KR20140111225A - Electronic commerce recommendation and analysis sysmem, and recommendation and analysis sysmem method - Google Patents

Abstract

Disclosed in the present invention is a product recommendation and analysis system for electronic commerce. The system includes: an electronic commerce service device which collects data from an electronic commerce client device, delivers analysis basis data which is the basis for product analysis to a recommendation and analysis device, provides recommendation product data for the client device through a web browser based on the data received from the recommendation and analysis device, and provides an operation tool interface to support operation of an electronic commerce service and analysis result data received from the recommendation and analysis device for an electronic commerce operation device through a web browser; and a recommendation and analysis device which receives the analysis basis data from the electronic commerce service device, analyzes the received data and/or performs product analysis upon a recommendation request, generates the analysis result data and the recommendation product data according to the product analysis result, and transmits the data to the electronic commerce service device. The analysis result data includes real-time analysis result data which is provided and updated in real time through the operation tool interface and result report data which aggregates at least one non-real-time analysis results and thus is provided not in real time. The real-time analysis result data and result report data are generated and communicated in dual ways in the electronic commerce service device as well as in the recommendation and analysis device.

Description

ELECTRONIC COMMERCE RECOMMENDATION AND ANALYSIS SYSMEM, AND RECOMMENDATION AND ANALYSIS SYSMEM METHOD,

The present invention relates to an electronic commerce system, and more particularly, to a system for analyzing a recommended commodity in real time in electronic commerce, a method of providing commodity recommendation, operating tools, and real-time analysis and result report through analyzed data .

In general, e-commerce website sales analysis methods were performed in such a way as to provide statistics on visitors to the site. The method comprising the steps of analyzing a page of a specific web site and a page of the address of the web site to determine whether the web site and the page have been called through the user's web browser and moved to another page, If the web browser also provides additional sales analysis methods, it may include the manner in which the entire user viewed and purchased the product. The analysis method of e-commerce site sales does not include more than the web-site analysis of the website, and practically does not analyze the purchase of the commodity inquiry and does not provide the related tool. The operator who operates the e-commerce website can not consider efficient product placement for sale on the e-commerce website, and has to perform arbitrary product placement through anticipation, and the additional cost to retrieve it, for example, I was forced to pay for the event. In addition, due to inappropriate product placement of e-commerce website operators, we were forced to take an adverse effect such as a decrease in sales. In addition, the e-commerce website customer sees an arbitrary product placement placed by the e-commerce website operator, thereby causing the e-commerce website to have a negative image, or the product that the customer needs in the main page of the website and on the main page There is a problem that it can not be arranged properly, resulting in a decrease in sales.

An object of the present invention to solve the above-mentioned problems is to provide a system for collecting and analyzing a history of goods on the basis of a product when a customer inquires or purchases goods on an electronic commerce website, By providing real-time analysis result report, operators can appropriately recommend, arrange and utilize necessary goods to customers in e-commerce website, contributing to increase sales through sales increase and appropriately placing e-commerce website client And to provide a recommendation analysis system and a recommendation analysis method in an electronic commerce that induce the purchase of goods.

Another object of the present invention is to provide a recommendation product to an electronic commerce customer through an electronic commerce service, to collect the products searched or searched by an electronic commerce customer in the electronic commerce system and to provide the product to the recommendation analysis system, And provide the operational analysis tool to the e - commerce operator in real - time analysis and report form and the operation tool to manage the commodity of e - commerce.

According to another aspect of the present invention, there is provided a system for analyzing and recommending goods through electronic commerce, the system comprising: a data collecting unit for collecting data of an electronic commerce client apparatus and transmitting analysis basis data based on a product analysis to a recommendation analyzing apparatus; Providing a recommended product information to the client device through a web browser based on the information received from the recommendation analyzing device; providing an operation tool interface for supporting the operation of the e-commerce service and analyzing result data received from the recommendation analyzing device, And an analysis unit for analyzing the product based on the analysis result and / or the recommendation request, receiving the analysis basic data and the analysis basic data from the electronic commerce service apparatus through the web browser, And the recommendation phase And transmits the generated analysis result data to the electronic commerce service apparatus, wherein the analysis result data includes at least one non-real-time analysis result and real-time analysis result data provided to be reflected in real time through the operating tool interface The real-time analysis result data and the result report data may be generated and transmitted / received by the electronic commerce service apparatus and the recommendation analyzing apparatus.

Wherein the recommendation analyzing apparatus comprises: an analysis and collection module for receiving analysis basis data received from the electronic commerce service apparatus and storing the analysis basis data in a database; analyzing data stored in the database and data received additionally requested by the electronic commerce service apparatus, A data analysis module for generating product information and storing the analysis result in the database; a real-time analysis unit for analyzing the analysis basic data received from the analysis collection module to generate real-time analysis result data, A real-time analysis module for real-time transmission to an electronic commerce service device, a result analyzing module for analyzing the result report data stored in the database or analyzing the result report data by a specific web site or a web page And may generate a report comprising a report module and the analysis module collection, the data analysis module, said analysis module in real time and a database that stores the data of the report module for storage in said database.

Wherein the real-time analysis result data includes information that can be easily converted into a format that can be transmitted in real-time, and includes information on orders for a predetermined period of time, page views for a predetermined period, Information on the expected order amount up to a predetermined period of time in the future, and expected order amount information calculated based on the corresponding price and the expected order number information.

