KR102545190B1 - Device for providing goods information in offline retail environment and control method thereof - Google Patents

Abstract

A control method of a product information providing device includes processing product data based on attribute information for each product category stored in a database, and providing the processed data to a consumer terminal, including the steps of processing product data for each category of product stored in the database. Product attribute information is generated based on a product information image captured by the user terminal.

Description

Product information providing device and product information providing device control method in offline retail environment {DEVICE FOR PROVIDING GOODS INFORMATION IN OFFLINE RETAIL ENVIRONMENT AND CONTROL METHOD THEREOF}

It relates to a product information providing device and a control method of the product information providing device providing processed data to consumers based on data collected offline.

As various online businesses are active, traditional distribution businesses are also under pressure to develop differentiated promotion methods. However, many products are still sold in offline stores or online stores. In addition, 91% of shopping worldwide is still done in offline stores, and information about the consumer's purchase journey is the main information that can confirm what stimulation and information they have encountered in offline stores.

However, data obtained through offline stores is difficult to collect compared to online data, and although it is attracting attention as very valuable data because it contains actual consumers' offline lives, both offline stores and online stores provide It was difficult to grasp the purchase journey, and accordingly, it was difficult to derive products suitable for consumers who purchase offline.

It is intended to provide a product information providing device and a control method of the product information providing device that can collect log data of consumers searched offline and effectively provide service information generated based on the collected log data to users.

A control method of an apparatus for providing product information according to an aspect includes processing product data based on attribute information for each category of products stored in a database, and providing the processed data to a consumer terminal, the stored data stored in the database. Product attribute information for each product category is generated based on a product information image captured by the user terminal.

Processing the product data may include processing the product data based on attribute information accumulated during a period selected by the user.

Processing the product data may include combining at least two or more of product categories stored in a database and one or more elements of personal information to generate a user's product search keyword corresponding to a combination result.

The step of processing the product data may include measuring the number of product views for each product category, and the step of providing the processed data to the consumer terminal may include providing the number of product views for each product category to the consumer terminal. can

The processing of the product data includes processing the product data based on the product category-specific attribute information and purchase information stored in the database, and the purchase information of the product stored in the database is included in the purchase receipt image captured by the user terminal. may have been created based on

The attribute information may include promotion information, and processing the product data may include calculating a ratio of a user who visits a preset store during a promotion period and a user who visits a store during a non-promotion period.

Processing the product data may include generating a relationship diagram for each element by combining elements of a plurality of pieces of personal information stored in the database.

The personal information element may include at least one of the user's gender, age, skin type, skin concern, skin tone, skin color, and taste.

According to another aspect of the product information providing device, the product information providing device includes a processor, the processor processes product data based on attribute information for each category of products stored in a database, and provides the processed data to a consumer terminal; Attribute information of each product category stored in the database may be generated based on a product information image captured by the user terminal.

The processor may process product data based on attribute information accumulated during a period selected by the user.

The processor may generate a user's product search keyword corresponding to a combination result by combining at least two or more of product categories stored in the database and one or more elements of personal information.

In a computer-readable recording medium according to another aspect, a method including processing product data based on attribute information for each category of products stored in a database and providing the processed data to a consumer terminal is recorded. Attribute information for each product category stored in the database is generated based on a product information image captured by the user terminal.

Processing the product data may include processing the product data based on attribute information accumulated during a period selected by the user.

According to the above-described problem solving means, by collecting information on various purchase journeys of consumers offline and processing meaningful data to product sellers into structured data based on the collected purchase journeys, personalized product planning, etc. can be used throughout.

1 is a conceptual diagram of a product information providing system according to an embodiment.
2 is a diagram showing various objects included in a product information image.
3 to 7 are exemplary diagrams of processed data displayed on a data consumer terminal.

