KR102452485B1 - Sales data analysis method and apparatus - Google Patents

Abstract

The present invention discloses a sales data analysis method and apparatus. The present invention stores sales data and, at the request of the user terminal, performs data analysis from various angles according to various variables such as products, sales channels, and buyers in various ways and provides them to the user, thereby providing the user with sales data that is more than a simple sum of sales. It can provide hidden information on the back of the product and provide more efficient information about the market situation in which the product is distributed.

Description

Sales data analysis method and apparatus

The present invention relates to a sales data analysis method and apparatus, and more specifically, to a sales data analysis method and apparatus for providing a user by analyzing sales data from various angles according to various variables such as market flow, product, sales channel, and buyer. is about

In various business fields that sell products, actual sales data is the most important information for diagnosing business conditions and reading market trends. However, in the related art, the sum of sales calculated by accumulating the purchase amounts of sales data for a certain period of time and the sum of sales by region calculated by accumulating sales data by sales region are merely provided as statistical information.

This prior art simply reduces the effort of users manually calculating the sales data, but does not provide meaningful information to the business operator that is hidden behind the sales data.

An object of the present invention is to provide a sales data analysis method and apparatus that can analyze sales data from various angles according to various variables, such as products, sales channels, and buyers, and provide them to users.

A sales data analysis method performed by a sales data analysis device according to a preferred embodiment of the present invention for solving the above-described problems includes: (a) the sales data analysis device receives sales data from sales servers and stores the sales data in a memory to do; (b) transmitting, by the sales data analysis device, an analysis service use menu to a user terminal and outputting the menu; (c) when receiving selection information for the analysis menu from the user terminal, the sales data analysis device displays a condition setting page for setting the conditions required for the analysis service item selected by the user on the user terminal, Receiving an analysis condition from the terminal; and (d) generating, by the sales data analysis apparatus, the analysis data by analyzing the data stored in the memory according to the analysis conditions set by the user terminal, and transmitting and displaying the analysis data to the user terminal. .

In addition, in step (d), the sales data analysis device generates a product creation rate indicating a ratio of sales of new products first released in a period selected by the user terminal to sales of all products belonging to the category in which the new products are included. , and the extinction rate of products representing the proportion of sales of discontinued products in the sales of all products belonging to the category including the discontinued product in the period selected by the user terminal, respectively, are calculated and provided to the user terminal as the analysis data can do.

Also, in step (d), the sales data analysis apparatus compares the product creation rate and the product extinction rate with the average product creation rate and the average product extinction rate of all products of the item to which the product belongs, respectively, and classifies it into four sections A category dynamic index may be generated and provided to the user terminal.

In addition, in step (d), the sales data analysis device calculates a brand growth index and a brand competitiveness index for the item and brand selected by the user terminal, and calculates the brand growth index and the brand competitiveness index for the entire item. By comparing the brand growth index average for the brand and the brand competitiveness index average, respectively, brand evaluation information classified into four sections may be generated and provided to the user terminal.

In addition, in step (d), the brand growth index is calculated as the ratio of the average monthly sales of the brand product in the current year to the average monthly sales of the brand product in the previous year, and the brand competitiveness index corresponds to the sales of all brand products It can be calculated as a percentage of sales of branded products.

On the other hand, a computer program according to a preferred embodiment of the present invention for solving the above-described problems is stored in a non-transitory storage medium and executed in a computer including a processor to perform the sales data analysis method described above.

On the other hand, the sales data analysis apparatus according to a preferred embodiment of the present invention for solving the above problems is a sales data analysis apparatus including a processor and a memory for storing predetermined instructions, and executing the instructions stored in the memory. The processor may further include: (a) receiving sales data from the sales servers and storing the sales data in the memory; (b) transmitting and outputting an analysis service use menu to the user terminal; (c) when receiving the selection information for the analysis menu from the user terminal, by displaying a condition setting page for setting the conditions necessary for the analysis service item selected by the user to the user terminal, receiving the analysis conditions from the user terminal step; and (d) analyzing the data stored in the memory according to the analysis conditions set by the user terminal to generate analysis data, and transmitting and displaying the analysis data to the user terminal to perform sales data analysis .

