CN111353817A - Guest group data generation method and system - Google Patents
Guest group data generation method and system Download PDFInfo
- Publication number
- CN111353817A CN111353817A CN202010118936.XA CN202010118936A CN111353817A CN 111353817 A CN111353817 A CN 111353817A CN 202010118936 A CN202010118936 A CN 202010118936A CN 111353817 A CN111353817 A CN 111353817A
- Authority
- CN
- China
- Prior art keywords
- group data
- commodity
- data
- custom
- user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
Landscapes
- Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Data Mining & Analysis (AREA)
- Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method and a system for generating guest group data, wherein the method for generating the guest group data comprises the following steps: acquiring marketing activity information; obtaining forecast customer group data according to the marketing activity information; acquiring custom guest group data; and combining the predicted customer group data and the custom customer group data to obtain potential customer group data. Compared with the prior art, the embodiment of the invention predicts the users of all the small merchants through the pre-trained commodity user prediction model according to the marketing activity information created by the small merchants to obtain the customer groups of the activity for purchasing related products with high probability, and then obtains the potential customer groups by combining the customer groups which are defined by the small merchants according to the difference of shops and activities, so that the marketing conversion rate and the marketing effect are improved.
Description
Technical Field
The invention relates to the technical field of internet information, in particular to a method and a system for generating customer group data.
Background
At present, the marketing objects of the small and micro shops mainly comprise the following categories, namely, customers arriving at the shops, and salesmen carry out face-to-face marketing; secondly, the customers who have the order records in the shop can make calls or send information to the customers according to the recorded customer information; thirdly, random crowd, shop staff publicize in places with large flow of people. The marketing scope is small, no pertinence exists, and no data support exists, so the marketing conversion rate is low, and the effect is poor. And moreover, marketing is completely carried out manually, and the labor cost is high.
Disclosure of Invention
The embodiment of the invention provides a method and a system for generating customer group data, which are used for providing the customer group data for small and micro merchants for marketing.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
in a first aspect, an embodiment of the present invention provides a method for generating guest group data, including:
acquiring marketing activity information;
obtaining forecast customer group data according to the marketing activity information;
acquiring custom guest group data;
and combining the predicted customer group data and the custom customer group data to obtain potential customer group data.
With reference to the first aspect, in a first possible implementation manner of the first aspect, the method further includes:
collecting user data, commodity data and user behavior data, and respectively establishing a user portrait, a commodity portrait and a behavior portrait;
and obtaining a commodity-user prediction model according to the user portrait, the commodity portrait and the behavior portrait.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the marketing campaign information includes a category of a commodity;
the obtaining of the forecast customer group data according to the marketing campaign information specifically includes:
and predicting to obtain the predicted customer group data of the commodity category by using the commodity-user prediction model according to the commodity category, and storing the predicted customer group data in an FTP server.
With reference to the first aspect, in a third possible implementation manner of the first aspect, the acquiring custom guest group data specifically includes:
and receiving custom guest group data imported by an import tool, and storing the custom guest group data in an ES database.
With reference to the first aspect, in a fourth possible implementation manner of the first aspect, the obtaining potential guest group data by combining the predicted guest group data and the custom guest group data specifically includes:
importing the prediction guest group data into a PG database to generate a first temporary table;
importing the custom guest group data into a PG database to generate a second temporary table;
and carrying out relational operation on the first temporary table and the second temporary table to obtain potential passenger group data.
In a second aspect, an embodiment of the present invention provides a guest group data generation system, including:
the acquisition module is used for acquiring marketing activity information;
the prediction module is used for acquiring prediction customer group data according to the marketing activity information;
the custom module is used for acquiring custom guest group data;
and the combination module is used for combining the predicted customer group data and the user-defined customer group data to obtain potential customer group data.
