KR101690423B1 - Laundry database utilizing big data building and marketing information extraction device - Google Patents

Laundry database utilizing big data building and marketing information extraction device Download PDF

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KR101690423B1
KR101690423B1 KR1020150107858A KR20150107858A KR101690423B1 KR 101690423 B1 KR101690423 B1 KR 101690423B1 KR 1020150107858 A KR1020150107858 A KR 1020150107858A KR 20150107858 A KR20150107858 A KR 20150107858A KR 101690423 B1 KR101690423 B1 KR 101690423B1
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information
laundry
big data
unit
customer
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KR1020150107858A
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Korean (ko)
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서동광
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주식회사 솔루오션
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06F17/30—
    • G06F17/30318—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0254—Targeted advertisements based on statistics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0255—Targeted advertisements based on user history

Abstract

The present invention relates to a method and system for building big data using a laundry database that builds big data based on the laundry and customer information received by a customer, selects an object desired by the advertiser through analysis of the big data, A laundry information integration unit for collecting laundry information from each of the laundry terminals through a network and integrating and collecting the laundry information into a database as big data; A big data statistic unit for analyzing and statistically processing big data integrated in the washing information integrating unit according to preset statistics; And a marketing information extracting unit for extracting marketing information for targeted target marketing by searching statistical processing and analyzed information in the big data statistics unit according to the requirements of the advertiser and providing it to the advertiser, Implement big data construction and marketing information extraction device.

Figure R1020150107858

Description

BACKGROUND OF THE INVENTION Field of the Invention [0001] The present invention relates to a laundry data base,

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to construction of big data and extraction of marketing information using a laundry database (DB). More particularly, the present invention relates to construction of big data based on laundry and customer information received by a customer, A large data construction and marketing information extraction device using a dry cleaner database that allows an advertiser to select a desired target and make a target advertisement.

In the dry cleaner, not only laundry such as dry cleaning but also water washing and clothes repair are being carried out. Such dry cleaners are becoming widely used, and are becoming larger, specialized and mechanized.

If you look at the laundry service method in a general laundry, there is a method in which the customer visits the laundry, leaves the laundry, and checks the laundry schedule. Alternatively, the owner visits the customer's house to collect the laundry, .

These two methods are a method in which the customer visits the laundry or the owner directly visits the customer's house. When the customer visits the laundry to take laundry, if there is no owner for the reason of delivery, the owner has to wait until the owner returns There is an inconvenience to visit the laundry again. In addition, since the owner must visit all the customers at home, it is time-consuming and physically painful. If the laundry is being delivered, even if the customer visits the laundry, the laundry can not be redeemed.

On the other hand, information and communication technologies typified by the Internet and mobile communication have changed the lifestyle of modern people. Almost all households, schools, and offices are equipped with personal computers capable of accessing the Internet, acquiring information using websites, purchasing products through electronic commerce, and exchanging news via e-mail. In addition, only a few years ago, people could only use mobile communication services based on voice calls using mobile communication terminals. However, recently, mobile communication terminals have been used for financial settlement, home automation, video shooting, photo shooting, It is now possible to receive various services such as internet access.

The rapidly developing information and communication technology is applied to various parts of real life, and various technologies for performing laundry service by combining such information communication technology are proposed in the laundry.

Patent Document 1 and Patent Document 2 described below disclose a conventional technology for providing laundry service by combining information communication technology with a laundry.

The prior art disclosed in Patent Document 1 is an RFID tag attached to a laundry of a customer; An RFID reader installed on a hanger for hanging laundry and reading tag information about an individual laundry from the RFID tag; A function of receiving and processing tag information read by an RFID reader through wireless communication with the RFID reader, a wireless communication module performing a function of transmitting a specific signal to an RFID reader, And a server including a management program for controlling the wireless communication module to transmit the signal to the RFID reader, wherein the wireless communication module stores tag information transmitted to the wireless communication module, the wireless communication module being electrically connected to the wireless communication module, System.

The laundry management system thus implemented can transmit the laundry process information of the laundry to the customer using the RFID technology, and automatically recognize and classify the laundry in the laundry, and deliver the laundry to the customer.

