition, the storage unit 3 stores an access status DB 31 that stores an access status from a user for each of the websites 11, 12,... And a high engagement that stores a high engagement user for each of the websites 11, 12,. A user DB 32 and a website evaluation DB 33 that stores evaluation values for each website are provided. The access status DB 31, the high engagement user DB 32, and the website evaluation DB 33 are databases that can be referred to and updated by being accessed from a program for executing each function in the control unit 4.

  FIG. 2 is a diagram showing an example of the access status for each Web site stored in the access status DB 31 of FIG. For the access status for each Web site, information on the Web site, access user, access start time, access end time, browsing time, read rate, read rate correction value corresponding to the column name of the access status DB 31 shown in FIG. Is included. This access status is acquired by an access status acquisition unit 41, which will be described later. For example, data obtained by acquiring all information of a user who accessed the website, a specific segment (user attributes such as gender and age, category, This is user data extracted by hobbies, etc.).

  The website is information for identifying the website, and is, for example, a URL (Uniform Resource Locator) of the website. The access user is information for identifying a user who has accessed the website, and is, for example, an ID unique to the user's terminal. The access start time and access end time are the start time and end time when the user accesses the Web site.

  The browsing time is a time calculated by the browsing time calculation unit 43 described later based on the access start time and the access end time. The read rate is a value calculated by the read rate calculating unit 42 to be described later and indicating how much the content described on the Web site has been browsed. For example, the read rate is indicated by a ratio of the Web site being scrolled and displayed. It is. The reading rate correction value is a value obtained by correcting the reading rate by a reading rate correction unit 44 described later.

  For example, an access user “U 1, U 2, U 3,...” Is accessing a website specified as “www.aaa.co.jp”. For example, since the access start time is “10:22:33” and the access end time is “10:33:44”, the user U1 calculates the viewing time as “00:11:11”. Is done. Further, the read rate is 22.5%, and this read rate is corrected, and the read rate correction value is 23.2%.

  FIG. 3 is a diagram illustrating an example of a high engagement user for each Web site stored in the high engagement user DB 32 of FIG. The high-engagement user for each website includes information on the website, the access user, the access start time, the access end time, the browsing time, the reading rate, and the reading rate correction value, as in the access status DB 31 shown in FIG. . This high-engagement user is extracted from the user stored in the access status DB 31 by a user extraction unit 45 described later under predetermined conditions, and stores the same information as the access status DB 31.

  For example, when the website is identified as “www.aaa.co.jp”, among the users “U1, U2, U3,...” Stored in the access status DB 31 illustrated in FIG. “U2, U3,...” Are extracted as high engagement users. For example, since the access start time is “12:33:44” and the access end time is “12:50:20”, the user U2 calculates the viewing time as “00:16:36”. Is done. The read rate is 60.7%, and this read rate is corrected, and the read rate correction value is 61.9%.

  FIG. 4 is a diagram illustrating an example of evaluation values for each Web site stored in the Web site evaluation DB 33 of FIG. The evaluation value for each Web site includes information on the Web site, the number of high engagement users, the high engagement user ratio, the user number deviation value, and the user ratio deviation value corresponding to the column names in the Web site evaluation DB 33 shown in FIG. included. This evaluation value is calculated by the evaluation unit 46 described later.

  The Web site is information for identifying the Web site, like the access status DB 31 of FIG. The number of high engagement users is the number of high engagement users extracted by the user extraction unit 45. The high engagement user ratio is the ratio of the number of high engagement users extracted by the user extraction unit 45 to the total number of users who have accessed the website. The number-of-users deviation value is a value calculated by the evaluation unit 46 as the deviation value based on the number of high-engagement users for each website. The user ratio deviation value is a value calculated by the evaluation unit 46 as a deviation value for the high engagement user ratio for each website.

  The control unit 4 shown in FIG. 1 controls the overall operation of the evaluation apparatus 1 by executing a program stored in the storage unit 3, and is composed of a CPU (Central Processing Unit) and the like. As functions of the control unit 4, an access status acquisition unit 41, a read rate calculation unit 42, a browsing time calculation unit 43, a read rate correction unit 44, a user extraction unit 45, and an evaluation unit 46 are provided. The access status acquisition unit 41 to the evaluation unit 46 are activated and executed by a program stored in the storage unit 3.

  The access status acquisition unit 41 acquires the access status when the user accesses the Web site 11, 12,. Specifically, a predetermined tag is incorporated into the HTML of the websites 11, 12,... And the access status is acquired when the website is accessed. For example, when a program described in a tag embedded in HTML is resident in a Web server or other monitoring server, and the Web site is accessed, the program is started and an access log is recorded. Is set to The access user, the access start time, and the access end time are acquired from the file storing the access status to the Web sites 11, 12,... Recorded by this program, and stored in the access status DB 31.

