CN115222456A - Marketing method, platform, equipment and medium based on big data user consumption preference - Google Patents
Marketing method, platform, equipment and medium based on big data user consumption preferenceDownload PDFInfo
- Publication number
- CN115222456A CN115222456ACN202210894131.3ACN202210894131ACN115222456ACN 115222456 ACN115222456 ACN 115222456ACN 202210894131 ACN202210894131 ACN 202210894131ACN 115222456 ACN115222456 ACN 115222456A
- Authority
- CN
- China
- Prior art keywords
- advertisement
- information
- user
- consumption preference
- consumption
- 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 OR CALCULATING; 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
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
- G06Q30/0271—Personalized advertisement
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0261—Targeted advertisements based on user location
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/178—Human faces, e.g. facial parts, sketches or expressions estimating age from face image; using age information for improving recognition
Landscapes
- Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Economics (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (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)
- Information Transfer Between Computers (AREA)
Abstract
Description
Technical Field
The invention belongs to the technical field of advertisement marketing platforms, and particularly relates to a marketing method, a marketing platform, marketing equipment and a marketing medium based on big data user consumption preference.
Background
Advertisement, as the name implies, is an advertisement that informs the general public of the society of something. The meaning of advertisement is broadly and narrowly defined. The advertisement refers to an advertisement for profit, and generally refers to a commercial advertisement, or economic advertisement, which is a means for business enterprises to distribute goods or services to consumers or users through advertisement media in a pay manner for promoting goods or providing services. Commercial advertisements are such economic advertisements.
Prior art CN208580426U discloses an advertisement push system based on face recognition technology and big data analysis, the advertisement push system includes remote terminal and data acquisition terminal, the protection frame at data acquisition terminal passes through fastening nut to be fixed on the wall just the surface of protection frame is equipped with spacing recess, protection frame's inside is equipped with controller, circuit board, memory, battery and wireless module, it establishes to gather camera and speaker the surface of protection frame, it is connected to gather camera and timer the input of controller, the output of controller is connected to wireless module, display screen one and speaker, wireless module's output is connected to remote terminal, remote terminal includes analysis host computer and display screen two.
The prior art CN109427132A discloses an intelligent commodity vending machine, a vending system and a commercial vending method thereof, and the intelligent commodity vending machine, the merchant background and the intelligent commodity vending machine are connected with the cloud server and the merchant background through the Internet in a network manner, so that data transmission is realized, personalized and customized shopping experience is provided for users in each cell, and meanwhile, the cloud server and the merchant background are used for data storage, statistics, analysis, classification and management.
The prior art CN105447186B discloses a user behavior analysis system based on a big data platform, which comprises: the system comprises a user behavior information acquisition interface, a basic data layer module, a user behavior information analysis module, a user behavior information correlation determination module, a user behavior information organization module, a correlation data set representation module, a user characteristic analysis module, an aggregation module and an application module. The system establishes a related data group between user behavior information (including effective information contained in the relationship between user behaviors and/or contents serving as behavior objects) by utilizing the mutual relation between the user behaviors and behavior objects thereof, the data group describes effective information contained in the relationship between the user behaviors, the starting point and the end point of a series of mutually related user behaviors can be accurately positioned, the quantifiable accurate measurement of the user behavior information can be realized based on the related data group, and the comprehensive statistical analysis of the series of mutually related user behaviors is realized.
Along with the popularization of intelligent mobile terminals, the advertisement push method based on the mobile terminal is more and more valued by merchants. How to improve the information push efficiency directly affects whether merchants can make greater profit, so improving the push efficiency is a problem faced by the current systems. The pushing adaptation degree is improved, so that the accuracy of a big data algorithm is improved, the recommendation quality is improved, and the accuracy of the current advertisement pushing is generally low, so that the adaptation degree of the advertisement pushing is low, and the advertisement conversion efficiency is low.
