TW202134977A - Information promotion method, mobile device and computer program product - Google Patents

Abstract

An information promotion method, a mobile device, and a computer program product are provided. In the method, discount information of one or more stores is obtained, user information including location information and ticker information of electronic ticket is obtained, the discount information of the stores is selected and sorted according to the location information to generate promotion information, and the promotion information is provided. The promotion information may further provide for payment operation by the electronic ticket. Accordingly, purchase behavior between the customer and the stores could be improved.

Description

Information recommendation method, mobile device and computer program product

The present invention relates to an information processing technology, and particularly relates to an information recommendation method, mobile device and computer program product.

Mobile payment, as its name implies, is to allow consumers to conveniently and carry out payment and consumption behaviors anytime, anywhere. The e-ticket cards that can be used for payment are, for example, credit cards, leisure cards, all-in-one cards, etc., and the places that can be used are convenience stores, mass merchandisers, supermarkets, department stores/shopping centers, chain restaurants, online stores, chain stores, etc. . Among them, the payment method may be Near-field communication (NFC) sensing, QR code scanning/reverse scanning, etc. Nowadays, mobile payment companies are contending, and the services they provide are usually through binding electronic ticket cards, and then using QR codes for forward/reverse scanning payments or NFC induction payments, and may even return the bonus points given by this payment operation, such as , Line Pay, Apple Pay, Google Pay, etc. The feature of mobile payment is nothing more than providing a quick checkout process, or even combining some bonus points to attract consumers to use it.

However, various mobile payment companies are similar, and most consumers have multiple e-ticket cards at the same time, and even each store has different discounts for each credit card bank or e-ticket card. For consumers, too much information is troublesome and complicated. When consumers really need to spend and look for discounts online, they are often at a loss.

In view of this, embodiments of the present invention provide an information recommendation method, server, and computer program product, which can integrate and recommend appropriate preferential information, and allow users to easily check out.

The information recommendation method of the embodiment of the present invention is suitable for recommending merchant discounts and includes the following steps: obtaining discount information of the store. Obtain user information, and this user information includes location information and e-ticket information. Select and sort the discount information of those stores based on this location information to generate recommended information. This recommendation information is provided, and the recommendation information can be used for payment by those electronic ticket cards.

The mobile device of the embodiment of the present invention includes (but is not limited to) a communication transceiver, a positioning module, and a processor. The communication transceiver transmits or receives data. The positioning module obtains the location information of this mobile device. The processor is coupled to the communication transceiver and the positioning module, and is configured to perform the following steps: obtain discount information of at least one store through the communication transceiver, obtain user information, select and sort the discount information of those stores according to the location information Generate recommendation information and provide this recommendation information. User information includes location information and e-ticket information. The recommended information is available for those e-ticket cards for payment operations.

The computer program product of the embodiment of the present invention can be loaded with a mobile device to execute the following steps: obtain user information and obtain recommended information. This user information includes location information and ticket information of at least one electronic ticket. The recommended information is the preferential information of at least one store selected and sorted based on the location information, and the recommended information can be used for payment by those e-ticket cards.

Based on the above, the information recommendation method, mobile device, and computer program product of the embodiments of the present invention determine whether the user’s location meets the conditions for providing recommended information, and accordingly provide preferential information about shops around the user’s location, and facilitate the user’s use of electronic Ticket card checkout. In this way, it can provide location-based services (LBS), which can help consumers and businesses to consume behavior.

In order to make the above-mentioned features and advantages of the present invention more comprehensible, the following specific embodiments are described in detail in conjunction with the accompanying drawings.

Fig. 1 is a schematic diagram of a transaction system 1 according to an embodiment of the present invention. Please refer to FIG. 1, the transaction system 1 includes a computer device 10 of at least one store, a mobile device 30 of at least one user, and a service platform server 50.

The computer equipment 10 may be a desktop computer, a notebook computer, a smart phone, a tablet computer, and other devices. The computer device 10 may include (but is not limited to) a processor (for example, a CPU, a special application integrated circuit (ASIC), a microprocessor, or a field programmable logic gate array (FPGA), etc.), a memory (for example, Random access memory (RAM), read-only memory (ROM), or flash memory, etc.), and communication transceivers (for example, networks that support mobile communications, Ethernet, or fiber optic networks) Card or module). In this embodiment, the computer device 10 is used by the store.