With reference to the second aspect, in a first possible implementation manner of the second aspect, the system further includes:
the modeling module is used for acquiring user data, commodity data and user behavior data and respectively establishing a user portrait, a commodity portrait and a behavior portrait; and obtaining a commodity-user prediction model according to the user portrait, the commodity portrait and the behavior portrait.
With reference to the first possible implementation manner of the second aspect, in a second possible implementation manner of the second aspect, the marketing campaign information includes a category of goods;
the prediction module is further to: and predicting to obtain the predicted customer group data of the commodity category by using the commodity-user prediction model according to the commodity category, and storing the predicted customer group data in an FTP server.
With reference to the second aspect, in a third possible implementation manner of the second aspect, the customization module is further configured to:
and receiving custom guest group data imported by an import tool, and storing the custom guest group data in an ES database.
With reference to the second aspect, in a fourth possible implementation manner of the second aspect, the combining module includes:
a first importing unit, configured to import the predicted guest group data into a PG database, and generate a first temporary table;
the second import unit is used for importing the custom guest group data into a PG database to generate a second temporary table;
and the operation unit is used for carrying out relational operation on the first temporary table and the second temporary table to obtain potential passenger group data.
The embodiment of the invention provides a method and a system for generating customer group data, which are used for providing the customer group data for small and micro merchants for marketing. The method for generating the customer group data comprises the steps of firstly obtaining marketing activity information; acquiring forecast customer group data according to the marketing activity information; then obtaining custom guest group data; and finally, combining the predicted customer group data and the user-defined customer group data to obtain potential customer group data. Compared with the prior art, the embodiment of the invention predicts the users of all the small merchants through the pre-trained commodity user prediction model according to the marketing activity information created by the small merchants to obtain the customer groups of the activity for purchasing related products with high probability, and then obtains the potential customer groups by combining the customer groups which are defined by the small merchants according to the difference of shops and activities, so that the marketing conversion rate and the marketing effect are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of an implementation environment in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of the server shown in FIG. 1;
fig. 3 is a flowchart of a method for generating guest group data according to an embodiment of the present invention;
fig. 4 is a block diagram of a guest group data generation system according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, those skilled in the art can obtain the embodiments without any inventive step in advance, and the embodiments are within the protection scope of the present invention.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Referring to fig. 1, a schematic diagram of an implementation environment according to an embodiment of the present invention is shown. The implementation environment comprises an intelligent terminal and a server. And a small business client is operated in the intelligent terminal. The intelligent terminal can be a mobile phone, a tablet computer, a laptop portable computer, a desktop computer and the like. The intelligent terminal and the server can be connected through a wireless network or a wired network. The server can be a server, a server cluster consisting of a plurality of servers, or a cloud computing service center.
As shown in fig. 2, the server includes an input unit, a processor unit, an output unit, a communication unit, a storage unit, a peripheral unit, and the like. These components communicate over one or more buses. Specifically, the method comprises the following steps:
the input unit is used for realizing the interaction between a user and the server and/or inputting information into the server. For example, the input unit may receive numeric or character information input by a user to generate a signal input related to user setting or function control. In the embodiment of the present invention, the input unit may be a touch panel, or may be other human-computer interaction interfaces, such as a physical input key, a mouse, or a joystick.
The processor unit is a control center of the server, connects various parts of the entire server using various interfaces and lines, and executes various functions of the server and/or processes data by operating or executing software programs and/or modules stored in the storage unit and calling data stored in the storage unit. The processor unit may be composed of an Integrated Circuit (IC), for example, a single packaged IC, or a plurality of packaged ICs connected with the same or different functions. For example, the processor Unit may include only a Central Processing Unit (CPU), or may be a combination of a GPU, a Digital Signal Processor (DSP), and a control chip (e.g., a baseband chip) in the communication Unit. In the embodiment of the present invention, the CPU may be a single operation core, or may include multiple operation cores.
The communication unit is used for establishing a communication channel, enabling the server to be connected to the remote equipment through the communication channel, and performing data interaction with the remote equipment, such as an intelligent terminal used by a small business user.
