KR102084719B1 - Sales forecast information providing system - Google Patents

Abstract

The present invention relates to a sales prediction information providing system for more accurately predicting consumer demand to help sellers to establish sales plans. According to an embodiment of the present invention, the sales prediction information providing system comprises: a seller device; a purchaser device; and a server. The seller device transmits sales plan information, sales product information and seller information to the server, the purchaser device accesses the server to view and evaluate the sales plan information registered by a plurality of seller devices and transmits a search record and a purchase request for an actual sale product registered by the seller to the server, and the server calculates the sales prediction information based on information received from the seller device and information received from the purchaser device and provides the calculated information to the seller device.

Description

Sales forecast information providing system

The present invention relates to a system for predicting sales demand and calculating sales-related information based on the demand, thereby providing the sales forecast information to the seller.

Sellers in the conventional e-commerce market did not perform sales activities in the state of specifically recognizing information related to demand for a specific item, such as consumers' purchase needs, purchasing power, trends, and interests. It is common to simply trade the purchased goods in the market according to the seller's standards, and accordingly, there are many differences between the quantity and type of goods supplied to the market by the seller and the quantity and type of goods actually requested by the buyer. Did.

In particular, if the demand for a specific product fails to predict, and the seller suddenly increases, sales may slow down, and there is a possibility of entering into excessive competition between sellers, and it may be difficult for all sellers to perform sales activities at an appropriate price. Can be.

Likewise, the majority of consumers need it, but as sellers do not recognize it properly, consumers cannot find the specific product items they want in the market.

In order to close such a gap between the consumer and the seller and to achieve a more effective sales behavior, the seller needs to predict the consumer's demand more accurately and establish a sales plan.

Registered Patent 10-1872220 (Network-based sales prediction information providing device)

The system for providing sales prediction information according to an embodiment of the present invention is intended to help the seller establish a sales plan by more accurately predicting consumer demand.

The system for providing sales prediction information according to an embodiment of the present invention includes a seller device, a buyer device, and a server, and the seller device transmits sales plan information, sales item information, and seller information to the server, and the buyer device Accesses the server, reads and evaluates the sales plan information registered by a plurality of seller devices, transmits a search record and a purchase request for the actual sales product registered by the seller to the server, and the server receives from the seller device It is characterized by calculating sales prediction information based on information and information received from the purchaser device, and providing the calculated information to the seller device.

Various embodiments of the present invention can help the seller to more accurately predict the buyer's demand, thereby helping to select a new sales item field and predict the quantity of goods purchased.

According to various embodiments of the present invention, since a buyer performs a natural language-based search for a product that he or she specifically wants, there is an effect of increasing the possibility of reflecting a desired product on a general web compared to a passive product purchase method.

1 is a system diagram showing the configuration of a system according to an embodiment of the present invention.
2 is a view showing the configuration of a server according to an embodiment of the present invention.
3 is a view showing the configuration of a transaction progress support unit according to an embodiment of the present invention.
4 and 5 are diagrams illustrating a flow of operations for providing sales prediction information according to an embodiment of the present invention.

Advantages and features of the present invention, and methods for achieving them will be clarified with reference to embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, and only the present embodiments allow the disclosure of the present invention to be complete, and are common in the technical field to which the present invention pertains. It is provided to fully inform the skilled person of the scope of the present invention, and the present invention is only defined by the scope of the claims.

The terminology used herein is for describing the embodiments and is not intended to limit the present invention. In the present specification, the singular form also includes the plural form unless otherwise specified in the phrase. As used herein, “comprises” and / or “comprising” does not exclude the presence or addition of one or more other components other than the components mentioned. Throughout the specification, the same reference numerals refer to the same components, and “and / or” includes each and every combination of one or more of the components mentioned. Although "first", "second", etc. are used to describe various components, it goes without saying that these components are not limited by these terms. These terms are only used to distinguish one component from another component. Therefore, it goes without saying that the first component mentioned below may be the second component within the technical spirit of the present invention.

