KR20090124488A - Analyzing system using web log file and analyzing method thereof - Google Patents

Abstract

PURPOSE: A data analysis system and a data analytical method using the same for performing the efficient marketing by analyzing weblog information of a client visiting web page are provided to expect efficient marketing and analyze the action of the client on the web page. CONSTITUTION: A searching unit(62) searches web log information of action data of a customer who connects a web page. A first customer database(64) includes weblog information DB of the client searched through searcher. An analyzing unit(66) performs segmentation analysis based on the weblog information DB of the client saved in the first customer database according to client. A second customer database includes the customer database information about by client fragmentation analyzed through the analysis section.

Description

Data analysis system using web log information and data analysis method using the same {ANALYZING SYSTEM USING WEB LOG FILE AND ANALYZING METHOD THEREOF}

The present invention relates to a data analysis system using web log information and a data analysis method using the same, and more specifically, based on web log information according to the behavior (activity) of a customer visited a web page by a seller without sales data. This paper is about data analysis system and more efficient data analysis method by analyzing this.

In the case of sellers (businesses, businesses) that sell goods, the customer's preferences for the goods being sold, the customer's age group, etc. are checked at the store. A marketing strategy was implemented.

However, the method of obtaining customer information through the store is limited to the customers who visit the store, and thus the customer information can be obtained. Therefore, more customer preferences, customer information about the goods, or other customer information can be obtained. How was it required?

Due to the development of information technology (IT), the Internet has made great progress through the Internet, which allows sellers to introduce store items to customers through web pages, and customers can access or purchase web pages. Web surfing is now possible to search for article-specific pages related to articles.

This development of information technology enables sellers to obtain information data of customers who access web pages through the Internet (web surfing), and the sellers can use their web surfing information to develop marketing strategies for customers. I could stand it.

For example, Korean Patent Application Publication No. 10-2004-0110971 (published December 31, 2004) discloses a "data analysis method incorporating a web log".

The data extraction step of extracting various company information and product data and analyzing the web server log, the data sending step of inputting the extracted data into the web house and sending it to each necessary place, and receiving the data It is about the data analysis method that integrates the weblog composed of the report preparation stage to prepare the report.

However, this technology extracts member data, product data, purchase data, etc. by analyzing web server logs, and then analyzes the behavior of customers who visited the web and sets campaign targets. Behavior can be effectively reflected.

However, when the product is a new product or when the seller starts the business for the first time, there is a problem that it is impossible to analyze the behavior of the customer in the initial stage of the new product or the initial stage of the business because there is no data on the purchase of the product.

In addition, Korean Patent Office Publication No. 10-2002-0045302 (published June 19, 2002) discloses a "product management method in electronic commerce".

This is not only based on analysis of user information and sales data, but also in e-commerce that analyzes usage patterns such as search patterns and purchase patterns through user path analysis using web mining technology that can scientifically analyze web server logs. It is about product management method.

However, in the case of this technology, a search pattern of a purchasing customer must exist before extracting a search pattern of a user, which is a problem in that it is not applicable to a company without new products or sales data.

Accordingly, a first object of the present invention is to provide a data analysis system using web log information which enables more efficient marketing by analyzing web log information according to the activity of a customer visiting a web page.

It is a second object of the present invention to provide a data analysis method using a data analysis system using the web log information that enables a more efficient marketing by analyzing a web log information of a customer without a sales data. It is.

In order to achieve the first object of the present invention described above, the present invention includes a search unit for searching the web log information that is the activity data of the customer accessing the web page; A first customer DB having the web log information DB of the customer searched through the search unit; An analysis unit for performing segmentation analysis for each customer based on the web log information DB of the customer stored in the first customer DB; A second customer DB having customer DB information on customer segmentation analyzed through the analysis unit; And it provides a data analysis system using the web log information including a report generation unit for generating a report for each customer based on the second customer DB.

In addition, in order to achieve the second object of the present invention, the present invention comprises the steps of retrieving the web log information of the customer who visited the web page in the search unit and storing it in the first customer DB; Analyzing, by the analysis unit, indexing, customer ratings, and customer rating movement status for each customer based on the web log information for each customer stored in the first customer DB and storing the same in the second customer DB; And it provides a data analysis method using the web log information comprising the step of generating a report in the report generation unit based on the customer-specific information stored in the second customer DB.

Using the data analysis system using the web log information according to the present invention and the data analysis method using the same, more efficient marketing can be expected by analyzing the behavior of the customer accessing the web page without the sales data.

In addition, by randomly selecting and analyzing the web log information according to the needs of the web log information according to the customer activity on the web page, it is possible to obtain a customer's behavior (activity) pattern that is important for each seller, thereby enabling more strategic marketing. .