  In addition to the items stored in the access status DB 31, the access status acquisition unit 41 directly accesses the Web sites 11, 12,... .., The number of times the user has referred to the Web sites 11, 12,... The access status acquisition unit 41 may acquire access data of all users who have accessed the websites 11, 12,... Or may acquire access data of users extracted in a specific segment. is there.

  The read rate calculation unit 42 calculates the read rate for each access when the user accesses the Web site 11, 12,. Specifically, a predetermined tag is incorporated into HTML of the websites 11, 12,... And when the website is accessed, the reading rate when the website is opened is recorded. For example, when a program described in a tag embedded in HTML is resident on a Web server or other monitoring server, and the Web site is accessed, the program starts and opens the Web site It is set to record the reading rate when. The read rate is calculated from the file storing the read rate of the Web sites 11, 12,... For each user calculated by this program, and stored in the read rate of the access status DB 31.

  Here, the reading rate of the Web sites 11, 12,. FIG. 5 is a schematic diagram showing a display example of a Web site for explaining the reading completion rate of FIG. This Web site is content displayed on the display screen P of an information processing apparatus such as a personal computer (PC) or a smartphone. Since the display content of this Web site is larger than the display screen P, the scroll bar T is displayed on the right side of the display screen P, and the content of the content displayed on the display screen P is moved up and down by sliding the scroll bar T up and down. To move to.

  For example, when this Web site is opened, the range that is initially displayed on the display screen P is about one third of the entire content. Therefore, as shown in FIG. 5 (a), the range displayed on the display screen P in the entire contents of this Web site is about one third upward, and is about 33%. Thus, the ratio of the range displayed on the display screen P in the entire content is set as the read rate of this Web site. In FIG. 5A, the read completion rate of the Web site is 33%.

  When the scroll bar T is slid downward in this state, the lower part of the content is displayed on the display screen P. Then, the reading rate of the website increases. Furthermore, when the scroll bar T is slid downward to display the content to the bottom as shown in FIG. 5B, the entire content of this website is displayed on the display screen P. . Therefore, in FIG. 5B, the reading rate of the website is 100%.

  That is, the reading rate of the website refers to the scroll rate on the display screen P. This is because when the user is interested in the contents of the website, the user scrolls the screen and browses the entire contents. This ratio is used as the reading rate and is used as an index value for evaluating the website. However, the calculation of the reading rate is not limited to the above method, and the reading rate may be calculated by a method other than the scroll rate depending on the nature of the website.

  The browsing time calculation unit 43 calculates a browsing time that is an access time when the user accesses the Web site 11, 12,. Specifically, it is calculated by subtracting the access start time from the access end time acquired by the access status acquisition unit 41 and stored in the access status DB 31, and stored in the browsing time of the access status DB 31.

  The reading rate correction unit 44 corrects the reading rate calculated by the reading rate calculation unit 42 using the browsing time calculated by the browsing time calculation unit 43 and stores it in the reading rate correction value of the access situation DB 31.

  Here, correction of the reading rate by the reading rate correction unit 44 will be described. FIG. 6 is a graph showing an example of the relationship between the average value of the browsing time and the total reading rate in FIG. In this graph, the horizontal axis is the sum of the reading rates shown in FIG. 2, the vertical axis is the average value calculated from the sum of the browsing time shown in FIG. 2, and the regression line L is plotted on the graph. It is the regression line calculated from the sum total of reading completion rate for every and the average value of browsing time.

  In this graph, the average value of the browsing time when the total of the reading completion rate is 100% is about 94 seconds as indicated by the point P. This value is considered to vary depending on the content displayed on the website, but is also considered to affect the reading rate of the website. As described above, the read rate is the scroll rate on the display screen P and depends on the user's behavior. Further, since the amount of content per page and the configuration of the page are different depending on the website, the value of the reading rate is different for each website. Therefore, in order to obtain a more objective index value by normalizing the influence of the browsing time on the reading rate and aligning the value of the reading rate, correction is performed by the average value of the browsing time.

  FIG. 7 is a schematic diagram showing an example of the reading rate correction value calculation means of FIG. The table shown in FIG. 7A shows the number of users whose reading rate total is 90% to 110% and the total browsing time of each user on a website with a predetermined period (for example, the last 30 days). The browsing time average is calculated from the number of users and the total browsing time, and the reading rate total is divided every 1%. From this table, as shown in FIG. 7 (b), a browsing time average value is extracted for each movement 10, and the moving average value is calculated.