Wherein the data analysis module provides a recommended product based on a product and a recommended product based on a customer based on the similarity between the products and the purchase history of the plurality of customers, A recommendation based on a personalized shopping cart of a specific customer, a wish list, a recently inquired product, and purchase product information.

The data analysis module analyzes i) order and product inquiry of the analysis requested goods, ii) analysis of an order signal and an inquiry signal of an inquiry signal for a requested product within a predetermined period, and iii) Real-time analysis result data is generated by performing at least one of purchase intention analysis based on purchase records made within a predetermined period of time, and the non-real-time analysis result data can be used as reference data in creating the result report data.

The iii) purchase propensity analysis may include an analysis of purchase intentions by region, sex, age, payment means, time period, and day of the week within a predetermined period.

The result report data includes an analysis of relative ratios of 1) all clicks, recommendation clicks, and order clicks of the client apparatus included in a predetermined period, and 2) analysis of ratio of actual orders to shopping items, Content.

Wherein the operating tool interface includes a first mode for automatically setting a priority for the current product arrangement in the electronic commerce service based on the real-time analysis result data, and a second mode for manually changing the current product arrangement through an external input 2 mode, and can support the manual change of the second mode by totally providing the result report data, the at least one non-real-time analysis result data and the real-time analysis result data, .

The operating tool interface may provide menus for total product analysis, page unit product analysis, product arrangement management, and product information management for manual change of the second mode.

Wherein the electronic commerce service apparatus further comprises: a product recommendation module that transmits a recommendation request for product recommendation from the client to the recommendation analyzing apparatus and provides recommended product information received from the recommendation analyzing apparatus to the client apparatus; A data collection module for collecting data necessary for analysis and providing the collected data to the recommendation analyzing apparatus, an operation tool interface providing module for providing the operating tool interface to the electronic commerce operating apparatus, a real-time analyzing request received from the electronic commerce operating apparatus, A real-time commodity analysis response module that transmits real-time analysis result data received from the recommendation analyzer to the recommendation analyzer and provides the real-time analysis result data to the ecommerce operating device in real time; A result report providing module for sending a request report to the recommendation analyzing device and providing the result report data received from the recommendation analyzing device to the electronic commerce operating device, and a product recommendation module, the data gathering module, A service device database for storing main data or temporary data of the real-time goods analysis response module and the result report providing module.

The data collection module collects data necessary for analysis and transmits the collected data to the recommendation analyzing device. The data required for the analysis includes information on the category of the product, inquiry information, shopping cart information, wish list registration information, Day, day, information per payment means, region, gender, inflow path, and current page information.

The electronic commerce service apparatus may transmit the data stored in the service apparatus database corresponding to the request in response to the request of the recommendation analyzing apparatus.

The electronic commerce operating apparatus may provide the information provided by each module of the electronic commerce service apparatus through either JavaScript or Chrome Web browser extension so as to provide the information on the same screen as the client apparatus.

According to another aspect of the present invention, there is provided a method for analyzing and recommending goods through an electronic commerce of the present invention, comprising: collecting data of an electronic commerce client apparatus in an electronic commerce service apparatus, The recommendation analyzing apparatus receiving the analysis basis data from the electronic commerce service apparatus and analyzing the product for the analysis and / or recommendation-requested commodity, Analyzing result data and recommendation product information, storing the resultant data in a database and transmitting the data to the electronic commerce service apparatus, and transmitting the recommended product information to the client apparatus based on the information received from the recommendation analyzing apparatus Provided through a browser, And providing the analysis result data received from the recommendation analyzing apparatus to the electronic commerce operating apparatus through a web browser, wherein the analysis result data is reflected in real time through the operating tool interface Real-time analysis result data and at least one non-real-time analysis result, and wherein the real-time analysis result data and the result report data are provided to the electronic commerce service apparatus and the recommendation analyzing apparatus And can be generated and transmitted / received.

Wherein the operating tool interface includes a first mode for automatically setting a priority for the current product arrangement in the electronic commerce service based on the real-time analysis result data, and a second mode for manually changing the current product arrangement through an external input 2 mode, and can support manual change of the second mode by providing the result report data, the at least one non-real-time analysis result data and the real-time analysis result data, .

Wherein the recommendation analyzing apparatus is provided with recommendation commodity-based recommendation commodity and customer recommendation commodity as the commodity recommendation information, wherein the recommendation commodity-based recommendation commodity is recommended on the basis of similarity between commodities and purchase details of a plurality of customers, Recommendations based on customers can be recommended based on personalized shopping carts, wish lists, recently viewed items, and purchased product information of a specific customer.

The real-time analysis result data includes information that can be easily converted into a format that can be transmitted in real time, and includes information on the number of orders up to a predetermined period, page view information , Expected order quantity information up to a predetermined period of time in the future, and expected order quantity information calculated based on the price and the expected order quantity information.

The recommendation analyzing device analyzes i) order and product inquiry of the analysis requested goods, ii) analysis of an order signal and an inquiry signal of an inquiry signal for the requested analysis item within a predetermined period, and iii) Real-time analysis result data by performing at least one of purchase intention analysis based on purchase records made within a predetermined period, and generating the result report data based on the non-real-time analysis result data.

According to the recommendation analysis system and the recommendation analysis method in the electronic commerce of the present invention, the e-commerce website customer can provide appropriate commodities and encourage them to purchase the commodities. In order to expect increase in sales through increase of commodities, Real - time commodity inquiry purchase analysis system, tool using this system, and method of providing real - time analysis result report are provided to efficiently operate electronic commerce.