Like reference numbers designate like elements throughout the specification. This specification does not describe all elements of the embodiments, and general content or overlapping content between the embodiments in the technical field to which the present invention belongs is omitted. The term 'unit, module, member, or block' used in the specification may be implemented as software or hardware, and according to embodiments, a plurality of 'units, modules, members, or blocks' may be implemented as one component, It is also possible that one 'part, module, member, block' includes a plurality of components.

Throughout the specification, when a part is said to be "connected" to another part, this includes not only the case of being directly connected but also the case of being indirectly connected, and indirect connection includes being connected through a wireless communication network. do.

In addition, when a certain component is said to "include", this means that it may further include other components without excluding other components unless otherwise stated.

Terms such as first and second are used to distinguish one component from another, and the components are not limited by the aforementioned terms.

Expressions in the singular number include plural expressions unless the context clearly dictates otherwise.

In each step, the identification code is used for convenience of description, and the identification code does not explain the order of each step, and each step may be performed in a different order from the specified order unless a specific order is clearly described in context. there is.

The product information search device may be a user terminal installed with an application that takes a product information image and performs a series of processes, receives a product information image taken from the user terminal, performs a series of processes, and exchanges data with the user terminal. It can also be a server that does Hereinafter, for convenience of description, an example in which a product information search device is implemented as a user terminal will be described.

The user terminal may be implemented as a computer or a portable terminal. Here, the computer includes, for example, a laptop, a desktop, a laptop, a tablet PC, a slate PC, etc. equipped with a web browser, and a portable terminal, for example, has portability and mobility. As a guaranteed wireless communication device, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication) -2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminal, smart phone (Smart Phone) based on all types of handhelds It may include a wireless communication device and a wearable device such as a watch, ring, bracelet, anklet, necklace, glasses, contact lens, or head-mounted-device (HMD).

A product name or unique identification code is written on the product. Alternatively, a price tag with product information written thereon may be located adjacent to the product.

1 is a conceptual diagram of a product information providing system according to an embodiment.

Referring to FIG. 1 , the product information providing system includes a product information search device 100 , a product information providing device 200 , and product information receiving devices 300 - 1 and 300 - 2 .

The product information retrieval apparatus 100 may photograph a product and an adjacent object together. The product information image captured by the product information search device 100 may include a product name, a unique identification code, or other information.

The product information image refers to a photographed image including information for identifying a product or information for distinguishing a specific product from other products. For example, the product information image may include product information. Product information may include information on various objects such as product name, price, promotion information, and unique identification code. That is, the product information image may be an image obtained by photographing a price tag having product information written thereon, an image obtained by photographing a product having product information written thereon, or an image obtained by photographing a packaging material having product information written thereon.

The product information search device 100 may identify product information from a captured product information image.

Specifically, the product information search apparatus 100 may specify at least one object in the product information image.

2 is a diagram showing various objects included in a product information image.

For example, the product information search apparatus 100 may display a product name (ob1), a price (ob2, 'price before discount', 'price after discount', etc.), promotion information (ob3, '1+1', 'price after discount', etc.) in the product information image. At least one of 'discount', 'accumulation', 'gift presentation', etc.), and a unique identification code ob4 may be specified. At this time, the product information retrieval device 100 may specify an object using a convolutional neural network (CNN) model. As an example, the product information retrieval device 100 may use a deep learning R-CNN (" Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation, Ross Girshick, Jeff Donahue, Trevor Darrell and Jitendra Malik, in CVPR 2014") An object can be specified by object detection technology based on the model.

The 'convolution' operation in the convolutional neural network model is an operation that extracts components of an image and can be implemented based on Equation 1 below.

[Equation 1]

The result is derived by passing the kernel matrix through the digitized image matrix to calculate the data of the pixel at its own location and the pixels adjacent to the periphery, and the data stored as the output matrix has the characteristics of the image.

However, if only the convolution operation is continued, overfitting with low accuracy occurs from a certain point in time. In order to prevent overfitting, the product information retrieval apparatus 100 may pool with large values from adjacent values of the output matrix. Yes, and dropout can be performed.