In addition, in step (d), the product creation rate indicating the ratio of sales of new products first released in the period selected by the user terminal to the sales of all products belonging to the category in which the new products are included, and the period selected by the user terminal The extinction rate of each product representing a ratio of sales of discontinued products to sales of all products belonging to a category including the discontinued product may be calculated and provided to the user terminal as the analysis data.

In addition, in step (d), the product creation rate and the product extinction rate are compared with the average product creation rate and the average product extinction rate of all products of the item to which the product belongs, respectively, to create a category dynamic index divided into four sections. It can be provided to the user terminal.

In addition, in step (d), the brand growth index and brand competitiveness index for the items and brands selected by the user terminal are calculated, and the brand growth index and the brand competitiveness index are averaged over the brand growth index for all brands of the item. and brand competitiveness index average, it is possible to generate brand evaluation information classified into four sections and provide it to the user terminal.

In addition, in step (d), the brand growth index is calculated as the ratio of the average monthly sales of the brand product in the current year to the average monthly sales of the brand product in the previous year, and the brand competitiveness index corresponds to the sales of all brand products It can be calculated as a percentage of sales of branded products.

The present invention stores sales data and, at the request of the user terminal, performs data analysis from various angles according to various variables such as products, sales channels, and buyers in various ways and provides them to the user, thereby providing the user with sales data that is more than a simple sum of sales. It can provide hidden information on the back of the product and provide more efficient information about the market situation in which the product is distributed.

Specifically, most products have a certain life span of new product launch and decline, but in practice, it was not easy to distinguish product life stages. Therefore, it is possible to support product development establishment and marketing decision-making by automatically diagnosing the category dynamic index stages (Launching, Growing, Maturing, Declining) in the market by calculating the new product creation rate and product extinction rate index.

In addition, before executing the business portfolio strategy, the BCG matrix was used as an evaluation technique to analyze the position and performance of the current business unit in order to make a decision on the retention or withdrawal of the business unit in consideration of the strategic aspects of the business unit currently in operation. , there were difficulties in interpreting the competitive situation and the benchmarking brand. Accordingly, it is possible to support relative brand competitiveness diagnosis and brand portfolio management through intuitive brand diagnosis (New Star Brand, Driver Brand, Mega Brand, Slugglish Brand) based on the growth index of various brands in the market and their position relative to the average market share.

1 is a view for explaining an overall connection relationship between a sales data analysis apparatus and a user terminal according to a preferred embodiment of the present invention.
2 is a block diagram showing a detailed configuration of a sales data analysis apparatus according to a preferred embodiment of the present invention.
3 is a flowchart illustrating a sales data analysis method according to a preferred embodiment of the present invention.
4A to 8B are diagrams for explaining an example of sales data analysis according to a preferred embodiment of the present invention.

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

1 is a view for explaining the overall connection relationship between the sales data analysis apparatus 200 and the user terminal 300 according to a preferred embodiment of the present invention.

Referring to FIG. 1 , an apparatus 200 for analyzing sales data according to a preferred embodiment of the present invention is connected to a plurality of sales servers 100 and user terminals 300 through a wired/wireless communication network, and the sales servers 100 ) receives the sales data, processes the sales data to generate sales analysis information, and provides it to the user terminals 300 .

In addition, the sales servers 100 receive a purchase request from a plurality of purchaser terminals 400 through a wired/wireless communication network, perform sales, generate sales data, and provide the sales data analysis apparatus 200 . Also, the sales servers 100 may be connected to the sales terminals 500 through a wired/wireless communication network to receive and store sales data from the sales terminals 500 .

In a preferred embodiment of the present invention, the sales servers 100 are implemented as servers that operate online open markets (Gmarket, 11st, Interpark, Amazon, etc.) and individual online sales sites, but are not limited thereto.