The mobile device 30 may be a device such as a smart phone, a tablet computer, or a smart watch. The mobile device 30 may include (but is not limited to) a processor (for example, CPU, ASIC, microprocessor, or FPGA, etc.), storage (for example, RAM, ROM, or flash memory, etc.), and a communication transceiver (for example, , Network cards or modules that support technologies such as mobile communications, Ethernet, or fiber optic networks) and positioning modules (for example, support for satellite positioning systems, base station positioning, indoor positioning, or other positioning technologies). In this embodiment, the mobile device 30 is used by the user. It is worth noting that the mobile device 30 is further loaded with a mobile payment application (APP), which includes a preferential information recommendation (software) module, and its function will be detailed in subsequent embodiments. Hereinafter, the operation of the mobile device 30 will be based on the processor.

The service platform server 50 may be a desktop computer, various types of servers (for example, cloud servers, database servers, or application servers, etc.), or workstations and other devices. The service platform server 50 may include (but is not limited to) a processor (for example, CPU, ASIC, microprocessor, or FPGA, etc.), storage (for example, RAM, ROM, or flash memory, etc.), and communication transceivers. Devices (for example, network cards or modules that support technologies such as mobile communications, Ethernet, or fiber optic networks).

In order to facilitate the understanding of the operation process of the present invention, a number of embodiments will be described below in detail. Hereinafter, the method described in the embodiment of the present invention will be described in conjunction with the devices, components, and modules in the transaction system 1 of FIG. 1. Each process of the method can be adjusted accordingly according to the implementation situation, and it is not limited to this.

FIG. 2 is a flowchart of an information recommendation method according to an embodiment of the present invention. Referring to FIG. 2, the processor of the mobile device 30 obtains preferential information of at least one store through its communication transceiver (step S210). Specifically, the store is responsible for maintaining and listing the discount information (that is, uploading the discount information to the service platform server 50), and uploading the discount information according to the interface standard or format established by the service platform server 50. In one embodiment, the preferential information is based on "one store, one data". For example, Carrefour has branches such as Songshan Store, Nangang Store, Beitou Store...etc. Since each branch’s location and size are different, even if their cooperative e-ticket cards and purchase discounts are the same, but the geographical location is different, in order to enable the system to provide services normally, it is still in accordance with the "one store, one data" Shelf in principle. Table (1) is an example to illustrate the format of recording preferential information: Table (1) shop Branch Geographic location Ticket card Offer content Validity period Carrefour Songshan Store 25.0619 121.5632 CITIC Platinum Card 5% off for full thousand From 2020/01/03 to 2020/03/01 Carrefour Nangang Store 25.05432 121.5966 CITIC Platinum Card Buy three toilet paper get one free From 2020/02/01 to 2020/02/29

On the other hand, the service platform server 50 builds a service platform, and may define various data structures and/or various programming interfaces, and provide operations such as database and/or real-time services for the store to perform discounts through the computer equipment 10 Shelves and users perform data query through the mobile device 30 (for example, query the priority information of a specific store or a specific electronic ticket card, etc.). The definition of the data structure is mainly to define the data fields of the discount information, as shown in Table (1), the necessary fields recommended (for example, store name, geographic location, applicable e-ticket card, discount content details, validity period, etc.), but not (Limited to this), and can further increase the store radius or discount offer range and other fields to assist the mobile device 50 in determining the store stay (to be detailed in subsequent embodiments).

Then, the mobile payment application of the mobile device 30 can download the computer from the service platform server 50 periodically or in response to a specific triggering behavior (for example, receiving an information update notification from the service platform server 50, booting up, connecting to the network, etc.) Preferential information uploaded by device 10. These preferential information may be organized by the aforementioned specific data structure or format. In some embodiments, the service platform server 50 may also actively push notification or broadcast preferential information to the mobile device 30. It should be noted that the mobile device 30 may first download simple information for subsequent comparison (for example, the geographic location of the store, the scope of the offer, or the validity period, etc.), and download more detailed offers after the comparison is matched. News. Alternatively, the mobile device 30 can also directly download detailed preferential information.