  For example, first, as shown in the first column of FIG. 7B, the average value of browsing time with a total reading rate of 90% to 99% is extracted, and the average value is calculated. Next, as shown in the second column of FIG. 7B, the average value of the browsing time with the reading rate total being 91% to 100% is extracted, and the average value is calculated. Next, as shown in the third column of FIG. 7B, the average value of the browsing time with a reading rate total of 92% to 101% is extracted, and the average value is calculated. In this way, the process is repeated until the reading completion rate sum is 101% to 110%. Then, the average values shown in the bottom column of each column in FIG. 7B are summed and divided by the number of columns to calculate the average value shown in FIG.

  Further, an average browsing time in which the total reading rate of the entire website to be evaluated shown in FIG. 7D is 100% and an average browsing time in which the total reading rate of the entire website is 100% (FIG. 7 ( In order to calculate the difference in the ratio from (calculated in c)), division is performed as shown in FIG. Thereafter, weighting is performed by multiplying a predetermined value (for example, 0.7) that is considered to be the influence ratio of the browsing time, and this value is set as a correction value. This predetermined value can be changed depending on the degree of influence of the browsing time. The correction rate is corrected by multiplying the correction value by the reading rate shown in FIG. The correction of the reading rate is not limited to the method described above. For example, the extraction width of the reading rate sum and the moving width when calculating the moving average value may be changed, and the average without using the moving average may be changed. A value may be calculated.

  The user extraction unit 45 extracts a user as a high-engagement user when a sum of correction values of the read rate calculated in the predetermined period (for example, the latest 30 days) calculated by the read rate correction unit 44 is a high engagement user, Store in the high engagement user DB 32. For example, in the example stored in the high engagement user DB 32 illustrated in FIG. 3, 100% or more of the correction rate correction value sum is extracted as the high engagement user.

  Note that, for example, the number of times the user accessing the website 11, 12,... Acquired by the access status acquisition unit 41 refers to the website 11, 12,. , 12,... Can also be extracted. For example, during the last 30 days, the total of correction values of the reading completion rate is 100% or more, the number of times of directly referring to the websites 11, 12,... Is once or more, and the websites 11, 12,. Can be extracted as a high-engagement user. Furthermore, when it is considered that the influence of the browsing time is small, a high engagement user may be extracted using the reading rate before correction.

  The evaluation unit 46 calculates the evaluation value of the website based on the number and ratio of high engagement users. Specifically, the number of high engagement users is acquired for each website from the number of users stored in the high engagement user DB 32. In addition, by dividing the number of users stored in the access status DB 31 from the number of users stored in the high engagement user DB 32, the percentage of high engagement users is calculated for each website. These values are stored in the website evaluation DB 33.

  Moreover, based on the high engagement user number and the high engagement user ratio of the entire website to be evaluated, respective deviation values are calculated and stored in the user number deviation value and the user ratio deviation value of the website evaluation DB 33. The user number deviation value and the user ratio deviation value are for objectively evaluating whether the websites 11, 12,... Have more or fewer high engagement users than other websites. used. For example, let (number of users deviation value x 0.8 + user ratio deviation value x 1.2) ÷ 2 be an adjustment deviation value, which is a score for evaluating a website. The values 0.8 and 1.2 in this equation are values for weighting the respective deviation values, and can be changed depending on the weighting ratio. Further, this score may be calculated for each user segment, for example, for each sex, age, unmarried / married, etc.

  The websites 11, 12,... Are websites for providing various types of information and services. For example, an EC site for selling products, a recruitment site for personnel distribution, and information provision There are portal sites.

<Process flow>
Hereinafter, an example of an evaluation method executed by the evaluation apparatus 1 will be described with reference to FIG. FIG. 8 is a flowchart showing an evaluation method by the evaluation apparatus 1 of FIG.

  As the processing of step S101, the access status acquisition unit 41 stores a status of access to the Web sites 11, 12,... Managed by the Web server of the Web sites 11, 12,. The access user, the access start time, and the access end time are acquired from and stored in the access status DB 31.

  As a process of step S102, the read rate calculation unit 42 stores the read rate of the Web sites 11, 12,... For each user managed by the Web server of the Web sites 11, 12,. The read rate is calculated from the stored file and stored in the read rate of the access status DB 31.

  As the processing of step S103, the browsing time calculation unit 43 calculates the browsing time by subtracting the access start time from the access end time stored in the access status DB 31, and stores the calculated browsing time in the access status DB 31.

  As the process of step S104, the read rate correction unit 44 calculates the browsing time average from the total browsing time stored in the access status DB 31, extracts the browsing time average value for each movement 10, and the moving average value thereof. Is calculated. An average value is further calculated from each moving average value, and a difference in ratio with the average browsing time at which the total reading rate of the entire website to be evaluated is 100% is calculated. The correction value is calculated by multiplying the value by a predetermined value (for example, 0.7) and performing weighting.

  As a process of step S105, the read rate correction unit 44 corrects the read rate by multiplying the read rate stored in the access status DB 31 by the correction value calculated in step S104, and reads the access status DB 31. Store in the rate correction value.