The user terminals 300 are implemented as information communication devices capable of accessing the sales data analysis device 200 through a wired/wireless communication network. The user terminals 300 are manipulated by users who use the sales data analysis service of the present invention, and transmit selection information on a service to be provided to the sales data analysis device 200 , and the sales data analysis device 200 . Receive analysis data from and display it to the user.

2 is a block diagram showing a detailed configuration of a sales data analysis apparatus 200 according to a preferred embodiment of the present invention.

Referring to FIG. 2 , the sales data analysis apparatus 200 according to the preferred embodiment of the present invention includes a communication module 210 , a processor 230 , and a memory 220 .

The memory 220 is installed in the processor 230 to store program codes and instructions capable of performing the operation of the sales data analysis apparatus 200 , and to receive information received from the sales servers 100 through the communication module 210 . Store sales data. In addition, the memory 220 stores the data processed by the processor 230 and the analysis data generated by the processor 230 according to the present invention.

The communication module 210 communicates with the sales servers 100 and the user terminals 300 through a wired/wireless communication network, receives sales data from the sales servers 100 , and receives the processor 230 and the memory 220 . and transmits the analysis data input from the processor 230 to the user terminals 300 .

The processor 230 executes program codes and instructions stored in the memory 220 to control the above-described components to execute the functions of the present invention. Specifically, the processor 230 stores the sales data received from the sales servers 100 in the memory 220 , and transmits an analysis menu to the user terminals 300 to receive selection information from the user terminals 300 . Receive, generate analysis data by analyzing sales data according to the selection information, and store the analysis data in the memory 220 and provide the analysis data to the user terminals 300 .

An analysis process performed by the processor 230 of the present invention on sales data will be described in detail with reference to FIGS. 3 and 4A to 8B .

3 is a flowchart illustrating a sales data analysis method according to a preferred embodiment of the present invention, and FIGS. 4A to 8B are views illustrating an example sales data analysis method according to a preferred embodiment of the present invention.

Hereinafter, a function of the sales data analysis apparatus 200 and a sales data analysis method according to a preferred embodiment of the present invention will be described with further reference to FIGS. 3 and 4A to 8B . Here, it should be noted that the functions performed by the sales data analysis apparatus 200 are substantially functions performed by the processor 230 therein.

First, the sales data analysis apparatus 200 receives and stores sales data from the sales servers 100 ( S310 ). The sales data analysis method of the present invention continuously collects and stores sales data from the sales servers 100 because the reliability of the analysis data increases as the number of sales data to be analyzed increases.

In addition, the sales data stored in step S310 basically include the following information as field items, and additional information may be included in some embodiments.

[Sales Date, Sales Time, Sales Region, Product Classification (Item), Product Unique Number, Brand, Price, Sales Channel (Site), Buyer Identification Information, Buyer Age, Buyer Gender, Buyer’s Residence Area]

If the user terminal 300 accesses the sales data analysis apparatus 200 while the above-described step S310 is continuously performed, the sales data analysis apparatus 200 returns to the user terminal 300 the analysis service use menu of the present invention. is transmitted and output (S320). Analysis service menu items displayed on the user terminal 300 include product (item) analysis, brand analysis, sales channel analysis, buyer analysis, and comparative analysis items, each of which will be described later.

Upon receiving the selection information for the analysis menu from the user terminal 300, the sales data analysis apparatus 200 displays a condition setting page for setting the conditions required for the analysis service item selected by the user to the user terminal 300, An analysis condition is received from the terminal 300 (S330).

Thereafter, the sales data analysis apparatus 200 analyzes the data stored in the memory 220 according to the analysis conditions set by the user terminal 300 to generate analysis data (S340), and transmits the analysis data to the user terminal 300 (S340). is transmitted and displayed (S350).

Hereinafter, analysis data generated in step S340 and distributed in step S350 will be described with reference to FIGS. 4A to 8B .

First, in step S330 , when the user terminal 300 selects “product (item or category) analysis” from the main analysis menu and selects “market size change analysis” as a sub-analysis menu, the sales data analysis device 200 ) is the classification condition (large, medium, small), period condition (year, quarter, month, day, direct input), buyer condition (gender) for market size change analysis of product (item), as shown in FIG. 4a , age) is displayed on the user terminal 300 .