In addition, FIG. 3 is an example to illustrate the scope of discounts. Please refer to Figure 3, regarding the geographic location corresponding to the merchant or its discount information (such as the latitude and longitude coordinates of Table (1)), the location of the store (for example, the center of the store's area, the center of gravity, or any location within its range) Is the center of the circle, and set the corresponding discount offer range. For example, the first store is a discount providing range R1 formed by a radius r1, and the second store is a discount providing range R2 formed by a radius r2. The size of the radius and the shape of the discount offer range may be set by the store itself, but may also be set uniformly on the service platform server 50.

It should be noted that the contents in Table (1) and FIG. 3 are only used for exemplary description, and are not intended to limit the embodiment of the present invention. The range of discounts in Fig. 3 is an example of a circle, but it may also be a quadrilateral or other geometric shapes. In addition, in other embodiments, a store may have multiple pieces of information on the shelf.

The processor of the mobile device 30 obtains user information of at least one user (step S230). Specifically, user information includes (but is not limited to) the user's location information, and at least one electronic ticket card (e.g., electronic wallet, mobile bill payment account, transfer payment account, online payment account, credit card, financial card, Or membership card, etc.) ticket information (for example, name, type, expiration date, authentication information, and/or payment method, etc.). The mobile payment application of the mobile device 30 obtains the location information of the user (for example, the latitude and longitude coordinates, or the relative position of a specific reference landmark, etc.), and the electronic ticket card and the ticket card information set by the user through the positioning module. In some embodiments, each piece of position information can be accompanied by a timestamp to confirm the movement track of the mobile device 30.

Then, the processor of the mobile device 30 selects and sorts the preferential information of one or more stores according to the location information of the user to generate recommendation information of a specific user (step S250). Specifically, the mobile payment application of the mobile device 30 can compare the user's location (based on location information), stay time, and/or ticket information with the discount information, and determine whether to provide the matching discount information To the user. That is, take the initiative to provide suitable preferential information.

Regarding information filtering and sorting, in one embodiment, the mobile device 30 can set the discount offer range of each store, determine the distance relationship between the location information and the discount offer range of these stores, and based on the distance relationship corresponding to these stores Select and sort the discount information of those stores. For the scope of the preferential provision, please refer to the aforementioned description of FIG. 3, which will not be repeated here. The mobile device 30 can download these discount offer ranges from the service platform server 50 or preset the discount offer ranges by itself. The distance relationship may be the distance between the location corresponding to the location information and the center, the center of gravity, the nearest contour, or any of the locations of the discount providing range. In some embodiments, the distance relationship may consider obstacles around the user's location (for example, obstacles such as walls, beams, etc. can be obtained by downloading and comparing a floor plan), rather than a simple straight-line distance. For example, the distance relationship is the shortest path of the electronic map. Then, the mobile device 30 can select the distance relationship that the location information corresponds to the store within the discount offer range. That is, the scope of its discounts covers the discount information of the store where the mobile device 30 is located.

In one embodiment, the mobile device 30 may further sort the discount information of the stores according to the distance between the corresponding locations of the location information in the distance relationship and those stores. For example, the mobile device 30 sorts the stores according to the relative distance corresponding to the distance relationship, and sorts the stores with the closer distance in the front, and sorts the stores with the farther distance in the back. In other embodiments, the mobile device 30 may also sort these stores randomly.

In another embodiment, the mobile device 30 can determine the electronic ticket card owned by the user and the electronic ticket card corresponding to the discount information, and select the discount information of a store that has the same or similar electronic ticket card information corresponding to the electronic ticket card. In some embodiments, the mobile device 30 may further rank the closer the expiration date corresponding to the discount information to the current time is higher, and rank the expiration date closer to the current time at the lower end. In addition, the mobile device 30 excludes discount information outside the valid period.

If the comparison matches (for example, the location and/or the ticket card match), the mobile device 30 uses the matching discount information as the recommendation information (that is, the recommendation information is generated based on the selected discount information), and provides a lump sum or more. Multiple pieces of recommended information are given to the user (step S270). Specifically, the mobile device 30 can present the recommended information through a message prompt interface (via a display (for example, LCD, or OLED, etc.)). In addition, the ranking of the recommended information may be based on the aforementioned ranking method (for example, distance and/or expiration date, etc.).

Figure 4 is an example illustrating the presentation of recommended information. Please refer to FIG. 4, the display 35 of the mobile device 30 displays sorted recommendation information 401, 402, 403. Recommended information 401, 402, 403 can include store name (for example, BellaVita, or ATT 4FUN), e-ticket card (for example, China Trust Platinum Card, or Cathay Pacific Enjoying Card), expiration date (for example, from now until 12/ On the 31st, until 8/8, or until 11/30), and discount content (e.g., get a gift for a thousand, or get a tie for a gift of 3,000, etc.).

It is worth noting that these recommended information can be further used by the user to use the corresponding e-ticket card for payment operations (for example, credit card/financial card checkout, third-party payment, e-wallet payment, online payment, etc.). Specifically, the basic requirements of most consumers for payment operations are speedy and effective, and the satisfaction of them can increase consumers' sense of pleasure. When the user receives a notification of recommended information (for example, a push notification or program interface presentation, etc.), it is likely to make a payment next. When the user reads and understands the details of the discount, and decides which discount (or which electronic ticket card to use for payment), he can open the payment interface from the discount notification interface of the mobile payment application.

The mobile device 30 can detect the user's selection operation of those recommended information (for example, click/confirm/circle selection operation on a specific location) through an input device (for example, a touch panel, a mouse, or a button, etc.), and select the user Select the e-ticket card corresponding to the recommended information corresponding to the selected operation, and provide the payment checkout interface of the selected e-ticket card (for example, display a QR code, display a camera shooting screen, a fingerprint input prompt, or a prompt screen when the device is close to the credit card machine, etc.) .

Taking Fig. 4 as an example, there are three recommended information 401~403 on the preferential notice interface. The user only needs to click any one of the recommended information 401~403 notifications, and the mobile device 30 can bring up the payment checkout interface and its flow. The e-ticket card selected for payment is the e-ticket card matched with this recommended information, so that the user does not need to manually select it. The payment method is different for each mobile payment application, and this payment operation will not affect or change the original default payment e-ticket card. For example, start the QR code forward or reverse scanning operation, or present a notification of approaching the credit card machine, etc.

In some embodiments, the mobile payment application can obtain the user's response to the operation on the interface through the message prompt interface and the input device, so as to know whether the user agrees to use the electronic ticket to pay. If agreed, the mobile payment application will start the payment process without changing the payment process of the mobile device's original default e-ticket card. Users can make payments in accordance with the existing payment procedures. If they do not agree, the mobile payment application compares the location of the mobile device 30 with the preferential information, and determines whether to cancel the message prompt interface of the recommended information selected above. After the message prompt interface is cancelled, it will no longer prompt the user within a certain time interval (for example, 10, 15 or 20 minutes, etc.).

On the other hand, for the recommended information that has been provided, the mobile device 30 can further determine whether the user is no longer applicable to the recommended information (for example, the user leaves the store), and delete or cancel the recommended information or change the ranking accordingly. For example, the interface removes the recommended information of some stores whose users have left the scope of their offers, or sorts the recommended information of these stores to the end.

Regarding the judgment of the user leaving or staying in the scope of the offer, since the user may go back and forth between different stores, the accumulated stay time can be used to judge the user's willingness to spend in a particular store. Figure 5 is an example of staying judgment. Please refer to FIG. 5, assuming that this first store has a discount providing range R1 formed by a radius r1. The mobile device 30 can accumulate the first stay time that the location corresponding to its location information is within the discount providing range R1 of the first store (that is, the location where the user is located is within a radius r1 from the store). If the first stay time is greater than the first time threshold, the mobile device 30 confirms that the location information corresponds to the discount providing range R1. That is, the user stays in the store and has a high willingness to spend. Otherwise, the mobile device 30 has not confirmed that the location information corresponds to the discount providing range R1, and continues to determine until the first stay time returns to zero.

For example, the user's path may be: position 501, position 503, position 501, and position 503 in sequence. The time of the mobile device 30 at the locations 501, 503 will be accumulated for the first stay time, and the time at the locations 502, 504 will not be accumulated for the first stay time.

In some scenarios, the user is not in the first store (for example, at location 502) but the location is within the discount providing range R1. For these users passing through the first store, the path is likely to be: position 504, position 502, position 504, and position 504 in sequence. Therefore, the design of staying judgment needs to be fault-tolerant. The embodiment of the present invention further provides a judgment mechanism for the user to leave the range. The mobile device 30 also accumulates the second stay time when the location corresponding to its location information is outside the discount providing range R1 of the first store (that is, the location where the user is located is outside the radius r1 from the store). For example, the time of the mobile device 30 at the location 504 will be accumulated to the second stay time. Then, if the first stay time is less than the first time threshold but the second stay time is greater than the second time threshold (which may be the same as the first time threshold, but may also be different), the mobile device 30 determines that the user has left the first time threshold. The store may have no intention of spending in the first store, and the first stay time will be zero. Conversely, if the second stay time is less than the second time threshold but the first stay time is greater than the first time threshold, the mobile device 30 can determine that the user still intends to stay in the first store for consumption. In addition, for the store that the user has left, the mobile device 30 may remove or sort the corresponding recommendation information to the back.

In another embodiment, the mobile device 30 can directly compare the geographic location of the store with the location information of the mobile device 30. If the distance between the user’s location and the store is greater than the distance threshold, the mobile device 30 determines that the user has left the first store or does not intend to spend in the first store, and there is no need to accumulate the second stay time, and the first stay time can be directly returned zero. In this way, it is possible to identify whether the user is a customer of shop consumption. For in-store guests, the mobile device 30 only provides notifications of corresponding preferential information. For those who are not in-store or have left, the mobile device 30 does not provide a notification corresponding to the preferential information, or deletes the notification of the provided preferential information.

Fig. 6 is another example of staying judgment. Referring to FIG. 6, compared with FIG. 5, the newly added second store has a discount providing range R2 formed by a radius r2. If the user is at the location 601, it is likely that the first stay time in two stores will be accumulated and the first time threshold will be reached at the same time, and the mobile device 30 can provide a notification of the preferential information of the two stores. It is worth noting that, in order to facilitate the checkout of the user, the mobile device 30 may further perform recommendation information according to the average distance of the path (that is, the average distance between the user's location and the geographic location of the store within a period of time). Sort, so that the preferential notifications of stores with shorter average distances are sorted in a higher priority position.

It should be noted that the aforementioned first and second time thresholds may be changed according to the user's behavior (for example, habitual stay time, past movement path, etc.), or may be provided by the computer device 10 according to the size or nature of the store Customized settings. In addition, in addition to the aforementioned notification of preferential information, in addition to determining that the user is a store guest, the user still needs to set the e-ticket card cooperated with the store in the mobile payment application.

Another embodiment of the present invention provides a computer program product for executing each step of the above-mentioned information recommendation method (the embodiments shown in FIG. 2 to FIG. 6). The computer program product includes a plurality of program instructions, and after the processor in the mobile device 30 loads and executes these program instructions, the above-mentioned information recommendation method and the functions of the mobile device 30 can be implemented.

In summary, the information recommendation method, mobile device, and computer program product of the embodiments of the present invention include the following features:

The server establishes a store-listing discount information platform, and provides store-listing discount information, and each store can put it on the shelves according to its individual circumstances to improve the accuracy and completeness of the data.

Through mobile device positioning, the user's mobile behavior is calculated and exchanged with the background preferential information platform to infer the location of the store where the user may be located.

Proactively send notifications of appropriate discount information according to different stores, and users can know all the discounts available in the store and the e-ticket card held by the user at the first time, without having to spend additional time searching for discount information on the Internet.

Click on the offer information notification to bring up the electronic ticket payment process related to this offer. Users can use this ticket to make payment immediately without changing the original payment settings.

