TWI742505B - Appointed merchant recommendation system sending marketing messgae and method thereof - Google Patents

Abstract

An appointed merchant recommendation system sending marketing message comprises a client database, a merchant database, an analytic module, a map module and an internet publishing module. The client database is configured to store a plurality of client information, each client information comprises a plurality of geographic locations. The merchant database is configured to store a plurality of merchant information, each merchant information comprises a merchant location. The analytic module retrieves one from the plurality of client information, calculates a plurality of weights corresponding to the plurality of geographic locations according to a current time and a current date, and calculates a plurality of search radii according to a default distance. The map module calculates a plurality of search regions and a search range according to the plurality of geographic locations with the plurality of radii and generates a recommendation list selected from the merchant database. The internet publishing module sends a marketing message according to the recommendation list.

Description

Special merchant recommendation system and method for sending marketing messages

The invention relates to a financial business promotion system, in particular to a system and method for recommending special merchants for sending marketing messages.

The popularity of the Internet and smart phones has spawned various new types of applications and service methods. In terms of daily purchase behavior, people can now use their mobile devices to directly check out, the so-called mobile payment. Different from the traditional use of cash or credit cards, the use of mobile devices to pay for various services or goods brings more convenience to consumers.

However, in the implementation and development stage of mobile payment, customers often do not know which merchants can make direct purchases through mobile payment. Therefore, customers may first go to the official mobile payment website to check the address of the designated merchant, and then use the address to query the map to obtain the route to the nearby designated merchant. Such cumbersome steps bring a lot of inconvenience to consumers. In addition, the various discounts released by special stores lack direct and instant channels to inform consumers. On the whole, there is still a lack of a system and method for matching mobile payment customers and special merchants.

In view of this, the present invention is to provide customers with customized recommendations for special merchants on mobile payment, so as to increase the number of customers joining the mobile payment platform and expand the scope of the special merchants.

According to an embodiment of the present invention, a special merchant recommendation system for sending marketing messages includes: a customer database, a merchant database, an analysis module, a map module, and a network publishing module. The customer database is used to store multiple customer information, and each customer information includes location information and consumption information. Location information includes multiple geographic locations, which are home address, company address, global positioning system location address, branch address, and ATM address. Consumption information includes consumption type and consumption amount. The business database is used to store a plurality of business information, each business information includes a business location and a preferential plan, and the preferential plan includes a plurality of preferential strategies. The analysis module is electrically connected to the customer database. The analysis module is used to obtain a piece of customer information from the customer database, calculate a weight corresponding to each geographic location in the customer information according to the current date and the current time, and according to a forecast Set the distance and multiple weights to calculate a search radius corresponding to each geographic location. The map module is electrically connected to the customer database, the merchant database, and the analysis module. The map module is used to calculate multiple search areas based on multiple geographic locations in the customer information and multiple search radii corresponding to these geographic locations. The search area calculates a search range, and filters out a recommended list from multiple business locations based on the search range and consumption information, and the recommended list includes a plurality of recommended businesses. The map module further includes a task module. The task module is used to select one of multiple discount strategies from the discount solutions corresponding to multiple recommended merchants according to the current date and current time. The network publishing module is electrically connected to the map module and used to send a marketing message according to the recommendation list. The marketing message includes a plurality of preferential strategies selected by the task module. Marketing messages are sent to email addresses, websites or mobile communication devices in the form of newsletters, web banner advertisements or push broadcasts.

According to an embodiment of the present invention, a method for recommending a special merchant for sending marketing messages includes: storing a plurality of customer information in a customer database, each customer information including location information and consumption information; storing a plurality of merchant information in a merchant Database, each business information includes business location and preferential plan, preferential plan includes multiple preferential strategies; obtain one customer information from the customer database; calculate multiple geographic locations in the extracted customer information based on the current date and current time Each corresponds to a weight; calculates the search radius corresponding to multiple geographic locations based on a preset distance and multiple weights; calculates multiple searches based on multiple geographic locations in the customer information and multiple search radii corresponding to these geographic locations Area; calculate a search range based on these search areas; filter a recommended list from multiple merchant locations based on the search range and consumption information. The recommended list includes a plurality of recommended merchants, and the corresponding offers from the recommended merchants are based on the current date and current time Select one of multiple preferential strategies in the plan; and send a marketing message according to the recommendation list. The marketing message includes the preferential strategy selected by the multiple recommended merchants.