The output unit includes, but is not limited to, an image output unit and a sound output unit. The image output unit is used for outputting characters, pictures and/or videos. The image output unit may include a display panel, such as a display panel configured in the form of an LCD (Liquid crystal display), an OLED (Organic Light-Emitting Diode), a Field Emission Display (FED), and the like.
The storage unit may be used to store software programs and modules, and the processing unit executes various functional applications of the server and implements data processing by running the software programs and modules stored in the storage unit. The storage unit mainly comprises a program storage area and a data storage area, wherein the program storage area can store an operating system and an application program required by at least one function. In an embodiment of the invention, the Memory unit may include a volatile Memory, such as a Nonvolatile dynamic Random Access Memory (NVRAM), a phase change Random Access Memory (PRAM), a Magnetoresistive Random Access Memory (MRAM), and a non-volatile Memory, such as at least one magnetic disk Memory device, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a flash Memory device, such as a flash Memory (NOR) or a flash Memory (NAND flash Memory). The nonvolatile memory stores an operating system and an application program executed by the processing unit. The processing unit loads the operating program and data from the non-volatile memory into the memory and stores the digital content in the mass storage device.
The power supply is used to power the various components of the server to maintain their operation, including an external power supply that directly powers the server, such as an AC adapter or the like. In some embodiments of the invention, the power supply may be more broadly defined and may include, for example, a power management system, a charging system, a power failure detection circuit, a power converter or inverter, a power status indicator (e.g., a light emitting diode), and any other components associated with power generation, management, and distribution of the server.
The method for generating guest group data provided by the embodiment of the present invention is applied to a server in the implementation environment shown in fig. 1, and the method may include the following steps, as shown in fig. 3:
step S10, obtaining marketing activity information;
step S20, obtaining forecast customer group data according to the marketing activity information;
step S30, obtaining custom guest group data;
and step S40, combining the predicted passenger group data and the custom passenger group data to obtain potential passenger group data.
According to the marketing activity information created by the commercial tenants sent by the small micro-business client, the embodiment of the invention selects the customer group matched with the marketing activity in the customer group information system integrating all small micro-business, namely the customer group purchasing the commodities related to the marketing activity with a high probability to become the forecast customer group, and combines the forecast customer group and the custom customer group selected by each commercial tenant to obtain the potential customer group of the marketing activity, and provides the potential customer group for the small micro-business to carry out marketing.
According to an embodiment of the present invention, before step S10, the method further includes:
collecting user data, commodity data and user historical behavior data of all small and micro merchants; establishing a user portrait according to the user data; establishing a commodity image according to the commodity data; establishing a behavior portrait according to historical behavior data of a user; and constructing a commodity user prediction model according to the user portrait, the commodity portrait and the behavior portrait.
Wherein, user portrayal is established, including gender, age, membership grade, interest preference, purchasing power, address and the like; establishing commodity data including the types and values, whether the commodity is a popular commodity, whether the commodity is a high-frequency consumable and the like; and establishing a behavior portrait, including browsing, searching, collecting, paying attention, sharing, ordering, paying and the like. According to the user portrait, the commodity portrait and the behavior portrait, a commodity user prediction model is constructed, and the method specifically comprises the following steps: selecting characteristics and corresponding characteristic data from the user portrait, the commodity portrait and the behavior portrait, and training the characteristic data by using a machine learning algorithm to obtain a commodity-user prediction model, wherein each commodity category corresponds to one commodity-user prediction model. Wherein the machine learning algorithm may be a Random Forest (RF) algorithm, a Principal Component Analysis (PCA) algorithm, a domain decomposition machine (FFM) algorithm, a Logistic Regression (LR) algorithm, etc.
