CN110930180A - Data analysis method and system based on regional membership marketing scene and computer equipment - Google Patents
Data analysis method and system based on regional membership marketing scene and computer equipment Download PDFInfo
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Abstract
The invention discloses a data analysis method, a system and computer equipment based on a regional membership marketing scene, wherein the method comprises the following steps: according to the distribution condition of physical stores of a merchant, carrying out gridding division on a target area, wherein each physical store corresponds to a grid; building a store information database, and corresponding the gridded regional geographical position information with the entity store code information and the gridding code information; constructing a user information database; and matching address information generated by the user triggering online behavior to acquire entity store information corresponding to the area where the user is located, and attributing the user to an effective marketing area of an offline store through the online behavior of the user. The method and the system position the online address information of the user by acquiring the address information data generated by the online behavior of the user, thereby generating the actual geographical contact between the online user and the offline store through the address, accurately attributing the online user to the marketable area range of the offline store, and further realizing the gridding management of the sales area.
Description
Technical Field
The invention belongs to the technical field of electronic commerce, and particularly relates to a data analysis method, a data analysis system and computer equipment based on a regional membership marketing scene.
Background
In the conventional retail industry, a physical store accumulates a large amount of consumer groups by absorbing members, and develops various marketing activities by periodically pushing commodity information.
With the development of electronic commerce, the O2O (Online To Offline) model is becoming mature, and O2O is a commerce model that combines the Online transaction of goods or services based on an electronic commerce website with the actual experience of goods or services based on a physical store, so that the electronic commerce website becomes the foreground of the transaction of the physical store, and the physical store becomes the background of the transaction of the electronic commerce website.
In recent years, online consumption platforms are continuously enlarged, and companies of entity stores under original deep ploughing lines are also arranged in electronic commerce of march troops. The on-line abundant marketing means makes the on-line member team develop and grow continuously. If the online member and the offline physical store member are fused, the merchant can conveniently know the consumed groups and the potential consumed groups around the physical store, and the integration marketing is convenient.
Patent No. 201710944600.7 discloses a transaction data processing method, apparatus and system. In a scene that a user purchases commodities in an entity store (namely, an offline shopping scene), transaction data is generated by taking an online identity of the user on a third party/online transaction server as an offline commodity, or transaction data is generated by taking an online price of the offline commodity for the offline commodity, and the transaction data is respectively synchronized to a store terminal and a user terminal, so that an online and offline combined transaction data processing mode is realized, convenience of offline transactions in the aspects of management, maintenance, operation and the like can be driven by utilizing online advantages, competitiveness of the entity store in an e-commerce environment is improved, and development of the entity store is promoted. However, the patent does not precisely manage the offline physical stores, and does not precisely associate the online members with the offline physical stores through addresses.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a data analysis method based on a regional membership marketing scene, so that accurate association of online members and offline physical stores through position information is realized.
The technical solution for realizing the purpose of the invention is as follows: a data analysis method based on a regional membership marketing scene comprises the following steps:
according to the distribution condition of physical stores of a merchant, carrying out gridding division on a target area, wherein each physical store corresponds to one grid, and two adjacent grids are not overlapped;
building a store information database;
constructing a user information database;
and matching address information generated by the user triggering online behaviors to acquire the entity store information corresponding to the area where the user is located, and attributing the user to the effective marketing area of the entity store through the online behaviors of the user.
Preferably, the gridding and dividing the target area specifically includes:
the method comprises the steps that a radiation area is established by taking the geographic position of an entity store as a center, the radiation area is a closed polygon, the radiation areas of two adjacent entity stores are not repeated, the closed polygon areas established by all the entity stores in a target area jointly form a net, and gridding division of the target area is achieved.
Preferably, the store information database includes:
the geographical position information of the shop area of the merchant entity comprises longitude and latitude data corresponding to a central point of the geographical position of the shop and longitude and latitude information of a radiation area boundary, and is simultaneously recorded into an online map tool;
the physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number;
grid coding information comprising grid numbers, wherein each grid has a unique grid number;
the above information corresponds to each other.