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

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

The spatially relative terms “below”, “beneath”, “lower”, “above”, “upper”, etc., are as shown in the figure. It can be used to easily describe a correlation between a component and other components. Spatially relative terms should be understood as terms including different directions of components in use or operation in addition to the directions shown in the drawings. For example, if a component shown in the drawing is turned over, a component described as "below" or "beneath" of another component will be placed "above" the other component. Can be. Accordingly, the exemplary term “below” can include both the directions below and above. The component can also be oriented in other directions, so that spatially relative terms can be interpreted according to the orientation.

In the present specification, the computer means all kinds of hardware devices including at least one processor, and may be understood as a meaning encompassing software configurations operating in the corresponding hardware device according to embodiments. For example, a computer may be understood as meaning including, but not limited to, a smart phone, a tablet PC, a desktop, a laptop, and a user client and application running on each device.

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

1 is a system diagram showing the configuration of a system according to an embodiment of the present invention.

As shown in FIG. 1, a system according to an embodiment of the present invention may include a server 100, a seller device 200, and a buyer device 300. In addition, both the seller device 200 and the buyer device 300 may access the server 100 to transmit and receive commerce related information.

When describing each component, first, the server 100 according to an exemplary embodiment of the present invention derives an agreement related to commerce such as goods or services between the seller device 200 and the buyer device 300, and supports the actual transaction. Can be. In addition, the seller device 200 may receive the sales prediction information calculated by the server 100 and support the seller to establish a strategy based on the received sales prediction information. The sales prediction information calculated by the server 100 may include, for example, items (or services) for sale items, quantity information, marketing information, sales statistics information, and the like. According to various embodiments of the present disclosure, the server 100 may perform a natural language processing operation based on an artificial intelligence algorithm. In addition, the server 100 may analyze a search word in the form of a natural language input by a buyer based on a natural language processing operation, and accordingly may calculate sales prediction information reflecting a buyer's needs. Also, according to various embodiments of the present disclosure, the server 100 may perform a matching operation between the buyer device 300 and the seller device 200 according to a predetermined criterion to support transactions.

In addition, the seller device 200 may receive sales prediction information calculated through a predetermined processing and calculation operation from the server 100, and input sales plan information to the server correspondingly. For example, the seller device 200 may upload to the server 100, including detailed information on items of goods or services to be sold and information on conditions for sale.

According to various embodiments, the sales plan information input by the seller device 200 may be provided to a plurality of purchaser devices 300 side, and accordingly, the buyer may view sales plan information uploaded by a plurality of sellers through the buyer device 300. have.

The buyer device 300 may provide reaction information to sales plan information provided by the server 100. For example, the buyer can check the product information being planned for sale provided by the server 100 in the form of a list, and can vote for or purchase reservations on items of the product they are willing to purchase among the checked product information. have. The server 100 may evaluate and classify the seller's sales plan information based on the buyer's voting information or the purchase reservation information received from the buyer device 300.

In addition, the purchaser device 300 may transmit a purchase request signal for a sale product for which a substantial sale is made to the server 100, and may transmit evaluation information for a corresponding product after the actual purchase is made.

The description of the commerce information recommendation system according to the embodiment of the present invention will be described in more detail through the following drawings.

2 is a view showing the configuration of a server according to an embodiment of the present invention.

As illustrated in FIG. 2, the server 100 according to an embodiment of the present invention may include a communication unit 110, a storage unit 120, and a control unit 130. In addition, the control unit 130 may include a natural language search support unit 131, a sales plan evaluation support unit 132, an external needs reflecting unit 133, a sales prediction information calculation unit 134, and a transaction progress support unit 135.

The communication unit 110 may use a network to transmit and receive data between a user device and a server, and the type of the network is not particularly limited. The network may be, for example, an Internet Protocol (IP) network that provides a large data transmission / reception service through an Internet Protocol (IP) or an All IP network that integrates different IP networks. In addition, the network includes a wired network, a Wibro (Wireless Broadband) network, a mobile communication network including WCDMA, a HSDPA (High Speed Downlink Packet Access) network, and a mobile communication network including a Long Term Evolution (LTE) network, LTE advanced (LTE-A) ), 5G (Five Generation), a mobile communication network, a satellite communication network and a Wi-Fi (Wi-Fi) network, or may be made by combining at least one of them.