Thereafter, the product information search apparatus 100 may extract the location of an object from the product information image using a data classification algorithm (eg, Support Vector Machine (SVM), SoftMax) and may specify the object.

In addition, the product information search apparatus 100 may perform pre-processing on the product information image before specifying the object in order to increase the accuracy of the product information image. Pre-processing may be, for example, performing image binarization conversion, noise removal, surrounding background removal, resolution change, and the like.

As an example, the product information search apparatus 100 may extract a price stack image from a product information image and convert the price stack image into a uniformly sized image. In addition, by calculating the coordinates of the objects in the price stack, the image data of the object can be converted into numerical data using numerical data for each coordinate. The product information search apparatus 100 may specify an object based on numerical data of an image according to these coordinates.

Also, the product information search apparatus 100 may identify text in a photographed image and extract text data. At this time, the product information search apparatus 100 may identify text by reading the entire image area or may identify text for each specified object.

As an embodiment, the product information search apparatus 100 may detect text in a product information image using an optical character recognition (OCR) method or the like.

In order to accurately detect text, the product information search apparatus 100 may learn a deep learning model by matching the misrecognized product name with the corrected product name after classifying cases with and without typos among the recognized text results.

Also, the product information search apparatus 100 may obtain location information of a place where the product information image was photographed as meta information. Depending on the embodiment, information on the shooting time may also be obtained as meta information. Location information may be obtained by extracting shooting coordinates from a product information image, or may be obtained by collecting a separate GPS or the like.

The product information retrieval apparatus 100 may store attribute information of a product in which a product information image is captured based on text data for each recognized object in a database.

The database may be included in the product information search device 100, or may be included in a separate server or product information providing device 200, and the hardware location is not limited. Hereinafter, for convenience of description, it is assumed that the database is included in the product information search apparatus 100 .

The product information retrieval apparatus 100 may store attribute information (eg, product name, price, promotion information, ingredients, unique identification code, etc.) of a corresponding product for each product category in a database. In addition, the product information search apparatus 100 may specify store information corresponding to the product information image based on location information of a place where the product information image was photographed, and store the store information as attribute information as well.

For example, the product information retrieval apparatus 100 may vectorize and store product attribute information using a deep learning-based prediction algorithm.

Specifically, the product information retrieval apparatus 100 may vectorize ingredient and attribute information for each cosmetic type by using Word2Vec, and vectorize the distance between cosmetic ingredients by using a Continuous Bag-of-Words (CBOW) model. Since Word2Vec and CBOW are known technologies, detailed descriptions are omitted. This is to allow a product including a component that is close to the property information calculated based on the user's photographing record and search history to be recommended later.

The product information search apparatus 100 may capture a purchase receipt image or obtain it from an external device. Similarly in this case, the product information retrieval apparatus 100 may be a user terminal installed with an application that takes a purchase receipt image and performs a series of processes, or receives a purchase receipt image captured from the user terminal and performs a series of processes. However, for convenience of description, an example in which the product information retrieval apparatus 100 is implemented as a user terminal and obtains a purchase receipt image will be described as an example.

The purchase receipt contains information related to the purchase of various products. The purchase receipt photographed by the product information search device 100 may include various purchase-related information such as store information, product name, price, promotion information, quantity information, purchase time information, buyer information, and a unique identification code. .

The purchase receipt image refers to an image in which information capable of identifying a consumer's purchase details is photographed. For example, the purchase receipt image may include purchase information. Purchase information may include information on various objects such as store information, buyer information (name, phone number, etc.), product name, price, promotion information, quantity information, purchase time information, buyer information, and a unique identification code. The purchase receipt image may be an image of a paper receipt directly photographed offline or an image of an online receipt issued online.

The product information search apparatus 100 may identify purchase information from the captured purchase receipt image.

Specifically, the product information search apparatus 100 may specify at least one object in the purchase receipt image.