Preferably, the user information database includes:
the user address information comprises longitude and latitude information corresponding to the address information;
the physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number;
grid coding information comprising grid numbers, wherein each grid has a unique grid number;
the above information corresponds to each other.
Preferably, the user information database is divided into two types, wherein the first type is a historical database which comprises address information, entity store code information and grid code information generated by historical user behaviors;
the second type is an incremental database, which includes incremental user behavior generated address information, physical store code information and grid code information.
Preferably, the matching of the address information generated by the user triggering the online behavior specifically includes:
performing first matching on the generated address information in a user information database, if consistent address information exists, successfully matching for the first time, and simultaneously acquiring entity store code information and grid code information from the user information database;
otherwise, the first matching is failed, and then the longitude and latitude information corresponding to the address is obtained by calling an online map tool;
and carrying out second matching on the longitude and latitude information in a store information database:
if the longitude and latitude is in the radiation area of the physical store, the second matching is successful, and meanwhile, the physical store coding information and the grid coding information are obtained from the store information database; inserting the related information into an increment database of the user information database as increment data;
otherwise, the second matching fails, and prompt information is sent out.
Preferably, the method further comprises a target area judging step after the first and/or second matching fails, and whether the address information generated by the user triggering on-line behavior is in the target area is judged.
A data parsing system based on a regionalized membership marketing scenario, comprising:
the target area gridding division module is used for gridding and dividing a target area according to the distribution condition of physical stores of merchants, each physical store corresponds to one grid, and two adjacent grids are not overlapped;
a store information database;
a user information database;
and the information matching module is used for matching address information generated by the user triggering online behavior, acquiring the information of the physical store corresponding to the area where the user is located, and attributing the user to the effective marketing area of the offline store through the online behavior of the user.
Compared with the prior art, the invention has the following remarkable advantages: 1) according to the online marketing management method, online address information of a user is positioned through online behaviors (such as access, purchase and the like) of the user, a text type address is converted into a numerical value type longitude and latitude, an effective marketing range of a store in a business sense is converted into a corresponding grid longitude and latitude numerical value of the store in a digital sense, and online members and offline physical stores are accurately associated through the addresses, so that more accurate grid management can be performed on the physical stores, and subsequent marketing activities are facilitated; 2) the online user and the offline store are digitally and accurately connected, and the purpose of online and offline member fusion is achieved, so that online and offline integrated marketing can be performed on the members, O2O fusion is further realized, and intelligent retail is better pursued; 3) according to the invention, the online address information of the user is positioned by acquiring the address information data generated by the online behavior of the user, so that the online user and the offline store generate actual contact on the geographic position through the address, and the purpose of accurately attributing the online user to the marketable area range of the offline store is achieved through the correlation of the position information data, thereby realizing the grid management of the sales area.
The present invention is described in further detail below with reference to the attached drawing figures.
Drawings
Fig. 1 is an overall flowchart of a data analysis method based on a regional membership marketing scenario according to the present invention.
Fig. 2 is a flowchart of a method for matching address information generated by a user triggering an online behavior according to the present invention.
FIG. 3 is a block diagram of a data parsing system based on a localized membership marketing scenario according to the present invention.
Fig. 4 is a schematic diagram of an embodiment of the present invention.
Detailed Description
With reference to fig. 1, the data parsing method based on the regional membership marketing scenario of the present invention includes the following steps:
according to the distribution condition of physical stores of a merchant, carrying out gridding division on a target area, wherein each physical store corresponds to one grid, and two adjacent grids are not overlapped;
building a store information database;
constructing a user information database;
and matching address information generated by the user triggering online behaviors to acquire the entity store information corresponding to the area where the user is located, and attributing the user to the effective marketing area of the entity store through the online behaviors of the user.
