KR20230095868A - Method, apparatus, and program for providing business analysis information to provide benchmark information through collecting and analyzing data based on automatization - Google Patents

Abstract

The present invention is a business analysis information providing method performed by a business analysis information providing device, comprising the steps of collecting and merging online commerce data, and determining a benchmark target according to a predetermined benchmark purpose based on the online commerce data. , and providing information of the benchmark object or providing information obtained by comparing and analyzing online commerce data of the benchmark object and online commerce data of a specific company.

Description

Business analysis information providing method, apparatus, and program for providing benchmark information through automation-based data collection and analysis

The present invention relates to a technology for providing information on a benchmark target based on online commerce data or diagnosing a company's business problem and providing a business strategy through comparative analysis between the benchmark target and the company.

The domestic online commerce market is growing rapidly, but the statistical solutions related to the online commerce business that exist in the market are at a very rudimentary level that only provides simple data listings. is difficult. In other words, since statistical solutions at the current level only provide statistics visualization and do not inform business problems, it can be said that there is no statistical solution that diagnoses problems in online commerce business yet. In this situation, a Growth Hacking team composed of data analysts and developers is needed to explore the business problems of online commerce business, but most small and medium-sized online commerce companies are inevitably burdened in terms of cost. Accordingly, there is a problem in that small and medium-sized online commerce companies generally make decisions based on the manager's intuition.

Korean Patent Registration No. 10-1715737

An object of the present invention is to provide a business analysis information providing method, apparatus, and program for providing insight for business growth by analyzing various indicators based on online commerce data.

The purpose of the present invention is to collect and merge online commerce data to find a benchmark target according to the purpose, to diagnose problems and provide strategies through comparative analysis of benchmark target information or benchmark target and specific companies It is to provide a business analysis information providing method, device, and program.

An object of the present invention is to learn the names of items included in data acquired from various online malls, analyze the tendencies of the data, convert them into one unified name, and then convert the data to secure online commerce data. An object of the present invention is to provide a business analysis information providing method, apparatus, and program for constructing a database by merging.

The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

A first aspect of the present invention for achieving the above object is a method for providing business analysis information, comprising the steps of collecting and merging online commerce data, determining a benchmark target according to a predetermined benchmark purpose based on the online commerce data. and providing information of the benchmark object or providing information obtained by comparing and analyzing online commerce data of the benchmark object and online commerce data of a specific company.

Preferably, the collecting and merging of the online commerce data includes acquiring online commerce data by date from at least one online mall in which a specific business is located, analyzing each item included in the acquired online commerce data, and The method may include converting the item name by determining one of preset item names, and loading pre-stored online commerce data and the acquired online commerce data for each online mall according to the converted item name.

Preferably, the step of converting the item name includes determining the item name of each item included in the acquired online commerce data, and if the determined item name does not match the item name of the pre-stored online commerce data, the item name or item value Analyzing a characteristic, determining one of item names of pre-stored online commerce data based on the characteristic, and learning an item name of online commerce data based on the determined item name and the determined item name.

Preferably, the step of determining the benchmark target includes setting at least one criterion of the industry, sales level, and purchase cycle, and determining the benchmark target by filtering online commerce data according to the set criterion. steps may be included.

Preferably, the step of setting the criterion is the step of receiving selection of at least one criterion of the type of industry, sales level, and purchase cycle from the user of the specific company, and if the selected criterion is the type of industry, the type of business of the specific company Setting the industry classified into the same or similar range as a reference value, and if the selected criterion is the sales level or purchase cycle, the reference value is similar to or higher than the current value of the sales level or purchase cycle of the specific company Including the step of setting to , but whether the similarity or increase and the range of similarity or increase compared to the current value can be determined by the user.

Preferably, the providing of the information includes extracting online commerce data collected by date and loaded for each online mall with respect to the benchmark object, merging the extracted online commerce data into one, and the merged online commerce data. Extracting a benchmark indicator from commerce data, and providing information on the benchmark indicator, wherein the benchmark indicator includes sales by period, sales by purchase channel, sales by order method, number of orders, and purchase cycle. , repurchase rate, unit price per customer, user log, customer lifetime value, review conversion rate, friend recommendation rate, and purchase conversion rate.

Preferably, the providing of the information includes comparing online commerce data of the benchmark target with online commerce data of the specific company, determining a business problem of the specific company according to the comparison result, and In order to solve the business problem, a step of recommending a business strategy of the benchmark target and providing expected results according to the strategy may be included.

Preferably, the step of recommending the business strategy and providing the expected performance includes the time when the same or similar problem as the business problem of the specific company appears from the online commerce data of the benchmark target, and when the problem does not appear after the corresponding time. The step of specifying a time period, the step of analyzing the online commerce data of the benchmark object between the two periods to analyze the strategy of the benchmark object for problem solving, and the analysis of the analyzed benchmark object strategy and the corresponding strategy A step of providing change information of a performance index of a benchmark target may be included.

Preferably, the step of obtaining a performance indicator for the execution of the business strategy for each period, the step of determining the degree of effectiveness of the strategy by comparing the performance indicator and the expected performance, and the degree of effect of the business strategy and the business strategy , learning a business strategy based on the determined business problem, and the type of business, sales level, and purchase cycle of the specific company.

A second aspect of the present invention for achieving the above object is an apparatus for providing business analysis information, including a memory for storing one or more instructions and a processor for executing the one or more instructions stored in the memory, wherein the processor comprises the one or more instructions. By executing the above instructions, the method according to the disclosed embodiment is performed.

A third aspect of the present invention for achieving the above object is a computer program for providing business analysis information, which is combined with a computer as hardware and stored in a computer-readable recording medium to perform the method according to the disclosed embodiment.

Other specific details of the invention are included in the detailed description and drawings.