According to the embodiment of the invention, the user data, the commodity data and the historical user behavior data of all the small and micro merchants are summarized, the machine learning algorithm is adopted for training to obtain the commodity-user prediction model, the commodity-user prediction model can be used for obtaining the high-probability potential customers for purchasing a certain commodity, and compared with the method for searching the potential customers by manually counting and analyzing the data, the prediction accuracy is higher, so that the marketing conversion rate is higher, the effect is better, the time consumption for obtaining the predicted customer group is short, the efficiency is high, and the cost is low.
In step S10, the pico-shop establishes a marketing campaign through the pico-shop client, the pico-shop client sends the marketing campaign information to the server, and the server obtains the marketing campaign information.
According to one embodiment of the invention, the marketing campaign information includes a category of goods for the marketing campaign. In step S20, predicted customer group data of the product category is predicted from the product category using a product-user prediction model, and the predicted customer group data is stored in an FTP server.
In the embodiment of the invention, when the micro merchant creates the marketing campaign, the associated commodity of the campaign is selected, for example, a promotion campaign is created, and the information of the promotion campaign comprises the commodity category of the commodity participating in the campaign. According to the commodity category, a commodity-user prediction model corresponding to the commodity category is selected, all users of the small and micro merchants are predicted to obtain a prediction customer group of the commodity category, the prediction accuracy is high, marketing is provided for the small and micro merchants, the marketing conversion rate is high, the marketing effect is good, and the time consumption for obtaining the prediction customer group is short, the efficiency is high, and the cost is low. And generating an FTP file by the obtained predicted guest group data, and storing the FTP file in an FTP server so as to be called by other systems. And the predicted customer group data corresponding to each commodity category can be obtained by automatically predicting at regular time (for example, every day) through a commodity-user model, the FTP files corresponding to each category are generated and stored in the FTP server, and when the small merchant creates a marketing campaign, the latest FTP file corresponding to the commodity category of the marketing campaign is directly read, so that the predicted customer group data is obtained, the response time from the creation of the marketing campaign to the acquisition of the potential customer group data is greatly shortened, and the physical examination of the small merchant is improved.
According to an embodiment of the present invention, step S30 specifically includes: and receiving custom guest group data imported by an import tool, and storing the custom guest group data in an ES database.
In the embodiment of the invention, the small micro-merchants can autonomously select some customer groups as custom customer groups for marketing according to the differences of their stores or marketing activities, the custom customer group data can be imported into the server through the import tool, and the server stores the custom customer group data in the ES database after receiving the custom customer group data.
According to an embodiment of the present invention, step S40 specifically includes: importing the prediction guest group data into a PG database to generate a first temporary table; importing the custom guest group data into a PG database to generate a second temporary table; and carrying out relational operation on the first temporary table and the second temporary table to obtain potential passenger group data.
According to the embodiment of the invention, the predicted customer group data and the customized customer group data are both imported into the PG database, and the relation operation is carried out in the PG database to obtain the potential customer group data, the combination of the two parts of customer group data is not in the FTP server or the ES database, so that the safety and stability of the predicted customer group data in the FTP server and the customized customer group data in the ES database can be ensured, and the predicted customer group data or the customized customer group data can be conveniently and independently extracted by other platforms.
The customer group data generation method provided by the embodiment of the invention provides customer group data for small and micro merchants to carry out marketing. Firstly, acquiring marketing activity information; acquiring forecast customer group data according to the marketing activity information; then obtaining custom guest group data; and finally, combining the predicted customer group data and the user-defined customer group data to obtain potential customer group data. Compared with the prior art, the embodiment of the invention predicts the users of all the small merchants through the pre-trained commodity user prediction model according to the marketing activity information created by the small merchants to obtain the customer groups of the activity for purchasing related products with high probability, and then obtains the potential customer groups by combining the customer groups which are defined by the small merchants according to the difference of shops and activities, so that the marketing conversion rate and the marketing effect are improved.