The gridding and dividing the target area specifically comprises:
the method comprises the steps that a radiation area is established by taking the geographic position of an entity store as a center, the radiation area is a closed polygon, the radiation areas of two adjacent entity stores are not repeated, the closed polygon areas established by all the entity stores in a target area jointly form a net, and gridding division of the target area is achieved. The radiation area corresponding to the store can be divided according to the geographic position of the store, the conditions of surrounding cells and the like, the radiation area is actually a closed polygon, a plurality of polygons are spliced to form a net, the radiation area is called as a grid, the grid division avoids superposition, the grids cannot be overlapped, and one grid can only correspond to one store. When the radiation area is constructed, the consumption situation and the population distribution situation of the local area can be combined for division, so long as the grids formed by all the physical stores can cover the whole target area. In a store with high sales ability, the radiation area can be expanded appropriately, and in a store with low sales ability or a new store, the radiation area can be reduced appropriately. The target area is the area where the merchant is ready for sales coverage and may be a country, a province, a city, a county, or the like.
The store information database includes:
the geographical position information of the shop area of the merchant entity comprises longitude and latitude data corresponding to a central point of the geographical position of the shop and longitude and latitude information of a radiation area boundary, and is simultaneously recorded into an online map tool; the online map tool is an existing online map and the like, including a Gade map, a Baidu map, a Beidou map and the like.
The physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number; the arrangement method of store numbers can be determined by a merchant, as long as one entity store corresponds to one number.
And grid coding information comprising grid numbers, wherein each grid is provided with a unique grid number.
The geographical position information of the merchant physical store region, the physical store code information and the grid code information are in one-to-one correspondence, and one of the information can be matched with the other two information.
The user information database includes:
the user address information comprises longitude and latitude information corresponding to the address information;
the physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number;
grid coding information comprising grid numbers, wherein each grid has a unique grid number;
the user address information, the entity store code information and the grid code information are in one-to-one correspondence, and one of the information can be matched with the other two information. The user information database is used for accelerating the matching speed and shortening the matching time.
The user information database is divided into two types, one type is a historical database which comprises address information, entity store code information and grid code information generated by historical user behaviors; the historical user behavior refers to address information input by previous users when purchasing or browsing commodities, and the format is general province | city | district | street | district | number of house. One user can correspond to a plurality of address information.
The second type is an incremental database which comprises address information, entity store code information and grid code information generated by incremental user behaviors; the address information generated by the new user is included, and the new address information data added by the existing user is also included.
The geographical position information of the merchant physical store area, the physical store code information and the grid code information in the store information database are in one-to-one correspondence. Each merchant physical store regional geographical position information only corresponds to one physical store coded information and only corresponds to one grid coded information.
The specific matching of the address information generated by the user triggering the online behavior is as follows:
performing first matching on the generated address information in a user information database, if consistent address information exists, successfully matching for the first time, and simultaneously acquiring entity store code information and grid code information from the user information database;
otherwise, the first matching is failed, and then the longitude and latitude information corresponding to the address is obtained by calling an online map tool;
and carrying out second matching on the longitude and latitude information in a store information database:
if the longitude and latitude is in the radiation area of the physical store, the second matching is successful, and meanwhile, the physical store coding information and the grid coding information are obtained from the store information database; inserting the related information into an increment database of the user information database as increment data;
otherwise, the second matching fails, and prompt information is sent out.
In the matching process, first matching is carried out in a user information database, when the first matching fails, an online map tool is called to obtain longitude and latitude information corresponding to the address, and the longitude and latitude information is utilized to carry out second matching in a store information database. Therefore, the matching time can be greatly shortened, and the relevant information of the entity store corresponding to the address information generated by the online behavior triggered by the user can be quickly acquired.
With reference to fig. 2, the longitude and latitude information is subjected to second matching in the store information database, specifically:
if the longitude and latitude are in the radiation area of the physical store (the longitude and latitude are in the longitude and latitude range of the boundary of the radiation area, namely the address is in the radiation range of the physical store), matching is successful, and meanwhile, the physical store code information and the grid code information are obtained from the store information database; because the geographical position information of the merchant physical store area, the physical store code information and the grid code information in the store information database are in one-to-one correspondence relationship, the only physical store code information and the grid code information can be obtained through the longitude and latitude information, and the related information is inserted into the incremental database of the user information database as incremental data, so that the data in the database is expanded, and the next quick matching is facilitated. And if the longitude and latitude are not in the radiation area of the physical store, the second matching fails, and prompt information is sent.
And after the first and/or second matching fails, a target area judgment step is also included, and whether the address information generated by the user triggering on-line behavior is in the target area is judged. The target area is judged after the first matching failure or
And performing the second matching failure, or performing the first matching failure and the second matching failure. In practice, when the newly added address information exceeds the radiation area of the physical store, for example, the target area of the business service is within the geographic range of province a, but the newly added address is province C and exceeds the radiation range of all the physical stores of the business, at this time, prompt information needs to be sent for background processing.
Preferably, after the second matching fails, the target area is judged, whether the address information generated by the online platform member is in the target area or not is judged, if not, the corresponding information record is empty, and prompt information is sent; and if the target area is in the target area, executing the matching step again, and performing a new round of matching.
According to the online marketing management method, online address information of the user is positioned through online behaviors (such as access, purchase and the like) of the user, the text type address is converted into the numerical latitude and longitude, the effective marketing range of the store in the business sense is converted into the latitude and longitude array value of the corresponding grid of the store in the digital sense, and the online member and the offline entity store are accurately associated through the address, so that more accurate grid management can be carried out on the entity store, and subsequent marketing activities are facilitated.
With reference to fig. 3, a data parsing system based on a regional membership marketing scenario includes:
the target area gridding division module is used for gridding and dividing a target area according to the distribution condition of physical stores of merchants, each physical store corresponds to one grid, and two adjacent grids are not overlapped; the gridding and dividing the target area specifically comprises the following steps:
the method comprises the steps that a radiation area is established by taking the geographic position of an entity store as a center, the radiation area is a closed polygon, the radiation areas of two adjacent entity stores are not repeated, the closed polygon areas established by all the entity stores in a target area jointly form a net, and gridding division of the target area is achieved.
A store information database comprising:
the geographical position information of the shop area of the merchant entity comprises longitude and latitude data corresponding to a central point of the geographical position of the shop and longitude and latitude information of a radiation area boundary, and is simultaneously recorded into an online map tool;
the physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number;
and grid coding information comprising grid numbers, wherein each grid is provided with a unique grid number.
A user information database comprising:
the user address information comprises longitude and latitude information corresponding to the address information;
the physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number;
grid coding information comprising grid numbers, wherein each grid has a unique grid number;
the above information corresponds to each other.
The user information database is divided into two types, wherein the first type is a historical database and comprises address information generated by historical user behaviors, corresponding physical store regional geographical position information, physical store coding information and grid coding information;
the second type is an incremental database which comprises incremental address information generated by user behaviors, corresponding physical store regional geographical position information, physical store coding information and grid coding information.
And the information matching module is used for matching address information generated by the user triggering online behavior, acquiring the information of the physical store corresponding to the area where the user is located, and attributing the user to the effective marketing area of the offline store through the online behavior of the user.
The specific matching of the address information generated by the user triggering the online behavior is as follows:
performing first matching on the generated address information in a user information database, if consistent address information exists, successfully matching for the first time, and simultaneously acquiring entity store code information and grid code information from the user information database;
otherwise, the first matching is failed, and then the longitude and latitude information corresponding to the address is obtained by calling an online map tool;
and carrying out second matching on the longitude and latitude information in a store information database:
if the longitude and latitude is in the radiation area of the physical store, the second matching is successful, and meanwhile, the physical store coding information and the grid coding information are obtained from the store information database; inserting the related information into an increment database of the user information database as increment data;
otherwise, the second matching fails, and prompt information is sent out.