As described above, according to the present invention, according to the purpose of benchmarking, find a benchmark target and provide information on various indicators of the benchmark target, or diagnose the company's business problems and develop strategies through comparative analysis between the benchmark target and the company. It provides an effective way to grow your business.

In addition, by acquiring and merging online commerce data from various online malls, there is an effect of properly securing online commerce data that is the basis for analysis.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

1 is a configuration diagram showing a system for providing business analysis information according to the present invention.
2 is a configuration diagram illustrating an apparatus for providing business analysis information according to an embodiment.
3 is a flowchart illustrating a method of providing business analysis information according to an exemplary embodiment.
4 is a flowchart illustrating a method of providing benchmark information according to an exemplary embodiment.
5 and 6 are exemplary diagrams illustrating provided business analysis information according to an embodiment.

Advantages and features of the present invention, and methods of achieving them, will become clear with reference to the detailed description of the following embodiments taken in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, only these embodiments are intended to complete the disclosure of the present invention, and are common in the art to which the present invention belongs. It is provided to fully inform the person skilled in the art of the scope of the invention, and the invention is only defined by the scope of the claims.

Terminology used herein is for describing the embodiments and is not intended to limit the present invention. In this specification, singular forms also include plural forms unless specifically stated otherwise in a phrase. As used herein, "comprises" and/or "comprising" does not exclude the presence or addition of one or more other elements other than the recited elements. Like reference numerals throughout the specification refer to like elements, and “and/or” includes each and every combination of one or more of the recited elements. Although "first", "second", etc. are used to describe various components, these components are not limited by these terms, of course. These terms are only used to distinguish one component from another. Accordingly, it goes without saying that the first element mentioned below may also be the second element within the technical spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings commonly understood by those skilled in the art to which the present invention belongs. In addition, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless explicitly specifically defined.

The term "unit" or "module" used in the specification means a hardware component such as software, FPGA or ASIC, and "unit" or "module" performs certain roles. However, "unit" or "module" is not meant to be limited to software or hardware. A “unit” or “module” may be configured to reside in an addressable storage medium and may be configured to reproduce one or more processors. Thus, as an example, a “unit” or “module” may refer to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. Functions provided within components and "units" or "modules" may be combined into smaller numbers of components and "units" or "modules" or may be combined into additional components and "units" or "modules". can be further separated.

In this specification, a computer means any kind of hardware device including at least one processor, and may be understood as encompassing a software configuration operating in a corresponding hardware device according to an embodiment. For example, a computer may be understood as including a smartphone, a tablet PC, a desktop computer, a laptop computer, and user clients and applications running on each device, but is not limited thereto.

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

Although each step described in this specification is described as being performed by a computer, the subject of each step is not limited thereto, and at least a part of each step may be performed in different devices according to embodiments.

1 is a configuration diagram showing a system for providing business analysis information according to the present invention.

Referring to FIG. 1, the business analysis information providing system 100 includes a business analysis information providing device 110 (hereinafter referred to as “analysis device”) and an online commerce data providing device 120 (hereinafter referred to as “providing device”). ), and a user terminal 130 . Here, the analysis device 110, the providing device 120, and the user terminal 130 are connected through a network, and only one of the providing device 120 and the user terminal 130 is shown, but the number is limited. there is no

The analysis device 110 is a device that is connected to the providing device 120 and the user terminal 130 to perform a business analysis information providing method, and in one embodiment, may perform a benchmark information providing method. Preferably, the analysis device 110 collects, merges, and analyzes the online commerce data received from the providing device 120 to provide online commerce business analysis information of a specific company according to a request of the user terminal 130. . Here, online commerce data received from the providing device 120, business analysis information analyzed using the online commerce data, and feedback data for the business analysis information received from the user terminal 130 are stored and managed separately in a database. and can be used for artificial intelligence learning.

The provision device 120 is an online mall server and may provide online commerce data of a specific company that has agreed to provide data to the analysis device 110 to the analysis device 110 or allow the analysis device 110 to collect the online commerce data. let it be Preferably, the providing device 120 may correspond to an online mall server of a specific company that wants to receive the service provided by the analysis device 110 or a third-party online mall server in which the specific company is located. For example, It may correspond to Smart Store, Cafe24, Gododo Mall, shopify, N Store, Coupang, SSG, etc. In addition, the online commerce data of a specific company can also be used when analyzing the benchmark target.

The user terminal 130 is a device that can be equipped or manipulated by a user of a specific company who wants to receive business analysis information through the analysis device 110 . The user terminal 130 is, for example, the computer described above, and may install and execute an application or program for performing the business analysis information providing method provided by the analysis device 110, and may use a user interface (User Interface). ), the input/output of data can be controlled.

2 is a configuration diagram illustrating an analysis device according to an exemplary embodiment.

Referring to FIG. 2, the analysis device 110 includes a processor 111 and a memory 112, and preferably, a network interface (or communication interface) (not shown), a storage (not shown), or a bus ) (not shown) may be further included.

The processor 111 controls the overall operation of each component of the analysis device 110. Preferably, the processor 111 may include a central processing unit (CPU), a micro processor unit (MPU), a micro controller unit (MCU), or any type of processor well known in the art of the present invention. , may perform operations for at least one application or program for executing a method according to embodiments of the present invention.

In one embodiment, the processor 111 may include one or more cores (not shown), a graphics processing unit (not shown), or a connection path (eg, a bus) for transmitting and receiving signals to and from other components. The processor 111 may temporarily or permanently store signals (or data) processed in the processor 111 (RAM: Random Access Memory, not shown) and ROM (ROM: Read-Only Memory, not shown) may be further included. In addition, the processor 111 may be implemented in the form of a system on chip (SoC) including at least one of a graphics processing unit, RAM, and ROM. In addition, the processor 111 may perform the method described with reference to FIGS. 3 and 4 by executing one or more instructions stored in the memory 112 .