The storage unit 120 may include, for example, an internal memory or an external memory. The internal memory includes, for example, volatile memory (for example, dynamic RAM (DRAM), static RAM (SRAM), or synchronous dynamic RAM (SDRAM)), non-volatile memory (for example, OTPROM (one time programmable ROM (PROM), programmable ROM (PROM), erasable and programmable ROM (EPROM), electrically erasable and programmable ROM (EEPROM), mask ROM, flash ROM, flash memory (e.g. NAND flash or NOR flash, etc.), hard drives, Or it may include at least one of a solid state drive (SSD).

The external memory may be a flash drive, such as compact flash (CF), secure digital (SD), micro secure digital (Micro-SD), mini secure digital (SD-SD), extreme digital (XD), It may further include a multi-media card (MMC) or a memory stick. The external memory may be functionally and / or physically connected to the electronic device through various interfaces.

The controller 130 may also be referred to as a processor, a controller, a microcontroller, a microprocessor, or a microcomputer. Meanwhile, the control unit may be implemented by hardware or firmware, software, or a combination thereof.

In the case of implementation by firmware or software, an embodiment of the present invention may be implemented in the form of a module, procedure, function, etc. that performs the functions or operations described above. The software code can be stored in the memory and driven by the control unit. The memory may be located inside or outside the user terminal and the server, and may exchange data with the control unit by various means already known.

Specifically, the control unit 130 may include a natural language search support unit 131, a sales plan evaluation support unit 132, an external needs reflecting unit 133, a sales prediction information calculation unit 134, and a transaction progress support unit 135.

First, the natural language search support unit 131 may collect search words of users (buyers and sellers) who access the app or web supported by the server 100, and in particular, may support natural language search in sentence form as well as word type search terms. . The natural language search may be performed based on a known artificial intelligence-based natural language processing method, and the search word may be classified into items based on the search word or similarity of the natural language processing result.

The natural language search support unit 131 may assist a buyer to input a search word in a sentence form when a clear name for a product to be purchased does not exist or the corresponding name cannot be thought of. Alternatively, the natural language search support unit 131 may support a user to input a search word in a sentence form when a buyer needs to purchase a product but has not decided a specific product. For example, a buyer may enter a search term based on a natural language such as 'a device that automatically replaces a dog's bowel pad' or 'what would be good for a friend's house as a gift' in the search bar. In addition, the natural language search support unit 131 may analyze the content input in the search box and search and display pre-registered sales items corresponding thereto.

In addition, the natural language search support unit 131 not only searches the search word in the form of a sentence input by the buyer in the search box based on the natural language processing operation, but also collects and classifies the search term, and the collected and classified search term related information is later. Provided to the sales prediction information calculation unit 134, it can be used to calculate user interest statistics. To this end, the natural language search support unit 131 may classify search terms collected from all buyers' devices accessing the server 100 (running an application that supports server 100 access) into periods and by buyer characteristics (by gender, age, etc.). have.

In particular, the acquired search term has a purpose to help the seller to establish a sales plan in the future, so the natural language search support unit 131 may perform a purchase operation when a specific product corresponding to the search result is not searched or in response to the search result If not, it can be collected by weighting the number of searches for each.

The sales plan evaluation support unit 132 may perform an evaluation support operation on the sales plan information uploaded by the seller. Specifically, the sales plan evaluation support unit, when the seller inputs sales plan information such as item items to be sold and quantity to be purchased through the seller device 100, and transmits it to the server 100, allows the buyer to evaluate the sales plan information I can apply.

The sales plan evaluation support unit 132 may assist the buyer to perform a mock order to obtain evaluation information from a buyer (eg, a user having a buyer account). For example, when the sales plan evaluation support unit 132 reads the sales plan information, the sales plan evaluation support unit 132 may display a page, a pop-up, and the like inquiring a purchase intention for the corresponding product and induce a mock order to be performed. At this time, the mock order may be performed under the same environment as the actual purchase page, and may be performed by selecting and entering purchase items, purchase quantities, and other requests.

The sales plan evaluation support unit 132 may perform evaluation through direct buyer voting, in addition to the buyer's evaluation method through a mock order. The sales plan evaluation support unit 132 may obtain evaluation information based on the number of votes of a buyer who has a purchase intention, and may determine whether the number of votes is greater than or equal to a reference value according to various embodiments. The sales plan evaluation support unit 132 sends a notification message to encourage the seller who uploaded the sales plan information to proceed with the corresponding sales plan, when the specific sales plan information receives a vote count exceeding an expected threshold set by the seller according to an embodiment. Can provide.