When the user terminal 300 sets the corresponding condition, the processor 230 reads sales data satisfying the corresponding condition from the memory 220 to generate analysis data, and transmits the analysis data to the user terminal 300 to output do. In the example shown in FIG. 4A , the daily or monthly sales volume or sales amount is displayed as a line graph according to the selection of the user terminal 300 . Of course, the shape of the graph may be modified in various ways.

On the other hand, when the user terminal 300 selects "product (item or category) analysis" from the main analysis menu and selects "item (category) growth rate analysis" as a sub analysis menu, the sales data analysis apparatus 200 is shown in FIG. As shown in 4b, the user can select the classification condition (large, medium, small), period condition (year, quarter, month, day, direct input), and buyer condition (gender, age) for growth rate analysis as shown in 4b. displayed on the terminal 300 .

When the user terminal 300 sets the corresponding condition, the processor 230 reads sales data satisfying the corresponding condition from the memory 220 to generate analysis data, and transmits the analysis data to the user terminal 300 to output do. In the example shown in FIG. 4B , the sales data analysis apparatus 200 sets a classification condition (large-cosmetics all) according to the selection of the user terminal 300 to display the monthly sales volume in a bar graph, and the sales volume growth rate is a line Displayed in a graph. Of course, the shape of the graph may be modified in various ways, and the sales growth rate may be displayed.

In the same way, as shown in Fig. 4c, the user terminal 300 selects "product (item or category) analysis" from the main analysis menu, and selects "item (category) share analysis" as the sub analysis menu, , when a middle-category (eg, lip cosmetics) is selected as the classification condition, the sales data analysis apparatus 200 reads data satisfying the condition from among the sales data stored in the memory 220 , and for each detailed item for each period After summing the sales and summing the sales of all lip cosmetics, the proportion of sales of detailed items in the total sales is calculated, and the share of each item in the period is calculated and output to the user terminal 300 and displayed. In the example shown in FIG. 4C , for convenience of explanation, the occupancy rates of only two detailed items are displayed, but of course, more items may be added.

Similarly, as shown in FIG. 4D , the user terminal 300 selects “Product (item or category) analysis” from the main analysis menu, selects “Analyze most sold products” as a sub-analysis menu, and the analysis period and When a classification condition is selected, the sales data analysis apparatus 200 reads data satisfying the condition among the sales data stored in the memory 220, selects the top products sold the most in the corresponding period, and selects the user terminal 300 Print it out and display it. In the example shown in FIG. 4D, the graph area is divided to occupy an area ratio corresponding to the sales volume of the product, and the product name and sales volume are displayed in the corresponding zone. of course there is

On the other hand, when the user terminal 300 selects "product (item or category) analysis" from the main analysis menu, selects "product creation rate/extinction rate analysis" as a sub-analysis menu, and selects the analysis period and classification conditions, sales The data analysis apparatus 200 reads data satisfying a condition from among the sales data stored in the memory 220 .

In this case, the product creation rate refers to the ratio of the sales of new products launched for the first time in the corresponding period to the sales of all products belonging to the category in which the new products are included. The product extinction rate represents the ratio of sales of discontinued products in the relevant period to sales of all products belonging to the category in which the product is included.

The user can predict growth potential and determine the position in the product life cycle through the diagnosis of the relevant market from the product creation rate and product extinction rate. A high product creation rate can be viewed as a market where new products and product expansion are high, so new product development and product expansion strategies are needed. On the other hand, in the case of a market with a high product extinction rate, a market with a high number of declining products requires brand portfolio management or abolition of weak products to maintain market share.

The sales data analysis apparatus 200 calculates a product creation rate and a product extinction rate for each product category according to a condition selected by the user, and transmits the calculation to the user terminal 300 for display. In the example shown in FIG. 4E, in the case of a product lip lacquer, it can be seen that the product creation rate is relatively high (2nd overall) and the product extinction rate is relatively low (6th overall), which indicates that the lip lacquer market is in the early stage of the market. Launching can be diagnosed. In the case of the initial market launch (launching), it refers to the market that requires efforts to recognize and use the product as a product introduction period.