Memory 112 stores various data, commands, or information. Preferably, the memory 112 may store programs (one or more instructions) for processing and control of the processor 111, and the programs stored in the memory 112 may be divided into a plurality of modules according to functions. can

Steps of a method or algorithm described in connection with an embodiment of the present invention may be implemented directly in hardware, implemented in a software module executed by hardware, or implemented by a combination thereof. A software module may include random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any form of computer readable recording medium well known in the art to which the present invention pertains.

Components of the present invention may be implemented as a program (or application) to be executed in combination with a computer, which is hardware, and stored in a medium. Components of the present invention may be implemented as software programming or software elements, and similarly, embodiments may include various algorithms implemented as data structures, processes, routines, or combinations of other programming constructs, such as C, C++ , Java (Java), can be implemented in a programming or scripting language such as assembler (assembler). Functional aspects may be implemented in an algorithm running on one or more processors.

Hereinafter, with reference to FIGS. 3 and 4 , a method of providing business analysis information performed by the analysis device 110 and a method of providing benchmark information will be described.

3 is a flowchart illustrating a method of providing analysis information according to an exemplary embodiment.

Referring to FIG. 3 , the analysis device 110 collects and merges online commerce data (step S310). Preferably, the analysis device 110 may acquire online commerce data by date from at least one online mall in which a specific business is located. Here, the specific company is a company that has agreed to receive the business analysis information providing service by providing online commerce data to the analysis device 110, and the analysis device 110 is the device 120 of the company's online mall, or a specific company. Online commerce data may be periodically obtained from the providing device 120 of a third party's online mall in which a business is located.

Preferably, the analyzer 110 analyzes each item included in the acquired online commerce data, determines one of preset item names, converts the item name, and converts the item name to the previously stored online commerce data and the acquired online commerce data. can be loaded by online mall. The online commerce data obtained in various forms through this process can be unified into one form and then stored and managed separately for each online mall. A method of storing and managing online commerce data can be easily modified by a person skilled in the art.

More specifically, the analysis device 110 determines the item name of each item included in the acquired online commerce data, and checks whether the determined item name matches the item name of the pre-stored online commerce data. The item name of the pre-stored online commerce data may be set by the user terminal 130 or may be set based on the item name of the online commerce data obtained from the company's online mall of a specific company. Preferably, the analysis device 110 may load the online commerce data for each online mall without changing the item name when the determined item name matches the item name of the pre-stored online commerce data, and the determined item name matches the item name of the pre-stored online commerce data. If not, the item name of the item or the characteristics of the item value can be analyzed. For example, if the online commerce data is in Excel format, the item may be a column, the item name may be a column name, and the item value may be a column value. Even if the item names are expressed differently, if the characteristics of the item names themselves or the tendencies of the item values are the same or similar, it can be determined that they correspond to the same item. Therefore, the analysis device 110 analyzes the characteristics of the item names or item values. The analysis device 110 may determine the item name of online commerce data obtained based on the analyzed characteristics as one of previously stored item names of online commerce data.

For example, when the item name of the pre-stored online commerce data is "order number" and the item names of the acquired online commerce data are not matched with "order_id" and "order_num", the analysis device 110 determines the number of each item name itself. By analyzing the characteristics, it is determined that both “order_id” and “order_num” represent “order number”, or by analyzing the characteristics of the item values, the characteristics of the item values included in “order number”, “order_id”, and “order_num” are analyzed. If it is determined that these are the same or similar, “order_id” and “order_num” can be determined as “order number” to convert the item name to “order number”.

In addition, the analysis device 110 may learn the item name of the online commerce data based on the item name determined through comparative analysis between the item name determined from the acquired online commerce data and the previously stored online commerce data, and through this, the newly acquired item name The item name determination of the online commerce data and matching with the item name of the previously stored online commerce data are advanced to perform more accurately. For example, since it was learned that “order_id” and “order_num” are item names that match “order number” through item name determination of “order_id” and “order_num”, “order_id” or “order_id” or If there is “order_num”, it can be matched directly with “order number” without analyzing the characteristics of the item name or item value.

In various embodiments, the analysis device 110 may learn characteristics of item names and match new item names with item names of pre-stored online commerce data. For example, if the item name includes "order", the analysis device 110 may match it with "order number", but is not limited thereto.

In addition, the analysis device 110 may learn the characteristics of item names using a natural language processing-based learning model, and match new item names with item names of pre-stored online commerce data. For example, the analysis device 110 may parse each item name. For example, the analysis device 110 may parse the item name “order_id” into “order” and “id”.

The analysis device 110 may parameterize the parsed item name through word embedding. In addition, the analysis device 110 may perform item name matching through similarity analysis between the parameterized item name and the item name of the pre-stored online commerce data.

As another example, the analysis device 110 may determine the meaning of each parsed item name based on a pre-stored database and perform item name matching through a combination of parsed item names.

As another example, the analysis device 110 may input a parameterized item name to a pre-learned model (eg, a neural network model), obtain an output thereof, and match item names corresponding thereto.

In various embodiments, the analysis device 110 may perform item name matching based on characteristics of data included in data items. For example, the characteristics of the data of the order number and the characteristics of the data of the order amount may be different from each other. For example, the order number may have a certain number of digits (e.g., 8 digits) appear regularly, while the order amount may have fewer digits than the order number, and the number of digits may not be constant and may fluctuate widely. . The analysis device 110 may perform item name matching based on the characteristics of the data and the distribution of the data. The analysis device 110 may perform item name matching more accurately by performing analysis of data characteristics and item names together.