In addition, the sales plan evaluation support unit 132 may provide the sales prediction information calculation unit 134 with respect to the sales plan evaluation information generated through a method such as a mock order and voting. The sales plan evaluation information collected by the sales plan evaluation support unit 132 may be data for calculating the sales forecast information in the sales prediction information calculation unit 134.

In addition, the control unit 130 according to an embodiment of the present invention may be configured to include an external needs reflector 133. The external needs reflector 133 is typing information (text input in a specific area designated by the buyer (eg, SNS, messenger, writing text message, etc.), not on the web or on the app for the buyer to access the server 100 of the present invention) ) And selection information (links, images, selected text, etc.) and based on this, the needs of the buyer can be judged.

Specifically, the external needs reflector 133 first collects the buyer's typing information or selection information in the external area (to refer to other areas other than on the web or the app to access the server 100) with the consent of the buyer. can do. To collect such information, first, the external needs reflector 133 may check whether or not the purchaser is authorized to collect typing information or selection information among external areas.

According to various embodiments of the present disclosure, the external needs reflector 133 is a specific app (eg, a specific messenger app), in which the buyer approves the collection of information in case the user wants to collect information only in a typing action or a selection action performed in a specific app. ) Or a specific type of operation (eg, copy operation after typing).

The external needs reflector 133, when a specific app approved to enable information collection in the external area is executed, collects all typing information written in the app or collects only sentences containing condition words set by the buyer You can specify whether to do it. The external needs reflector 133 may collect the entire typing information based on the purchaser's settings, or may collect only the typing sentence including the condition word.

According to an embodiment of the present disclosure, the external needs reflector 133 may collect a corresponding sentence when input of a sentence containing a condition word is detected after receiving a condition word that is a criterion for collecting typing information. Alternatively, when the input of the condition word is detected, the external needs reflector 133 collects the text including the text within a certain range of the condition word (eg, 5 messages before the message to 5 messages after the condition word). can do. For example, when the word 'need' is pre-registered as a conditional word, the external needs reflector 133 includes the conditional word 'required' there is?' In addition, you can select one of the messages, 'Birthday Gift', as the text to be collected.

The sales prediction information calculation unit 134 statistically combines natural language search results detected by the natural language search support unit 131, evaluation results obtained from the sales plan evaluation support unit 132, and text information collected by the external needs reflector 133, and based on the results You can calculate sales forecast information.

Specifically, the sales prediction information calculation unit 134 may first classify and label information obtained from the natural language search support unit 131, the sales plan evaluation support unit 132, and the external needs reflector 133, respectively.

Thereafter, the sales prediction information calculator 134 may selectively acquire and process some of the acquired data according to the type of sales prediction information to be calculated. The types of sales prediction information calculated by the sales prediction information calculation unit 134 include main seller interest field information of individual sellers, information about expected sales areas of all sellers, main interest information of individual buyers, and interest trend information of all buyers. can do.

In addition, the sales prediction information calculating unit 134 may generate each sales prediction information for various period units, for example, in units of 1 month, 3 months, and 1 year.

According to one embodiment, the sales prediction information calculating unit 134 extracts only information related to information registered by the seller for sale and information related to voting information among a plurality of acquired information when calculating information on a main selling interest of an individual seller. And based on this, statistical data can be generated. As another example, the sales prediction information calculating unit 134 extracts only the typing information of the buyer obtained from the natural language search support unit 131 and the external needs reflector 133 among the plurality of pieces of information obtained from all buyers' interest trend information. You can generate sales forecast statistics. That is, the sales prediction information calculating unit 134 may select and process only some items related to information to be generated among the acquired data, according to the nature of the sales prediction information to be generated.

The sales prediction information calculation unit 134 may analyze and classify sales fields planned by all sellers based on the information obtained from the sales plan evaluation support unit 132, and calculate the number of competitors in the same field and the expected sales size. . Thereafter, the sales prediction information calculating unit 134 calculates an estimated purchase size through buyers 'interests, buyers' purchasing power, purchase trends, etc. through natural language search words, data obtained from buyers, message texts obtained through external applications, and the like. Can be.