In the conventional technology disclosed in Patent Document 2, after accessing a laundry service site through a QR code attached to a laundry, the washing application is automatically downloaded and stored. After the user executes a washing application according to the user's operation, A customer terminal for transmitting the laundry information input through the laundry service site to a server operating the laundry service site; A laundry service server for downloading the laundry application and generating a collection and delivery schedule of the laundry based on the laundry information transmitted from the customer terminal; And a laundry terminal for downloading the laundry application and displaying the collection and delivery schedule generated by the laundry service server on the screen.

The laundry management system implemented in this way enables the customer and the laundry manager to send and receive general status information about the laundry through the QR code, thereby providing convenience to the customer and efficient laundry management for the owner.

Korean Registered Patent No. 10-0934008 (registered on December 17, 2009) Korean Registered Patent No. 10-1335212 (Registered on November 25, 2013)

However, the above-described conventional technology has an advantage in that laundry can be efficiently managed using a technology such as information communication, but it is impossible to build big data by using laundry information or customer information, There are disadvantages that are impossible.

In addition, the related art has a disadvantage in that it is difficult to select a desired target by an advertiser by analyzing a customer relationship or to target a target based on a current living standard of a customer.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made to solve the above-mentioned problems occurring in the prior art, and it is an object of the present invention to provide an apparatus and method for creating big data based on laundry data and customer information received by a customer, And an object of the present invention is to provide a big data construction and marketing information extracting device using a laundry database that allows targeted advertisements to be made.

Another object of the present invention is to provide a big data construction and marketing information extraction device using a laundry database that can select target objects that can be marketed by region and customer through customer relationship analysis based on Big Data .

In order to achieve the above object, the apparatus for extracting big data and extracting marketing information using the laundry database according to the present invention collects laundry information from respective laundry terminals through a network, integrates the laundry information, A laundry information integration unit; A big data statistic unit for analyzing and statistically processing big data integrated in the washing information integrating unit according to preset statistics; And a marketing information extracting unit for extracting marketing information for targeted target marketing by searching statistical processing and analyzed information in the big data statistics unit according to the requirements of the advertiser and providing the marketing information to the advertiser.

The laundry information integrating unit includes a laundry information collecting unit for collecting laundry information transmitted from each laundry machine through a network; And a big data constructing unit for constructing the laundry information collected by the laundry information collecting unit as big data, wherein the laundry information includes at least one of laundry information and customer information.

The big data statistic unit may include a big data retrieval unit for retrieving the big data constructed by the big data construction unit and extracting washing information; An age-specific statistical unit for statistically processing the laundry information extracted by the big data search unit by age; And a family member statistics unit for statistically processing the laundry information extracted by the big data search unit by family members.

The big data statistics unit may include a statistic unit for each fashion trend that statistically processes the laundry information extracted from the big data search unit by fashion trends; A hobby / activity range statistics unit that statistically processes the laundry information extracted by the big data search unit by hobby and activity range; And a customer condition analyzer for analyzing customer condition by analyzing the laundry information extracted by the big data searching unit.

The big data statistic unit may include a living level statistics unit for statistically processing the laundry information extracted by the big data searching unit according to living standards; And a garment type analyzing unit for analyzing the laundry information extracted by the big data searching unit by season and by region.

The marketing information extracting unit may include an advertiser request information input unit receiving the request information of the advertiser; A big data retrieving unit for retrieving the big data based on the request information of the advertiser and extracting statistical information corresponding to the request information; An object selector for selecting an object suitable for an object requested by the advertiser from the statistical information retrieved by the big data retrieval unit; And a marketing information providing unit for extracting target marketing information for marketing consulting for each region and each customer based on the statistical information selected by the target selecting unit and providing the extracted target marketing information to the advertiser.

Also, the apparatus for extracting big data and building marketing information using the laundry database according to the present invention can manage laundry by accessing a laundry terminal using a laundry application for managing laundry, receive laundry-related marketing information transmitted from an advertiser, And a customer terminal for displaying the customer terminal.

According to the present invention, it is possible to build big data on the basis of the laundry and customer information received by the customer, and to increase the efficiency of advertisement by selecting an object desired by the advertiser through analysis of the big data .