Through this, the analysis device 110 can easily manage the database by automatically determining and collecting item names that can be set differently for each platform or user.

When all item names of the acquired online commerce data are determined, the analysis device 110 loads the pre-stored online commerce data and the acquired online commerce data for each online mall according to the determined item names. Accordingly, a data warehouse may be constructed.

The analysis device 110 analyzes the online commerce data (step S320). The analysis device 110 may analyze online commerce data of a specific company, that is, a company seeking to receive a business information providing service through the analysis device 110, from the online commerce data collected and merged in step S310, or With reference to 4, it is possible to analyze the online commerce data of the benchmark target to be described. Preferably, the analysis device 110 may obtain business indicators from online commerce data, and the business indicators include sales by period, sales by purchase channel, sales by order method, number of orders, purchase cycle, repurchase rate, unit price per customer, user It may correspond to at least one of a log, a customer lifetime value, a review conversion rate, a friend recommendation rate, and a purchase conversion rate, but is not limited thereto and may correspond to any index obtainable from online commerce data.

In various embodiments, the analysis device 110 may obtain more various business indicators from online commerce data of a benchmark object to be analyzed. For example, the business index may include user data as a benchmark target. For example, information on user data (eg, gender, age, etc.) of a benchmark target may be obtained.

In various embodiments, the analysis device 110 may obtain more various business indicators from online commerce data of a benchmark object to be analyzed. For example, the business index may include user data as a benchmark target. For example, information on user data (eg, gender, age, etc.) of a benchmark target may be obtained.

The analysis device 110 provides online commerce business information (step S330). Preferably, the analysis device 110 provides online commerce business information according to the analysis result in step S320, which the user can check through the user terminal 130. For example, for online commerce business information, as shown in FIG. 5 , analysis results for each business indicator may be schematized, and a meaning, analysis method, or interpretation method for each business indicator may be provided.

The analysis device 110 diagnoses a business problem and provides a strategy (step S340). Preferably, the analysis device 110 may diagnose a problem of a specific company based on the online commerce data of the specific company. That is, it is to diagnose a problem based on one's previous online commerce data. Alternatively, the analysis device 110 may diagnose a problem through comparative analysis of online commerce data of a specific company and online commerce data of a benchmark target. Preferably, the analysis device 110 may provide a business strategy for a problem from among preset business strategies, or may provide a business strategy for a benchmark target.

A detailed method of diagnosing business problems and providing a business strategy using online commerce data of a benchmark target will be described with reference to FIG. 4, and only a method of using online commerce data of a specific company will be described here. For convenience of explanation, two embodiments are separately described, but the method described with reference to FIGS. 3 and 4 can be implemented in various combinations, which can be easily performed by a person skilled in the art.

In one embodiment, the analysis device 110, in S320, obtains a business indicator from online commerce data of a specific company. Here, the specific company is a company that wants to be diagnosed with a business problem and provided with a strategy through the analysis device 110, and preferably, the analysis device 110 is the company's own online mall or a third party's online mall where the specific company is located. A business index may be obtained by analyzing the online commerce data acquired and merged from .

The acquired business indicators and online commerce business information therefor may be provided in step S330, and the analysis device 110 analyzes the business indicators in step S340 to diagnose business problems of a specific company. Preferably, the analysis device 110 may confirm the existence of a singular factor corresponding to an increase, a repetition of fluctuations, or a decrease in the business index. Here, it is said that the singular factor corresponds to a rise, a repetition of fluctuations, or a decline, but even when a trend that has not been shown before exists in each business index, it can be determined that the singular factor exists.

The analysis device 110 compares the business index in which the idiosyncratic factor exists with previous business indicators of a specific company or business indicators of other companies classified in the same or similar industry as the specific company, and according to the comparison result, the idiosyncratic factor is related to the business problem. You can judge whether it is applicable or not. In one embodiment, the analysis device 110 may compare the business index of the benchmark target to determine whether the business problem corresponds to, and the method of determining the benchmark target and obtaining the benchmark business index is shown in FIG. 4 The method described with reference to may be applied.

More specifically, the analysis device 110 may check whether the previous business index has the same or similar trend as the outlier, or compare the outlier with the previous business index for each period corresponding to a specific year/month/week. , it is possible to determine whether an idiosyncratic factor corresponds to a business problem according to the existence of a trend or the result of comparison with previous business indicators for each cycle. Preferably, the analysis device 110 determines that the same or similar trend as the singular factor in the previous business indicator is periodically repeated at a specific time and the range of rise, rise, or fall is compared with the previous business indicator. If it is within the range, it can be determined that the singular factor does not correspond to the business problem, and if the same or similar trend as the singular factor does not exist in the previous business index, it can be determined that the singular factor corresponds to the business problem. Alternatively, the analysis device 110 compares the previous business index corresponding to the previous month/previous week with the singular factor, and the range of rise, rise, or fall corresponding to the singular factor exceeds a preset standard range compared to the previous business index, If the trends are different by comparing the previous business index and the singular factor of the corresponding period for each year corresponding to the time when the singular factor appeared, the singular factor can be determined to correspond to a business problem. For example, a drop in sales during off-season is natural, but an excessively large drop in sales corresponds to a business problem, and a drop in sales during a peak season corresponds to a business problem.

In addition, the analysis device 110 compares the idiosyncratic factors of a specific company with the business indicators of other companies, and when the business indicators of the other companies have the same or similar tendencies as the outliers, the idiosyncratic factors of the specific company and the idiosyncratic factors of the other companies It is possible to compare factors to determine whether the difference exceeds a predetermined standard range, and to determine whether or not a singular factor corresponds to a business problem according to the existence of a tendency or the degree of difference between the singular factors of a particular company and other companies. there is. For example, a drop in sales of a specific company during the off-season tends to be the same for other companies, and does not correspond to a business problem. If the difference between the factors exceeds a preset standard range, it is determined to correspond to a business problem. Here, the other company may be another company in the same or similar industry as the specific company, or may correspond to the benchmark target, and if the benchmark target is applicable, after the benchmark target is determined by the method described in FIG. 4 below Whether it corresponds to a business problem can be determined, which can be easily performed by a person skilled in the art.