For example, the product information search apparatus 100 may specify at least one of store information, product name, price, promotion information, quantity information, purchase time information, and a unique identification code in the purchase receipt image. At this time, the product information retrieval device 100 may specify an object using a convolutional neural network (CNN) model. As an example, the product information retrieval device 100 may use MobileNet ("MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications, Howard AG, Zhu M, Chen B, Kalenichenko D, Wang W, Weyand T, Andreetto M, Adam H, arXiv:1704.04861, 2017.; MobileNetV2: Inverted Residuals and Linear Bottlenecks, Sandler M, Howard A, Zhu M, Zhmoginov A, Chen LC. arXiv preprint. arXiv:1801.04381, 2018.") An object can be specified by object detection technology based on the model.

The MobileNet model is a model based on a simplified structure using a convolutional layer divided in the depth direction. The convolutional product for the entire image is calculated, but factored into convolutional products per channel and 1 x 1 convolutional product, so that the purchase receipt image Included objects can be detected. In the case of using the MobileNet model, it is possible to detect objects at high speed while being relatively less constrained in terms of size and shape of images than conventional methods. In particular, the usability of the model in a user terminal such as a mobile device is increased.

Also, the product information search apparatus 100 may perform pre-processing on the purchase receipt image before specifying the object in order to increase the accuracy of the purchase receipt image. Pre-processing may be, for example, performing image binarization conversion, noise removal, surrounding background removal, resolution change, and the like.

Also, the product information search apparatus 100 may identify text in the captured purchase receipt image and extract text data. At this time, the product information search apparatus 100 may identify text by reading the entire image area or may identify text for each specified object.

As an embodiment, the product information search apparatus 100 may detect text in the purchase receipt image using an optical character recognition (OCR) method or the like.

The product information search apparatus 100 may perform post-processing on text data.

As an embodiment, the product information search apparatus 100 may post-process text data based on at least one of character unit information and text context information of the purchase receipt image.

For example, the product information retrieval apparatus 100 may infer, as promotion information, that a price discount event has occurred through a % (percent) or - (minus) sign in the purchase receipt image in which the promotion information is damaged.

In addition, the product information retrieval apparatus 100 may match information corresponding to a specific object by utilizing contextual information between surrounding texts in a purchase receipt image in which specific object information is damaged.

The product information retrieval apparatus 100 may match user purchase information acquired from product attribute information photographed by a user terminal and a purchase receipt image to a user, and store the matched product information in a database.

Specifically, the product information retrieval apparatus 100 obtains the user's personal information from a separate personal information server, and the elements constituting the personal information (eg, the user's gender, age, skin type, skin concern, skin tone) , skin color, taste, etc.) and attribute information and purchase information of the product are matched to finally store product information of interest for each user. Here, the personal information may be acquired or input as member registration information of an application installed in the user terminal.

In addition, the product information retrieval apparatus 100 may place more weight on the user's purchase information obtained from the purchase receipt image than the product attribute information captured by the user terminal and store the information. In fact, this is because the product actually purchased reflects the user's preference more than the product photographed and searched for by the user.

In this way, when interest product information for each user is obtained from a plurality of users, it is possible to specify a product of interest based on the personal information of potential consumers, and to predict purchase of potential consumers.

In order to accurately predict purchase, the product information retrieval apparatus 100 may perform a test based on product information of interest for each user obtained from a plurality of users.

Specifically, the product information search apparatus 100 may perform a test using a binary logistic regression analysis method such as Equation 2.

[Equation 2]

y is a dependent variable, whether or not a product is viewed (including product information images taken or products directly searched by keyword through a user terminal) or whether a product is purchased, and X is a matrix made up of independent variables, and the independent variables include elements of personal information (For example, gender, age, skin type, skin concern, skin tone, skin color, taste, etc.) and online activity information of various users obtained through the user terminal may be included.

Through such a test, the elements constituting user information (eg, information about the user such as the user's personal information and user activity information) (eg, the user's gender, age, skin type, skin concerns, Skin tone, skin color, taste, etc.), which factors have a significant impact on product inquiry or purchase, and furthermore, it is possible to select users who are highly likely to view or purchase a specific product.