The sales prediction information calculation unit 134 compares the calculated expected sales size with the expected purchase size, and if the expected sales size is less than a preset reference value compared to the expected purchase size, the demand is greater than the supply. You can affirm your sales plan. Conversely, the sales prediction information calculating unit 134 may negatively evaluate the seller's sales plan because the supply is greater than the demand when the expected sales size is greater than or equal to a predetermined reference value compared to the expected purchase size.

As described above, the seller can predict the market situation of the field to be sold in the future based on the analysis result through the sales prediction information calculation unit 134, stop the sales plan in the field where the supply is high in demand, and the supply to demand There are many areas where you can change your sales plan.

Further, when calculating the expected sales size, the sales prediction information calculation unit 134 may be data summed up by classifying the size of a sales company performing an actual sales activity and the size of a sales company that has established a sales plan. The size of a previously entered sales company performing an actual sales activity can calculate the sales size based on the amount of the actual transaction, and can also be calculated based on information registered by the seller. In addition, when calculating the estimated sales size information, the sales prediction information calculation unit 134 may add an accuracy weighting value more than a reference value to the size of a company that has established a sales plan without actually selling the sales size of an existing seller.

In addition, the sales prediction information calculating unit 134 may calculate the calculated sales forecast size, and then calculate the individual size of the seller. The sales prediction information calculating unit 134 may extract the number of employees of the seller, annual sales, and the like from the seller registration information and calculate the individual size of the seller based on the extracted sales information.

  In addition, the sales prediction information calculating unit 134 may classify the size of the seller step by step (eg, step 5).

In short, the sales prediction information calculating unit 134 may determine the total number of sellers in a specific sales field, and may determine the number of sellers who have already entered the market and the number of sellers who are planning to enter the total number of sellers. In addition, the sales prediction information calculating unit 134 may determine a seller size stage (eg, 1 stage 1 scale, 2 stages 4 scales, etc.) for each of the previously entered seller and the planned seller.

The sales prediction information calculation unit 134 may calculate and provide various types of threat factors so that a specific seller can identify the threat factors before entering the market. Threat factors may include threats caused by expansion of large business, threats caused by low barriers to entry.

First, the sales prediction information calculation unit 134 may check whether a specific seller requests a threat before entering the market. In response to a specific seller's request for a threat factor, the sales prediction information calculating unit 134 may calculate a threat factor for each type and provide it to the request seller.

First, the sales prediction information calculating unit 134 may determine whether a threat factor exists due to the expansion of the sales size of a large enterprise among a plurality of threat factors, and provide the related information to a seller who has registered a sales plan. The sales prediction information calculating unit 134 is a reference step among sellers who are expected to enter a market (or, for example, three) of a seller having a size greater than or equal to a reference level (eg, four steps) among all sellers, or a seller who is planning to enter the market ( Yes, step 4) If it is determined that a seller of a size greater than or equal to the reference value exists, it may be determined that a threat factor caused by a large company (eg, a threat caused by the expansion of the sales size of the large company) exists. In this case, the reference step and the reference value may be calculated differently according to the overall market size (sales, etc.) of the corresponding sales field. Alternatively, the reference step and the reference value may be calculated differently depending on the type of sales field.

The sales prediction information calculating unit 134 may also determine the presence or absence of a threat factor due to a low entry barrier, which is the total number of sellers, the number of sellers who are going to enter the market, the increase rate of the number of sellers entering the market, and the total sellers. It can be judged based on the ratio of small companies below the reference level.

For example, the sales prediction information calculating unit 134 may correspond to a case of a reference value or higher. According to various embodiments of the present disclosure, the sales prediction information calculating unit 134 may determine that a threat factor due to a low entry barrier exists even when the number of sellers entering the market during the reference time (eg, 1 month) shows an increase over the reference value. .

 In short, the sales prediction information calculation unit 134 may recognize that a specific seller has requested a calculation of a threat factor as a sales plan including information such as a sales field, sales items, and sales scale is registered. In addition, the sales prediction information calculating unit 134 may determine whether a threat factor exists, and when it is determined that the threat factor exists, may provide information related to the threat factor to a seller (request seller) who has registered a sales plan.