Preferably, when the singular factor corresponds to a business problem, the analysis device 110 generates and provides a growth equation capable of measuring the business growth rate according to the change in the business indicator by combining the business indicators in which the singular factor exists. can For example, if the business metrics for which singular factors exist are review conversion rate, friend referral rate, per customer price, and customer lifetime value, the growth equation is “(review conversion rate) X (friend referral rate) X (friends per month). Number of recommendations) X (Monthly customer price YoY) X ((M+1) average customer lifetime value)”.

The analysis device 110, in step S340, provides a business strategy according to business problems (step S430). Preferably, the analysis device 110 may recommend at least one pre-stored business strategy associated with a business problem.

In various embodiments, the analysis device 110 may calculate a target metric based on a growth equation and provide information on the target metric. In addition, by providing an action plan to achieve a target indicator and providing a page for performing the action plan (for example, execution of events such as exhibitions or advertisements), the user can be induced to carry out the action plan accordingly. there is. The analysis device 110 may monitor and provide changes in indicators as the user performs the action plan, and provide additional action plans for indicators that have not been achieved. Through this, the user can achieve the goal naturally by proceeding with the event according to the action plan provided until the goal indicator is achieved.

In various embodiments, the analysis device 110 may obtain more various business indicators from online commerce data of a benchmark object to be analyzed. For example, the business index may include user data as a benchmark target. For example, information on user data (eg, gender, age, etc.) of a benchmark target may be obtained.

The analysis device 110 may determine and provide priorities among the recommended business strategies based on the impact, reliability, and execution easiness of each recommended business strategy. Here, impact represents the degree of improvement in business indicators through the strategy, reliability represents the degree of empirical evidence, and ease of implementation represents the time and resources required to implement the strategy. Information on impact, reliability, and execution easiness for each business strategy may be defined in advance.

The analysis device 110 may select at least one of the recommended business strategies from a user of a specific company. That is, the analysis device 110 may recommend at least one business strategy to the user terminal 130, provide information and priority for each recommended business strategy, and the user terminal 130 may recommend the business strategy. is to choose at least one business strategy to put into action.

In one embodiment, the analysis device 110 may directly provide the execution of the business strategy selected by the user from the analysis device 110 or, if it is possible to link with a service provider associated with the implementation of the business strategy, the business strategy Linkage information for the execution of can be provided.

For example, advertisement publication or campaign progress may be directly provided through the analysis device 110 . In this case, it is possible to easily collect and analyze advertisement publication or campaign progress information, progress information, and performance information. Alternatively, the same information may be collected and analyzed through linked service providers.

As another example, a message transmission service for customers can also be conducted through its own platform or linked service, and through this, the progress and performance of the action plan can be analyzed.

As another example, if a special exhibition is to be held, a service for generating a special exhibition page on the platform and promoting and selling products may be provided. Specifically, in the case of providing an action plan to open a special exhibition as a business strategy, a menu for directly setting the special exhibition can be provided through the platform, and information related to the exhibition setting can also be generated and generated based on the provided business strategy. can be provided. The user may proceed with the exhibition setting using the provided information, and proceed with the exhibition name and product registration within the corresponding page. In this case, the performance of the exhibition can be automatically collected and analyzed.

In various embodiments, the user's product sales page information may be interlocked with the platform to automatically create a special exhibition page. The theme information of the special exhibition is generated based on the recommended business strategy, and accordingly, the name and design of the special exhibition may be automatically generated according to a preset template or standard. In addition, information about products to be sold in the exhibition, sales amount, discount rate, etc. may be automatically interlocked and created based on the user's product sales page and the provided business strategy. The user can review and approve the created page information so that the special exhibition can be started.

In various embodiments, an advertisement action plan for a special exhibition may also be created together and automatically executed through the platform. For example, SEO optimization for a special exhibition page, uploading of special exhibition information through a user's SNS, and execution of paid advertisements on a portal site or SNS may be automatically performed. The advertisement publication may be performed within a budget range set by the user, and information on an appropriate budget may also be provided in advance.

The analysis device 110 may monitor information on user influx, purchase conversion, sales, etc. according to the progress of the exhibition in real time, and may modify the exhibition setting or advertising strategy by itself. For example, products that sell well can be placed higher up, and products that are recommended to users with a high purchase conversion rate can be placed higher up. Conversely, products that you want to increase sales rates or products that target users who are targeting inflows can be placed higher up.

In various embodiments, the analysis device 110 determines that the inflow and purchase conversion rate of a specific product or a specific user group is less than the target compared to the benchmark target even if the sales or conversion rate is higher than the predetermined target, the corresponding product The composition of the exhibition page or the advertising strategy can be modified to increase the sales or the inflow and purchase conversion of the corresponding user base.

In various embodiments, the analysis device 110 may obtain and monitor information on a user introduced through an action plan related to an event such as a special exhibition. The analysis device 110 may monitor whether or not the user has repurchased and whether or not the user has exited, and may generate information on the user to be managed.

For example, the user to be managed may refer to a user who accesses a product sales page of a corresponding company within a predetermined period (eg, one week) after the end of the event, but is not limited thereto. When it is determined that the user to be managed accesses the product sales page, the analysis device 110 may generate an event to induce continuous visits of the user to be managed. As another example, if a user who has purchased a product through the exhibition page wants to access the exhibition page through the url of the exhibition page within a preset period, redirect to the product sales page, and classify the user as a user subject to management can do.