Based on the above content, a special merchant recommendation system and method for sending marketing messages disclosed in the present invention, by analyzing the collected customer information and business information, calculates to find out the recommended merchants and businesses that individual customers have a tendency to consume in their life circles. The preferential strategies provided by these recommended merchants are instantly sent to customers' mobile communication devices or email addresses in the form of e-news, customized web banners, or push broadcasts, including marketing messages including recommended merchants and preferential strategies; The recommended merchants and discounts provided are adjusted according to the current date and time. Therefore, it is possible to find the special merchants that best meet the current needs of customers, achieve the effect of matching special merchants and mobile payment customers, and increase the use of mobile payment.

The above description of the disclosure and the following description of the implementation manners are used to demonstrate and explain the spirit and principle of the present invention, and to provide a further explanation of the patent application scope of the present invention.

The detailed features and advantages of the present invention will be described in detail in the following embodiments. The content is sufficient to enable anyone familiar with the relevant art to understand the technical content of the present invention and implement it accordingly, and according to the content disclosed in this specification, the scope of patent application and the drawings. Anyone who is familiar with relevant skills can easily understand the purpose and advantages of the present invention. The following examples further illustrate the viewpoints of the present invention in detail, but do not limit the scope of the present invention by any viewpoint.

Please refer to FIG. 1, which is a diagram illustrating the architecture of a special merchant recommendation system for sending marketing messages according to an embodiment of the present invention, including: a customer database 12, a merchant database 14, an analysis module 3, and a map module 5. Network publishing module 7. The following will introduce in detail according to the function of each component in the system.

The customer database 12 stores a plurality of customer information, and each customer information includes location information and consumption information. Specifically, the location information includes multiple geographic locations, such as home address, company address, Global Positioning System (GPS) location address, branch address, and Automated Teller Machine (ATM) address. Consumption information includes consumption type and consumption amount. In practice, financial institutions that provide mobile payment can obtain the above-mentioned location information from the personal information and counter records kept by the customer, and obtain the GPS location address from the customer’s mobile communication device, as well as from the customer every time a credit or financial card is used. Obtain the above-mentioned consumption information from the consumption record of the transaction behavior.

The merchant database 14 stores the business information of a plurality of special merchants. The designated merchants refer to merchants that have reached an agreement with financial institutions to provide consumers with mobile payment. Each business information includes the location of the business and the preferential plan. The preferential plan includes multiple preferential strategies, such as discounts or consumer cash rewards. These preferential strategies are set by the special merchants and financial institutions themselves, and recorded In the merchant database 14.

Please refer to Figure 1. The analysis module 3 is electrically connected to the customer database 12. In practice, the analysis module 3 is, for example, an application program running on a server of a financial institution. The analysis module 3 obtains a piece of customer information from the customer database 12, and calculates a weight corresponding to each of the multiple geographic locations in the customer information based on the current date and current time, and then calculates these based on a preset distance and multiple weights. Each location corresponds to a search radius.

For example, for an office worker who works on weekdays, the location at each time of the day includes the home, the road from the home to the company, the company and the company's surroundings, as shown in the first and second columns of the table below. The analysis module 3 can sort out the "time-place" relationship table of the same type of customers based on the personal information of all customers kept in the financial institution through big data analysis and summarization, and the third to fifth rows of the table below Set the weight values of each location at different times in the, and these weight values may fluctuate and adjust as more customer information is collected in the customer database. It should be noted that, in order to facilitate understanding and explanation, the following table only distinguishes the weight combinations of different states by "time"; in practice, in order to make a more accurate assessment of the scope of activities of different types of customers at different times, the analysis module 3 Date or special festival classification conditions can be added, so more types of weight combination setting values can be defined in advance.