The system also comprises a target area judging module, a target area judging module and a prompt module, wherein the target area judging module is used for judging whether the address information generated by the online platform member is in the target area, and if not, the prompt module sends prompt information; and if the target area is in the target area, calling an information matching module to perform a new round of matching.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
according to the distribution condition of physical stores of a merchant, carrying out gridding division on a target area, wherein each physical store corresponds to one grid, and two adjacent grids are not overlapped;
building a store information database;
constructing a user information database;
and matching address information generated by the user triggering online behaviors to acquire the entity store information corresponding to the area where the user is located, and attributing the user to the effective marketing area of the entity store through the online behaviors of the user.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
according to the distribution condition of physical stores of a merchant, carrying out gridding division on a target area, wherein each physical store corresponds to one grid, and two adjacent grids are not overlapped;
building a store information database;
constructing a user information database;
and matching address information generated by the user triggering online behaviors to acquire the entity store information corresponding to the area where the user is located, and attributing the user to the effective marketing area of the entity store through the online behaviors of the user.
The invention establishes accurate relation between the online user and the offline physical store in number, and achieves the purpose of online and offline member fusion, thereby performing online and offline integrated marketing on the members, further realizing O2O fusion, and better stepping to intelligent retail.
The present invention is described in further detail below with reference to specific steps.
A data analysis method based on a regional membership marketing scene comprises the following steps:
step 1, store data preparation, namely recording the codes of all physical stores of a merchant and longitude and latitude data corresponding to the geographic position central points of all the physical stores into a store information database, and inputting an online map tool;
and 2, dividing a target area into grids, namely dividing a radiation area corresponding to the physical store according to the geographic position of the physical store, the condition of a peripheral cell and the like, wherein the radiation area is actually a closed polygon, and a plurality of polygons are spliced to be just like a grid, so that the radiation area is called as a grid, the grids are divided to avoid superposition, the grids cannot be overlapped, and one grid only corresponds to one store.
When grid division is carried out, a corresponding store is selected or input, the geographic position of the store is positioned by the online map tool according to the latitude and longitude of the store, a polygon is drawn around the store according to a sales coverage area, and then a drawing result is submitted. The system positions the longitude and latitude values of each end point of the polygon, and records the corresponding store code, longitude and latitude value data and grid code (which can be automatically generated by the system according to a certain code specification) into a store information database.
And 3, preparing address data, namely storing the longitude and latitude values corresponding to the existing addresses into a user information database in advance in order to avoid the situation that the same address is obtained by calling an online map tool for multiple times and avoid the situations of return delay, blockage and the like of an external platform possibly occurring in the real-time calling process.
① preparing stock data, acquiring address information of platform member, wherein the format is general province | city | district | street | district | house | number, calling on-line map tool, acquiring longitude and latitude corresponding to each address, storing the corresponding relation between the address and the longitude and latitude into a history database for later stage matching with address data generated by user behavior.
② preparing incremental data, if a new address is generated by user behavior, acquiring the maintained address data in real time, calling an online map tool in real time to acquire the longitude and latitude corresponding to the address, and inserting the longitude and latitude as the incremental data into an incremental database.
And 4, matching the longitude and latitude of the user behavior address, and matching the address stored in the user information database according to the user behavior address after the user triggers the online behavior to generate address information (for example, the address where the user is located is positioned after the user access behavior is authorized, the goods receiving address of the user is obtained after the user purchase behavior is generated, and the like) to obtain the longitude and latitude value corresponding to the user behavior address, the entity store code information and the grid code information. If the relevant information is not matched, step 5 is executed.
And 5, after the longitude and latitude values corresponding to the user behavior addresses are obtained, carrying out second matching on the longitude and latitude values in the store information database according to related tool components (such as an IsPtInPoly static method of JAVA) to obtain grid codes corresponding to corresponding arrays.