 The transaction progress support unit 135 may support the uploading of sale product information, the purchaser's product selection operation, and the purchaser's payment operation so that the seller's actual sale action can be performed.

The transaction progress support unit 135 may be configured as illustrated in FIG. 3.

3 is a view showing the configuration of the transaction progress support unit 135 according to an embodiment of the present invention.

As illustrated in FIG. 3, the transaction progress support unit 135 may include a matching support unit 135a and a transaction execution unit 135b.

The matching support unit 135a may match a buyer who wants to purchase a specific product and a seller who wants to sell a specific product. Similar to the conventional method, the matching support unit 135a may perform a general matching operation that provides a list of sellers and a list of sellers selling products to be purchased by the buyer in response to the buyer's search operation. Furthermore, according to more various embodiments, the matching support unit 135a may advertise on behalf of the seller the need for a sale item corresponding to a field of interest to the user. The advertisement operation may be implemented through an operation such as displaying the generated advertisement phrase, product image, etc. on the buyer interface, or displaying the result list together.

The advertisement phrase may be text information calculated based on the usual collected information such as the buyer's conversation message and search word.

In addition, the matching support unit 135a may perform a matching support operation between the selling goods field and the seller so that the seller may list information on the selling field where the demand of the buyer exists but the seller does not exist and allow the seller to select.

 The transaction execution unit 135b may support a practical transaction operation. Specifically, it is possible to provide seller information and sale item information to a buyer, and perform the overall operation of payment. In addition, the transaction execution unit 135b may collect information on the reason for dissatisfaction such as refund and return, and reflect this, to assist the future sales prediction information calculation unit 134 to correct the sales prediction information.

According to various embodiments of the present invention, the server 100 of the present invention may not only recommend the type and quantity of products suitable for sale to a user (seller), but may also serve as a wholesaler.

This will be described in detail with reference to FIGS. 4 and 5.

4 and 5 illustrate a flow of operations for providing sales prediction information according to an embodiment of the present invention.

Referring to FIG. 4, according to an embodiment, the sales prediction information providing system 402 may collect sales-related data from a data provider 401 composed of a portal and an e-commerce API. At this time, the collected data is related to keyword search volume, number of product sellers, and other trend figures, and related data can be periodically obtained from a related company. The sales prediction information providing system 402 periodically acquires data related to product production, inventory, and the like from pre-linked research companies in order to acquire statistical data generated based on relatively large amount of sample data according to various embodiments. Can be.

The sales prediction information providing system 402 may additionally perform data collection and processing operations for calculating sales prediction information based on various methods described based on FIGS. 2 and 3. Thereafter, the sales prediction information providing system 402 provides the calculated sales prediction information to the user (eg, one-person seller) 403 side, and based on this, the user provides information related to the type and quantity of items to be purchased from the wholesaler 405 side. Can be obtained. Subsequently, the user can purchase goods to be sold at retail from the wholesaler 405 side, and the purchased goods can be sold in a space such as SNS.

Another embodiment of the present invention relates to a case in which the sales prediction information providing system 402 functions as a wholesaler 405 as shown in FIG. 5. In this case, the sales prediction information providing system 402 processes the data received from the data provider 401, such as portal and e-commerce API, to generate sales prediction information, and based on this, the user 403 sells products suitable for retail wholesale can do. And the sales prediction information providing system 402, in connection with the wholesaler 405 side, when the product information suitable for the user to sell in retail is generated, generates advertisement content to induce the purchase of the product, and thereby leads the sale can do. For example, the sales prediction information providing system 402 may generate information on a product-specific margin trend (market price trend), and provide the same.

Alternatively, the sales prediction information providing system 402 may provide information related to real-time sales volume at the wholesaler 405 (eg, product information with a low supply rate compared to the demand forecast value). Accordingly, the user (seller) 403 sells the product for retail sale Can be easily selected.

At this time, the wholesaler 405 may refer to both a website and individual wholesalers selling goods by a number of wholesalers such as 'Alibaba', 'Domaekkuk'.

According to various embodiments, the sales prediction information providing system 402 may match individual wholesalers and users (retailers). To this end, the sales prediction information providing system 402 may evaluate the similarity between the attributes of the wholesale goods sold and the attributes of the seller's purchased goods, and perform matching according to the ranking with high similarity.