Although the present invention has been disclosed in the above embodiments, it is not intended to limit the present invention. Anyone with ordinary knowledge in the relevant technical field can make some changes and modifications without departing from the spirit and scope of the present invention. The protection scope of the present invention shall be subject to those defined by the attached patent application scope.

1: Trading system 10: Computer equipment 30: mobile device 50: service platform server S210~S270: steps r1, r2: radius R1, R2: Offer scope 501~504, 601: location 35: display 401~403: Recommended information

Fig. 1 is a schematic diagram of a transaction system according to an embodiment of the present invention. FIG. 2 is a flowchart of an information recommendation method according to an embodiment of the present invention. Figure 3 is an example illustrating the scope of the offer. Figure 4 is an example illustrating the presentation of recommended information. Figure 5 is an example of staying judgment. Fig. 6 is another example of staying judgment.

S210~S270: steps

Claims (10)

An information recommendation method suitable for recommending merchant offers, including: Obtain discount information from at least one store; Obtain a user information, where the user information includes a location information and ticket information of at least one electronic ticket; Select and sort the discount information of the at least one store based on the location information to generate a recommendation information; and Provide the recommended information, where the recommended information is used for the at least one electronic ticket card to perform payment operations. The information recommendation method according to claim 1, wherein the step of selecting and sorting the preferential information of the at least one store according to the location information includes: Set the scope of discounts provided by each store; Determine the distance relationship between the location information and the offer range of the at least one store; and The preferential information of the at least one store is selected and sorted according to the distance relationship corresponding to the at least one store. The information recommendation method according to claim 2, wherein the step of selecting and sorting the preferential information of the at least one store according to the distance relationship corresponding to the at least one store includes: Choosing the distance relationship is that the location information corresponds to at least one store within the scope of the offer; and The preferential information of the at least one store is sorted according to the distance between the corresponding location of the location information in the distance relationship and the at least one store. The information recommendation method according to claim 2, wherein the at least one store includes a first store, and the step of selecting and sorting the preferential information of the at least one store according to the distance relationship corresponding to the at least one store includes: Accumulate a first stay time in which the location corresponding to the location information is within the offer range of the first store; Accumulate a second stay time when the location corresponding to the location information is outside the range of the first store's offer; If the first stay time is less than a first time threshold but the second stay time is greater than a second time threshold, then it is determined that the user has left the first store. The information recommendation method according to claim 1, wherein before the step of providing the preferential information, it further includes: Select the discount information of the e-ticket corresponding to the ticket information. A mobile device including: A communication transceiver, which transmits or receives data; A positioning module to obtain the location information of the mobile device; and A processor, coupled to the communication transceiver and positioning module, and configured to: Obtain preferential information of at least one store through the communication transceiver; Obtain a user information, where the user information includes the location information and the ticket information of at least one electronic ticket; Select and sort the discount information of the at least one store based on the location information to generate a recommendation information; and Provide the recommended information, where the recommended information is used for the at least one electronic ticket card to perform payment operations. The mobile device according to claim 6, wherein the processor is further configured to: Set the scope of discounts provided by each store; Determine the distance relationship between the location information and the offer range of the at least one store; and The preferential information of the at least one store is selected and sorted according to the distance relationship corresponding to the at least one store. The mobile device according to claim 7, wherein the processor is further configured to: Choosing the distance relationship is that the location information corresponds to at least one store within the scope of the offer; and The preferential information of the at least one store is sorted according to the distance between the corresponding location of the location information in the distance relationship and the at least one store. A computer program product that loads a program through a mobile device to execute: Obtain a user information, where the user information includes a location information and ticket information of at least one electronic ticket; and Obtain a recommendation information, where the recommendation information is preferential information of at least one store selected and sorted according to the location information, and the recommendation information is used for the at least one electronic ticket card to perform payment operations. The computer program product according to claim 9, wherein the preferential information of the at least one store is related to the ticket information of the at least one electronic ticket, and the mobile device further executes: Select the e-ticket card corresponding to the recommended information corresponding to the user's selection operation; and Provide the payment checkout interface of the selected e-ticket card.

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