Disclosure of Invention
The invention aims to provide a marketing method, a marketing platform, marketing equipment and a marketing medium based on big data user consumption preference, which are used for solving the problems of low adaptation degree of advertisement push and low advertisement conversion efficiency caused by low advertisement push accuracy at present.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides a marketing method based on big data user consumption preference, comprising the following steps:
s1, acquiring commodity browsing record information and consumption record information generated by a user through a user terminal and corresponding user information, and acquiring geographical position information of the user terminal;
s2, acquiring consumption preference information corresponding to the user information according to the commodity browsing record information and the consumption record information; binding consumption preference information with the geographical location information;
s3, according to the geographical position information, obtaining advertisement terminal information of a region corresponding to the geographical position information; at least one advertising terminal is arranged;
s4, acquiring all advertisement information in an advertisement library; according to the consumption preference information, matching recommended advertisements corresponding to the consumption preferences in all the advertisement categories to obtain a recommended advertisement table;
and S5, delivering the corresponding advertisement in the recommended advertisement table to the advertisement terminal corresponding to the advertisement terminal information.
According to the technology, the consumption preference of different user groups in the geographical position can be obtained by obtaining the geographical position information corresponding to the consumption preference information; therefore, the remote control advertisement terminals such as the elevator advertisement terminal and the community advertisement terminal which are arranged at present can put advertisements matched with the consumption preference of the user at the position according to the corresponding geographic position, so that the put advertisement content is more accurate, the advertisement conversion rate is improved, and the problems that the accuracy of the current advertisement push is low, the adaptation degree of the advertisement push is low, and the advertisement conversion efficiency is low are solved.
In one possible design, in step S1, the time of daily generation of the commodity browsing record is also obtained; when the consumption preference of the user is obtained according to the commodity browsing record and the consumption record in the step S2, the consumption preference of the user is counted according to different time periods in each day, and the consumption preference of the area corresponding to the geographic position in each day in different time periods is obtained by combining the geographic position; and then delivering advertisements corresponding to the consumption preferences of the corresponding time period to the advertisement terminal according to the time. By acquiring the daily time of the commodity browsing record, the liveness of the user in different time periods in the geographic position can be known, the consumption preference and the time period are correlated, advertisements corresponding to the consumption preference of the corresponding time period are released to the advertisement terminal according to the time, and the advertisement releasing accuracy is further improved.
In one possible design, a movement law of the user is obtained according to the geographical position distribution of the user terminal used by the user, and advertisements are delivered to the advertisement terminal of the geographical position according to the movement law of the user and the corresponding consumption preference. By analyzing the geographical location distribution of the user using the user terminal so as to obtain the movement law of the possibility of the user, for example, from home to company, the user can be roughly tracked, thereby realizing accurate advertisement delivery.
In one possible design, a play weight is set for each recommended advertisement in the recommended advertisement table according to each recommended advertisement. After each recommended advertisement is obtained, because the number of the advertisements is large, some consumption preferences with high advertisement heat degree are covered, and therefore the weight is specially set for each recommended advertisement, and the advertisements can be put according to the playing weight and the preferences.
In one possible design, the user information includes an age of the user, and accordingly, the obtained consumption preference has a corresponding age stage of the user; and adjusting the playing weight of each recommended advertisement based on the current user age identified by the face identification module arranged on the advertisement terminal. The advertisement delivery is carried out by combining the consumption preferences of different age groups in the region according to the current user age identified by the face identification module arranged on the basis of the advertisement terminal, and the advertisement delivery accuracy is further improved.