An embodiment of the present invention further provides a system for generating guest group data, as shown in fig. 4, including:
the acquisition module is used for acquiring marketing activity information;
the prediction module is used for acquiring prediction customer group data according to the marketing activity information;
the custom module is used for acquiring custom guest group data;
and the combination module is used for combining the predicted customer group data and the user-defined customer group data to obtain potential customer group data.
According to one embodiment of the invention, the system further comprises:
the modeling module is used for acquiring user data, commodity data and user behavior data and respectively establishing a user portrait, a commodity portrait and a behavior portrait; and obtaining a commodity-user prediction model according to the user portrait, the commodity portrait and the behavior portrait.
According to one embodiment of the invention, the marketing campaign information comprises categories of goods;
the prediction module is further to: and predicting to obtain the predicted customer group data of the commodity category by using the commodity-user prediction model according to the commodity category, and storing the predicted customer group data in an FTP server.
According to an embodiment of the invention, the customization module is further configured to:
and receiving custom guest group data imported by an import tool, and storing the custom guest group data in an ES database.
According to one embodiment of the invention, the bonding module comprises:
a first importing unit, configured to import the predicted guest group data into a PG database, and generate a first temporary table;
the second import unit is used for importing the custom guest group data into a PG database to generate a second temporary table;
and the operation unit is used for carrying out relational operation on the first temporary table and the second temporary table to obtain potential passenger group data.
The customer group data generation system provided by the embodiment of the invention provides customer group data for the small and micro merchants to carry out marketing. The acquisition module acquires marketing activity information; the prediction module acquires prediction customer group data according to the marketing activity information; the user-defined module acquires user-defined guest group data; and the combination module combines the predicted customer group data and the user-defined customer group data to obtain potential customer group data. Compared with the prior art, the embodiment of the invention predicts the users of all the small merchants through the pre-trained commodity user prediction model according to the marketing activity information created by the small merchants to obtain the customer groups of the activity for purchasing related products with high probability, and then obtains the potential customer groups by combining the customer groups which are defined by the small merchants according to the difference of shops and activities, so that the marketing conversion rate and the marketing effect are improved.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
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 a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for generating guest group data, comprising:
acquiring marketing activity information;
obtaining forecast customer group data according to the marketing activity information;
acquiring custom guest group data;
and combining the predicted customer group data and the custom customer group data to obtain potential customer group data.
2. The method of claim 1, further comprising:
collecting user data, commodity data and user behavior data, and respectively establishing a user portrait, a commodity portrait and a behavior portrait;
and obtaining a commodity-user prediction model according to the user portrait, the commodity portrait and the behavior portrait.
3. The method of claim 2, wherein the marketing campaign information comprises categories of items;
the obtaining of the forecast customer group data according to the marketing campaign information specifically includes:
and predicting to obtain the predicted customer group data of the commodity category by using the commodity-user prediction model according to the commodity category, and storing the predicted customer group data in an FTP server.
4. The method according to claim 1, wherein the obtaining custom guest group data specifically includes:
and receiving custom guest group data imported by an import tool, and storing the custom guest group data in an ES database.
5. The method of claim 1, wherein the combining the predicted customer base data and the custom customer base data to obtain potential customer base data comprises:
importing the prediction guest group data into a PG database to generate a first temporary table;
importing the custom guest group data into a PG database to generate a second temporary table;
and carrying out relational operation on the first temporary table and the second temporary table to obtain potential passenger group data.
6. A guest group data generating system, comprising:
the acquisition module is used for acquiring marketing activity information;
the prediction module is used for acquiring prediction customer group data according to the marketing activity information;
the custom module is used for acquiring custom guest group data;
and the combination module is used for combining the predicted customer group data and the user-defined customer group data to obtain potential customer group data.
7. The system of claim 6, further comprising:
the modeling module is used for acquiring user data, commodity data and user behavior data and respectively establishing a user portrait, a commodity portrait and a behavior portrait; and obtaining a commodity-user prediction model according to the user portrait, the commodity portrait and the behavior portrait.