Specifically, the product information retrieval apparatus 100 determines the probability that a user having certain user information searches for or purchases a specific product by using a product purchase/view prediction model to which at least one of a deep learning algorithm and a machine learning algorithm is applied, and , Accordingly, it is possible to determine a user to be targeted for advertisement and to determine a product to be recommended to the user.

The product purchase and inquiry prediction model may include a Recurrent Neural Network (RNN), and may be, for example, one using Long-Short Term Memory (LSTM).

In this way, the product information retrieval device 100 converts the entire process of the offline user's itinerary into data, thereby deriving decision-making factors for product purchase and inquiry, and providing retailers or manufacturers with purchase predictions of offline users. It can provide practical insights.

The product information providing device 200 processes product data based on product attribute information for each product category stored in a database, and transfers the processed data to an offline retail terminal 300-1 or a product manufacturer terminal 300-2. ) can be provided to a separate data consumer terminal such as

3 to 7 are exemplary diagrams of processed data displayed on a data consumer terminal.

The product information providing apparatus 200 according to an embodiment may process product data based on attribute information accumulated during a specific period selected by the user (during the second week of October in FIGS. 3 and 4 ).

The product information providing device 200 may also process product data based on a specific offline retail store (store A in FIGS. 3 and 4 ).

Specifically, the product information providing device 200 may generate statistical information for each element of personal information based on inquiry/purchase data of products for each category accumulated during a specific period.

For example, as shown in FIG. 3 , the product information providing device 200 determines which gender and age users most frequently searched for products belonging to the skincare-essence category based on product inquiry data accumulated for a week. After determining, product data may be processed. The processed data may be provided to the consumer terminals 300-1 and 300-2.

Also, the product information providing device 200 may generate a user's product search keyword corresponding to a combination result by combining at least two or more of categories for each product and at least one element of personal information.

For example, as shown in FIG. 3, when a product category called cream and women and women in their 20s are selected as elements of personal information, women and users in their 20s search for products in the skin care-cream category most frequently. One keyword may be determined, and a connection relationship between the corresponding keyword and the keyword may be provided to the consumer terminals 300-1 and 300-2.

Also, although not shown, the product information providing device 200 may measure the number of views or purchases for each product category and rank them.

In addition, the product information providing device 200 may generate a behavioral analysis result of users visiting a specific store based on product search/purchase data for each category accumulated during a specific period.

For example, referring to FIG. 4 , the product information providing device 200 is a user who visited a specific store during the promotion period (eg, a user who obtained a product information image of a specific store or a user determined by a purchase receipt image). ) and the percentage of users who visited during the non-promotional period (usual period) can be calculated.

Also, the product information providing device 200 may determine the number of revisits of the user for each promotion period or non-promotion period.

For example, referring to FIG. 4 , the product information providing device 200 may classify a user who has visited only once during a promotion period and a user who has visited multiple times during a promotion period, and a user who has visited only once and a user who has visited multiple times during a non-promotion period. Classification may be performed, and classification results may be provided to consumer terminals 300-1 and 300-2.

Also, the product information providing device 200 may determine a user's visit rate and product inquiry rate for each promotion performed during a specific period.

For example, referring to FIG. 4 , the product information providing device 200 may map product inquiry rates (search rates) and store visit rates of Promotions A, Promotions B, and Promotions C together, and the mapped result is a consumer terminal. (300-1, 300-2) can be provided.

Based on this, the data consumer (offline retail manager or manufacturer) can determine which promotion has the most product inquiries or store visits.

In addition, the product information providing device 200 may convert visitor patterns of each promotion into data for each period, and provide the data to the consumer terminals 300-1 and 300-2.

Accordingly, the consumer terminals 300-1 and 300-2 can grasp the store visit rate during the non-promotion period and the store visit rate during the promotion period in chronological order.