In addition, by providing the analyzed product recommendation to the e-commerce customer, the sales through the e-commerce system is increased, and the e-commerce manager analyzes it in real time and provides it to the customer immediately so as to operate the e-commerce system efficiently, The result of analyzing the actual result of the product is provided to the e-commerce operator in a real-time screen, and it is provided as a result report so that the product recommendation management can lead to an increase in sales.

1 is a block diagram schematically showing a configuration of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention;
FIG. 2 is a detailed block diagram specifically illustrating a configuration of an electronic commerce service apparatus and a recommendation analyzing apparatus of a recommendation analyzing system in an electronic commerce according to an embodiment of the present invention.
3 is a detailed block diagram specifically illustrating the configuration of an operation tool module of an electronic commerce operation apparatus of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.
4 is a view showing a display screen of a real-time analysis result of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention,
FIG. 5 is a flowchart illustrating a process of processing real-time analysis data by an operation tool module of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention;
FIG. 6 is a diagram showing a display screen of an order and product view trend analysis of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention;
FIG. 7 is a view showing an analysis display screen for each route of the recommendation analysis system in an electronic commerce according to an embodiment of the present invention; FIG.
FIG. 8 is a view showing a purchase tendency analysis display screen of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention;
9 is a view showing a result report display screen of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention,
10 is a conceptual diagram showing a format of analysis basic data in a recommendation analysis system in an electronic commerce according to an embodiment of the present invention;
11 is a view showing a display screen in an operational tool interface of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail.

It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the relevant art and are to be interpreted in an ideal or overly formal sense unless explicitly defined in the present application Do not.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In order to facilitate the understanding of the present invention, the same reference numerals are used for the same constituent elements in the drawings and redundant explanations for the same constituent elements are omitted.

1 is a block diagram schematically illustrating a configuration of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention. 1, a recommendation analysis system in an electronic commerce according to an embodiment of the present invention includes a client device 110, an electronic commerce service apparatus 120, a recommendation analysis apparatus 130, and an electronic commerce operation apparatus 140).

Referring to FIG. 1, a client device 110 is a customer of an electronic commerce service (for example, an Internet shopping mall) provided by the electronic commerce service apparatus 120, Lt; / RTI > The client device 110 is connected to the electronic commerce service apparatus 120 through a communication network and can transmit and receive a plurality of messages to and from the electronic commerce service apparatus 120 from the time of connection to the end of the connection, And may be recorded in the electronic commerce service apparatus 120. Here, the analysis basic data may include a plurality of pieces of information necessary for analyzing a product such as a product order, a product inquiry, a payment means, customer gender information, time information on access route information, page information and the like. May be sent directly to the recommendation analyzer 130, depending on the analysis underlying data case of the client device 110. [ The client device 110 may request product inquiry and analysis from the electronic commerce service apparatus 120. In response to the product inquiry and analysis request, the electronic commerce service apparatus 120 relays the analysis request to the recommendation analyzer 130. The recommendation analyzer 130 analyzes the result including the real-time analysis result data and the result report data Data can be transmitted to the electronic commerce service apparatus 120 and the electronic commerce service apparatus 120 can transmit the recommendation commodity information to the client apparatus 110. [

The electronic commerce service apparatus 120 may receive a product inquiry and analysis request from the client device 110. [ In addition, the electronic commerce service apparatus 120 may receive a real-time or non-real-time analysis request from the electronic commerce operating apparatus 140. Upon receiving the requests, the electronic commerce service apparatus 110 may send the requests to the recommendation analyzer 130. In addition, the e-commerce service apparatus 120 may send analysis request data as well as analysis basis data from the client apparatus 110 to the recommendation analysis apparatus 130. [ The electronic commerce service apparatus 120 can transmit data necessary for analysis in addition to analysis basis data to the recommendation analyzing apparatus 130. [ At this time, the recommendation analyzer 130 may request the recommendation analyzer 130 to select necessary data. The electronic commerce service apparatus 120 selects real-time analysis result data (for example, data that can be aggregated in real time such as order number information and number-of-views information) among the information received from the recommendation analyzing apparatus 130, (140). The real-time analysis result data may be data transmitted in real time to the electronic commerce operating device 140 and used by an operator to manage the operation of the Internet shopping mall such as product arrangement in real time. In addition, the electronic commerce service apparatus 120 may select data transmitted in non-real-time, such as result report data, and transmit the non-real-time data to the electronic commerce operating apparatus 140 in non-real time.

Recommendation analyzer 130 may receive a request from electronic commerce 120 to perform real-time or non-real-time analysis. In addition, the analysis basis data and the analysis result data can be recorded and stored in the own big data database. The cumulative stored data allows the analysis after the initial analysis to be performed more efficiently based on the originally analyzed data. The recommendation analyzer 130 can generate recommended product information through analysis. In addition, the recommendation analyzer 130 can generate real-time analysis result data for a specific product through real-time analysis, and the real-time analysis result data is transmitted to the electronic commerce operation apparatus 140 as well as the electronic commerce service apparatus 120 It is transmitted and used in real time. In addition, the recommendation analyzer 130 can generate non-real-time data in the form of a result report by synthesizing a plurality of analysis data, and the result report data is transmitted to the electronic commerce operation apparatus 140 via the electronic commerce service apparatus 120 . In some cases, real-time analysis data and result report data may be provided directly to the client device 110 via operator settings or settings on the electronic commerce service device 120. According to another embodiment of the present invention, one or more of the real-time analysis data and the result report can be transmitted directly to the electronic commerce operating apparatus 140 without going through the electronic commerce service apparatus 120.