In addition, the sales data analysis apparatus 200 generates a category dynamic index using the calculated product creation rate and product extinction rate, and transmits it to the user terminal 300 for display.

The category dynamic index means that the product creation rate and product extinction rate are compared with the average product creation rate and product extinction rate of all products of the item to which the product belongs, and classified into four sections as shown in Table 1 below.

Product creation rate Product extinction rate section above average below average Launching (initial market) above average above average Growing (growth market) below average above average Declining (declining market) below average below average Maturing (maturity market)

The category dynamic index sets the product creation rate as an X-axis coordinate value, and sets the product extinction rate as a Y-axis coordinate value, and displays the current location of each product in any one of the 1st to 4th quadrants and can be displayed on the user terminal, Each quadrant is divided with the average value of the product creation rate and product extinction rate as the central axis.

In the fourth quadrant, the product creation rate is higher than the average but the product extinction rate is lower than the average, indicating the initial stage of the market (initial market). Quadrant 1 is an area with high product creation rate and high product extinction rate, indicating a growing market (growth market) and a highly competitive market situation. Quadrant 2 is an area where product creation rate is low and product extinction rate is high, indicating a declining market (declining market) because there are few new products launched and many products exiting the market, indicating the need for cost reduction efforts. Quadrant 3 is an area with low product creation rate and low product extinction rate, indicating a late acceptance market (mature market) that has reached maturity.

In the example shown in FIG. 4E , it can be seen that lipstick is located in a growing market, lip lacquer is in an early market, lip balm is in a declining market, and lip gloss, lip liner, and lip tint are located in a mature market.

On the other hand, when the user terminal 300 selects “product (item or category) analysis” from the main analysis menu, selects “category view map” as a sub-analysis menu, and selects the analysis period and classification condition, sales data analysis The device 200 reads data satisfying a condition from among the sales data stored in the memory 220 .

Thereafter, the sales data analysis apparatus 200 calculates a sales growth index and a sales growth index for the corresponding products as in the example shown in FIG. 4f , sets the X-axis for each product as a sales growth index, and Y The axis is mapped on the area (category map) set as the sales growth index and displayed on the user terminal 300 .

The sales growth index is calculated by dividing the sales amount for a certain period (monthly or yearly) at the current time by the sales amount for a certain period (monthly or yearly) at the base point (for example, one year ago), which indicates how much sales have increased compared to the reference point. .

Similarly, the sales growth index is calculated by dividing the sales volume over a period of time (monthly or yearly) at the current point in time by the sales volume over a period (monthly or yearly) at a base point (eg, one year ago), which is how much sales have increased compared to the base point in time. indicates what has been done.

This category map is divided into four quadrants with the average of the sales growth index and the average of the sales growth index as central axes, and each quadrant intuitively shows the market situation. For example, the first quadrant is a market in which the sales volume and sales amount of products increase at the same time, indicating that the qualitative growth of the market itself is expected. This indicates that competition is expected to intensify. In addition, the third quadrant is a market in which the sales volume and sales amount of products decrease at the same time, indicating a situation in which a market contraction is inevitable. indicates that

Meanwhile, in step S330 , when the user terminal 300 selects “brand analysis” from the main analysis menu and “brand share analysis” as a sub-analysis menu, the sales data analysis apparatus 200 is shown in FIG. 5A . As shown above, the user terminal displays a screen to select classification conditions (large, medium, small), period conditions (year, quarter, month, day, direct input), and buyer conditions (gender, age) for analysis of market share by brand as described above. (300) is indicated.

When the user terminal 300 sets the corresponding condition, the processor 230 reads sales data satisfying the corresponding condition from the memory 220 to generate analysis data, and transmits the analysis data to the user terminal 300 to output do. In the example shown in FIG. 5A , a daily or monthly sales amount or sales volume line graph for each brand is displayed on the user terminal 300 as analysis data according to the selection of the user terminal 300 . Of course, the shape of the graph may be modified in various ways.