Also, the product information providing device 200 may generate a relationship diagram for each element by combining a plurality of elements of personal information.

For example, referring to FIG. 5 , the product information providing device 200 searches products for a relationship between a user's skin type (dry, combination, oily) and skin concerns (whitening, wrinkles, trouble, dryness, oiliness). /You can judge based on the purchase data, and you can diagram the relationship.

Specifically, when the product information providing device 200 finds that users with dry skin have the most skin concerns about dryness and oiliness, the dryness and oily spots are displayed on the "dry skin" chart. can be made In addition, if it is recognized that users with combination skin have various skin concerns, the product information providing device 200 may rank each skin concern and display a darker point for skin concerns with a higher rank.

Although not shown, the product information providing device 200 may aggregate visit rates for each offline retail store, rank the visit rates of offline retail stores based on the aggregated visit rates, and provide the information to consumer terminals 300-1 and 300-2. It is also possible to do

Meanwhile, the product information providing device 200 may generate and deliver reports for each product to the consumer terminals 300-1 and 300-2.

Referring to FIG. 6 , the product information providing device 200 determines a user's inquiry rate (search amount) for a specific product for a specific period (eg, October), a statistical analysis result of user information that has viewed a specific product, Comparison results with competitors' products can be made into a report and periodically provided to the consumer terminals 300-1 and 300-2.

For example, the product information providing device 200 calculates the number of product views (monthly search volume) for product A during October, and provides information on stores that sell product A and information on stores where product A is most frequently viewed. may be determined, and the determination result may be provided to the consumer terminals 300-1 and 300-2.

Also, the product information providing device 200 may sequentially list the number of product views of product A for each store during October and provide ranking information to the consumer terminals 300 - 1 and 300 - 2 .

Also, the product information providing device 200 may arrange the number of views of product A in chronological order and provide the information to the consumer terminals 300-1 and 300-2. At this time, it is possible to arrange by store, or it is also possible to arrange by summing the number of views of a plurality of stores.

In addition, the product information providing device 200 may determine competing products of the product to be reported and provide product information on the competing products to the consumer terminals 300-1 and 300-2.

For example, referring to FIG. 7 , the product information providing device 200 determines product B, which is a competitive product having similar attribute information to product A, which is a reporting target, calculates the number of product views of competing product B, and Information on stores selling Product B and information on stores where Competitive Product B is most frequently inquired may be determined, and the determination result may be provided to the consumer terminals 300-1 and 300-2.

In addition, the product information providing device 200 may time-sequentially chart the number of product views of product A and the number of views of competitor product B, which are the subject of reporting, on a social network service (SNS). The number of times a product A is mentioned can also be plotted together as a social index.

By charting the index in a time series like this, data consumers can predict at what time the promotion effect of a specific product will increase.

Referring back to FIG. 1 , the consumer terminals 300-1 and 300-2 display the data received from the product information providing device 200 to the data consumer (eg, offline retail store manager or manufacturer). .

The consumer terminals 300-1 and 300-2 may be implemented as computers or portable terminals equipped with displays. Here, the computer includes, for example, a laptop, a desktop, a laptop, a tablet PC, a slate PC, etc. equipped with a web browser, and a portable terminal, for example, has portability and mobility. As a guaranteed wireless communication device, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication) -2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminal, smart phone (Smart Phone) based on all types of handhelds It may include a wireless communication device and a wearable device such as a watch, ring, bracelet, anklet, necklace, glasses, contact lens, or head-mounted-device (HMD).

The product information search device 100, the product information providing device 200, and consumer terminals 300-1 and 300-2 are provided with hardware resources and/or software required to implement the technical idea of the present invention. It can, and does not necessarily mean a single physical component or a single device. That is, the product information providing system may refer to a logical combination of hardware and/or software provided to implement the technical idea of the present invention, and if necessary, it is installed in devices spaced apart from each other to perform each function, thereby presenting the present invention. It may be implemented as a set of logical configurations for implementing the technical idea of the invention.