Following the previous example, the operation mode of the analysis module 3 will be explained below. The analysis module 3 looks up the table above according to the current time (for example, 3 pm, 1500), and obtains the weight 1 of the company address is 0.9, the weight 2 of the GPS location address is 0.6, and the weight 3 of the home address is 0.3, where the GPS location address The customer’s smartphone or other mobile communication device can periodically return the customer’s most recent location information. The analysis module 3 further includes setting a preset distance, for example, 1000 meters. Therefore, the analysis module 3 can calculate the corresponding three sets of search radii as 900 meters, 600 meters, and 300 meters according to the preset distance and the three weights. It should be noted that the value range of the preset distance can also be adjusted adaptively according to whether the customer has a vehicle. Therefore, the same preset distance may not be applied to all customers in the customer database 12.

The map module 5 is electrically connected to the customer database 12, the merchant database 14 and the analysis module 3. The map module 5 itself has a map information, and a plurality of geographic locations in a customer information selected by the analysis module 3 And the search radius calculated by the analysis module 3 calculates a plurality of search areas on the map. Please refer to Figure 1 and Figure 2 together. Specifically, the map module 5 takes the company address a1, the GPS address a2, and the home address a3 as the centers, and cooperates with the three sets of search radii calculated by the analysis module 3. Three circular search ranges are calculated above, as shown in Figure 2: The search range corresponding to the company address a1 and the search radius is 900 meters is S1; the search range corresponding to the GPS address a2 and the search radius is 600 meters is S2 ; And the search range corresponding to the home address a3 and the search radius is 300 meters is S3. Map module 5 and then calculate a search range of the search area S _A in accordance with S1 ~ S3, In practice, the map module 5 performs a set of operations to calculate the search range S _A, for example, take the three search area S1 ~ S3 of any two The intersection of, or the union of three search areas S1~S3. In FIG. 2, the map module 5 calculated based search range S _A union taken.

On the other hand, the map module 5 pre-marks the business location of each business information in the business database 14 on the map. Thus, the map module 5 after each calculation of a customer's search range S _A, can then identify Businesses within this search range S _A, such as indicated in FIG. 2 m1 ~ m6, these screened The business information of recommended businesses m1~m6 is used as a recommendation list and sent to the network publishing module 7. Based on the above screening method, it can be ensured that the recommended merchants m1~m6 selected are within the life circle of the customer’s frequent activities, and the recommended merchants m1~m6 in the recommended list are adjusted in real time based on the current time and the GPS positioning information reported by the customer. list of.

Please review Figure 1. The network publishing module 7 is electrically connected to the map module 5, and the network publishing module 7 is used to send a one-line marketing message according to the recommendation list. Marketing messages are sent to the customer’s email address, financial institution’s website or customer’s mobile communication device in the form of e-newslet, web banner advertisement or push broadcast. In this way, for ordinary consumers, they can instantly know the nearby special merchants that can use mobile payment when checking emails, browsing bank websites or viewing mobile phone push broadcasts, and then go to use mobile payment for consumption behavior. For special merchants, the special merchant recommendation system for sending marketing messages disclosed by an embodiment of the present invention can be included in the recommendation list by the map module 5 when the customer is near the location of the merchant, thereby increasing its exposure. For financial institutions, providing the special merchant recommendation system for sending marketing messages disclosed in the present invention can increase customers' willingness to use mobile payment and attract more potential customer groups to join the ranks of mobile payment.

In another embodiment of the invention, the map module 5 in addition to S _A filter according to search criteria from multiple business locations in the recommended list, map module 5 further comprising a database of customer information for the previous 12 consumption screened Recommended list for further screening. In this way, it can be ensured that the recommended merchants in the screened recommendation list are not only an easy-to-reach incentive for customers, but the items sold or serviced by these recommended merchants are more sufficient to arouse high customer interest.