8. The system of claim 7, wherein the marketing campaign information comprises categories of items;
the prediction module is further to: and predicting to obtain the predicted customer group data of the commodity category by using the commodity-user prediction model according to the commodity category, and storing the predicted customer group data in an FTP server.
9. The system of claim 6, wherein the customization module is further configured to:
and receiving custom guest group data imported by an import tool, and storing the custom guest group data in an ES database.
10. The system of claim 6, wherein the combining module comprises:
a first importing unit, configured to import the predicted guest group data into a PG database, and generate a first temporary table;
the second import unit is used for importing the custom guest group data into a PG database to generate a second temporary table;
and the operation unit is used for carrying out relational operation on the first temporary table and the second temporary table to obtain potential passenger group data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010118936.XA CN111353817A (en) | 2020-02-26 | 2020-02-26 | Guest group data generation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010118936.XA CN111353817A (en) | 2020-02-26 | 2020-02-26 | Guest group data generation method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111353817A true CN111353817A (en) | 2020-06-30 |
Family
ID=71197291
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010118936.XA Pending CN111353817A (en) | 2020-02-26 | 2020-02-26 | Guest group data generation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111353817A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114143566A (en) * | 2021-11-01 | 2022-03-04 | 北京达佳互联信息技术有限公司 | Information pushing method, device, equipment and storage medium |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110827071A (en) * | 2019-10-30 | 2020-02-21 | 苏宁云计算有限公司 | Store activity pushing method and device and computer storage medium |
-
2020
- 2020-02-26 CN CN202010118936.XA patent/CN111353817A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110827071A (en) * | 2019-10-30 | 2020-02-21 | 苏宁云计算有限公司 | Store activity pushing method and device and computer storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114143566A (en) * | 2021-11-01 | 2022-03-04 | 北京达佳互联信息技术有限公司 | Information pushing method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lee | A GA-based optimisation model for big data analytics supporting anticipatory shipping in Retail 4.0 | |
| Mahajan et al. | Innovation diffusion in a dynamic potential adopter population | |
| US9536002B2 (en) | Digital consumer data model and customer analytic record | |
| Ng et al. | Integrated knowledge management strategy: a preliminary literature review | |
| US10650437B2 (en) | User interface generation for transacting goods | |
| CN106952072A (en) | A kind of method and system of data processing | |
| Da Cunha et al. | Selection of modules for mass customisation | |
| CN110750697B (en) | Merchant classification method, device, equipment and storage medium | |
| CN111222952B (en) | Marketing guest group recommendation method and device | |
| CN110363485A (en) | Intelligent social activity creation method and device | |
| US20190066137A1 (en) | Systems and methods for modeling impact of commercial development on a geographic area | |
| CN115564531A (en) | Commodity combination recommendation method and device, equipment, medium and product thereof | |
| CN107977876B (en) | Method and device for processing order information | |
| CN111353817A (en) | Guest group data generation method and system | |
| CN114722789B (en) | Data report integrating method, device, electronic equipment and storage medium | |
| CN110796520A (en) | Commodity recommendation method and device, computing equipment and medium | |
| US20150206158A1 (en) | System and method for spend analysis of the service category | |
| CN111553749A (en) | Activity push strategy configuration method and device | |
| Fajri et al. | MSME business tranformation through mobile e-commerce applications | |
| KR20180114707A (en) | Apparatus for trading goods through performance notification, method thereof and computer recordable medium storing program to perform the method | |
| US20160110767A1 (en) | Coupon provider | |
| CN112330351B (en) | Method for selecting address, address selecting system and electronic equipment | |
| JP7027606B1 (en) | Information processing equipment, information processing methods and information processing programs | |
| CN111738789A (en) | Article information pushing method, device, equipment and storage medium | |
| JP7248838B1 (en) | Provision device, provision method and provision program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |