Electronic device for data analysis and operation method thereof

Abstract

A method for analyzing data in an electronic device according to one embodiment of the present invention is characterized by comprising the steps of: obtaining a plurality of log data related to the use of an electronic commerce service from a plurality of user terminals; generating behavior tracking data related to the use of the electronic commerce service for each user on the basis of the plurality of log data; extracting data satisfying a first condition from the behavior tracking data of the plurality of users; and displaying a dashboard including the extracted data.

Description

Electronic device for data analysis and method of operation thereof

[0001] The present invention relates to an electronic device for data analysis and a method for operating the same. More specifically, the present invention relates to an electronic device and a method for operating the same, which collects log data related to the use of an e-commerce service from user terminals of users, and analyzes the collected log data to obtain information related to the service or the user.

[0002] As internet use becomes more widespread, the e-commerce market is expanding. Particularly with the spread of infectious diseases, the proportion of people visiting offline stores to purchase items is decreasing, while the proportion of people purchasing items through e-commerce using computers or smartphones is rapidly increasing.

[0003] As the e-commerce market expands, collecting diverse information, including user behavior patterns, shopping habits, and service preferences, is crucial. This data is generated in the millions, and log data from user visits to websites or applications includes session information, click events, and purchase records. By efficiently collecting and analyzing this data, e-commerce service providers can gain real-time insights necessary for developing business strategies and improving service quality.

[0004] Meanwhile, there are a wide variety of methods for extracting and classifying necessary information from vast amounts of log data. To monitor diverse user activities and make informed decisions, data must be effectively analyzed and applied to business operations. As data analysis becomes increasingly important, e-commerce service providers need methods and systems that extract key information from diverse log data and utilize it in real time to improve the quality of their e-commerce services.

[0005] In this regard, reference may be made to prior literature such as KR 10-1743269 B1 and KR 10-2014-0055282 A.

[0006] The present invention aims to provide a method for collecting log data of users using an e-commerce service in real time and storing the same in a database according to desired conditions.

[0007] In addition, the present invention aims to provide a method for processing log data stored in a database and displaying information necessary for improving service quality on a dashboard.

[0008] The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by a person having ordinary skill in the technical field to which the present invention belongs from the description below.

[0009] A method for analyzing data in an electronic device according to one embodiment of the present invention is characterized by comprising: acquiring a plurality of log data related to the use of an e-commerce service from a plurality of user terminals; generating behavioral tracking data related to the use of the e-commerce service for each user based on the plurality of log data; extracting data satisfying a first condition from the behavioral tracking data of the plurality of users; and displaying a dashboard including the extracted data.

[0010] In one embodiment, the behavior tracking data is characterized in that it includes at least one of information related to access to at least one page and information related to user input on at least one page.

[0011] In one embodiment, the first condition is characterized by including at least one of a condition regarding a date or a condition regarding identifier information of a user terminal.

[0012] In one embodiment, the behavior tracking data includes information about a page accessed by a user terminal, and the extracting step is characterized in that it includes a step of extracting data about the number of visits corresponding to a first date and a first page based on the behavior tracking data of the plurality of users.

[0013] In one embodiment, if the number of visits satisfies a preset condition, the dashboard is characterized in that it further includes a message related to the number of visits.

[0014] In one embodiment, the method further comprises: generating an event related to the store when the first page is a page related to the store; and transmitting information related to the event to the plurality of user terminals.

[0015] In one embodiment, the behavior tracking data includes information about a page accessed by a user terminal, and the extracting step further includes a step of extracting data about a conversion rate between a plurality of pages related to the e-commerce service based on the behavior tracking data of the plurality of users; and a step of determining a depth of at least one page among the plurality of pages within the service based on the conversion rate.

[0016] In one embodiment, the behavior tracking data includes information about search terms received from user terminals, and the extracting step includes a step of extracting data about the number of searches related to a first category by time zone based on the behavior tracking data of the plurality of users, and further includes a step of transmitting recommended store information related to the first category to the plurality of user terminals in the first time zone when the number of searches related to the first category in the first time zone satisfies a preset condition.

[0017] In one embodiment, the behavior tracking data includes information about user input within a page of a user terminal, and the extracting step includes a step of extracting data about user input within a second page of a first user terminal based on the behavior tracking data of the plurality of users, and the displaying step includes a step of displaying a message including identifier information of the first user terminal and information about the second page on the dashboard when information about user input within the second page of the first user terminal satisfies a preset condition.

[0018] In one embodiment, the behavior tracking data further includes information about the time at which the user terminal accessed the page, and the extracting step includes a step of extracting data about an average stay time corresponding to a third page based on the behavior tracking data of the plurality of users, and the displaying step includes a step of displaying information about the third page and the average stay time information on the dashboard when the average stay time corresponding to the third page satisfies a preset condition.

[0019] In one embodiment, the behavior tracking data includes platform information corresponding to a user terminal, and the step of displaying a dashboard including the extracted data includes a step of classifying and displaying the extracted data based on the platform information.

[0020] In one embodiment, the behavior tracking data includes information about a page accessed by a user terminal and information about a loading time of the page accessed by the user terminal, and the extracting step includes a step of extracting data about a loading time of a fourth page corresponding to a second user terminal based on the behavior tracking data of the plurality of users, and the displaying step further includes a step of displaying identifier information of the second user terminal and information about the fourth page on the dashboard when the loading time of the fourth page satisfies a preset condition.

[0021] A non-transitory storage medium according to one embodiment of the present invention is characterized by being a computer-readable non-transitory storage medium having recorded thereon a program for executing the above-described method on a computer.