  As processing of step S106, the user extraction unit 45 extracts a user whose sum of correction values of the reading completion rate calculated in step S105 is equal to or higher than a threshold value as a high engagement user, and stores the user in the high engagement user DB 32. .

  As processing of Step S107, evaluation part 46 acquires the number of high engagement users for every website from the number of users stored in high engagement user DB32, and stores it in the number of high engagement users of website evaluation DB33. Further, by dividing the number of users stored in the access status DB 31 from the number of users stored in the high engagement user DB 32, a high engagement user ratio is calculated for each website and stored in the website evaluation DB 33.

  As a process of step S108, the evaluation unit 46 calculates a deviation value from the number of high engagement users of the entire website to be evaluated, and stores the deviation value in the deviation number of users in the website evaluation DB 33. Further, the deviation value is calculated from the ratio of high engagement users of the entire website to be evaluated, and stored in the user ratio deviation value of the website evaluation DB 33.

  As described above, in the evaluation apparatus according to the present embodiment, the read rate calculation unit 42 calculates the read rate of the websites 11, 12,. A user whose calculated read rate is equal to or higher than a predetermined value is extracted as a high engagement user by the user extraction unit 45. Based on the number and ratio of the extracted high engagement users, the evaluation unit 46 calculates a deviation value based on the number and ratio of the high engagement users in the entire evaluation target website and uses the deviation value as an evaluation value. Therefore, it becomes possible to quantify the degree of interest of a user who accesses the website, and it is possible to objectively compare the websites.

  Further, the browsing time calculation unit 43 calculates the browsing time of the websites 11, 12,..., And the reading rate correction unit 44 calculates a correction value of the reading rate from the total browsing time, and corrects the reading rate. . As a result, the reading rate that is affected by the browsing time that varies depending on the content is corrected, so that the websites can be compared more objectively.

  While the embodiments according to the disclosure have been described above, these can be implemented in various other forms, and can be implemented with various omissions, substitutions, and changes. These embodiments and modifications, as well as those obtained by omission, substitution, and change are included in the technical scope of the claims and their equivalents.

DESCRIPTION OF SYMBOLS 1 Evaluation apparatus, 2 Communication part, 3 Memory | storage part, 4 Control part, 11, 12, ... Web site, 31 Access status DB, 32 High engagement user DB, 33 Web site evaluation DB, 41 Access status acquisition part, 42 Reading rate calculation unit, 43 browsing time calculation unit, 44 reading rate correction unit, 45 user extraction unit, 46 evaluation unit, NW network

Claims (7)

An access status acquisition unit for acquiring a user's access status to the website;
A read rate calculation unit that calculates a read rate for each access of the user to the Web site;
A user extraction unit that extracts high-engagement users whose sum of the reading rates in a predetermined period is equal to or greater than a threshold;
An evaluation device comprising: an evaluation unit that calculates an evaluation value of the website based on the number and / or ratio of the high engagement users. A browsing time calculation unit that calculates a browsing time for each access to the website of the user;
A reading rate correction unit that corrects the reading rate based on the browsing time;
The evaluation apparatus according to claim 1, wherein the user extraction unit extracts the high engagement user whose sum of the reading rates corrected by the reading rate correction unit is a threshold value or more.   The evaluation device according to claim 2, wherein the read rate correction unit calculates a moving average value within a predetermined value range with respect to a total sum of the read rates, and corrects the read rate using the moving average value.   The high-engagement user, wherein the user extraction unit includes a sum of the reading rates, a number of times the user directly referred to the website, and a number of times the user referred to the website again is a predetermined value or more. The evaluation apparatus according to any one of claims 1 to 3, wherein: is extracted.   The evaluation unit calculates a deviation value of the number of users of the high engagement user and / or a deviation value of a ratio of the number of users, and calculates an evaluation value of the website by performing predetermined weighting. The evaluation apparatus of any one of Claim 4. An access status acquisition step of acquiring the access status of the user to the website by the access status acquisition unit;
A read rate calculation step of calculating a read rate for each access to the web site of the user by a read rate calculation unit;
A user extraction step of extracting a high engagement user whose sum of the reading rates in a predetermined period is equal to or greater than a threshold by a user extraction unit;
An evaluation method comprising: an evaluation step of calculating an evaluation value of the website based on the number and / or ratio of the high engagement users by an evaluation unit. An access status acquisition step for acquiring a user's access status to the website;
A read rate calculation step of calculating a read rate for each access of the user to the website;
A user extraction step of extracting high-engagement users whose sum of reading rates in a predetermined period is equal to or greater than a threshold;
An evaluation program for causing an electronic computer to execute an evaluation step of calculating an evaluation value of the website based on the number and / or ratio of the high engagement users.

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