In addition, the product information search device 100, the product information providing device 200, and the consumer terminals 300-1 and 300-2 are algorithms for controlling the operation of components constituting each or a program reproducing the algorithm. Alternatively, it may include a memory that stores a database for applications, and a processor that performs the above-described operation using the database stored in the memory. In this case, the memory and the processor may be implemented as separate chips. Alternatively, the memory and the processor may be implemented as a single chip.

Meanwhile, the disclosed embodiments may be implemented in the form of a recording medium storing instructions executable by a computer. Instructions may be stored in the form of program codes, and when executed by a processor, create program modules to perform operations of the disclosed embodiments. The recording medium may be implemented as a computer-readable recording medium.

Computer-readable recording media include all types of recording media in which instructions that can be decoded by a computer are stored. For example, there may be read only memory (ROM), random access memory (RAM), magnetic tape, magnetic disk, flash memory, optical data storage device, and the like.

As above, the disclosed embodiments have been described with reference to the accompanying drawings. Those skilled in the art to which the present invention pertains will understand that the present invention can be implemented in a form different from the disclosed embodiments without changing the technical spirit or essential features of the present invention. The disclosed embodiments are illustrative and should not be construed as limiting.

Claims (13)

In the control method of a product information providing device,
processing product data based on attribute information for each category of products stored in the database, the attribute information including promotion information, and personal information of users; and
Including providing the processed data to the consumer terminal,
Product attribute information for each product category stored in the database is generated based on a product information image captured by a user terminal;
Processing the product data,
Based on product search data for each category accumulated during a specific period selected by the user, the most searched keywords for product search of a specific category by specific users corresponding to at least two elements selected from among the elements of the personal information generating;
Calculating a first ratio between a user who visits a preset store during a promotion period and a user who visits the store during a non-promotion period;
calculating a second ratio between a user who visited the store only once and a user who visited the store multiple times among users who visited the store during the promotion period; and
calculating a third ratio between a user who visited the store only once and a user who visited the store multiple times among users who visited the store during the non-promotion period;
including,
The processed data provided to the consumer terminal,
A control method of a product information providing device including the first ratio, the second ratio, and the third ratio. delete delete According to claim 1,
Processing the product data,
Including the step of measuring the number of product views by category of the product,
Providing the processed data to the consumer terminal,
A control method of a product information providing device comprising the step of providing the consumer terminal with the number of product views for each category of the product. According to claim 1,
Processing the product data,
Further comprising processing product data based on category-specific attribute information and purchase information of products stored in the database;
The control method of the product information providing device, wherein the product purchase information stored in the database is generated based on a purchase receipt image captured by a user terminal. delete According to claim 1,
Processing the product data,
The control method of the product information providing device further comprising generating a relationship diagram for each element by combining elements of a plurality of personal information stored in the database. According to claim 1,
The elements of the personal information include at least two of gender, age, skin type, skin concern, skin tone, skin color, and taste. In the product information providing device,
The product information providing device includes a processor,
the processor,
Processing product data based on the attribute information for each product category stored in the database and personal information of users;
Provide the processed data to the consumer terminal,
Product attribute information for each product category stored in the database is generated based on a product information image captured by the user terminal,
When the processor processes the product data,
Based on product search data for each category accumulated during a specific period selected by the user, the most searched keywords for product search of a specific category by specific users corresponding to at least two elements selected from among the elements of the personal information create,
Calculating a first ratio of users visiting a preset store during a promotion period and users visiting the store during a non-promotion period;
Calculate a second ratio between users who visit the store only once and users who visit the store multiple times among users who visit the store during the promotion period;
Calculate a third ratio of users who visit the store only once and users who visit the store multiple times among users who visit the store during the non-promotion period;
The processed data provided to the consumer terminal,
The product information providing device including the first ratio, the second ratio, and the third ratio. delete delete A computer-readable recording medium on which a control method of the product information providing device according to any one of claims 1, 4, 5, 7 and 8 is recorded. delete

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