In addition, according to the present invention, it is possible to select a target object capable of marketing by customer level and region and customer through customer relationship analysis based on Big Data, and it is possible to provide marketing information for marketing consulting.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of an apparatus for extracting big data and extracting marketing information using a laundry database according to a preferred embodiment of the present invention;
FIG. 2 is a block diagram of an embodiment of the laundry information integrating unit of FIG. 1;
FIG. 3 is a block diagram of an embodiment of the big data statistics unit of FIG. 1,
FIG. 4 is a block diagram of an embodiment of the marketing information extracting unit of FIG. 1;
FIGS. 5A and 5B illustrate examples in which a customer terminal processes laundry information or performs targeted marketing advertisement through a laundry management application. FIG.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an apparatus for extracting big data and extracting marketing information using a laundry database according to a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram of an apparatus for extracting big data and extracting marketing information using a laundry database according to a preferred embodiment of the present invention; FIG.

The big data construction and marketing information extraction device using the laundry database according to the present invention includes a laundry terminal 100, a network 200, a laundry information integration unit 300, a big data statistics unit 400, a marketing information extraction unit 500 and a customer terminal 600.

The laundry terminal 100 is provided in each of the dry cleaners and transmits the laundry information acquired by the laundry cleaner to the laundry information integrating unit 300 through the network 200. The laundry terminal 100 may be implemented as a personal computer (PC) or a plurality of the laundry terminals. The greater the number of the laundry terminals 100, the higher the availability of the big data to be constructed.

Here, the network 200 is a mobile communication network. Internet, and wired communication network. In the present invention, the term " network " means a network including both a wired network and a wireless network.

The washing information integrating unit 300 collects laundry information from each of the laundry terminals 100 through the network 200 and integrates them into a database (DB) with big data.

As shown in FIG. 2, the washing information integrating unit 300 includes a washing information collecting unit 310 for collecting washing information transmitted from each washing machine through the network 200; And a big data constructing unit 320 for constructing the laundry information collected by the laundry information collecting unit 310 as big data.

The laundry information may include at least one of laundry information and customer information. It is desirable to use only the information of the customer who agreed to provide his / her information in advance. The customer information preferably includes at least one of a customer name, a mobile phone number, a home address, a date of birth, a customer type (personality & tendency), a customer ranking (sales ranking & customer fashion style).

The big data statistics unit 400 analyzes and statistically processes large data integrated in the washing information integrating unit 300 according to preset statistics.

As shown in FIG. 3, the big data statistic unit 400 includes a big data retrieval unit 410 for retrieving the big data constructed by the big data construction unit 320 and extracting washing information. An age-specific statistic unit 420 for statistically processing the laundry information extracted by the big data search unit 410 according to age; A family member statistics unit 430 for statistically processing the laundry information extracted by the big data search unit 410 for each family member; A fashion trend-specific statistics unit 440 for statistically processing the laundry information extracted by the big data search unit 410 for each fashion trend; A hobby / activity range statistics unit 450 for statistically processing the laundry information extracted by the big data search unit 410 by hobbies and activity ranges; A customer condition analyzer 460 for analyzing customer condition by analyzing the laundry information extracted by the big data retrieving unit 410; A living level statistics unit 470 for statistically processing the laundry information extracted by the big data search unit 410 according to living standards; And an apparel class analyzing unit 480 for analyzing the laundry information extracted by the big data searching unit 410 into seasonal and regional clothing types.

The marketing information extracting unit 500 extracts marketing information for targeted target marketing by searching statistical processing and analyzed information in the big data statistic unit 400 according to the requirements of the advertiser and provides the advertiser with the marketing information do.

As shown in FIG. 4, the marketing information extractor 500 includes an advertiser request information input unit 510 for receiving advertiser's request information; A big data retrieving unit 520 for retrieving the big data based on the request information of the advertiser and extracting statistical information corresponding to the request information; An object selector 530 for selecting an object suitable for an object requested by the advertiser from the statistical information searched by the big data search unit 520; And a marketing information providing unit 540 for extracting target marketing information for marketing consulting according to regions and customers based on the statistical information selected by the target selecting unit 530 and providing the extracted marketing information to an advertiser.

The customer terminal 600 manages laundry by accessing the laundry terminal 100 using a laundry application for managing laundry, and receives and displays laundry-related marketing information transmitted from an advertiser. Here, the customer terminal 600 is a customer terminal that has agreed to receive a marketing advertisement text message in advance, and may be a terminal of a manager of a laundry managing the laundry, or a terminal of a customer who leaves laundry in the laundry.