The electronic commerce operation apparatus 140 is an apparatus controlled by an operator of an electronic commerce service (for example, an Internet shopping mall), and can perform control for the overall operation of the electronic commerce service. The electronic commerce operating apparatus 140 may operate through an operating tool interface provided by the electronic commerce service apparatus 120. [ The operational tool interface can receive the real-time analysis data and the result report described above and display it to the operator for viewing, and can help the operator to operate the e-commerce service more smoothly through several operating tools. The electronic commerce operation apparatus 140 can control the electronic commerce service through an operation tool module (not shown). The e-commerce operation apparatus 140 can automatically rearrange the e-commerce service items (according to a pre-stored manner), register the commodities, etc. based on the received real-time analysis data and the result report, , Design editing, and so on. The electronic commerce operation apparatus 140 transmits a control signal to the electronic commerce service apparatus 120 for service operation such as product rearrangement, registration and design editing.

FIG. 2 is a detailed block diagram specifically illustrating a configuration of an electronic commerce service apparatus and a recommendation analyzing apparatus of a recommendation analyzing system in an electronic commerce according to an embodiment of the present invention.

2, the electronic commerce service apparatus 120 includes a product recommendation module 121, a data collection module 122, a real-time product analysis response module 123, an operation tool interface provision module 124, A service device database 125 and a service device database 126. Also, although not shown in the drawings, each of the modules can communicate with the client device 110, the recommendation analyzing device 130, and the electronic commerce operating device 140 via a communication network using a communication module (not shown) have.

The product recommendation module 121 receives a product recommendation request from the client device 110. [ The product recommendation request may include product category information (e.g., may be a product query word). That is, if a recommendation request for product category information is input through a web browser of the shopping mall, the recommendation analyzing unit 130 converts the recommendation request signal for a product corresponding to the category based on the input, 132). In addition, the product recommendation module 121 can provide recommended product information received from the recommendation analyzer 130 to the client device 110 via the web browser in response to the product recommendation request. At this time, the recommended product information may include at least one of a recommended product based on the product and a recommended product based on the customer. The recommendation items based on the product are selected based on the similarity between the products and the purchases of various customers. The recommendation items based on the customers are personalized recommendations for specific customers such as shopping carts, wish lists, recent inquiry / Means a product. That is, the client device 110 can receive at least one of recommended product information meeting two criteria according to the customer's selection. In some cases, the product recommendation module 121 may request the big data database 135 of the recommendation analyzer 130 to receive recommended product information.

The data collection module 122 may collect various data from the client device 110. [ The data collection module 122 collects all the basic data necessary for analysis such as product inquiry, purchase of goods, product search, specific category search, shopping cart act, and inclusion in the wish list transmitted by the client device 110. For example, the analysis basic data may include at least one of a product category inquiry, a product inquiry, a shopping cart addition, a wish list registration, a product purchase (by hour / day / day / payment means), a customer's area, sex, age, Or more. The collected analysis base data is transmitted to the data analysis module 132 of the recommendation analyzer 130.

The real-time commodity analysis response module 123 receives the real-time analysis request for the specific commodity or the specific commodity group from the operation tool module of the electronic commerce operation device 140 and transmits the real- And can request real-time analysis data as needed. Then, the real-time analysis result data received from the real-time analysis module 133 of the recommendation analyzer 130 can be transmitted to the operation tool module. At this time, an optimized interface and function can be provided through the operation tool module. The real-time commodity analysis response module 123 may preferably operate in a network environment that can be transmitted in real time. In addition, when the traffic is crowded, if the packet loss rate is high or the available bandwidth is small, the real-time commodity analysis response module 123 can be set to operate preferentially than other components in the electronic commerce service apparatus 120. In addition, the real-time merchandise analysis response module 123 converts the format into a format suitable for real-time communication so as to enable real-time communication in the communication with the electronic commerce operating apparatus 140 and the recommendation analyzing apparatus 130. At this time, if a large amount of information is included, a delay may occur. Therefore, only the number of inquiry information, the number of orders (number of purchases), and simple related information can be achieved through real-time communication.

The operating tool interface providing module 124 provides an operating tool interface to the electronic commerce operating device 140. The operational tool interface can be designed to perform one or more of the following functions: overall product analysis, page-based product analysis, product arrangement management, and product information management. That is, the real-time analysis result data and the result report can be visualized and provided through the operating tool interface, and management of product arrangement management and the like can be facilitated.

The result report providing module 125 receives the result report request from the operation tool module and transmits the result report request to the report module 134 of the recommendation analyzing apparatus 130. In addition, it receives the result report data corresponding to the request from the recommendation analyzer 130, and transmits the result report data to the operation tool module.

The service device database 126 stores the main data of the product recommendation module 121, the data collection module 122, the real-time product analysis response module 123, the operation tool interface provision module 124, Temporary data can be stored. The product recommendation module 121, the data collection module 122, the real-time commodity analysis response module 123 and the result report provision module 125 may store the data to be requested to the recommendation analysis apparatus 120 in the database 126 Can be obtained from the data.