[0022] An electronic device for data analysis according to one embodiment of the present invention comprises: a transceiver for transmitting and receiving information with a plurality of user terminals; and a processor for obtaining a plurality of log data related to the use of an e-commerce service from the plurality of user terminals, generating behavioral tracking data related to the use of the e-commerce service for each user based on the plurality of log data, extracting data satisfying a first condition from the behavioral tracking data of the plurality of users, and displaying a dashboard including the extracted data.

[0023] The present invention can analyze user characteristics by collecting and analyzing data related to the use of e-commerce services by users in real time.

[0024] The present invention can improve user experience by improving e-commerce services based on user characteristics analyzed based on data related to users' use of the service.

[0025] The present invention can quickly detect and respond to service problems or failures based on collected data, and can predict and prevent future failures by analyzing user usage patterns.

[0026] The effects that can be obtained through the present invention are not limited to the effects mentioned above, and other effects that are not mentioned can be clearly understood by a person having ordinary skill in the art to which the present invention belongs from the description below.

[0027] FIG. 1 is a schematic diagram illustrating the configuration of a system for analyzing data according to various embodiments.

[0028] FIG. 2 is a diagram schematically illustrating the operation of a system for analyzing data according to one embodiment of the present invention.

[0029] FIG. 3 is a flowchart illustrating the operation of an electronic device performing a method of analyzing data according to various embodiments of the present invention.

[0030] FIG. 4 is a diagram illustrating a dashboard according to one embodiment of the present invention.

[0031] FIGS. 5A and 5B are diagrams illustrating a dashboard according to various embodiments of the present invention.

[0032] FIG. 6 is a drawing schematically illustrating each component of an electronic device according to one embodiment of the present invention.

[0033] In describing the embodiments, descriptions of technical details that are well known in the technical field to which the present invention pertains and are not directly related to the present invention will be omitted. This is to avoid obscuring the gist of the present invention by omitting unnecessary explanations and to convey the gist more clearly.

[0034] For the same reason, some components in the attached drawings are exaggerated, omitted, or schematically depicted. Furthermore, the dimensions of each component do not entirely reflect its actual size. Identical or corresponding components in each drawing are assigned the same reference numbers.

[0035] The advantages and features of the present invention, and the methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided only to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Like reference numerals designate like elements throughout the specification.

[0036] At this time, it will be understood that each block of the processing flowchart drawings and combinations of the flowchart drawings can be performed by computer program instructions. These computer program instructions can be loaded into a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, so that the instructions executed by the processor of the computer or other programmable data processing equipment create a means for performing the functions described in the flowchart block(s). These computer program instructions can also be stored in a computer-available or computer-readable memory that can be directed to a computer or other programmable data processing equipment to implement the functions in a specific manner, so that the instructions stored in the computer-available or computer-readable memory can produce an article of manufacture that includes a command means for performing the functions described in the flowchart block(s). The computer program instructions can also be loaded onto a computer or other programmable data processing equipment, so that a series of operation steps are performed on the computer or other programmable data processing equipment to create a computer-executable process, so that the instructions that execute the computer or other programmable data processing equipment can provide steps for performing the functions described in the flowchart block(s).

[0037] Additionally, each block may represent a module, segment, or portion of code that contains one or more executable instructions for performing a specific logical function(s). It should also be noted that in some alternative implementation examples, the functions described in the blocks may occur out of order. For example, two blocks depicted in succession may actually be executed substantially concurrently, or the blocks may sometimes be executed in reverse order, depending on their respective functions.

[0038] Here, the term '~ unit' used in this embodiment means a software or hardware component such as an FPGA or ASIC, and the '~ unit' performs certain roles. However, the '~ unit' is not limited to software or hardware. The '~ unit' may be configured to be on an addressable storage medium and may be configured to regenerate one or more processors. Thus, as an example, the '~ unit' includes components such as software components, object-oriented software components, class components, and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and '~ units' may be combined into a smaller number of components and '~ units' or further separated into additional components and '~ units'. In addition, the components and '~ units' may be implemented to regenerate one or more CPUs within a device or a secure multimedia card.

[0039] The expression “at least one of a, b and c” described throughout the specification may encompass ‘a alone’, ‘b alone’, ‘c alone’, ‘a and b’, ‘a and c’, ‘b and c’, or ‘all of a, b and c’.

[0040] The "terminal" mentioned below may be implemented as a computer or portable terminal that can connect to a server or other terminal via a network. Here, the computer includes, for example, a notebook, desktop, laptop, etc. equipped with a web browser, and the portable terminal may include, for example, a wireless communication device that guarantees portability and mobility, and may include all types of handheld-based wireless communication devices such as communication-based terminals such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution), smartphones, tablet PCs, etc.

[0041] Below, with reference to the attached drawings, embodiments of the present disclosure are described in detail so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein.

[0042] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings.

[0043] FIG. 1 is a schematic diagram illustrating the configuration of a system for analyzing data according to various embodiments.

[0044] Referring to FIG. 1, a data analysis system according to various embodiments of the present invention may include an electronic device (100) and a user terminal (110). Meanwhile, the system illustrated in FIG. 1 only illustrates components related to embodiments of the present invention. Therefore, those skilled in the art will appreciate that, in addition to the components illustrated in FIG. 1, other general-purpose components may also be included.