When a user subject to management accesses a product sales page, the analysis device 110 may display a banner on one side of the sales page to access the special exhibition page. Although the special exhibition has already ended and access by general users is not possible, if the user subject to management accesses the special exhibition page through the corresponding banner, the planned product can be purchased at a discounted price through the special exhibition page.

When a user subject to management purchases a product again through the special exhibition page, the user may be classified as a user subject to secondary management. When a user subject to secondary management revisits the product sales page within a preset period of time, a message notifying the end of the special exhibition is provided, but the corresponding user can be provided with a coupon to purchase the product again at the same discount amount as the special exhibition. . Through this, users who have been introduced through the exhibition can be naturally induced to continuously purchase products through the product sales page.

In one embodiment, the above-described method for diagnosing business problems and providing strategies may be automatically performed periodically or automatically whenever a unique factor occurs in online commerce data to provide an analysis of the unique factor and a business strategy accordingly. It can be.

In addition, the analysis device 110 may automatically diagnose business problems and provide business strategies using a preset algorithm. Preferably, the analysis device 110 determines a business indicator having problems among business indicators using a preset algorithm, finds and provides a business strategy that has the highest correlation with the growth of the corresponding business indicator, and applies the business strategy to a specific company. can make it Through this, a specific company can check the growth stage of the business and predict changes in business indicators by exploring factors that greatly affect the improvement of business indicators.

In one embodiment, the analysis device 110 may collect online commerce data during the implementation of the business strategy. The analysis device 110 may compare and analyze the collected online commerce data with previous online commerce data to determine a business strategy performance index and evaluate the business strategy according to the performance index. Here, performance indicators and evaluation results can be scored. Business strategy evaluation may be performed at regular intervals, and whether or not the business strategy provided by the analyzer 110 is effective in improving business indicators may be checked, and additional countermeasures may be provided according to the evaluation result. The analysis device 110 provides the evaluation information to the user terminal 130, and according to the feedback of the user terminal 130, the current business strategy is continuously performed, another business strategy is performed, or the next business according to priority is performed. strategies can be recommended. For example, if the evaluation information is judged to be ineffective, but the implementation period was short, it can be recommended to continue the current business strategy, and if the evaluation information is judged to be effective, a greater improvement In order to do so, it may be recommended to implement another or next business strategy. Here, based on the business problem, business strategy, and performance indicator, a business strategy recommended according to the business problem may be learned based on artificial intelligence.

In one embodiment, the analysis device 110 is a user terminal (not shown) of a user who purchases a product of a specific company or has a high interest through an online mall of a specific company or a third party online mall in which a specific company is located. A questionnaire template for measuring customer loyalty may be provided and a response of the user terminal 130 may be analyzed to provide customer loyalty (Net Promoter Score) and morphological analysis results.

4 is a flowchart illustrating a method of providing benchmark information according to an exemplary embodiment.

Referring to FIG. 4 , the analysis device 110 collects and merges online commerce data (step S410). Since step S410 is performed in the same way as step S310, a redundant description will not be made here.

The analysis device 110 determines a benchmark target according to a predetermined benchmark purpose based on the online commerce data (step S420). Preferably, the benchmark purpose may be set in advance by the user terminal 130, and the analysis device 110 may set one standard among industry type, sales level, and purchase cycle according to the benchmark purpose, and set If the criterion is an industry, an industry classified as the same or similar to the industry of a specific company is set as the reference value. It can be set to similar or upward compared to the value. Here, a specific company is a company that has requested the provision of benchmark information through the analysis device 110 . Among the criteria for determining the benchmark target, the purchase cycle may be calculated for each online mall. For example, the purchase cycle for each user is obtained (eg, purchase once a month, etc.) and the median value of the purchase cycle for each user is calculated. After obtaining, the purchase cycle may be calculated for each online mall.

Preferably, the setting of the criterion, whether similar or upward based on the criterion, and the range of similarity or upward relative to the current value may be determined based on data received from the user terminal 130 . At least one criterion among industry, sales level, and purchase cycle may be selected from the user terminal 130 and a reference value for the selected criterion may be set. For example, a user may want to benchmark a strategy by finding a company with a similar industry and purchase cycle as our company, but with higher sales, as a benchmark target. You may want to benchmark a company with a higher level of performance, and you may want to find a company in another industry that has a similar sales or purchase cycle as your benchmark and refer to its strategy. This allows you to set a baseline value.

Preferably, the analysis device 110 may determine a benchmark target by filtering online commerce data according to set criteria. When a plurality of criteria are selected among the industry type, sales level, and purchase cycle, and each reference value is determined, the analysis device 110 searches for a benchmark target that meets all of the selected criteria and their values or has the highest matching degree. can The determined benchmark target may be one or multiple, and when there are multiple benchmark targets, information on the determined plurality of benchmark targets is provided to the user terminal 130 for comparative analysis with online commerce data of a specific company. You can select a target to be benchmarked. Alternatively, when the user terminal 130 specifies a benchmark target, a specific benchmark target may be directly determined without a process of determining the benchmark target.

The analysis device 110 provides benchmark target information or information obtained by comparing and analyzing online commerce data of a benchmark target and online commerce data of a specific company (step S430).

Preferably, the analysis device 110 may extract and merge online commerce data collected by date and loaded for each online mall with respect to the benchmark target. Next, the analysis device 110 may extract a benchmark indicator from the merged online commerce data and provide information on the benchmark. Here, the benchmark indicators are sales by period, sales by purchase channel, sales by order method, number of orders, purchase cycle, repurchase rate, unit price per customer, user log, customer lifetime value, review conversion rate, friend referral rate, and purchase conversion rate. It may correspond to at least one of, but is not limited thereto, and may correspond to all indicators obtainable from online commerce data.