In the same manner, when the user terminal 300 selects “Brand analysis” from the main analysis menu and “Best selling brand analysis” as the sub analysis menu, the sales data analysis device 200 is as shown in FIG. 5B . Similarly, according to the user's selection, the brands from the first place to a predefined rank are selected according to the sales volume or sales amount ranking, and transmitted to the user terminal 300 for display.

In addition, in the same manner, when the user terminal 300 selects “Brand Analysis” from the main analysis menu and “Market Concentration Analysis” as the sub-analysis menu, the sales data analysis apparatus 200 is shown in FIG. 5C . As shown above, the sales volume or sales amount of all brand products included in the category selected by the user is cumulatively summed from the 1st place according to the sales volume or sales amount ranking, and the cumulative amount is displayed in a graph, and 80% of the total sales amount or total sales amount is displayed. By marking the intervals, it is possible to intuitively check whether the total sales or the majority (80%) of sales are concentrated in a few branded products. As the upward slope of the market concentration graph as shown in FIG. 5C becomes gentle, the sales volume or sales amount is distributed among a plurality of brand products, which means that the market concentration is low.

On the other hand, in step S330, when the user terminal 300 selects “brand analysis” from the main analysis menu and “brand view map analysis” as a sub-analysis menu, the sales data analysis apparatus 200 is as described above. In the same way, a screen where you can select item classification conditions (large, medium, small), period conditions (year, quarter, month, day, direct input), and buyer conditions (gender, age) for brand-specific view map analysis is displayed on the user terminal 300 .

When the user terminal 300 sets the corresponding condition, the processor 230 reads the sales data satisfying the corresponding condition from the memory 220 to generate the brand competitiveness (MS) index and the brand growth index as analysis data, and the brand By comparing the growth index and the brand competitiveness index with the brand growth index average and the brand competitiveness index average for all brands of the item, respectively, as shown in Table 2, brand evaluation information classified into four sections is generated, FIG. 5D As shown in , it is transmitted and output as analysis data to the user terminal 300 .

Brand Competitiveness Index Brand Growth Index section above average below average Maga Brand above average above average Driver Brand below average above average NEW STAR Brand below average below average Sluggish Brand

In the example shown in FIG. 5D , the brand competitiveness (MS) index represents the ratio of sales of the brand product to the sales of all brand products as the share of each brand product, and the brand growth index is the average monthly sales of the brand product in the previous year. It represents the ratio of the average monthly sales of the brand product in the year.

The brand view map is divided into four quadrants with the average value of the brand competitiveness (MS) index and the brand growth index as the central axis, and each quadrant intuitively shows the position of the brand product in the market.

For example, a brand product belonging to the first quadrant (Driver Brand) is a brand that has a high market share and has grown higher than the average. Brand products belonging to the second quadrant (NEW STAR Brand) have a low market share but are growing higher than the average, which is interpreted as attracting attention as a new emerging brand in the market.

In addition, brand products belonging to the third quadrant (Sluggish Brand) have a low market share and a low growth rate compared to the average. Brand products belonging to Quadrant 4 (Maga Brand) have a high market share but a low growth rate compared to the average, which is interpreted as a mass brand with high brand competitiveness in the market.

On the other hand, in step S330, when the user terminal 300 selects "channel analysis" from the main analysis menu and "channel weight analysis" as a sub analysis menu, the sales data analysis apparatus 200 is the same as described above. In this way, a screen to select classification conditions (large, medium, small), period conditions (year, quarter, month, day, direct input), buyer conditions (gender, age), brand and manufacturer, etc. is displayed on the user terminal (300). ) is indicated in

When the user terminal 300 sets the corresponding condition, the processor 230 reads the sales data satisfying the corresponding condition from the memory 220 and sums the sales amount or sales amount of all sales data satisfying the corresponding condition, where, The sales amount or sales ratio for each sales channel is generated as analysis data, and as shown in FIG. 6A , it is transmitted and output as analysis data to the user terminal 300 . By checking the weight of each channel, the user can know through which sales channel buyers make purchases for each product item and each brand.