[0045] In one embodiment, a user terminal (110) corresponding to a user of an e-commerce service is installed with an application that provides an e-commerce service, and can access a server related to the e-commerce service under the control of the application and use the e-commerce service based on information exchange with the server. The e-commerce application may include an application for buyers, an application for sellers, an application for delivery personnel, etc., depending on who the user of the application is. That is, the user terminal (110) can be used by various users, including customers who purchase items through the service, sellers who sell items through the service, and delivery personnel who deliver purchased items from sellers to customers. The user terminal (110) may be a mobile device such as a smartphone or tablet PC, or a static device such as a desktop PC, and any device on which an e-commerce or delivery brokerage service application can be installed and executed can be used as the user terminal (110) without limitation.

[0046] In one embodiment, a user terminal (110) can exchange information with an electronic device (100) that includes a system for analyzing data. For example, the electronic device (100) can obtain log data from the user terminal (110). The electronic device (100) can store the log data obtained from the user terminal (110) in its database, and by analyzing the stored data, can contribute to improving the quality of e-commerce services. For example, the electronic device (100) can provide personalized services or quickly detect and address system problems by collecting and analyzing log data from users using the e-commerce service. Accordingly, the user experience can be enhanced and the efficiency of service operation can be increased.

[0047] FIG. 2 is a diagram schematically illustrating the operation of a system for analyzing data according to one embodiment of the present invention.

[0048] Referring to FIG. 2, the electronic device (100) can obtain log data from the user terminal (110). For example, the electronic device (100) can obtain log data in real time from the user terminal (110) by utilizing Lumberjack as illustrated in FIG. 2. The log data obtained from the user terminal (110) may include page information (page 1, page 2, page 3), identifier information (schemaid) corresponding to each page within the service, and identifier information (pcid) of the user terminal. In addition, the obtained log data may additionally include information regarding actions performed through the user terminal (110) within the e-commerce service, such as page entry, logging in, entering a search term, and purchasing an item.

[0049] Thereafter, the electronic device (100) can process the log data acquired in real time and store it in the first database (101). The log data acquired in real time can be processed using Flink, and this process can be referred to as Flink Streaming. At this time, the data stored in the first database (101) can be data classified by date and user from the data acquired in real time from the user terminal (110). In addition, the data stored in the first database (101) can be behavior tracking data in the form of sequentially listing user behavior information through a specific user terminal within the service on a specific date. For example, as illustrated in FIG. 2, the data collected in real time<schemaid, page, pcid, 쪋> Log data in the form of Flink is used to represent information about a series of user actions within the service corresponding to pcid1. <day, pcid1, <page 1, time1>,<page 2, time2> , can be converted into the format of 쪋>, and the converted data can be stored in the first database (101).

[0050] In addition, the electronic device (100) can extract data in a new format by reprocessing the data stored in the first database (101) to obtain desired information. For example, since the data stored in the first database (101) sequentially lists user behavior information through a specific user terminal on a specific date, the number of visits (uv) to a specific page on a specific date can be known by utilizing this. In addition, depending on the type of information on service use included in each data stored in the first database (101), data on the average residence time of a specific page, the conversion rate between pages provided by the service, and the popular categories at a specific time zone can be extracted from the data stored in the first database (101). In this way, the new format data obtained by reprocessing the data stored in the first database (101) can be stored in the second database (102). For example, as illustrated in FIG. 2, the data stored in the second database (102) includes information on the number of daily visits to a specific page.<day, page, time, uv> It can be data in the form:

[0051] Additionally, the electronic device (100) can provide visualized information about the service and users using the service by displaying a dashboard (103) that includes some of the data stored in the first database (101) or the second database (102). The method by which the electronic device (100) collects and analyzes log data related to service use will be described in detail below with reference to FIG. 3.

[0052] FIG. 3 is a flowchart illustrating the operation of an electronic device performing a method of analyzing data according to various embodiments of the present invention.

[0053] Referring to FIG. 3, in step S310, the electronic device (100) can obtain multiple log data related to the use of an e-commerce service from multiple user terminals (110).

[0054] The electronic device (100) may obtain log data from the user terminal (110) corresponding to each user using the e-commerce service. In one embodiment, the log data obtained from the user terminal (110) may include date information, identifier information of the user terminal, and may further include at least one of an IP address corresponding to the user terminal, location information corresponding to the user terminal, platform information corresponding to the user terminal, information regarding the page accessed by the user terminal, information regarding user input (e.g., search word input, button click) within the page of the user terminal, and information regarding the time at which the user input occurred. Meanwhile, the information included in the log data collected by the electronic device (100) from the user terminal (110) is not limited to the examples described above, and may include any information deemed necessary for the e-commerce service provider to analyze matters related to the use of the service. In addition, the log data obtained from the user terminal (110) may be obtained using any method for collecting log data.

[0055] In step S320, the electronic device (100) may generate behavioral tracking data related to the use of e-commerce services for each user based on a plurality of log data. In one embodiment, the electronic device (100) may store the behavioral tracking data generated in step S320 in a first database (101).

[0056] When log data acquired in real time from user terminals (110) corresponding to multiple users using the service simultaneously is stored in a database without being classified by user, a cumbersome process of extracting log data in which the identifier information of the user terminal included in the log data matches the identifier information of the user terminal corresponding to the specific user must be performed for all log data stored in the database in order to check the log data for a specific user at a later time. As the amount of data stored in the database increases, the time required to extract the desired log data will further increase.

[0057] To solve this problem, log data acquired in real time can be classified by user based on the identifier information of the user terminal included in each log data to generate behavior tracking data including information on the user's behavior within the service, and this can be stored in the first database (101). At this time, the generated user-specific behavior tracking data can include at least one of information related to access to at least one page and information related to user input on at least one page based on the information included in the log data acquired in step S310. For example, information related to access to at least one page can include information such as page identification information of the page accessed by the user and page access time, and information related to user input on at least one page can include information such as page identification information of the page related to the user input, information on the type of user input, and the time at which the user input occurred. In addition, the behavior tracking data can further include any data necessary for analyzing the user's behavior related to the use of the service among the information included in the log data acquired in step S310.