The recommendation analyzer 130 may include an analysis acquisition module 131, a data analysis module 132, a real time analysis module 133, a report module 134 and a big data database 135. Although not shown in the figure, each module of the recommendation analyzer 130 may communicate with the client device 110, the electronic commerce service apparatus 120, and the electronic commerce operation apparatus (not shown) via a communication network 140). ≪ / RTI >

The analysis acquisition module 131 receives the analysis basis data collected from the data analysis module 121 of the electronic commerce service apparatus 120. The analysis acquisition module 131 may receive data directly from the client device 110 as the case may be. The analysis acquisition module 131 can easily categorize the information for analysis. That is, data can be collected and categorized so that it can be directly used for analysis of specific products, specific product categories, customer areas, time zones, etc., and the collected data can be stored in the big data database 135 .

The data analysis module 132 substantially acquires data from the analysis collection module 131 or the big data database 135, analyzes the requested product or product category, and generates recommended product information. The analysis request may be received through the product recommendation module 121 or the operation tool interface providing module 124. The data analysis module 132 first inquires whether there is existing analysis data in relation to the goods or the category of goods requested to be analyzed in the big data database 135. If there is existing analysis data in the big data database 135, can do. If additional data is needed than the currently secured data, for example, only data from the present time to 2005 are present. If information up to 2003 is required, the data analysis module 132 adds the data to the service device database 126 Data can be requested and delivered for analysis. As described above, the data analysis module 132 can recommend a product-based recommendation product and a customer-based recommendation product. The recommendation commodity-based recommendation commodity is recommended on the basis of the number of orders and the number of inquiries, such as the commodity most sought by a plurality of purchasers, but a plurality of commodities can be recommended in consideration of the similarity of the commodities. The recommendation product based on the customer is related to the past behavior and the set of the presently configured product through the purchase behavior pattern of the customer up to the present (for example, a product inquiry, a product category inquiry, a product purchase, a shopping cart addition, And a method of recommending the product having the highest relevance can be used. The generated recommended product information may be transmitted to the product recommendation module 121 and / or the service device database 126. In addition, the data analysis module 132 may be configured to analyze the order and the product inquiry (see FIG. 6) for the requested product, ii) the order signal and the inquiry signal Real-time analysis result data can be generated by performing at least one of an access path analysis (see FIG. 7) of the purchase history analysis (see FIG. 7) and a purchasing propensity analysis (see FIG. At this time, the purchase propensity analysis may include an analysis of the purchase tendency by region, gender, age, payment means, time period, and day of the week within a predetermined period. The non-real-time analysis result data thus generated can be used as a reference data when creating the result report data.

It can also be stored in the big data database 135 itself. As a result, the big data database 135 can acquire a larger amount of analysis result data as the analysis is repeated, and more easily analyze the customer or the product in the future.

The real-time analysis module 133 receives a real-time analysis request from the real-time goods analysis response module 123 of the electronic commerce service apparatus 120 and performs real-time analysis. The real-time analysis module 133 analyzes real-time based on the data received from the analysis collection module 121 to generate real-time analysis result data, and transmits the real-time analysis result data to the real-time product analysis response module 123. The real-time analysis result data may include at least one of an order number information, a page view number information, an expected order number information, and an expected order amount information for a specific product (which may be plural). Here, the order number information represents the number of order signals for the product within a predetermined period, the page view number information represents the number of pages of the corresponding product page up to the predetermined period, And the expected order amount represents an amount of money obtained by calculating the expected product number and the expected number of orders. The real-time analysis information is not only relatively simple information that can be directly checked in real time, but also a real-time analysis and real-time transmission / reception because it is calculated with a small calculation amount. Also, the real-time analysis module 133 may convert the real-time analysis result data into a format that can be transmitted in real time, and may transmit the real-time analysis result data to the real-

The report module 134 generates the result report data requested from the result report providing module 125 and transmits the result report data to the result report providing module 125. The report module 134, like the data analysis module 132, queries the first big data database 135 in response to the request to see if there is a result report stored therein. The report module 134 generates a result report based on the analysis result data in the data analysis module 132 and outputs the generated report to the big data database 135 before being sent to the result report provision module 125. [ Lt; / RTI > The results report includes a ratio analysis of each click through the total number of clicks (sum of referrals + order clicks), recommendation clicks, and order clicks, and the ratio of the actual number of orders to the shopping cart, And the like. The resulting report can be done on a specific web site or web page basis.

The big data database 135 stores data recorded by the analysis acquisition module 131, the data analysis module 132, the real time analysis module 133 and the report module 134, records the analyzed data and the result report data can do.

3 is a detailed block diagram illustrating a configuration of an operation tool module of an electronic commerce operation apparatus of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention. 3, an operation tool module 300 according to an exemplary embodiment of the present invention includes a receiving unit 310, a transmitting unit 320, a control unit 330, a user interface 340, a display unit 350, . ≪ / RTI >

Referring to FIG. 3, the receiving unit 310 may receive data from the electronic commerce service apparatus 120 and the recommendation analyzing apparatus 130. The transmission unit 320 may transmit an analysis request or a control request for the electronic commerce service to the electronic commerce service apparatus 120.

The control unit 330 may generate control signals for transmission and reception of signals and general electronic commerce services. The control unit 330 may include a mode setting unit 332. The mode setting unit 332 may set an automatic change mode for automatically changing the product arrangement of the electronic commerce service (for example, an Internet shopping mall) based on the received real-time analysis result data, And a manual change mode in which the manual change mode is manually changed to the manual change mode. When the automatic change mode is selected, the priority of the product arrangement in the e-commerce service is automatically changed based on the real-time analysis result data. An example of real-time analysis result data will be described in detail with reference to FIG. The operation of the control unit 330 will be described in detail with reference to FIG.