Furthermore, the sales prediction information providing system 402 may perform a wholesaler matching operation according to characteristics of a user who is a retailer, for example, in response to whether the retailer stays abroad, whether to perform direct delivery, the degree of margin pursued, sales experience, etc. It can be done.

Although the present invention has been described in detail with reference to the above-mentioned examples, those skilled in the art can make modifications, alterations and modifications to the examples without departing from the scope of the present invention. In short, in order to achieve the intended effect of the present invention, it is not necessary to separately include all the functional blocks shown in the drawings or to follow all the order shown in the drawings in the order shown, and even if not, any number of technical aspects of the present invention described in the claims Note that it can fall within the scope.

100: server
110: communication unit
120: storage unit
130: control unit
131: Natural language search support
132: Sales plan evaluation support department
133: External needs reflector
134: sales forecast information calculation unit
135: Transaction progress support

Claims (8)

In the system for providing sales prediction information comprising a seller device, a buyer device and a server,
The seller device is
The sales plan information, sales goods information and seller information are transmitted to the server.
The purchaser device
Access to the server, view and evaluate sales plan information registered by a plurality of seller devices, and transmit search records and purchase requests for actual sales products registered by the seller to the server,
The server
Calculate sales prediction information based on information received from the seller device and information received from the buyer device, and provide the calculated information to the seller device,
The server
Includes a control unit for collecting the buyer's search term record from the buyer's device to calculate the sales forecast information, and calculates the buyer's demand information based on the collected search term record;
The control unit
Search for the search term in the form of a sentence that the buyer entered in the search box,
Collects and classifies the search terms, but classifies the search terms collected from all buyers accessing the server by period and by buyer characteristics, and when there is no specific product corresponding to the search result, the natural language is collected by weighting the search number Search support;
When the seller inputs the sales plan information including the item item to be sold and the quantity to be purchased and sends it to the server, the sales plan information is supported for the buyer to evaluate, but as the buyer views the sales plan information, the purchase intention is made. A sales plan evaluation support unit that displays a querying page or pop-up, induces a mock order to be performed, and evaluates the sales plan information based on purchase item and purchase quantity information on the mock order;
In the specific application specified by the buyer, when the typing action and the specific action specified are collected, the text entered by the buyer is collected,
An external needs reflecting unit that collects the entire sentence including the condition word or text within a predetermined range of the condition word when detecting that the text including the condition word, which is the word set by the purchaser, is input;
Sales forecast information is calculated based on data obtained from the natural language search support unit, the sales plan evaluation support unit, and the external needs reflector, wherein the sales forecast information is information of major sales interests of individual sellers, and sales areas of all sellers Sales forecast information calculation unit that includes information, major interest information of individual buyers and interest trend information of all buyers, and selectively acquires and processes some of the obtained data according to the type of sales forecast information that the buyer intends to calculate ; And
Includes a transaction progress support unit to support the upload of sales goods information, the buyer's item selection action, and the buyer's payment action so that the actual sales action is performed.
The sales prediction information calculation unit
Estimated sales size and estimated purchase size are calculated based on the acquired data, and the calculated expected sales size is compared with the expected purchase size, and if the expected sales size is less than a preset reference value compared to the expected purchase size, the seller's sales Positively evaluate the plan,
The estimated sales scale is classified by summing up the size of the seller performing the actual sales activity and the size of the registered seller who has established a sales plan, and adds accuracy weights to the size of the seller performing the actual sales behavior.
Calculate and provide the threat factor so that the seller can check the threat factor before entering the market,
If the proportion of all sellers or sellers who are planning to enter the market is more than the reference value, the threat factor exists when the number of sellers entering the market within the reference period increases more than the reference value. Sales forecasting information providing system. delete delete delete delete delete delete According to claim 1,
The transaction progress support department
A matching support unit listing information on a sales field in which a buyer has a demand, but the seller does not exist, and supporting matching between a sales item field and a seller to enable the seller to select a sales field; And
Includes a transaction performing unit that provides seller information and sales item information to the buyer, performs the overall operation of payment, collects information on the reason for dissatisfaction after purchase, and reflects this to make sales forecast information corrected and calculated. Sales forecast information providing system.

Images