Since one grid code corresponds to one store code, the grid code can be mapped to the corresponding store code. Therefore, the user is affiliated to the effective marketing area of the offline store through the online behavior of the user, and the purposes of fusion of online and offline members and fine grid management are really achieved.
The present invention will be described in further detail with reference to examples.
Examples
In this embodiment, a purchasing behavior generated by a user is taken as an example, and with reference to fig. 4, the method specifically includes the following steps:
s1, establishing a corresponding relation table, recording the mapping relation between the store codes and the longitude and latitude, wherein the store code corresponding to the first store is A001, the longitude and latitude corresponding to the center position of the store is (32.1,118.4), the store code corresponding to the second store is A002, and the longitude and latitude corresponding to the center position of the store is (32.5,118.7), and the table is marked as table 1.
TABLE 1
| Shop code | Latitude of store | Longitude of store |
| A001 | 32.1 | 118.4 |
| A002 | 32.5 | 118.7 |
And S3, drawing grids around the store according to the actual sales area of the store by an online map tool, forming a longitude and latitude array by the longitude and latitude of each end point of the grids, and storing the corresponding relation as a table 2.
TABLE 2
| Shop code | Grid latitude | Grid longitude | Grid numbering |
| A001 | 31.8 | 116.4 | W001 |
| A001 | 32.6 | 116.1 | W001 |
| A001 | 32.5 | 120.7 | W001 |
| A001 | 31.3 | 119.4 | W001 |
And S4, if the address A exists in the information table of the common distribution address of a certain user, the corresponding longitude and latitude are (32.2,118.6), and the address A falls within the grid range of the A-store, recording the mapping relation between the address A and the A001-store into a data table, and recording the mapping relation as table 3.
TABLE 3
| Address | Address latitude | Address longitude | Address mapping grid | Address-corresponding store |
| A | 32.2 | 118.6 | W001 | A001 |
And S5, two orders of a certain user are generated, wherein one order is an order of the address A, the other order is an order of the address B, and the address B is not in the table 3. And matching the two order addresses with the table 3, matching the order of the address A with the A001 store, and analyzing that the order of the address B cannot be matched, transmitting the address B to an online map tool, acquiring the longitude and latitude corresponding to the address B, and analyzing that the longitude and latitude fall within the grid range of the store B, inserting the mapping relation between the address B and the store A002 into the table 3, and printing an A002 store code on the order of the address B, so that the detailed data table processing is completed.
In the later stage, the number of online buyers and offline buyers corresponding to the A001 store can be obtained according to the clustering or summarizing of each order, and the related attributes and preferences of the buyers can be checked.
The invention locates the offline address information of the user through the online behavior (such as access, purchase and the like) of the user, and converts the text type address into the longitude and latitude of the numerical type. The effective marketing range of the store in the business sense is converted into the longitude and latitude array value of the corresponding grid of the store in the digital sense, so that the purposes of fine grid management and online and offline member integration marketing are achieved by analyzing accurate geographic information data.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present invention should be subject to the appended claims.
Claims (10)
1. A data analysis method based on a regional membership marketing scene is characterized by comprising the following steps:
according to the distribution condition of physical stores of a merchant, carrying out gridding division on a target area, wherein each physical store corresponds to one grid, and two adjacent grids are not overlapped;
building a store information database;
constructing a user information database;
and matching address information generated by the user triggering online behaviors to acquire the entity store information corresponding to the area where the user is located, and attributing the user to the effective marketing area of the entity store through the online behaviors of the user.
2. The method of claim 1, wherein the grid division of the target area specifically comprises:
the method comprises the steps that a radiation area is established by taking the geographic position of an entity store as a center, the radiation area is a closed polygon, the radiation areas of two adjacent entity stores are not repeated, the closed polygon areas established by all the entity stores in a target area jointly form a net, and gridding division of the target area is achieved.