The user interface 340 is an interface for receiving external input. The operator can manually control the settings of the operating device and the various operations of the electronic commerce service through the user interface 340. [

The display unit 350 may display an operating tool interface through a web browser. The display unit 350 displays the result report data as well as real-time analysis result data and non-real-time analysis result data (e.g., a trend analysis result, an access path analysis and a purchase propensity analysis result) Management can be facilitated.

4 is a view showing a real-time analysis display screen of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

Referring to FIG. 4, the real-time analysis result data 410-1, 410-2, 410-3, 410-4, 410-5, and 410-6 may appear as shown in FIG. 4 through an operation tool interface. A plurality of items can be arranged according to the priority order. The real-time analysis result data 410-1, 410-2, 410-3, 410-4, 410-5, and 410-6 may be displayed in any one of a plurality of products (in FIG. 4, ). As described above, the real-time analysis result data 410-1, 410-2, 410-3, 410-4, 410-5, and 410-6 includes the number of orders (o) The expected order quantity OpV, and the expected order quantity EspV information. If the mode setting unit 332 of the operation tool module selects the automatic change mode, it is possible to set the product arrangement to be prioritized in order of the number of orders relatively based on the number of orders (o) information. At this time, other information such as the number of page views (v: view), the number of expected orders (OpV), and the expected order amount (EspV) information are used as references and the priority can be determined in addition to the order number information o. In the case of the manual change mode, the controller 330 displays such analysis information to the operator but does not directly perform the change itself. At this time, if the operator wants to request another level analysis other than the real-time analysis request, the real-time analysis result data 410-6 can be selected and clicked. At this time, the operation tool interface can provide a menu for the trend analysis 420, a menu for the path-by-path analysis 430, and a menu for the purchase propensity analysis 440. When the menu is clicked, To the operating tool interface providing module 124 of the commerce service apparatus 120 and receive the analysis result information from the database 126 of the electronic commerce service apparatus 120. [

5 is a flowchart illustrating a process of processing real-time analysis data by an operation tool module of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

Referring to FIG. 5, when the operation tool module receives the real-time result data, it first determines whether the mode is the automatic change mode (S510). This can be changed through user settings, and the default can be set to either the automatic change mode or the manual change mode. If the mode is not the automatic change mode, the shopping mall such as the product arrangement can be managed manually according to the input of the user interface (S512).

In the case of the automatic change mode, it is determined which of the automatic change modes is set (S520). This can be stored as a setting in a storage unit (which may be a kind of buffer) (not shown) of the operation tool module, and it can be retrieved and confirmed. If it is not changed to a special setting, the priority order among the products can be changed according to the default method (S522). The default method may be set to any one of the order-based priority change method, the page view number based priority change method, the expected order number based priority change method, and the expected order amount based priority change method. This can be identified through identification information on the priority change method.

The priority changing method is set to a specific method (for example, any one of a priority order changing method based on the order number, a priority changing method based on the page view number, a priority changing method based on the expected order number, and a priority changing method based on the expected order amount) If so, the method information set from the repository may be obtained (S530). At this time, the specific method may be a method newly added by the operator in a new way rather than the method initially set, and the new method should be programmed and stored in the storage.

After the method information is acquired, the priority of the product arrangement is changed according to the obtained method (S540). For example, according to the order change method based on the expected order amount, the goods having the highest expected order amount become the first items, and then the goods are arranged in the order in the next order.

Then, the control signal is transmitted so that the products are arranged according to the changed priority order (S550).

FIG. 6 is a diagram showing a display screen of an order and product view trend analysis of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

Referring to FIG. 6, the order and product view trend analysis result data may include a number of orders for a specific product or a specific product group, a total general view number, and a trend graph for the number of views through the current path. This can be generated based on the product identification information or the product category information, time stamp information, product inquiry / order information of the analysis basic data. The interval information to be analyzed can be set through the operation tool interface. The result data may be provided in a graphical format, but may be provided in other representations (e.g., tables, strings, etc.).

FIG. 7 is a view showing an analysis display screen of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention; FIG.

Referring to FIG. 7, the analysis result data for each path may include a table for analyzing an access path up to an order and an inquiry in order and inquiry for a specific product or a specific product group for a predetermined period. This can be generated based on the product identification information or product category information of the analysis basic data, time stamp information, product inquiry / order information, and access path information. The interval information to be analyzed can be set through the operation tool interface. The result data may be provided in a table format, but may be provided in other representations (e.g., graphs, strings, etc.).

FIG. 8 is a view showing an analysis screen of purchase tendency analysis of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

Referring to FIG. 8, the purchase tendency analysis result data is an analysis of a purchase tendency of a customer in an order (or an inquiry behavior) for a predetermined period, and the customer's tendency to purchase is analyzed according to the region, sex, And a graph analyzing one or more of the daily buying behavior. This can be generated based on customer identification information of the analysis basic data, time stamp information, product order information, region, sex, age information, and payment means information of the customer. The interval information to be analyzed can be set through the operation tool interface. The result data may be provided in a graphical format, but may be provided in other representations.