In the same way, when the user terminal 300 selects "channel analysis" from the main analysis menu, selects "analyze the most sold products by channel" as a sub analysis menu, and sets the above conditions and a specific channel, FIG. As shown in 6b, the most sold product in the corresponding channel can be inquired.

Similarly, when the user terminal 300 selects "channel analysis" from the main analysis menu, selects "analysis of the most sold brands by channel" as a sub analysis menu, and sets the above conditions and a specific channel, in FIG. 6c As shown, the most sold brand in the corresponding channel can be inquired.

On the other hand, in step S330, when the user terminal 300 selects "Buyer Analysis" from the main analysis menu and selects "Brand Buyer Analysis" or "Buyer Analysis by Channel" as sub analysis menus, it is shown in FIG. 7A . As described above, analysis data is generated and provided to the user terminal so that the proportion of buyers by gender and the proportion of buyers by age can be checked for each brand or each channel.

In addition, in step S330 , when the user terminal 300 selects “buyer analysis” from the main analysis menu and selects “purchase number and amount analysis” as sub analysis menus, as shown in FIG. 7b , 1 Analysis data is generated and provided to the user terminal so that the average number of purchases per person and the average purchase amount per person can be checked.

In addition, when the user terminal 300 selects “Buyer Analysis” from the main analysis menu and “Customer Propensity Analysis” as the sub analysis menus, as shown in FIG. 7C , according to the purchase amount and purchase amount of the customers, The customer's tendency is classified into Heavy-Mid-Light and High-Med-Low, respectively, and the purchaser's tendency is displayed according to the condition (eg, channel, brand, region, etc.) selected by the user terminal 300 .

In addition, in step S330 , when the user terminal 300 selects “Buyer Analysis” from the main analysis menu and selects “Growth Index Analysis by Region” as the sub analysis menus, as shown in FIG. 7D , each region By calculating the sales volume or sales amount at the time of analysis compared to the sales volume or sales amount at the reference point, the sales volume growth index or sales growth index is generated as analysis data, and the growth index for each region is classified into increase, similarity, and decrease grades and each other according to the grade It may be displayed in a different color and provided to the user terminal 300 .

Finally, in step S330, the user terminal 300 selects “comparative analysis” from the main analysis menu, and uses “market share analysis by brand”, “channel analysis by brand”, and “maximum by brand” as sub analysis menus. When selecting "comparison of products for sale", "comparison of customers by brand", etc., the sales data analysis apparatus 200 displays a selection page so that the user terminal 300 can select a brand to compare and set conditions for items to be compared by brand. provided, and when the user terminal 300 selects the conditions, analysis data is generated according to the selection conditions and displayed on the user terminal 300 .

Specifically, referring to FIG. 8A , the sales data analysis apparatus 200 may compare and display the market shares of the brands selected by the user terminal 300 and the items selected by the user by month.

Also, as shown in FIG. 8B , the sales data analysis apparatus 200 may compare and display market shares for brands selected by the user terminal 300 and items selected by the user for each sales channel.

In addition, for the brands selected by the user terminal 300 , the sales data analysis apparatus 200 may compare and display the most sold products of each brand on the user terminal 300 , and the characteristics of the purchaser for each brand may be compared with each other and displayed on the user terminal 300 .

The sales data analysis method according to the preferred embodiment of the present invention described so far may be implemented as a computer program stored in a non-transitory storage medium by being implemented as instructions executable by a computer.

The storage medium includes all kinds of recording devices in which data that can be read by a computer system is stored. Examples of computer-readable storage media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage device. In addition, the computer-readable storage medium is distributed in networked computer systems, so that the computer-readable code can be stored and executed in a distributed manner.

So far, with respect to the present invention, the preferred embodiments have been looked at. Those of ordinary skill in the art to which the present invention pertains will understand that the present invention may be implemented in a modified form without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments are to be considered in an illustrative rather than a restrictive sense. The scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the scope equivalent thereto should be construed as being included in the present invention.