3. The method for resolving data based on a regional membership marketing scenario of claim 1, wherein the store information database comprises:
the geographical position information of the shop area of the merchant entity comprises longitude and latitude data corresponding to a central point of the geographical position of the shop and longitude and latitude information of a radiation area boundary, and is simultaneously recorded into an online map tool;
the physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number;
grid coding information comprising grid numbers, wherein each grid has a unique grid number;
the above information corresponds to each other.
4. The method of claim 1, wherein the user information database comprises:
the user address information comprises longitude and latitude information corresponding to the address information;
the physical store code information comprises the numbers of physical stores, and each physical store has a unique physical store number;
grid coding information comprising grid numbers, wherein each grid has a unique grid number;
the above information corresponds to each other.
5. The method for analyzing data based on the regional membership marketing scenario as claimed in claim 4, wherein the user information database is divided into two categories, the first category is a historical database, which includes address information generated by historical user behaviors, corresponding entity store code information and grid code information;
the second type is an incremental database which comprises incremental address information generated by user behavior, corresponding entity store code information and grid code information.
6. The method of claim 5, wherein the matching of the address information generated by the user triggered online behavior is specifically as follows:
performing first matching on the generated address information in a user information database, if consistent address information exists, successfully matching for the first time, and simultaneously acquiring entity store code information and grid code information from the user information database;
otherwise, the first matching is failed, and then the longitude and latitude information corresponding to the address information is obtained by calling an online map tool;
and carrying out second matching on the longitude and latitude information in a store information database:
if the longitude and latitude is in the radiation area of the physical store, the second matching is successful, and meanwhile, the physical store coding information and the grid coding information are obtained from the store information database; inserting the related information into an increment database of the user information database as increment data;
otherwise, the second matching fails, and prompt information is sent out.
7. The method of claim 6, further comprising a target area determination step after the first and/or second matching fails, wherein the target area determination step determines whether the address information generated by the user triggered online behavior is in the target area.
8. A data analysis system based on regional membership marketing scenes is characterized by comprising:
the target area gridding division module is used for gridding and dividing a target area according to the distribution condition of physical stores of merchants, each physical store corresponds to one grid, and two adjacent grids are not overlapped;
a store information database;
a user information database;
and the information matching module is used for matching address information generated by the user triggering online behavior, acquiring the information of the physical store corresponding to the area where the user is located, and attributing the user to the effective marketing area of the physical store through the online behavior of the user.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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| CN201911066148.4A CN110930180B (en) | 2019-11-04 | 2019-11-04 | Data analysis method, system and computer equipment based on regional member marketing scene |
| CA3159785A CA3159785A1 (en) | 2019-11-04 | 2020-07-29 | Data parsing method based on regionalized membership marketing scene, system and computer equipment |
| PCT/CN2020/105640 WO2021088434A1 (en) | 2019-11-04 | 2020-07-29 | Data analysis method and system based on regionalized membership marketing scene, and computer device |
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| CN201911066148.4A CN110930180B (en) | 2019-11-04 | 2019-11-04 | Data analysis method, system and computer equipment based on regional member marketing scene |
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| WO2021088434A1 (en) * | 2019-11-04 | 2021-05-14 | 苏宁云计算有限公司 | Data analysis method and system based on regionalized membership marketing scene, and computer device |
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| CN113781132A (en) * | 2020-06-15 | 2021-12-10 | 北京沃东天骏信息技术有限公司 | Online shopping guide method and device |
| CN116188066A (en) * | 2023-03-10 | 2023-05-30 | 广州南方学院 | Intelligent distribution method and system for store clients based on geographic position |
| CN116757737A (en) * | 2023-08-10 | 2023-09-15 | 山景智能(北京)科技有限公司 | Marketing method and device based on address information |
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Also Published As
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| WO2021088434A1 (en) | 2021-05-14 |
| CA3159785A1 (en) | 2021-05-14 |
| CN110930180B (en) | 2023-07-28 |
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