9 is a view showing a result report display screen of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

Referring to FIG. 9, the resulting report data may include content for analysis results of a particular shopping mall (e.g., a web site or a web page). The resulting report can include information on the analysis results for a particular product (or group of products) over a specific period of time. For example, it may include the total click-through rate for the product, or the click-through rate for order clicks, the overall click rate for each funnel, and the order click rate. The results can also include results for clicks on product details, clicks on shopping carts, clicks on items of interest, and clicks on order clicks. Furthermore, the results report may include the results of the analysis of the entire product registered on a particular page. The result of the analysis can be displayed through a graph, a table, a character string or other expression means, and can be transformed into a form convenient for the user to view.

10 is a conceptual diagram showing a format of analysis basic data in a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

Referring to FIG. 10, the analysis basis data 1000 should include both information required for real-time and non-real-time analysis. Basically, the analysis basic data 1000 may include a customer ID, i.e., information capable of identifying a customer, a product ID (information for identifying the product), and product category information. The product category information is category information including the product, and items such as a round T-shirt and a V-neck T-shirt can be bundled together in a category called a T-shirt. The analysis basic data 1000 may include at least one of product inquiry information, shopping cart addition information, wish list registration information, time stamp information, payment means information, region ID information, gender information, access route information, .

Here, the product inquiry information indicates whether the corresponding click or request is for product inquiry, and the shopping basket addition information indicates information indicating whether to include an item in the shopping basket. The wish list registration information indicates that the product is registered in the wish list You can display information about what you want to do. The time stamp information indicates information for indicating a time at which a specific action occurs. The payment means information includes information on the payment means for purchasing (for example, there may be a credit card, an accountless deposit, a real-time account transfer, a mobile payment, a deposit, etc.) when a purchase action occurs. The region ID is information for identifying the region to be ordered by the customer, the gender information is information for identifying the gender of the customer who performs the order or inquiry, the access route information is information about the route The current page information may include information for identifying a page where the current action occurs.

11 is a view showing a display screen in an operational tool interface of a recommendation analysis system in an electronic commerce according to an embodiment of the present invention.

Referring to FIG. 11, the operation tool interface may include a menu for product registration, a menu for managing product display, a menu for changing the display order, and a menu for design editing.

Here, the product registration is a menu for newly registering a product that is not currently displayed, and the display management is a menu for controlling the overall product display such as the number of products to be displayed on a page. The display order changing menu is a menu for determining the priority order of merchandise display and determining which products are arranged in order on a page according to the number of pages. The display order change menu may be a menu for displaying a product that receives the most attention on the first page or the main page by changing the priority of the product based on the real-time analysis result data described above. In addition, the operational tool interface can provide functionality for setting the duration and page in real time analysis requests.

According to an embodiment of the present invention, the e-commerce operation apparatus may be provided with a function of either JavaScript or a chrome web browser extension so that the information provided by each module of the electronic commerce service apparatus can be provided on the same screen as the client apparatus, Can be provided through one.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the inventions as defined by the following claims It will be understood that various modifications and changes may be made thereto without departing from the spirit and scope of the invention.

Claims (18)