Preferably, the analysis device 110 may compare online commerce data of a benchmark target with online commerce data of a specific company, and determine a business problem of the specific company according to the comparison result. More specifically, the analysis device 110 may set a specific period of time, compare online commerce data during the specific period of time, and analyze a difference in each benchmark indicator. The analysis device 110 may not determine a business problem if the analyzed difference is within a predetermined standard range, but may determine a business problem if it exceeds a predetermined standard range or exhibits a different tendency. In addition, information on the reason for determining the business problem as a business problem through comparison between information on the business problem and an indicator of a benchmark target may be provided to the user terminal 130 .

Preferably, the analysis device 110 may recommend a business strategy as a benchmark target in order to solve a business problem and provide expected performance according to the strategy. More specifically, the analysis device 110 may specify a time when a problem identical to or similar to a business problem of a specific company appears and a time when the problem does not appear after the corresponding time from online commerce data as a benchmark target. Alternatively, if the current level of the specific company for the benchmark indicator and the target level that the specific company wants to reach are specified according to the benchmark purpose of the specific company, the analysis device 110 determines the level of the specific company in the online commerce data of the benchmark target. It is possible to specify the time when the current level was reached and the time when the target level of a specific company was reached. Next, the analysis device 110 analyzes the online commerce data of the benchmark target between the two periods to analyze the business strategy of the benchmark target for solving business problems, and analyzes the analyzed benchmark target business strategy and the corresponding business strategy. It can provide information on changes in performance indicators of benchmark targets according to Alternatively, the analysis device 110 may generate the above-described growth equation using a benchmark indicator in which a business problem exists, and use the growth equation to predict change in a specific company's performance indicator according to the execution of a business strategy. can provide

In various embodiments, the analysis device 110 may obtain information about user distribution based on user data of a benchmark target. For example, the main customer base may be different depending on the industry. By comparing the user distribution of the benchmark target and the user distribution of a specific company, it is possible to provide information on the user base to focus on to increase the sales of the specific company. For example, if women in their 20s are the main target group, but there are fewer women in their 20s than the benchmark target in a specific company's user distribution, a marketing strategy targeting women in their 20s can be recommended.

In addition, the analysis device 110 may obtain information about the ratio of VIP customers in the benchmark target. For example, the VIP customer ratio can be calculated based on the purchase amount, purchase cycle, or number of repeat purchases. The analysis device 110 may compare the VIP customer ratio of a specific company with the VIP customer ratio of the benchmark target, and provide information indicating that the specific company should increase the VIP customer ratio. Similarly, in this case, you can provide a marketing strategy to increase VIP customers and reduce customer churn.

In addition, the analysis device 110 may provide information by comparing and analyzing information on advertisement publication and result information, inventory quantity, type of product, etc. with a benchmark target, and provide a response strategy.

For example, the analysis device 110 may analyze performance when a benchmark target and a specific company run the same or similar campaign. As a result of the analysis, if a specific company's performance is lacking compared to the benchmark target, a strategy to compensate for this can be presented.

In addition, the analysis device 110 may analyze whether a benchmark target and a product sold by a specific company have high involvement or low involvement. For example, if the repurchase cycle and average purchase amount are high, it can be judged as a high involvement product.

In addition, the analysis device 110 may analyze a benchmark target and a sales route of a specific company to analyze a ratio between a company's mall and an outside mall. For example, depending on the type of product, there is a product with a high proportion of sales in the company's own mall and a product with a high proportion of sales in an external mall. The analysis device 110 may present a sales strategy based on its own mall and an external mall based thereon.

In various embodiments, the analysis device 110 may also collect and analyze financial indicators. Based on this, it is possible to collect information on cost, advertising cost, fee, transport cost, etc. of a specific company, and provide information for establishing and analyzing financial benchmark strategies such as margin and contribution profit.

In various embodiments, the analysis device 110 may obtain more various business indicators from online commerce data of a benchmark object to be analyzed. For example, the business index may include user data as a benchmark target. For example, information on user data (eg, gender, age, etc.) of a benchmark target may be obtained.

Preferably, the analysis device 110 may analyze a strategy of a benchmark target by analyzing a cross-sectional analysis of a benchmark indicator in which a business problem appears, as well as a correlation between benchmark indicators. For example, by analyzing online commerce data, the information that benchmark indicator B and benchmark indicator C have been improved is not directly implemented to improve benchmark indicator A through correlation analysis between benchmark indicators. Based on this, information on the business strategy of the benchmark can be provided. That is, not a business strategy for a benchmark indicator with a business problem, but a business strategy for another benchmark indicator that has a correlation with the benchmark indicator with a business problem can be provided.

In addition, the analysis device 110 may provide information on how the benchmark target performed the corresponding business strategy together with the business strategy of the benchmark target. For example, if the business strategy of the benchmark target is “mobile/web main page UI change”, information on the UI before and after the change can be provided together, and the business strategy of the benchmark target is “short-term event”. In the case of “recruiting customers through”, information on the type of event, event expression method, or event-related advertisement method may be provided together, and the information on this may be obtained by web surfing performed by the analysis device 110. .

In one embodiment, the analysis device 110 may obtain a performance indicator for the performance of the business strategy for each period and compare the performance indicator with the expected performance to determine the degree of effectiveness of the business strategy. The analysis device 110 may provide information on the degree of effectiveness of the business strategy to the user terminal 130, and may recommend other business strategies according to the degree of effectiveness of the business strategy. In addition, the analysis device 110 may learn artificial intelligence about a business strategy recommendation based on a business strategy, the degree of effectiveness of the business strategy, a business problem, a specific business type, sales level, and purchase cycle.