In another embodiment of the present invention, the map module 5 further includes a task module (not shown). The task module is used to select one of a plurality of discount strategies from the discount schemes provided by the recommended merchants according to the current date and current time, and the marketing message distributed by the network publishing module 7 further includes the information provided by the task module. The selection comes from the respective preferential strategies of multiple businesses. For example, the task module can set an order from a product each provided by a plurality of special merchants, and inform the customer through a marketing message that if they complete the transaction of these products by mobile payment in the specified order, they can return it A certain amount of consumer rebate, or enjoy more favorable discounts when you next purchase at these special merchants. The task module can combine the concepts of Geocatching and Geomarketing, and use big data to analyze the respective discount plans of multiple merchants to produce customized marketing messages suitable for each customer. It allows customers to increase their willingness to go to recommended merchants and use mobile payment for consumption when acquiring the marketing information sent by the network publishing module 7, thereby increasing the popularity of mobile payment.

Please refer to FIG. 3, which is a flowchart of a method for recommending a special merchant for sending marketing messages according to an embodiment of the present invention. Please refer to step P1: save customer information. Specifically, the financial institution stores a plurality of customer information in the customer database 12, and each customer information includes a location information and a consumption information.

Please refer to step P2: save business information. In detail, after the financial institution has negotiated with the special merchant, it will store the information of each merchant, including the location of the special merchant and the preferential plan provided. The preferential plan includes multiple preferential strategies, and store these business information in the merchant database 14 in.

Please refer to Step P3: Retrieve a customer information. Specifically, the analysis module 3 obtains one of a plurality of customer information stored in the customer database 12. In practice, the special merchant recommendation system for sending marketing messages disclosed in the present invention may include multiple analysis modules 3 in parallel and repeatedly performing this step P3 in order to publish the most immediate recommendation list to the respective smartphones of different customers.

Please refer to Step P4: Calculate the weights and search radius corresponding to multiple geographic locations. Following the example mentioned above, the analysis module 3 queries the weight table above to obtain the respective weight values of the company address a1, the GPS address a2, and the home address a3 according to the current time when it is executed, and according to the analysis model The preset distance and the aforementioned weight value in group 3 respectively calculate the search radius corresponding to each of these geographic locations.

Please refer to Step P5: Calculate the search area and search range. In detail, the map module 5 calculates multiple search areas based on the multiple geographic locations in the customer information and the search radius corresponding to these geographic locations, such as the search areas S1~S3 depicted in Figure 2, and then the map module 5 The search area is calculated according to a search range S _a S1 ~ S3.

Please refer to Step P6: Filter the recommended list based on consumer information and search scope. In detail, the map module 5 filters out a recommended list from multiple locations stored in the merchant database 14 according to the search range. The recommended list includes a plurality of recommended businesses, and these recommended businesses are all located in the search range calculated in step P5 S of _A within.

In another embodiment of the present invention, the recommendation list screened in step P6 further includes screening based on the consumption information stored in the customer database 12 by the map module 5. In this way, the map module 5 can use the aforementioned mechanism to find out a number of special merchants that best meet the customer's consumption needs and are within the scope of the customer's activities.

In step P6 of another embodiment of the present invention, the map module 5 further includes a task module. The task module selects a preferential strategy from the preferential schemes provided by multiple recommended merchants respectively according to the current date and the current time. In other words. The recommendation list screened out by the map module 5 not only includes a list of merchants suitable for customers to go to and use mobile payment, but also includes preferential strategies provided by each recommended merchant on the list. In addition, the task module can also provide a consumption task mode, such as integrating the preferential strategies of multiple merchants, and after the customer goes to multiple recommended merchants on the recommendation list in the order specified by the task module to use mobile payment for consumption. Customer consumption rebate, or get a more favorable discount ratio. The design of the task module can be adjusted in real time based on the marketing strategy to increase the willingness of customers to spend after learning the marketing information.

Please refer to Step P7: Send marketing messages. In detail, the network publishing module 7 sends marketing messages according to the recommendation list. In another embodiment of the present invention, the sent marketing message further includes a plurality of preferential strategies selected by the task module. With the cooperation of marketing messages and task modules, it is expected that customers can participate in physical promotions of mobile payment merchants, increase revenue instantly, deepen customer impressions, and create a good relationship between customers and designated merchants.