The operation of the big data construction and marketing information extraction apparatus using the laundry database according to the preferred embodiment of the present invention will be described in detail as follows.

First, the laundry terminal 100 provided at each of the dry cleaners acquires customer information with agreement with a customer who leaves laundry, and registers laundry information corresponding to the acquired customer information. In order to obtain customer information and use the laundry information here, customers may be given the benefit of discounting laundry costs, providing mileage, or giving them the right to participate in a sweepstakes event . In addition to these benefits, you may also receive various well-known benefits that you may receive in return for providing information. The customer information includes at least one of a customer name, a mobile phone number, a home address, a date of birth (optional), a customer type (personality and propensity), a customer ranking (sales ranking and customer fashion style) .

The customer who provided the customer information is considered to download and use the laundry management application so as to confirm his laundry information or to receive and confirm the target marketing advertisement later.

The customer information and the laundry information collected in the laundry terminal 100 provided at the respective dry cleaners are transmitted to the laundry information integrating unit 300 through the network 200. [ Each manager of the laundry manager collects laundry information in advance and transmits laundry information and customer information collected in real time or at regular intervals in advance in consultation with a service manager who extracts target marketing information.

The washing information integrating unit 300 collects laundry information from each of the laundry terminals 100 through the network 200 and integrates them into a database (DB) with big data. In this case, the larger the number of the laundry terminals 100, the greater the amount of big data to be constructed and the higher the utilization thereof.

The washing information collecting unit 310 in the washing information integrating unit 300 collects washing information transmitted from each washing machine through the network 200. Then, the big data constructing unit 320 constructs a plurality of pieces of laundry information collected by the laundry information collecting unit 310 as big data and converts them into a database. Since each of the laundry terminals uses the same laundry management application, the format for providing the laundry information and the customer information is the same. Therefore, since the big data construction unit 320 also provides the laundry information and the customer information in the same format, the database can be made very convenient.

The big data statistic unit 400 analyzes and statistically processes the data using the big data collected from the respective dry cleaners.

For example, the big data retrieval unit 410 of the big data statistics unit 400 retrieves the big data constructed by the big data construction unit 320 and extracts the laundry information and the customer information. Then, the age-specific statistics unit 420 statistically processes the laundry information and the customer information extracted by the big data search unit 410 according to age. For example, based on the date of birth information of the customer information, the washing information is classified into 10, 20, 30, 40, 50, 60, 70, 80 or more. The laundry information classified here includes customer information. In addition, the washing information classified by age is again classified into male and female. It is also possible to classify the age-based classifications into the above-mentioned age classes, and further classify the above-mentioned age groups into more or more groups and collectively classify them.

Next, the family member statistics unit 430 statistically processes the laundry information extracted by the big data search unit 410 for each family member. For example, the family members are classified based on the home address of the customer information, and the laundry information is classified into the family members. That is, bundles of customers having the same home address, family members based on a specific family member are classified, and the family members are combined to combine laundry information and family member information. For example, if the name of a specific family member is Hong Gil-dong, it can be classified as Hong Gil-dong family, male suit + female clothing, school uniform skirt + uniform pants, male in their forties, middle and high school children .

In addition, the fashion trend-specific statistics unit 440 statistically processes the laundry information extracted by the big data search unit 410 for each fashion trend. For example, customers will be classified according to fashion trends by using classification criteria such as retro fashion style, personal image, brand, domestic brand, foreign brand, luxury brand.

In addition, the hobby / activity range statistics unit 450 statistically processes the laundry information extracted by the big data search unit 410 for each hobby and activity range. For example, the laundry information is statistically processed on the basis of the customer information by the customer's hobbies and the range of the area in which the customer operates. For this purpose, it is desirable to acquire the hobby information of the customer when obtaining consent of the SMS text message and consent of the customer information in advance, and obtain the information of the activity area of the customer.

Next, the customer condition analyzing unit 460 analyzes the laundry information extracted by the big data searching unit 410 and analyzes the customer condition. Here, the condition analysis considers the laundry information of the customer, the weather information of the day, the discomfort index information, and the like, and analyzes what clothes the user wears in what weather. If the actual laundry is left in the laundry, it is preferable to use the weather data of the previous day for the weather information since it is often the case that the clothes are put on the previous day rather than the day.