In a second aspect, the invention provides a marketing platform based on big data user consumption preference, which comprises a user information acquisition module, a user consumption information acquisition module, a position information acquisition module, a consumption preference calculation module, an information binding module, an advertisement information acquisition module, an advertisement terminal information acquisition module, a recommended advertisement list acquisition module and an advertisement delivery module; wherein, the
The user information acquisition module is used for acquiring user information;
the user consumption information acquisition module is used for acquiring commodity browsing record information and consumption record information generated by a user through a user terminal;
the position information acquisition module is used for acquiring the geographical position information of the user terminal;
the consumption preference calculation module is used for acquiring consumption preference information of the user according to the commodity browsing record and the consumption record;
the information binding module is used for binding the consumption preference with the geographical location information;
the advertisement terminal information acquisition module is used for acquiring advertisement terminal information of an area corresponding to the geographical position information according to the geographical position information;
the advertisement information acquisition module is used for acquiring all advertisement information in the advertisement library;
the recommended advertisement table acquisition module is used for matching recommended advertisements corresponding to the consumption preference in all the advertisement categories according to the consumption preference information to acquire a recommended advertisement table;
and the advertisement putting module is used for putting the corresponding advertisement in the recommended advertisement table to the advertisement terminal corresponding to the advertisement terminal information.
In one possible design, the system further comprises a user motion rule obtaining module, configured to obtain a motion rule of the user according to the geographical location distribution of the user using the user terminal; and the advertisement delivery module is also used for delivering advertisements to the advertisement terminals of the geographic positions according to the motion rules of the users and the corresponding consumption preferences.
In a possible design, the system further includes a weight setting module, configured to set a play weight for each recommended advertisement according to each recommended advertisement in the recommended advertisement table.
In a third aspect, the invention provides a marketing device based on big data user consumption preference, which comprises a memory and a processor, wherein the memory and the processor are connected with each other through a bus; the memory stores computer execution instructions; the processor executes the computer-executable instructions stored in the memory to cause the processor to perform a marketing method based on big data user consumption preferences as set forth in the first aspect and any one of the possible designs of the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium, having stored thereon instructions for executing the marketing method based on big data user consumption preference as described in the first aspect and any one of the possible designs of the first aspect when the instructions are run on a computer.
Has the advantages that:
1. the consumption preference information of different user groups in the geographical position can be acquired through the geographical position information corresponding to the acquired consumption preference information; from this, but to the remote control's such as elevator advertisement terminal, district advertisement terminal that set up at present advertisement terminal, can put in the advertisement that matches with this position user consumption preference according to its geographical position that corresponds for the advertisement content of putting is more accurate, improves the advertisement conversion rate, and the solution is current advertisement propelling movement's precision is low, causes the adaptation degree of advertisement propelling movement low, the problem of advertisement conversion inefficiency.
2. The geographical position distribution of the user terminal used by the user is analyzed so as to obtain the movement rule of the possibility of the user, for example, the user can be roughly tracked from home to company, so that the accurate advertisement delivery is realized;
3. the advertisement delivery is carried out by combining the consumption preferences of different age groups in the region according to the current user age identified by the face identification module arranged on the basis of the advertisement terminal, and the advertisement delivery accuracy is further improved.
Drawings
FIG. 1 is a flow chart of a marketing method based on big data user consumption preference according to the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly described below with reference to the accompanying drawings and the embodiments or the description of the prior art, it is obvious that the following description of the structure of the drawings is only some embodiments of the present invention, and it is also possible for those skilled in the art to obtain other drawings based on the drawings without creative efforts. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto.
The embodiment is as follows:
as shown in fig. 1, in a first aspect, the present embodiment provides a marketing method based on big data user consumption preferences, including the following steps:
s1, acquiring commodity browsing record information and consumption record information generated by a user through a user terminal and corresponding user information, and acquiring geographical position information of the user terminal;
s2, acquiring consumption preference information corresponding to user information according to the commodity browsing record information and the consumption record information; binding the consumption preference information with the geographical location information;
s3, acquiring advertisement terminal information of a region corresponding to the geographical position information according to the geographical position information; at least one advertising terminal is arranged;
s4, acquiring all advertisement information in an advertisement library; according to the consumption preference information, matching recommended advertisements corresponding to the consumption preference in all the advertisement categories to obtain a recommended advertisement table;
and S5, delivering the corresponding advertisement in the recommended advertisement table to the advertisement terminal corresponding to the advertisement terminal information.
In a possible embodiment, in step S1, the time of daily generation of the commodity browsing record is also obtained; when the consumption preference of the user is obtained according to the commodity browsing record and the consumption record in the step S2, the consumption preference of the user is counted according to different time periods in each day, and the consumption preference of the area corresponding to the geographic position in different time periods in each day is obtained by combining the geographic position; and then delivering advertisements corresponding to the consumption preferences of the corresponding time period to the advertisement terminal according to the time.
In a possible implementation manner, according to the distribution of the geographic position of the user terminal used by the user, the movement law of the user's possibility is obtained, and according to the movement law of the user and the corresponding consumption preference, the advertisement is delivered to the advertisement terminal of the geographic position.
In one possible implementation manner, according to each recommended advertisement in the recommended advertisement table, a play weight is set for each recommended advertisement.
In one possible embodiment, the user information includes an age of the user, and accordingly, the obtained consumption preference has a corresponding age stage of the user; and adjusting the playing weight of each recommended advertisement based on the current user age identified by the face identification module arranged on the advertisement terminal.
In a second aspect, the embodiment provides a marketing platform based on big data user consumption preferences, which comprises a user information acquisition module, a user consumption information acquisition module, a position information acquisition module, a consumption preference calculation module, an information binding module, an advertisement information acquisition module, an advertisement terminal information acquisition module, a recommended advertisement table acquisition module and an advertisement delivery module; wherein, the
The user information acquisition module is used for acquiring user information;
the user consumption information acquisition module is used for acquiring commodity browsing record information and consumption record information generated by a user through a user terminal;
the position information acquisition module is used for acquiring the geographical position information of the user terminal;
the consumption preference calculation module is used for acquiring consumption preference information of the user according to the commodity browsing record and the consumption record;
the information binding module is used for binding the consumption preference with the geographical position information;
the advertisement terminal information acquisition module is used for acquiring advertisement terminal information of an area corresponding to the geographical position information according to the geographical position information;
the advertisement information acquisition module is used for acquiring all advertisement information in the advertisement library;
the recommended advertisement table acquisition module is used for matching recommended advertisements corresponding to the consumption preferences in all the advertisement categories according to the consumption preference information to acquire a recommended advertisement table;
and the advertisement putting module is used for putting the corresponding advertisement in the recommended advertisement table to the advertisement terminal corresponding to the advertisement terminal information.
In a possible implementation manner, the system further comprises a user motion rule obtaining module, configured to obtain a motion rule of the user according to the geographical location distribution of the user terminal used by the user; and the advertisement putting module is also used for putting advertisements to the advertisement terminal in the geographic position according to the motion rule of the user and the corresponding consumption preference.
In a possible implementation manner, the system further includes a weight setting module, configured to set a play weight for each recommended advertisement according to each recommended advertisement in the recommended advertisement table.
In a third aspect, the present embodiment provides a marketing device based on big data user consumption preference, comprising a memory and a processor, wherein the memory and the processor are connected to each other through a bus; the memory stores computer execution instructions; the processor executes the computer-executable instructions stored in the memory to cause the processor to perform a marketing method based on big data user consumption preferences as set forth in the first aspect and any one of the possible designs of the first aspect. For example, the Memory may include, but is not limited to, a Random-Access Memory (RAM), a Read-Only Memory (ROM), a Flash Memory (Flash Memory), a First-in First-out (FIFO), and/or a First-in Last-out (FILO), and the like; the processor may not be limited to use with processors of the X86, internet series, or other microprocessors; the transceiver may be, but is not limited to, a wired transceiver, a Wireless Fidelity (WiFi) Wireless transceiver, a bluetooth Wireless transceiver, a General Packet Radio Service (GPRS) Wireless transceiver, and/or a ZigBee protocol (ieee 802.15.4 standard-based low power local area network protocol, zigBee) Wireless transceiver, and the like. In addition, the marketing device based on the big data user consumption preference can also comprise, but is not limited to, a power supply module, a display screen and other necessary components.