Based on the above, the special merchant recommendation system and method for sending marketing messages disclosed in the present invention analyzes the customer information collected by the financial institution and the business information of the agreed-upon special merchants, and combines the big data calculation method to find out Recommended merchants and discount strategies provided by these recommended merchants for individual customers in their life circle, including the recommended merchants and discount strategies in the form of e-news, customized web banners or push broadcasts. Marketing messages to the customer’s mobile communication device or email address. The recommended merchants and their discounts provided are adjusted based on the difference between the current date and the current time. Therefore, it can find the special merchants that best meet the current needs of customers, achieve the function of matching special merchants and mobile payment customers, and improve mobile payment Usage.

Although the present invention is disclosed in the foregoing embodiments, it is not intended to limit the present invention. All changes and modifications made without departing from the spirit and scope of the present invention fall within the scope of the patent protection of the present invention. For the scope of protection defined by the present invention, please refer to the attached scope of patent application.

12: Customer database 14: Merchant database 3: Analysis module 5: Map module 7: Web publishing module a1: Company address a2: GPS address a3: Home address S1~S3: Search area S _A : Search range m1~m6: recommended merchants P1~P7: steps

FIG. 1 is a structural diagram of a special merchant recommendation system for sending marketing messages according to an embodiment of the present invention. FIG. 2 is a schematic diagram of a search area and a search range according to an embodiment of the present invention. FIG. 3 is a flowchart of a method for recommending a special merchant for sending marketing messages according to an embodiment of the present invention.

12: Customer database

14: Merchant database

3: Analysis module

5: Map module

7: Network publishing module

Claims (5)

A special merchant recommendation system for sending marketing messages includes: a customer database for storing a plurality of customer information, each of the customer information includes a location information, the location information includes a plurality of geographic locations; a merchant database, Used to store a plurality of business information, each of the business information includes a business location; an analysis module is electrically connected to the customer database, the analysis module is used to obtain the customer information from the customer database. One is to calculate a weight corresponding to each of the geographic locations in the customer information based on a current date and a current time, and to calculate a search radius corresponding to each of the geographic locations based on a preset distance and the weights; a map The module is electrically connected to the customer database, the merchant database and the analysis module. The map module is used to calculate a plurality of search areas based on the geographic locations and the search radii in the customer information. Some search areas calculate a search range, and filter out a recommendation list from the business locations based on the search range, the recommendation list includes a plurality of recommended businesses; and a network publishing module, which is electrically connected to the map module, The network publishing module is used to send a marketing message based on the recommendation list. The marketing message is sent to an email address, a website or a mobile communication device in the form of an e-newsletter, a web banner advertisement or a push broadcast. When storing the business information in the merchant database, it further includes storing a discount plan corresponding to each of the business information in the merchant database, and the discount plan includes a plurality of discount strategies. The special merchant recommendation system for sending marketing messages according to claim 1, wherein the geographic locations include a home address, a company address, a GPS location address, a branch address, and an ATM address. The special merchant recommendation system for sending marketing messages according to claim 1, wherein the map module performs a set operation according to the search areas to calculate the search range. A method for recommending special merchants for sending marketing messages, including: storing a plurality of customer information in a customer database, each of the customer information includes a location information and a consumption information, wherein the location information includes a plurality of geographic locations; The business database stores multiple business information, each of which includes a business location; an analysis module is used to obtain one of the customer information from the customer database; and the analysis module is based on a current date and Calculate a weight corresponding to each of the geographic locations in the customer information at a current time; use the analysis module to calculate a search radius corresponding to each of the geographic locations based on a preset distance and the weights; use a map module according to The geographic locations and the search radii in the customer information are used to calculate a plurality of search areas; the map module is used to calculate a search area according to the search areas; the map module is used to calculate a search area from the business locations according to the search area Filter out a recommended list, the recommended list including a plurality of recommended businesses; and A web publishing module is used to send a marketing message based on the recommendation list. The marketing message is sent to an email address, a website or a mobile communication device in the form of an e-newsletter, a web banner advertisement or a push broadcast. When the merchant database stores the business information, it further includes storing a discount plan corresponding to each of the merchant information in the merchant database, and the discount plan includes a plurality of discount strategies. As described in claim 4, the method for recommending special merchants for sending marketing messages, wherein before the recommendation list is filtered out, it further includes using the map module to screen according to the consumption information.

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