A system for analyzing and recommending goods through electronic commerce,
Collecting data of the electronic commerce client apparatus and transmitting analysis basis data based on the product analysis to the recommendation analyzing apparatus and providing recommendation product information to the client apparatus through the web browser based on the information received from the recommendation analyzing apparatus An operation tool interface for supporting the operation of the electronic commerce service and an electronic commerce service device for providing the analysis result data received from the recommendation analyzing device to the electronic commerce operating device through a web browser; And
Receiving the analysis basic data from the electronic commerce service apparatus and analyzing the product for the analysis and / or recommendation request, generating the analysis result data and the recommended product information according to the product analysis result, and transmitting the analyzed result data to the electronic commerce service apparatus A recommendation analyzing device for transmitting the recommendation analyzing device,
Wherein the analysis result data includes real-time analysis result data provided to be reflected in real time through the operating tool interface and result report data provided in non-real-time by synthesizing at least one non-real-time analysis result, And the result report data is generated and transmitted and received in the electronic commerce service apparatus and the recommendation analyzing apparatus. The apparatus of claim 1, wherein the recommendation analyzer
An analysis collection module for receiving analysis basis data received from the electronic commerce service apparatus and storing the analysis basis data in a database;
A data analysis module for analyzing data stored in the database and data received and requested additionally to the electronic commerce service apparatus to generate the recommended product information and storing analysis results in the database;
A real-time analysis module for analyzing real-time analysis basic data received from the analysis collection module to generate real-time analysis result data, converting the real-time analysis result data into a real-time transferable format and transmitting the data to the electronic commerce service device in real time;
A report module that inquires result report data stored in the database or generates a result report for each specific web site or web page based on the analysis result performed by the data analysis module and stores the result report in the database; And
And a database for storing data of the analysis collection module, the data analysis module, the real time analysis module, and the report module. 3. The method of claim 2,
Wherein the real-time analysis result data includes information that can be easily converted into a format that can be transmitted in real-time, and includes information on orders for a predetermined period of time, page views for a predetermined period, Information about expected orders, information on expected orders for the predetermined period of time in the future, and expected order amount information calculated based on the price and the expected order number information. 3. The method of claim 2,
Wherein the data analysis module provides a product recommendation product and a customer recommendation product,
The recommended product based on the product standard is recommended based on the similarity among the products and the purchase history of a plurality of customers,
Wherein the customer-recommended product is recommended on the basis of a personalized shopping cart, a wish list, a recently viewed product, and a purchased product information of a specific customer. 3. The method of claim 2, wherein the data analysis module
Ii) analysis of an access path for an order signal and an inquiry signal for the requested analysis item within a predetermined period of time, and iii) a purchase history Real-time analysis result data by performing at least one of the purchase tendency analysis on the basis of the real-
Wherein the non-real-time analysis result data is used as reference data in the creation of the result report data. 6. The method of claim 5,
And iii) the purchase propensity analysis includes an analysis of purchase tendency by region, sex, age, payment means, time period, and day of the week within a predetermined period. 3. The method of claim 2,
The result report data includes an analysis of relative ratios of 1) all clicks, recommendation clicks, and order clicks of the client apparatus included in a predetermined period, and 2) analysis of ratio of actual orders to shopping items, Wherein the recommendation analysis system comprises: 2. The method of claim 1,
A first mode for automatically setting a priority order of a current product arrangement in an electronic commerce service based on the real-time analysis result data, and a second mode for manually setting a current product arrangement through an external input,
Wherein the at least one non-real-time analysis result data and the real-time analysis result data, which form the basis of the result report data, the result report data, and the real-time analysis result data are integrated to support the manual change of the second mode Recommendation analysis system. 9. The method of claim 8,
Wherein the operational tool interface provides a menu for the overall product analysis, the page unit product analysis, the product arrangement management, and the product information management for the manual change of the second mode. The electronic commerce service apparatus according to claim 1, wherein the electronic commerce service apparatus
A commodity recommending module for transmitting a recommendation request message from the client to the recommendation analyzer and providing recommendation information received from the recommendation analyzer to the client device;
A data collection module for collecting data necessary for recommendation analysis among customer information associated with the client device and providing the collected data to the recommendation analyzer;
An operating tool interface providing module for providing the operating tool interface to the electronic commerce operating device;
A real-time commodity analysis response module that transmits a real-time analysis request received from the electronic commerce operating apparatus to the recommendation analyzing apparatus and provides real-time analysis result data received from the recommendation analyzing apparatus to the electronic commerce operating apparatus in real time;
A result report providing module that transmits a result report request received from the electronic commerce operating device to the recommendation analyzing device and provides result report data received from the recommendation analyzing device to the electronic commerce operating device; And
And a service device database storing important data or temporary data of the product recommendation module, the data collection module, the operation tool interface provision module, the real time goods analysis response module, and the result report provision module. Recommendation analysis system. 11. The system of claim 10, wherein the data collection module
The data necessary for the analysis is collected by the time of day, the day of the week, the day of the week, the date of payment, Wherein the recommendation analyzing system includes at least one of information, means-specific information, region, gender, inflow path, and current page information. 12. The method of claim 11,
Wherein the electronic commerce service apparatus transmits data stored in the service apparatus database corresponding to the request in response to the request of the recommendation analyzing apparatus. 12. The method of claim 11,
Wherein the electronic commerce operation apparatus provides the information provided by each module of the electronic commerce service apparatus through one of JavaScript script or Chrome Web browser extension so as to provide the same information on the same screen as the client apparatus. Recommendation Analysis System in Electronic Commerce. A method for analyzing and recommending goods through electronic commerce,
The electronic commerce service apparatus collecting data of the electronic commerce client apparatus and delivering analysis basis data to the recommendation analyzing apparatus based on the product analysis;
Receiving the analysis basic data from the electronic commerce service apparatus and analyzing and analyzing a product requested for recommendation;
Wherein the recommendation analyzing apparatus generates analysis result data and recommendation product information according to a product analysis result, stores the data in a database, and transmits the data to the electronic commerce service apparatus; And
Wherein the electronic commerce service apparatus provides the recommendation article information to the client apparatus through a web browser based on the information received from the recommendation analyzing apparatus and further includes an operation tool interface for operating the electronic commerce service and an analysis Providing the resultant data to the electronic commerce operating device through a web browser,
Wherein the analysis result data includes real-time analysis result data provided to be reflected in real time through the operating tool interface and result report data provided in non-real-time by synthesizing at least one non-real-time analysis result, And the result report data is generated and transmitted and received in the electronic commerce service apparatus and the recommendation analyzing apparatus. 15. The system of claim 14,
A first mode for automatically setting a priority order of a current product arrangement in an electronic commerce service based on the real-time analysis result data, and a second mode for manually setting a current product arrangement through an external input,
Wherein the second mode is manually changed by providing the result report data, the at least one non-real-time analysis result data and the real-time analysis result data that form the basis of the result report data, A method of product recommendation analysis. 15. The method of claim 14,
Wherein the recommendation analyzing apparatus provides, as the product recommendation information, a recommended product based on a product and a recommended product based on a customer,
The recommended product based on the product standard is recommended based on the similarity among the products and the purchase history of a plurality of customers,
Wherein the customer-recommended product is recommended on the basis of a personalized shopping cart, a wish list, a recently viewed product, and purchased product information of a specific customer. 15. The method of claim 14,
The real-time analysis result data includes information that can be easily converted into a format that can be transmitted in real time, and includes information on the number of orders up to a predetermined period, page view information And an expected order amount information calculated based on the expected order number information, the price, and the expected order number information until a predetermined period of time in the future. 15. The apparatus of claim 14, wherein the recommendation analyzer
Ii) analysis of an access path for an order signal and an inquiry signal for the requested analysis item within a predetermined period of time, and iii) a purchase history Analyzing at least one of real-time analysis result and purchase intention analysis based on the non-real-time analysis result data, and generating the result report data based on the non-real-time analysis result data.

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