In a fourth aspect, the present embodiment provides a computer-readable storage medium, where the storage medium stores instructions that, when executed on a computer, perform a marketing method based on big data user consumption preferences as described in the first aspect and any one of the possible designs of the first aspect. The computer-readable storage medium refers to a carrier for storing data, and may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash Memory, a flash disk and/or a Memory Stick (Memory Stick), etc., and the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.
Finally, it should be noted that: the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A marketing method based on big data user consumption preference is characterized by comprising the following steps:
s1, acquiring commodity browsing record information and consumption record information generated by a user through a user terminal and corresponding user information, and acquiring geographical position information of the user terminal;
s2, acquiring consumption preference information corresponding to user information according to the commodity browsing record information and the consumption record information; binding consumption preference information with the geographical location information;
s3, according to the geographical position information, obtaining advertisement terminal information of a region corresponding to the geographical position information; at least one advertising terminal is arranged;
s4, acquiring all advertisement information in an advertisement library; according to the consumption preference information, matching recommended advertisements corresponding to the consumption preference in all the advertisement information to obtain a recommended advertisement table;
and S5, delivering the corresponding advertisement in the recommended advertisement table to the advertisement terminal corresponding to the advertisement terminal information.
2. The big data user consumption preference-based integrated marketing method according to claim 1, wherein in step S1, the time of daily generation of a commodity browsing record is also obtained; when the consumption preference of the user is obtained according to the commodity browsing record and the consumption record in the step S2, the consumption preference of the user is counted according to different time periods every day, and the consumption preference of the area corresponding to the geographical position in different time periods every day is obtained by combining the geographical position; and then delivering advertisements corresponding to the consumption preferences of the corresponding time period to the advertisement terminal according to the time.
3. The integrated marketing method based on big data user consumption preference according to claim 1, characterized in that a movement law of the possibility of the user is obtained according to the geographical location distribution of the user using the user terminal, and an advertisement is delivered to an advertisement terminal where the geographical location is located according to the movement law of the user and the corresponding consumption preference.
4. The integrated marketing method based on big data user consumption preference of claim 1, wherein a play weight is set for each recommended advertisement according to each recommended advertisement in the recommended advertisement table.
5. The integrated marketing method based on big data user consumption preference according to claim 1, characterized in that the user information comprises user age, and accordingly, the obtained consumption preference has corresponding user age stage; and adjusting the playing weight of each recommended advertisement in the recommended advertisement table based on the current user age identified by a face identification module arranged on the advertisement terminal.
6. The marketing platform based on big data user consumption preference is characterized by comprising a user information acquisition module, a user consumption information acquisition module, a position information acquisition module, a consumption preference calculation module, an information binding module, an advertisement information acquisition module, an advertisement terminal information acquisition module, a recommended advertisement list acquisition module and an advertisement putting module; wherein, the
The user information acquisition module is used for acquiring user information;
the user consumption information acquisition module is used for acquiring commodity browsing record information and consumption record information generated by a user through a user terminal;
the position information acquisition module is used for acquiring the geographical position information of the user terminal;
the consumption preference calculation module is used for acquiring consumption preference information of the user according to the commodity browsing record and the consumption record;
the information binding module is used for binding the consumption preference with the geographical location information;
the advertisement terminal information acquisition module is used for acquiring advertisement terminal information of an area corresponding to the geographical position information according to the geographical position information;
the advertisement information acquisition module is used for acquiring all advertisement information in the advertisement library;
the recommended advertisement table acquisition module is used for matching recommended advertisements corresponding to the consumption preference in all the advertisement categories according to the consumption preference information to acquire a recommended advertisement table;
and the advertisement putting module is used for putting the corresponding advertisement in the recommended advertisement table to the advertisement terminal corresponding to the advertisement terminal information.