[0058] By generating user-specific behavioral tracking data based on collected log data and storing it in a database, users can identify log data for specific users without having to search through all of the database's log data. Instead, they can simply extract data from the storage space corresponding to that user. This approach allows for efficient database management and rapid retrieval of desired data. Therefore, even as the volume of data stored in the database increases, the time required to extract desired data can be reduced.

[0059] In step S330, the electronic device (100) can extract data satisfying the first condition from the behavior tracking data of multiple users.

[0060] In one embodiment, the first condition may include at least one of a date-related condition and a condition regarding identifier information of the user terminal. This first condition may be determined by the selection of an e-commerce service provider on the dashboard provided by the electronic device (100) and may be used to extract data regarding a specific date or data regarding the activities of a specific user.

[0061] For example, an e-commerce service provider may wish to analyze data for a specific date, such as a product launch date or a special event. In this case, by setting the specific date to be analyzed as the first condition, behavioral tracking data for multiple users corresponding to that date can be extracted from the first database (101). Furthermore, the e-commerce service provider may wish to analyze data, such as the behavioral patterns or purchase records of specific users, to provide personalized services. In this case, by setting the identifier information of the user terminal corresponding to the specific user to be analyzed as the first condition, behavioral tracking data corresponding to that user can be extracted from the first database (101). Furthermore, if a complaint regarding service use is received from a specific user, the e-commerce service provider may wish to analyze data regarding the specific user's service use on a specific date. In this case, by setting both the specific date to be analyzed and the identifier information of the user terminal corresponding to the specific user as the first condition, behavioral tracking data for the specific user on the specific date can be extracted.

[0062] In one embodiment, the first condition may be a condition for extracting a new format of data by reprocessing the behavioral tracking data stored in the first database (101). For example, when checking the number of visits to a specific page during a specific period, data stored in the first database (101) that have date information belonging to the specific period and the identification information of the page accessed by the user matching the identification information of the specific page are considered data that satisfy the first condition. The first condition may vary depending on the information the service provider wishes to check from the behavioral tracking data, and various examples related to the first condition will be described below with reference to FIGS. 5A and 5B.

[0063] In step S340, the electronic device (100) can display a dashboard including the data extracted in step S330.

[0064] In one embodiment, the electronic device (100) can display a dashboard containing analyzed information about the service and / or users using the service based on the extracted data. In this way, the dashboard provides important business intelligence to e-commerce service providers and provides the ability to visually view various information. Such a dashboard can include a variety of information.

[0065] In one embodiment, a dashboard may include data such as the number of orders, sales, user activity patterns, or a specific user's purchase history for a specific date. E-commerce service providers can set a time range on the dashboard to view data for a specific period or analyze the activity of specific users. For example, analysis results, such as why sales of a specific item category were high on a specific date or the purchasing patterns of a specific user group, can be displayed using visual elements such as graphs and charts.

[0066] In one embodiment, an e-commerce service provider can change a first condition to a second condition on a dashboard. Accordingly, the electronic device (100) can extract data that satisfies the changed second condition from among the behavioral tracking data stored in the first database (101) based on the changed second condition and display a dashboard including the extracted data. In this way, the e-commerce service provider can utilize the dashboard to dynamically check necessary information for various scenarios, thereby monitoring business trends in real time and assisting in making important decisions. This dashboard function can support data-driven decision-making and contribute to improving business performance. Examples of dashboards including various information related to service use will be described below with reference to FIGS. 4 to 5b.

[0067] FIG. 4 is a diagram illustrating a dashboard according to one embodiment of the present invention.

[0068] Referring to FIG. 4, the dashboard (400) may include areas (410) and (420). In one embodiment, area (410) may include an area (411) for selecting a specific date and an area (412) for selecting a specific user. Area (411) provides the service provider with the ability to select a specific date on the dashboard, and the service provider may use a calendar or date picker to specify the desired date. The service provider may then visually check the behavioral tracking data for the selected date or period.

[0069] In one embodiment, area (412) provides the service provider with the ability to select or filter specific users from the dashboard. The service provider can enter identifier information corresponding to a specific user's terminal or select a user from a drop-down list to view behavioral tracking data for that user. Furthermore, based on the user's behavioral tracking data, the service provider can analyze the user's purchase history, activity patterns, and other information in detail to provide personalized services or more quickly identify and respond to errors that occur during service use.

[0070] In one embodiment, the region (420) may include behavior tracking data extracted based on information selected from the region (410) among the behavior tracking data of multiple users stored in the first database (101) of the electronic device (100). Depending on the information selected from the region (410), the region (420) may display behavior tracking data for a specific date, behavior tracking data for a specific user, or behavior tracking data for a specific user on a specific date. The behavior tracking data displayed in the region (420) may include all information included in the collected behavior tracking data, or may include only information selected by the service provider from among the information included in the behavior tracking data. In the example illustrated in FIG. 4, data including date information, identifier information of the user terminal, page URL information, visit time information of the corresponding page, and behavior information related to the corresponding page, among the information included in the behavior tracking data, is displayed on the dashboard.

[0071] In one embodiment, the behavioral tracking data displayed in area (420) may be sorted based on specific information included in the behavioral tracking data, at the service provider's discretion. For example, the behavioral tracking data displayed in area (420) may be sorted based on visit time, and the service provider may identify a user's behavioral path within the service based on the behavioral tracking data displayed in area (420). In another example, the behavioral tracking data displayed in area (420) may be sorted based on page URL, and the service provider may collect information about the number of visits to a specific page and the user terminals that visited the page based on the behavioral tracking data displayed in area (420).

[0072] In this way, service providers can analyze the behavioral tracking data displayed in area (420) by sorting it based on various criteria, thereby gaining detailed insights into user behavior within the service, page usage statistics, or performance over a specific period. This enables e-commerce service providers to achieve efficient data management and real-time business intelligence.

[0073] However, simply displaying behavioral tracking data collected on a specific date or for a specific user on a dashboard, as shown in FIG. 4, does not make it easy to grasp information about users or services at a glance. Therefore, it is necessary to analyze desired information based on the behavioral tracking data stored in the first database (101) and visually display the analyzed information (e.g., daily access volume, hourly order volume, search term rankings, etc.). A dashboard including information analyzed based on the behavioral tracking data stored in the first database (101) will be described below with reference to FIGS. 5A and 5B.

[0074] FIGS. 5A and 5B are diagrams illustrating a dashboard according to various embodiments of the present invention.

[0075] First, referring to FIG. 5a, the dashboard (500) may include an area (510) and an area (520).

[0076] In one embodiment, the area (510) may be the area (410) of FIG. 4, and may include an area (511) for selecting a date and an area (512) for selecting identifier information corresponding to a user terminal. The service provider may select a specific date or a specific user through the areas (511) and (512), and if no specific date or user is selected, the data is based on data for all dates or all users.

[0077] Area (520), like area (420) of FIG. 4, may include data based on behavioral tracking data that satisfies a condition selected in area (510) among the behavioral tracking data stored in the first database (101) of the electronic device (100). Meanwhile, unlike area (420), area (520) may display data that satisfies a first condition among the plurality of behavioral tracking data instead of displaying some of the behavioral tracking data extracted from among the plurality of behavioral tracking data stored in the first database (101) of the electronic device (100). In this case, the data that satisfies the first condition may include data that analyzes the characteristics of a service or user among the plurality of behavioral tracking data.

[0078] For example, the dashboard (500) of FIG. 5A is an example of a dashboard that includes information on the conversion rate between pages related to the service for all service users during the period from January 1, 2024 to January 10, 2024. The service provider can change the analysis target period through area (511) and can also set the page conversion rate to be analyzed for some users through area (512). Area (520) can visually display information on the conversion rate between pages provided by the service. The page conversion rate refers to the rate at which users who visit a specific page convert from that page to another page, and is one of the important indicators for understanding and improving user behavior in the service.

[0079] In this regard, the electronic device (100) can extract data satisfying the first condition, including data for a specific period (in this example, from January 1, 2024 to January 10, 2024) and data in which the identification information of the page accessed by the user terminal matches the identification information of a specific page (e.g., page 1), from the behavior tracking data stored in the first database (101). In addition, data regarding pages accessed after the specific page can also be confirmed for the extracted data. In this way, the electronic device (100) can confirm the number of visits per page and the page entry path from the behavior tracking data stored in the first database (101) and display them in the area (520).

[0080] For example, in the example illustrated in FIG. 5a, it can be seen that the number of visits to page 1 during the period from January 1 to January 10, 2024 is 10,000, of which the number of times page 2 was entered after page 1 is 7,000, the number of times page 3 was entered after page 1 is 2,500, and the number of times the service was exited from page 1 is 500. Similarly, it can be seen that the number of times page 2 was entered or exited to page 4 or page 5, and the number of times page 3 was entered or exited to page 6, page 7, or page 8. In this way, the conversion rate between multiple pages provided within the service can also be confirmed from data on the number of visits per page and page entry paths. For example, it can be confirmed that the ratio of users who entered page 1 and then entered page 2, the ratio of users who entered page 2 and then entered page 4, and the ratio of users who entered page 1 and then entered page 4 are 7 / 10, 3 / 7, and 3 / 10, respectively.

[0081] Based on the page conversion rate information within such a service, the service provider can optimize the entry order by determining the depth of one of the multiple pages provided within the service. For example, if event information related to a store is provided through Page 4, and the service provider has established a business goal of exposing information about the event to more than 50% of users who visited Page 1, the service provider can determine that the event exposure rate did not reach the target through the conversion rate information between Page 1 and Page 4, as determined from the information provided in area (520). In this case, the service provider can increase the probability of Page 4 being exposed to users by changing the depth of Page 4 so that users can enter Page 4 directly from Page 1, or modify the event information related to the store to be provided through Page 2 or Page 1. In this way, the service provider can check the relationship and conversion rate between each page within the service at a glance based on the information about the page conversion rate displayed in the area (520) of the dashboard (500), and based on this, can optimize the connection relationship between each page or the depth of the page, thereby improving the user experience and helping to achieve the desired goal.

[0082] Additionally, if the number of visits to a specific page satisfies a preset condition, the electronic device (100) may further include a message related to the number of visits on the displayed dashboard. For example, if the number of visits to Page 1 on a specific date increases or decreases by a certain amount compared to the average daily visits to Page 1, a message indicating that the number of visits to Page 1 has increased or decreased may be displayed on the dashboard. In this way, if information regarding the increase or decrease in visits is displayed on the dashboard, the service provider can establish a business strategy based on this. For example, if the number of visits to pages related to a specific store increases after an event related to that store is set, the service provider can determine that the event has effectively attracted users and, based on this, can set similar events for other stores. For another example, if the number of visits to pages related to a specific store decreases, the service provider can check whether an error has occurred on that page, set an event related to that store to increase customer inflow, and transmit information related to the event to multiple user terminals using the service.

[0083] As another example, the dashboard (500) of FIG. 5b is an example of a dashboard that includes various information related to a service.

[0084] In one embodiment, the area (510) may further include an area (513) for selecting a page and an area (514) for selecting a time zone in addition to an area (511) for selecting a date and an area (512) for selecting identifier information corresponding to a user terminal. As described above, the service provider may analyze the characteristics of the service and the user based only on the behavior tracking data corresponding to a specific date, a specific user, a specific page, and a specific time zone through the areas (511), (512), (513), and (514), and may base it on the behavior tracking data for the entire range if no specific value is selected. Similar to FIG. 5A, the data displayed in the area (520) of FIG. 5B may be the result of extracting data satisfying the first condition from among the behavior tracking data stored in the first database (101). At this time, since the information that can be extracted or analyzed based on the behavioral tracking data may vary depending on the information contained in the behavioral tracking data stored in the first database (101), the data displayed on the dashboard may vary accordingly.

[0085] For example, the behavior tracking data may include information about search terms received from the user terminal. If the behavior tracking data includes information about search terms received from the user terminal, the electronic device (100) may reprocess the behavior tracking data of multiple users to extract data about the number of searches for the search term by time zone. In this regard, the number of searches for the search term itself may be checked, but it is also possible to check the number of searches for the category corresponding to the search term to more easily understand the trends of interests of users using the service by time zone. In this way, the electronic device (100) may reprocess the behavior tracking data of multiple users stored in the first database (101) to extract data about the number of searches by category by time zone, and may store the reprocessed data in the second database (102).

[0086] The electronic device (100) can extract data satisfying the period selected in the area (511) and the time zone selected in the area (514) within the area (510) from the search count data by category according to the time zone stored in the second database (102) and display related information on a dashboard. The data displayed on the dashboard may be the number of searches by category corresponding to the period and time zone selected by the service provider, or may be a ranking of search terms sorted based on the number of searches by category. In addition, information on the increase or decrease in ranking compared to the ranking of the previous period or time zone of the period and time zone selected by the service provider may also be displayed on the dashboard.

[0087] By displaying the number of searches or rankings by category on the dashboard, service providers can easily understand users' needs by period or time zone. They can then use this information to develop business strategies. For example, if the number of searches for a specific category during a specific time period meets a pre-defined condition, a list of stores within that category can be recommended. This improves the user experience by allowing users to easily access desired stores, and can encourage purchases, thereby increasing revenue for the service provider.

[0088] For another example, behavioral tracking data may include information about user input within a page. In this case, the information about user input may include information about actions the user performs within the page, such as clicking buttons (e.g., a login button, a page navigation button, a product purchase button, a refresh button), clicking links (e.g., a hyperlink), filling out forms, mouse movements, and touch actions. The electronic device (100) may reprocess the behavioral tracking data, which includes information about user input, to extract information about user input by a specific user within a specific page.

[0089] Service providers can analyze a user's behavior based on information about the user's input on a specific page, and can quickly detect and respond to problems that arise while the user is using the service. For example, the electronic device (100) can detect that the user has repeatedly clicked the refresh button or another button provided on the page more than a preset number of times based on information about the user's input on a specific page. If the user continues to click the same button, this may indicate a problem, such as the screen not transitioning as expected or the page not loading properly. In such cases, the electronic device (100) can display information about the user and the page on the dashboard, allowing the service provider to quickly determine whether a problem has occurred with the user or the page, and respond accordingly, thereby improving the user experience.

[0090] For another example, behavior tracking data may include information regarding the time a user terminal accesses a page. The electronic device (100) may reprocess the behavior tracking data, which includes information regarding the time a user terminal accesses a page, to extract data regarding the average user stay time for each page. For example, the stay time for a specific page may be determined by calculating the difference between the time the user terminal accesses a specific page and the time it accesses the next page. Furthermore, the average stay time for each page may be determined by checking the stay time for each page against the behavior tracking data stored in the first database (101). Furthermore, the electronic device (100) may display the average stay time for each page on the dashboard. However, displaying the average stay time for each page may not be effective. Therefore, the page and its average stay time information may be displayed only when the average stay time for the page satisfies a preset condition. For example, the preset condition may be set to display the page and its stay time information when the average stay time exceeds a preset time range. Furthermore, the preset time range may vary depending on the characteristics of the page. For example, a page containing a list of items requires time to browse the items, resulting in a relatively long average dwell time. On the other hand, a page where users complete an item selection and then proceed with a purchase requires less time to explore the information on the page, resulting in a relatively short average dwell time. Therefore, determining the time range based on the characteristics of the page can yield more meaningful data.

[0091] Service providers can leverage this information on average time spent on each page to develop business strategies. For example, pages with long dwell times may indicate users are particularly interested in them. Therefore, service providers can optimize the performance of these pages by enhancing their content or improving their marketing strategies. Furthermore, pages with short dwell times may indicate that they lack relevant information or are unsuitable for users. Therefore, service providers can improve the content of these pages to attract users' attention or offer more diverse content to provide users with a wider range of choices. Alternatively, service providers can modify the page structure or enhance the search function to help users easily find the information they want. Furthermore, they can collect direct user feedback to understand and reflect their needs for these pages.

[0092] For another example, behavior tracking data may include information about pages accessed by a user terminal and information about the loading time of the corresponding page. In this case, the electronic device (100) may extract data about the loading time for a specific page for a specific user based on the behavior tracking data. Furthermore, the electronic device (100) may display information about the loading time for a specific page for a specific user on a dashboard. The electronic device (100) may display information about the user and the corresponding page on the dashboard only when the loading time for the specific page for the specific user satisfies a preset condition. In this way, the electronic device (100) may continuously monitor the loading time based on the behavior tracking data, and if the loading time exceeds a preset threshold, it may deem it as an abnormal loading time and record the relevant information.

[0093] When abnormal loading times are detected, service providers can quickly identify which page the user is experiencing loading issues on and which device the user is using based on the user and page information displayed on the dashboard. Furthermore, by identifying the page in question on the dashboard, service providers can access information about other users using that page, and based on this information, determine whether the issue is a user issue or a page issue. By making loading time information available on the dashboard, service providers can quickly identify and address user issues.

[0094] For another example, behavior tracking data may include platform information corresponding to a user terminal. In this case, the electronic device (100) can extract only data corresponding to a specific platform from the platform information corresponding to the user terminal based on the behavior tracking data, and can identify information related to services and users based on the extracted data. Furthermore, the electronic device (100) can display a dashboard in which identified service and user-related information is categorized and displayed by platform. Furthermore, if an error is identified in a specific platform based on analysis results based on the data categorized by platform, platform information and error information can be displayed on the dashboard. By categorizing and displaying service and user-related information by platform, the characteristics and trends of the corresponding platform can be easily analyzed, and areas requiring service improvement can be quickly identified. This can enhance the user experience or improve service quality by quickly resolving issues occurring on a specific platform.

[0095] As described above, dashboards containing visually presented information are intuitively understandable to both users and service providers, enabling them to monitor business trends in real time and aid in making critical decisions. Furthermore, dashboard functionality enhances the usability of log data stored in databases, helping e-commerce service providers deliver better services and improve business performance.

[0096] FIG. 6 is a drawing schematically illustrating each component of an electronic device according to one embodiment of the present invention.

[0097] Referring to FIG. 6, the electronic device (600) may include a transceiver (610), a processor (620), and a memory (630). Only components related to the present embodiments are illustrated in the electronic device (600) illustrated in FIG. 6. Therefore, it will be apparent to those skilled in the art that the electronic device (600) may further include general components other than the components illustrated in FIG. 6. Since the electronic device (600) of FIG. 6 may be included in the electronic device (100) of FIGS. 1 and 2, descriptions of overlapping content with FIGS. 1 to 5B will be omitted.

[0098] The transceiver (610) can communicate with other devices. Accordingly, the electronic device (600) can transmit and receive information with other devices via the transceiver. For example, the electronic device (600) can communicate with a user terminal (110) or other devices via the transceiver.

[0099] Here, communication, i.e., transmission and reception of data, can be performed wired or wirelessly. To this end, the transceiver (610) may include a wired communication module that connects to the Internet, etc., via a LAN (Local Area Network), a mobile communication module that connects to a mobile communication network via a mobile communication base station to transmit and receive data, a short-range communication module that uses a WLAN (Wireless Local Area Network) series communication method such as Wi-Fi or a WPAN (Wireless Personal Area Network) series communication method such as Bluetooth or Zigbee, a satellite communication module that uses a GNSS (Global Navigation Satellite System) such as a GPS (Global Positioning System), or a combination thereof.

[0100] The processor (620) controls the overall operation of the electronic device (600). To this end, the processor (620) may perform calculations and processing of various types of information. For example, the processor (620) may perform various calculations and processing based on log data received from the user terminal (110) via the transceiver (610).

[0101] The processor (620) may be implemented as a computer or similar device based on hardware, software, or a combination thereof. In terms of hardware, the processor (620) may be implemented in the form of an electronic circuit that processes electrical signals to perform a control function, and in terms of software, the processor (620) may be implemented in the form of a program that drives the hardware processor (620). Meanwhile, unless otherwise specified in the above description, the operation of the electronic device may be interpreted as being performed under the control of the processor (620). That is, when modules implemented in the system for analyzing the above-described data are executed, the modules may be interpreted as controlling the processor (620) to perform the above-described operations of the electronic device. For example, the processor (620) may obtain multiple log data related to the use of e-commerce services from multiple user terminals through the transceiver (610), and may generate behavioral tracking data related to the use of e-commerce services for each user based on the obtained multiple log data. Additionally, the processor (620) can extract data satisfying a first condition from the behavior tracking data of multiple users and display a dashboard including the extracted data through a display included in the electronic device (600) or a separate display connected to the electronic device (600).

[0102] The memory (630) can store various types of information. The memory (630) can store data temporarily or semi-permanently. For example, the memory (630) of the electronic device (600) can store an operating system (OS) for operating the electronic device (600), data for hosting a website, a program for generating Braille, or data related to an application (e.g., a web application). Furthermore, the memory (630) can store modules in the form of computer code, as described above.

[0103] Examples of memory (630) may include a hard disk drive (HDD), a solid state drive (SSD), flash memory, read-only memory (ROM), random access memory (RAM), etc. This memory (630) may be provided as a built-in type or a detachable type.

[0104] In summary, the various embodiments may be implemented through various means. For example, the various embodiments may be implemented through hardware, firmware, software, or a combination thereof.

[0105] In the case of hardware implementation, the methods according to various embodiments may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, etc.

[0106] When implemented via firmware or software, the methods according to various embodiments may be implemented in the form of modules, procedures, or functions that perform the functions or operations described above. For example, software code may be stored in memory and executed by a processor. The memory may be located within or outside the processor and may exchange data with the processor via various known means.