In addition, the living-level statistics unit 470 performs statistical processing for each living level on the basis of the laundry information and the customer information extracted by the big data search unit 410. Here, it is preferable to use various information as a criterion for judging the living standard of the customer. For example, customers' lives can be measured using customer's occupation (professional, office, finance, large company, medium business, small business, etc.), residential space (apartment, villa, private house, etc.) The level can be predicted.

Finally, the clothing type analyzing unit 480 analyzes the laundry information extracted by the big data searching unit 410 as seasonal and regional clothing types. For example, it is possible to analyze seasonal and regional clothing types in accordance with season, clothes type sold according to season, and clothing type sold according to season, based on laundry information and customer information.

In this process, the big data is statistically processed and stored through customer linkage analysis.

When the advertiser who wants to advertise the advertisement delivers the advertiser requirement to target the advertisement of the advertiser, the marketing information extractor 500 searches the big data statistics part 400 for the statistical processing and analyzed information It extracts marketing information for targeted target marketing and provides it to advertisers.

For example, the advertiser request information input unit 510 of the marketing information extractor 500 receives and stores the request information of the advertiser. Here, the advertiser can provide various demand information for advertising his / her target to the target. For example, it is possible to select an age group, a sex, an advertisement item type, an area, and the like. The big data retrieval unit 52 retrieves the big data based on the request information of the advertiser and extracts statistical information corresponding to the request information and transmits the extracted statistical information to the object sorting unit 530. [ The big data search unit 520 extracts only the customer information corresponding to the advertiser's request and outputs the extracted customer information to the target sorting unit 530, .

Based on the statistical information extracted by the big data search unit 520, the target sorting unit 530 selects an object suitable for an object requested by the advertiser. Then, the marketing information providing unit 540 extracts target marketing information for marketing consulting for each region and each customer based on the statistical information selected by the target selecting unit 530, and transmits the extracted target marketing information to the advertiser. Here, the marketing information providing unit 500 may receive the advertiser's requirements and advertisements, select an object requested by the advertiser, and directly target the target.

That is, for example, an advertiser selects an object requested by an advertiser in accordance with a desired region, gender, age, living level, hobby, and the like, and delivers the selected customer information to the advertiser as target marketing advertisement information. The advertiser can maximize the advertisement efficiency by using the target marketing information.

Here, advertisers for marketing by region and target can be diverse.

For example, taxpayers and drug companies can use the nationwide laundry network to publicize and obtain customer information by distributing samples of new products.

When a franchisee is opened, the advertiser of the franchise head office can utilize it for marketing such as open advertisement and mobile coupon issue in the relevant area.

In addition, it is possible to target advertisements for each age group or region that want to advertise based on the area where they want to sell, using marketing information by region or target by a construction business selling company.

In addition, game developers and application developers can promote open beta services and promote various applications. In addition, companies that want to promote new products using the nationwide laundry network are planning product launch, publicity, sample test, recruitment of reporters , Network marketing, etc. Through the nationwide laundry infrastructure, many advertising contents and products can be promoted.

In addition, financial and insurance companies can design the product according to the living standard of the current family member by analyzing the product, analyzing the effect of advertisement, and analyzing the customer relationship management by giving the code of the recruitment using the nationwide laundry network. The customer may not be able to access the information.

In addition, advertising and marketing companies can be used for various advertising planning, advertising agency, and advertisement promotion cooperation. Clothing and fashion companies analyze customer's fashion code, interest analysis and repair items through customer relationship management, Can be identified and predicted.

In addition, regional and specific target advertisers can conduct regional advertising marketing by searching specific customer and specific local conditions through customer relationship management analysis.

FIG. 5A is an exemplary screen in which the laundry processing information and the marketing information are received and displayed on the screen. At the upper part of the screen, a message related to the customer laundry is displayed. At the lower part of the screen, a target marketing advertisement is displayed. The customer terminal 600 is a customer terminal that has agreed to receive a marketing advertisement text message in advance, and may be a terminal of a laundry manager who manages a laundry, or a terminal of a customer who leaves laundry in a laundry.

FIG. 5B shows a main screen when the laundry-related application is executed. A target marketing advertisement is displayed at the top of the screen, a menu (delivery request, collection request, laundry search, Marketing advertisements are displayed.

Although the present invention has been described in detail with reference to the above embodiments, it is needless to say that the present invention is not limited to the above-described embodiments, and various modifications may be made without departing from the spirit of the present invention.

100: Laundry terminal
200: Network
300: Laundry information integration department
310: Laundry information collecting section
320: Big data construction unit
400: Big data statistics section
420: Statistical Division by Age
430: Family Member Statistics Department
440: Statistics by Fashion Trend
450: Hobby / Activity Range Statistics Department
460: Customer condition analysis unit
470: Life-level statistics department
480: Apparel type analysis unit

Claims (7)

It is a device for building big data by using a laundry database that utilizes the network and extracting marketing information based on the built big data to perform targeted marketing,
A laundry information integrating unit for collecting laundry information from respective laundry terminals through a network, and integrating and collecting the laundry information into a database in the form of big data;
A big data statistic unit for analyzing and statistically processing big data integrated in the washing information integrating unit according to preset statistics; And
And a marketing information extracting unit for extracting marketing information for targeted target marketing by searching statistical processing and analyzed information in the big data statistics unit according to the requirements of the advertiser and providing the marketing information to the advertiser,
The big data statistics unit may include a family member statistics unit for statistically processing the extracted washing information by family members; A statistics section for each fashion trend that statistically processes the laundry information according to fashion trends; A hobby / activity range statistics unit for statistically processing the laundry information by hobbies and activities; And a customer condition analyzer for analyzing the customer condition by analyzing the laundry information,
The family member statistics unit classifies customers who have the same home address, classifies family members based on a specific family member, and combines laundry information and family member information to perform statistical processing on each family member,
The statistical department according to the fashion trends statistically processes the customers according to the fashion trends using the classification standard including the fashion style, the personal image, the brand, the domestic brand, the foreign brand, and the luxury brand,
Wherein the customer condition analyzing unit comprehensively considers the laundry information of the customer, the weather information of the day and the discomfort index information, and statistically processes the customer condition by analyzing which clothes the user wears for each weather according to the customer's condition Big data construction and marketing information extraction device utilized.
The washing information collecting unit may include a washing information collecting unit collecting laundry information transmitted from each of the dry cleaners through a network. And a big data establishing unit for building up the laundry information collected by the laundry information collecting unit as big data, wherein the laundry information includes at least one of laundry information and customer information. Data building and marketing information extraction device.
The big data statistic unit may include a big data search unit for searching for big data constructed by the big data construction unit and extracting laundry information; And an age-specific statistical unit for statistically processing the laundry information extracted by the big data searching unit according to the age of the user.
delete The big data statistic unit may further include a living level statistic unit for statistically processing the laundry information extracted by the big data searching unit according to living standards; Further comprising an apparel type analyzing unit for analyzing the laundry information extracted by the big data searching unit by season and by region clothing type.
The method of claim 1, wherein the marketing information extraction unit comprises: an advertiser requirement information input unit receiving the request information of the advertiser; A big data retrieving unit for retrieving the big data based on the request information of the advertiser and extracting statistical information corresponding to the request information; An object selector for selecting an object suitable for an object requested by the advertiser from the statistical information retrieved by the big data retrieval unit; And a marketing information providing unit for extracting target marketing information for marketing consulting for each region and each customer based on the statistical information selected by the target selecting unit and providing the extracted marketing information to the advertiser. Information extraction device.
The system of claim 1, further comprising a customer terminal connected to the laundry terminal using a laundry application for managing laundry, managing laundry, and receiving and displaying laundry-related marketing information transmitted from an advertiser,
Wherein the customer terminal is a terminal used by a customer who requests laundry, receives a target marketing advertisement, or is a terminal used by a manager of a laundry cleaner.
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Cited By (2)

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Publication number Priority date Publication date Assignee Title
CN109508855A (en) * 2018-09-27 2019-03-22 国网福建省电力有限公司信息通信分公司 A kind of sales service compliance discriminatory analysis method based on big data processing
KR20200050644A (en) * 2018-11-02 2020-05-12 주식회사 크립텍스 Method for providing product information using unattended laundry system and unattended laundry system for the same

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