100 : Sales Server
200: sales data analysis device
210: communication module 220: memory
230: processor
300: user terminal
400: buyer terminal
500: sales terminal

Claims (11)

A sales data analysis method performed in a sales data analysis device, comprising:
(a) receiving, by the sales data analysis device, sales data from sales servers and storing the sales data in a memory;
(b) transmitting, by the sales data analysis device, an analysis service use menu to a user terminal and outputting the menu;
(c) when receiving selection information for the analysis menu from the user terminal, the sales data analysis device displays a condition setting page for setting the conditions required for the analysis service item selected by the user on the user terminal, Receiving an analysis condition from the terminal; and
(d) generating, by the sales data analysis device, analyzing data stored in the memory according to the analysis conditions set by the user terminal, and transmitting and displaying the analysis data to the user terminal;

In step (d), the sales data analysis device
Product creation rate indicating the ratio of the sales of new products initially released in the period selected by the user terminal to the sales of all products belonging to the category in which the new products are included; and
The extinction rate of products representing the ratio of sales of discontinued products in the period selected by the user terminal to sales of all products belonging to the category including the discontinued product is calculated, respectively, and provided to the user terminal as the analysis data,
By comparing the product creation rate and the product extinction rate with the average product creation rate and the average product extinction rate of all products of the item to which the product belongs, respectively, a category dynamic index divided into four sections is generated and provided to the user terminal;

In step (d), the sales data analysis device
The brand growth index and brand competitiveness index for the items and brands selected by the user terminal are calculated, and the brand growth index and the brand competitiveness index are compared with the average brand growth index and brand competitiveness index average for all brands of the item, respectively. , creates brand evaluation information classified into 4 sections and provides it to the user terminal,
The brand growth index is calculated as the ratio of the average monthly sales of the brand product in the current year to the average monthly sales of the brand product in the previous year,
The brand competitiveness index is a sales data analysis method, characterized in that calculated as a ratio of the sales of the brand products to the sales of the total brand products. delete delete delete delete A computer program stored in a non-transitory storage medium and executed in a computer including a processor to perform the sales data analysis method of claim 1 .
A sales data analysis device comprising a processor and a memory for storing predetermined instructions, the device comprising:
The processor executing the instructions stored in the memory
(a) receiving sales data from sales servers and storing the sales data in the memory;
(b) transmitting and outputting an analysis service use menu to the user terminal;
(c) when receiving the selection information for the analysis menu from the user terminal, by displaying a condition setting page for setting the conditions necessary for the analysis service item selected by the user to the user terminal, receiving the analysis conditions from the user terminal step; and
(d) generating analysis data by analyzing the data stored in the memory according to the analysis conditions set by the user terminal, and transmitting and displaying the analysis data to the user terminal;

In step (d)
Product creation rate indicating the ratio of the sales of new products initially released in the period selected by the user terminal to the sales of all products belonging to the category in which the new products are included; and
The extinction rate of products representing the ratio of sales of discontinued products in the period selected by the user terminal to sales of all products belonging to the category including the discontinued product is calculated, respectively, and provided to the user terminal as the analysis data,
By comparing the product creation rate and the product extinction rate with the average product creation rate and the average product extinction rate of all products of the item to which the product belongs, respectively, a category dynamic index divided into four sections is generated and provided to the user terminal;

In step (d),
The brand growth index and brand competitiveness index for the items and brands selected by the user terminal are calculated, and the brand growth index and the brand competitiveness index are compared with the average brand growth index and brand competitiveness index average for all brands of the item, respectively. , creates brand evaluation information classified into 4 sections and provides it to the user terminal.
The brand growth index is calculated as the ratio of the average monthly sales of the brand product in the current year to the average monthly sales of the brand product in the previous year,
The brand competitiveness index is a sales data analysis device, characterized in that calculated as a ratio of the sales of the brand product to the sales of the entire brand product. delete delete delete delete

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