[0107] The electronic device according to the above-described embodiments may include a processor, a memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, a user interface device such as a touch panel, a key, an icon, etc. The methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable codes or program instructions executable on the processor. Here, the computer-readable recording medium includes a magnetic storage medium (e.g., read-only memory (ROM), random-access memory (RAM), floppy disk, hard disk, etc.) and an optical reading medium (e.g., CD-ROM, DVD: Digital Versatile Disc)). The computer-readable recording medium may be distributed to computer systems connected to a network, so that the computer-readable code may be stored and executed in a distributed manner. The medium may be readable by a computer, stored in a memory, and executed by a processor.

[0108] The present embodiment may be represented by functional block configurations and various processing steps. These functional blocks may be implemented by various hardware and / or software configurations that perform specific functions. For example, the embodiment may employ direct circuit configurations such as memory, processing, logic, look-up tables, etc., which may perform various functions under the control of one or more microprocessors or other control devices. Similarly, the present embodiment may be implemented in a programming or scripting language such as C, C++, Java, assembler, etc., including various algorithms implemented as a combination of data structures, processes, routines, or other programming configurations. Functional aspects may be implemented as algorithms that execute on one or more processors. Furthermore, the present embodiment may employ conventional techniques for electronic configuration, signal processing, and / or data processing. Terms like "mechanism," "element," "means," and "composition" can be used broadly and are not limited to mechanical or physical components. These terms can also encompass a series of software routines, such as those associated with a processor.

[0109] The above-described embodiments are merely examples, and other embodiments may be implemented within the scope of the claims set forth below.

Claims

1. In a method of analyzing data in an electronic device, A step of obtaining multiple log data related to the use of an e-commerce service from multiple user terminals; A step of generating behavioral tracking data related to the use of the e-commerce service for each user based on the plurality of log data; A step of extracting data satisfying a first condition from behavior tracking data of multiple users; and A step of displaying a dashboard including the extracted data. A data analysis method including:

2. In paragraph 1, A data analysis method, wherein the above behavior tracking data includes at least one of information related to access to at least one page and information related to user input on at least one page.

3. In paragraph 1, A data analysis method, wherein the first condition includes at least one of a condition regarding a date or a condition regarding identifier information of a user terminal.

4. In paragraph 1, The above behavior tracking data includes information about the page accessed by the user terminal, The above extraction step is, A data analysis method comprising a step of extracting data on the number of visits corresponding to a first date and a first page based on the behavior tracking data of the plurality of users.

5. In paragraph 4, A data analysis method, wherein if the above visit volume satisfies a preset condition, the dashboard further includes a message related to the visit volume.

6. In paragraph 5, If the first page above is a page related to the store, A step of generating an event related to the above store; and A step of transmitting information related to the event to the plurality of user terminals A data analysis method further comprising:

7. In paragraph 1, The above behavior tracking data includes information about the page accessed by the user terminal, The above extraction step is, A step of extracting data on the conversion rate between multiple pages related to the e-commerce service based on the behavior tracking data of the multiple users; and A step of determining the depth of at least one page among the plurality of pages within the service based on the conversion ratio. A data analysis method further comprising:

8. In paragraph 1, The above behavior tracking data includes information about search terms received from the user terminal, The above extraction step is, A step of extracting data on the number of searches related to the first category by time zone based on the behavior tracking data of the plurality of users, A step of transmitting recommended store information related to the first category to the plurality of user terminals in the first time period when the number of searches related to the first category in the first time period satisfies a preset condition. A data analysis method further comprising:

9. In paragraph 1, The above behavior tracking data includes information about user input within the page of the user terminal, The above extraction step is, A step of extracting data regarding user input within a second page of a first user terminal based on the behavior tracking data of the plurality of users, The above displaying step is, When information about user input in the second page of the first user terminal satisfies a preset condition, a step of displaying a message including identifier information of the first user terminal and information about the second page on the dashboard A data analysis method including:

10. In paragraph 1, The above behavior tracking data further includes information about the time the user terminal accessed the page, The above extraction step is, A step of extracting data on the average stay time corresponding to the third page based on the behavior tracking data of the plurality of users, The above displaying step is, A step of displaying information about the third page and information about the average stay time on the dashboard when the average stay time corresponding to the third page satisfies a preset condition. A data analysis method including:

11. In paragraph 1, The above behavior tracking data includes platform information corresponding to the user terminal, A data analysis method, wherein the step of displaying a dashboard including the extracted data includes the step of displaying the extracted data by classifying it based on the platform information.

12. In paragraph 1, The above behavior tracking data includes information about the page accessed by the user terminal and information about the loading time of the page accessed by the user terminal. The above extraction step is, A step of extracting data regarding the loading time of a fourth page corresponding to a second user terminal based on the behavior tracking data of the plurality of users, The above displaying step is, If the loading time of the fourth page satisfies a preset condition, a step of displaying identifier information of the second user terminal and information about the fourth page on the dashboard. A data analysis method further comprising:

13. A non-transitory computer-readable storage medium recording a program for executing the method of paragraph 1 on a computer.

14. As an electronic device for data analysis, A transceiver for transmitting and receiving information with multiple user terminals; and An electronic device comprising a processor that obtains a plurality of log data related to the use of an e-commerce service from the plurality of user terminals, generates behavioral tracking data related to the use of the e-commerce service for each user based on the plurality of log data, extracts data satisfying a first condition from the behavioral tracking data of the plurality of users, and displays a dashboard including the extracted data.

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