In addition, by checking the status of the grade shift by customer, it is possible to select a customer group to systematically manage the departure customer can be more strategic marketing.

Furthermore, by checking the e-mail responsiveness of customers, more strategic marketing can be conducted by referring to feedback based on the response result.

Hereinafter, a data analysis system using web log information and a data analysis method using the same will be described in detail with reference to the accompanying drawings.

1 is a schematic conceptual diagram illustrating a data analysis system using web log information according to an embodiment of the present invention.

Referring to FIG. 1, the data analysis system using web log information according to the present embodiment may be provided with various contents by accessing a web page 40 providing various contents and accessing the web page 40 through an internet network. Analysis system 60 for analyzing the web log information which is the activity data of the customer 20, the customer 20 accessing the web page 40 to generate a customer-specific activity pattern database (DB), and the customer 20 In addition to managing the web page 40 for providing a variety of content, and has a service provider 80 receives a customer-specific activity pattern database connected to the web page 40 from the analysis system 60.

Hereinafter, each component will be described in detail with reference to the accompanying drawings.

2 is a detailed conceptual diagram illustrating a data analysis system using web log information according to an embodiment of the present invention.

2, the analysis system 60 of the data analysis system using the web log information according to the present embodiment is a search for searching the web log information that is the activity data of the customer 20 connected to the web page 40 Based on the web log information DB of the customer 20 stored in the first and second customer DB 64 having the web log information DB searched through the search unit 62, 62 An analysis unit 66 for segmenting analysis by customer, a second customer DB 68 having customer DB information on customer segmentation analyzed by the analysis unit 66, and the second customer DB 68 It includes a report generation unit 72 for generating a report for each customer based.

The searcher 62 searches for web log information generated as the customer 20 accesses the web page 40 and performs activities. The web log information searched by the searcher 62 is performed by the customer 20. It can contain all the web log information generated by the activity of).

For example, visits to check the number of customer visits that can be identified through membership registration, the number of customer visits through membership registration, and the way through Path, the number of times that the web page 40 was viewed, the number of times the web page 40 was active (remaining), the number of recent web page visitors, the number of web page revisits, the elapsed time of web page re-visits, and the rate of web page re-visits. There is this.

The number of customer visits may include the number of unique visits and the total number of visits. In more detail, the number of unique visits is measured once even when the customer visits the web page 40 several times a day to check the number of customers who visited the web page 40 per day. The total number of visits is to check the total number of visits when the customer visits the web page 40 several times in one day, that is, the total number of times the customer visits the web page 40 in one day.

The number of times of viewing the web page 40 may include a number of times of viewing the entire page of the web page 40 and a number of times of reading a specific page in the web page 40.

The first customer DB 64 is a member identification, recent web page visits, customer visits, re-visits, re-visit rate, visit path, time spent on the web page, web searched through the search unit 62 The number of page views, the date of re-visit, and the like.

The analysis unit 66 analyzes the customer segmentation based on the first customer DB 64 in which the web log information of the customer retrieved through the search unit 62 is stored. Segmentation analysis by customer includes indexing by customer based on customer web log information, customer management ranking according to indexing, and movement status of customer management rating.

The customer segmentation analyzed by the analysis unit 66 will be described in more detail as follows.

First, indexing for each customer through the analysis unit 66 is to convert customer-specific web log information stored in the first customer DB 64 into a score. That is, the web page information such as the recent web page visits, the number of visits, the number of revisits, the rate of revisits, the time spent on the web pages, the number of web page views, and the elapsed days of revisits are scored.

For example, the number of re-visits, for example, is the number of visits to the web page over the course of one month is 100 points, more than 10 visits, 90 points for nine visits, 80 points for eight visits, weighted according to the number of visits The way to do it is. In another example, the time spent on a web page (active time) is 100 points for 30 minutes or more, 90 points for 25 minutes or more, and 80 points for 20 minutes or more. A few ways to score this.

This method of scoring the weighted web log information for each customer is applied to other web log information and is indexed.

And the customer management graded by the indexing through the analysis unit 66 is graded for each customer based on the index for each customer. In more detail, based on the index for each customer weighted to the web log information of the customer is given a rating for each customer to enable systematic management for each customer.

In this way, how to assign ratings by customer, the number of visits, web page stay time, re-visit number is described as follows.

Assuming three customers A, B, and C access the web page, customer A has 100 revisits, time spent on the web page, 100 web page views, and B customer revisits. 90 points, 90 points of time spent on a web page, 90 points of web page views, C customer 80 visits, 80 points of time spent on a web page, 80 points of Web page views, the analysis unit (66) In the case of being indexed through), the analysis unit 66 calculates the average of the scores indexed for each customer, and gives a grade as 1 grade for 90 points or more, 2 grades for 80 points or more, and 3 grades for 70 points or more. can do.

Accordingly, in the analysis unit 66, A and B customers may be given a grade of 1 grade, and C customers of 2 grades.

In addition to the method of averaging the indexing scores, the classifying method for each customer through the analyzing unit 66 may average the web log information by weighting it. For example, the weight may be assigned to 1.5, 1.3, 1.2, etc. in the order of the number of re-visits, the time spent on the web page, and the number of web page views, respectively, and the average may be calculated by reflecting the weighted value in the indexed score.

In addition, by performing the real-time or for a certain period of time to classify the rating for each customer through the analysis unit 66 may check the status (movement) of the grade classified by customer. In more detail, even if the first level classified by each customer is 1st level, the customer may maintain the 1st level in the subsequent classification according to the web log information that the customer accesses the web page, and fall to the 2nd or 3rd level. It may be. As such, it is to check the status of rating movement that varies by customer.

The second customer DB 68 has a customer-level indexing, a customer management grade according to the customer-indexing, and a moving status of the customer management grade analyzed through the analysis unit 66.

The report generator 72 generates a report for each customer based on the second customer DB 68 having the customer-specific DB analyzed by the analyzer 66.

The report generation method for each customer of the report generation unit 72 is based on the customer's index based on the index stored by the customer stored in the second customer DB 68, the customer management grade according to the customer index, and the moving status of the customer management grade. Indexing, grading, and movement can be graphed.

In addition to the graph method, it is possible to describe by customer indexing, rating, and movement status. For example, 'A customer has 10 times (100 points) of web page re-visits in the last month, 30 minutes or more (100 points) of time spent on a web page, and 10 times (100 points) for each section. ,… The customer management grade is 1 grade (100 points).

The analysis system 60 of the data analysis system using the web log information according to the present embodiment further includes an analysis setting unit 67 and a marketing unit 70.

The analysis setting unit 67 allows the analysis unit 66 to selectively set the web log information of the customer, which is the basis for the customer segmentation analysis.

In more detail, the analysis setting unit 67 selectively sets only the web log information to be segmented through the analysis unit 66 among the customer-specific web log information stored in the first customer DB 64. That is, all of the web log information may be needed as needed among the customer's web log information, for example, the visit route or the re-visit date may not be needed. As such, if necessary, the customer-specific DB analyzed through the private analysis unit 66 is selectively set.

The marketing unit 70 checks whether the e-mail sent and sent e-mail is checked for each customer based on the second customer DB 68, and indexes the checked e-mail to the second customer DB 68. To be transmitted and stored.

In more detail, the marketing unit 70 sends an advertisement mail associated with a web page to a customer stored in the second customer DB 68. The advertisement mail may be, for example, an advertisement mail related to the entire web page, or based on the page view frequency (view count score) of each part of the customer stored in the second customer DB 68 in the advertisement mail related to the entire web page. You can also add and send web page advertisement mails according to your preferences.

The marketing unit 70 may send the advertisement mail as described above for each customer, and then check whether the advertisement mail sent by the customer has been opened (OPEN) and, if so, whether the page is read (clicked) for each part. . Whether the customer checks the e-mail checked through the marketing unit 70 is indexed and transmitted to the second customer DB 68 and stored.

Indexing of the customer's email confirmation through the marketing unit 70 indexes the customer's email confirmation whether the statistics. In other words, it checks how many emails are sent to the customer, and how many times the email is checked, and through this, the email responsiveness of the customer is statistically indexed.

The e-mail responsiveness is transmitted to the second customer DB 68 through the marketing unit 70, and the report generation unit 72 is an existing index for each customer (score), customer management grade, and the movement status of the customer. Reports can be created in graph or narrative format, including email responsiveness.

The present invention also provides a data analysis method through a data analysis system using web log information. Hereinafter, descriptions of parts in common with the description of the data analysis system using the above-described web log information will be omitted or abbreviated.

3 is a flowchart illustrating a data analysis method using web log information according to an embodiment of the present invention.

Referring to FIG. 3, the web log information of the customer who visited the web page 40 is searched by the search unit 62 and stored in the first customer DB (S10). The customer-specific web stored in the first customer DB is stored. Analyzing the indexing by customer, the rating by customer, and the rating by customer based on the log information in the analyzing unit 66 and storing it in the second customer DB (S20), and the customer stored in the second customer DB The report generating unit 72 generates a report based on the star detailing information (S35).

The web log information searched through the search unit 62 in step S10 includes membership identification, recent web page visits, visits to customer bases, re-visits, re-visit rates, visit paths, time spent on web pages, and parts. The number of page views, the date of re-visit, and the like.

The report format generated by the report generation unit 72 in step S35 is a graph form or a sentence of the customer-specific indexing, customer-specific ratings, and customer-specific rating movement statuses stored in the second customer DB through the step S20. Can be written.

And the data analysis method using the web log information according to this embodiment step to selectively set the customer web log information that is the basis of the customer-specific analysis step (S20) through the analysis setting unit 67 (S15) ) May be further included.

The step S15 is a step of selectively setting the necessary web log information so that only the information considered necessary among the web log information of the customer can be analyzed in the step S20.

And the data analysis method using the web log information according to the present embodiment is to check whether the email sent and sent by the customer for each customer through the marketing unit 70 based on the customer segmentation DB stored in the second customer DB Step (S25), and may be further included in step (S30) to store the information in the second customer DB indexed by the marketing unit 70 whether the email check is checked through the check step (S25).

In step S25, the marketing unit 70 sends an email to the customer based on the customer segmentation DB stored in the second customer DB in step S20. The sending of the email is an advertisement mail related to a web page, and may be an advertisement mail related to an entire web page, and based on the number of page views of each part of a customer stored in the second customer DB in step S20 in the advertisement mail related to the entire web page. You can also send additional web page advertisements to your tastes.

Step S25 is a step of checking whether the customer has checked the e-mail after opening the e-mail to the customer and at the same time checking whether the page is read by the part.

The step S30 is a step of indexing whether the customer checked in the step S25 via the marketing unit 70 and stores it as the second customer DB.

In step S30, the indexing (score) of the customer's confirmation of the email stored in the second customer DB is stored in the graph form or described together with the indexing by the customer, the rating by the customer, and the rating by the customer through the step 35. It can be written in sentences.

While the above has been described with reference to a preferred embodiment of the present invention, those skilled in the art will be able to variously modify and change the present invention without departing from the spirit and scope of the invention as set forth in the claims below. It will be appreciated.

1 is a schematic conceptual diagram illustrating a data analysis system using web log information according to an embodiment of the present invention.

2 is a detailed conceptual diagram illustrating a data analysis system using web log information according to an embodiment of the present invention.

3 is a flowchart illustrating a data analysis method using web log information according to an embodiment of the present invention.

Brief description of the main parts of the drawing

40: web page 60: analysis system

62: search unit 64: the first customer DB

66: analysis unit 67: analysis setting unit

68: second customer DB 70: marketing department

72: report generation unit

Claims (7)

A retrieval unit for retrieving web log information which is activity data of a customer accessing a web page; A first customer DB having the web log information DB of the customer searched through the search unit; An analysis unit for performing segmentation analysis for each customer based on the web log information DB of the customer stored in the first customer DB; A second customer DB having customer DB information on customer segmentation analyzed through the analysis unit; And Data analysis system using a web log information including a report generation unit for generating a report for each customer based on the second customer DB. The method of claim 1, wherein the first customer DB is Includes customer visits, including visitor identification, recent web visits, unique visits and total visits, visits, rate of visits, visit path, web time, total page views, and specific page views. Data analysis system using the web log information, characterized in that it includes a web page reading frequency, and the re-visit date. The method of claim 1, wherein the analysis unit Data analysis system using the web log information, characterized in that based on the first customer DB, customer-specific indexing, customer management ranking according to the customer-specific indexing, and analyzing the movement status of the customer management rating. The method of claim 1, On the basis of the second customer DB to check whether the email sent to each customer and the sent email check, A marketing unit for indexing whether the checked e-mail is checked and transmitting it to the second customer DB; And And an analysis setting unit configured to selectively set the web log information of the customer which is the basis for the customer segmentation analysis in the analysis unit. The method according to claim 1 or 4, The second customer DB is a data analysis system using the web log information, characterized in that it comprises a responsiveness according to the customer scores, customer ratings, customer status movement status, and email response results. Retrieving the web log information of the customer who visited the web page in the search unit and storing the web log information in the first customer DB; Analyzing, by the analysis unit, indexing, customer ratings, and customer rating movement status for each customer based on the web log information for each customer stored in the first customer DB and storing the same in the second customer DB; And Data analysis method using the web log information comprising the step of generating a report in the report generator based on the customer-specific information stored in the second customer DB. The method of claim 6, Selectively setting the web log information of the customer, which is the basis of the analysis step for each customer, through an analysis setting unit; Checking whether the email is sent and checked by the customer through a marketing unit based on the customer-specific segmentation DB stored in the second customer DB; And A method of analyzing data using web log information, further comprising the step of indexing whether or not the checked email is checked through the email checking step and storing it in the second customer DB.

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