In one embodiment, the analysis device 110 may periodically analyze and provide information on the benchmark target, and if a target value that a specific company wants to reach is achieved in a specific business index of the benchmark target according to the benchmark purpose In addition to information on the benchmark target, it is possible to analyze and provide the business strategy of the benchmark target that had the greatest impact on achieving the target. In addition, when a singular factor corresponding to an unusual increase, repetition of fluctuations, or decline occurs in the benchmark target business index, the cause of occurrence of the singular factor may be analyzed and provided together with information on the occurrence of the singular factor.

6 is an exemplary view illustrating providing business analysis information according to an embodiment.

As described above, each step performed in FIGS. 3 and 4 has been separately described, but each step described in FIGS. 3 and 4 may be merged with each other, performed selectively, or performed in combination. will be. 6 is a result obtained by combining and merging the steps of FIGS. 3 and 4 with each other, and the analysis device 110 diagnoses a business problem with respect to a specific company from its online commerce data (“business problem”). , the results of diagnosing business problems through comparison with online commerce data of the benchmark target (“compared to the benchmark target”), and the predetermined business strategy for the business problem and the business strategy of the benchmark target (“business strategy”). ) is provided. For example, referring to FIG. 6 , the analysis device 110 diagnoses that there is a business problem in the funnel analysis result and customer lifetime value by integrating business indicators and benchmark indicators obtained from online commerce data for a specific company, and , it is possible to diagnose specific business problems for each index using the results of funnel analysis and data analysis corresponding to customer lifetime value. Then, a business strategy is recommended by obtaining a business strategy related to a business problem and a business strategy of a benchmark target, determining information on each business strategy and priorities among them, and recommending a business strategy for each business problem. A business strategy to be finally performed by being selected from may be determined.

Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art to which the present invention pertains can be implemented in other specific forms without changing the technical spirit or essential features of the present invention. you will be able to understand Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

100: Business analysis information provision system
110: business analysis information providing device
111: processor
112: memory
120: online commerce data providing device
130: user terminal

Claims (11)

In the business analysis information providing method performed by the business analysis information providing device,
collecting and merging online commerce data;
Based on the online commerce data, determining a benchmark target according to a predetermined benchmark purpose; and
The method of providing business analysis information comprising providing information of the benchmark object or providing information obtained by comparing and analyzing online commerce data of the benchmark object and online commerce data of a specific company.
The method of claim 1, wherein collecting and merging the online commerce data comprises:
Obtaining online commerce data by date from at least one online mall in which a specific company is located;
converting the item name by analyzing each item included in the acquired online commerce data and determining one of preset item names; and
and loading pre-stored online commerce data and the acquired online commerce data for each online mall according to the converted item name.
The method of claim 2, wherein converting the item name comprises:
determining an item name of each item included in the acquired online commerce data;
analyzing characteristics of the item name or item value if the determined item name does not match the item name of the pre-stored online commerce data;
determining one of the pre-stored online commerce data item names based on the characteristics; and
and learning an item name of online commerce data based on the determined item name and the determined item name.
The method of claim 1, wherein determining the benchmark target,
Setting at least one criterion of industry type, sales level, and purchase cycle; and
The method of providing business analysis information comprising the step of determining a benchmark target by filtering the online commerce data according to the set criteria.
The method of claim 4, wherein the step of setting the standard,
receiving a selection of at least one criterion from among a type of industry, a sales level, and a purchase cycle from a user of the specific company;
If the selected criterion is an industry, setting an industry classified into the same or similar range as the industry of the specific company as a reference value; and
If the selected criterion is the sales level or purchase cycle, setting the reference value to be similar to or higher than the current value of the sales level or purchase cycle of the specific company,
The method of providing business analysis information, characterized in that whether the similarity or increase and the range of similarity or increase compared to the current value are determined by the user.
The method of claim 1, wherein providing the information comprises:
extracting online commerce data collected by date for the benchmark object and loaded by online mall;
merging the extracted online commerce data into one;
extracting a benchmark indicator from the merged online commerce data; and
Including providing information on the benchmark indicator,
The benchmark indicator is at least one of sales by period, sales by purchase channel, sales by order method, number of orders, purchase cycle, repurchase rate, unit price per customer, user log, customer lifetime value, review conversion rate, friend recommendation rate, and purchase conversion rate. A method of providing business analysis information, characterized in that corresponding to one.
The method of claim 1, wherein providing the information comprises:
Comparing online commerce data of the benchmark target with online commerce data of the specific company;
Determining the business problem of the specific company according to the comparison result; and
and recommending a business strategy of the benchmark target in order to solve the business problem and providing expected results according to the strategy.
The method of claim 7, wherein the step of recommending the business strategy and providing expected performance comprises:
specifying a time when a problem identical to or similar to a business problem of the specific company appears and a time when the problem does not appear after the corresponding time from the online commerce data of the benchmark target;
Analyzing online commerce data of the benchmark target between the two periods to analyze a strategy of the benchmark target for solving the problem; and
A method of providing business analysis information comprising the step of providing change information of the analyzed benchmark target strategy and performance indicators of the benchmark target according to the strategy.
According to claim 7,
acquiring performance indicators for the performance of the business strategy for each period;
comparing the performance indicator with the expected performance to determine the effectiveness of the strategy; and
Business analysis information providing method comprising the step of learning a business strategy based on the business strategy, the degree of effectiveness of the business strategy, the determined business problem, and the type of business, sales level, and purchase cycle of the specific company. .
a memory that stores one or more instructions; and
a processor to execute the one or more instructions stored in the memory;
The processor performs the method of claim 1 by executing the one or more instructions.
A computer program stored in a computer-readable recording medium to be combined with a computer, which is hardware, to perform the method of claim 1.

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