7. The big data user consumption preference-based marketing platform of claim 1, further comprising a user motion law acquisition module for acquiring a motion law of the user's likelihood according to the geographical location distribution of the user using the user terminal; and the advertisement putting module is also used for putting advertisements to the advertisement terminal in the geographic position according to the motion rule of the user and the corresponding consumption preference.
8. The big data user consumption preference-based marketing platform of claim 1, further comprising a weight setting module for setting a play weight for each recommended advertisement according to each recommended advertisement in the recommended advertisement table.
9. The marketing device based on the big data user consumption preference is characterized by comprising a memory and a processor, wherein the memory and the processor are connected with each other through a bus; the memory stores computer-executable instructions; the processor executes the memory-stored computer-executable instructions to cause the processor to perform the marketing method based on big data user consumption preferences of any one of claims 1 to 5.
10. A storage medium having stored thereon instructions for executing the marketing method based on big data user consumption preference according to any one of claims 1 to 5 when the instructions are executed on a computer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210894131.3ACN115222456A (en) | 2022-07-27 | 2022-07-27 | Marketing method, platform, equipment and medium based on big data user consumption preference |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210894131.3ACN115222456A (en) | 2022-07-27 | 2022-07-27 | Marketing method, platform, equipment and medium based on big data user consumption preference |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115222456Atrue CN115222456A (en) | 2022-10-21 |
Family
ID=83614389
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210894131.3APendingCN115222456A (en) | 2022-07-27 | 2022-07-27 | Marketing method, platform, equipment and medium based on big data user consumption preference |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115222456A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823355A (en)* | 2023-06-13 | 2023-09-29 | 广东健怡投资有限公司 | Advertising push methods, devices, equipment and storage media |
| CN117808535A (en)* | 2023-12-29 | 2024-04-02 | 深圳博十强志科技有限公司 | Advertisement putting method and system based on user big data analysis |
| CN118172112A (en)* | 2024-05-11 | 2024-06-11 | 江西旅游商贸职业学院 | Marketing strategy intelligent analysis system and method based on big data |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105761101A (en)* | 2016-02-04 | 2016-07-13 | 云南今日游情科技有限公司 | High-precision advertisement push system and method of mobile terminal based on mutual selection |
| CN106204123A (en)* | 2016-07-01 | 2016-12-07 | 深圳中兴网信科技有限公司 | The method for pushing of advertising message and device |
| CN107563836A (en)* | 2017-07-31 | 2018-01-09 | 上海与德科技有限公司 | Billboard leasing method, server and storage medium |
| CN108156228A (en)* | 2017-12-15 | 2018-06-12 | 维沃移动通信有限公司 | A kind of ad data method for pushing and device |
| CN110310155A (en)* | 2019-06-28 | 2019-10-08 | 河北工业职业技术学院 | Advertisement placement method, device and server |
| CN110706012A (en)* | 2018-07-10 | 2020-01-17 | 官伟岩 | Automatic vending machine-based advertisement accurate delivery method |
| US20200098010A1 (en)* | 2018-09-20 | 2020-03-26 | PAG Financial International LLC | System and method for providing recommendations based on consumer location |
| CN111582938A (en)* | 2020-05-09 | 2020-08-25 | 北京精准沟通传媒科技股份有限公司 | Advertisement putting method and device and electronic equipment |
| CN112396467A (en)* | 2020-11-30 | 2021-02-23 | 武汉星辰文汇科技有限公司 | Operator DSP (digital Signal processor) support system and method based on big data |
| CN112465572A (en)* | 2021-02-03 | 2021-03-09 | 广州宜推网络科技有限公司 | Advertisement push monitoring system based on big data |
| CN113129078A (en)* | 2021-05-10 | 2021-07-16 | 武汉极风世界网络科技有限责任公司 | Social software advertisement information delivery method based on feature recognition and data visualization analysis |
| CN114742582A (en)* | 2022-03-30 | 2022-07-12 | 深圳市东信时代信息技术有限公司 | Advertisement putting method based on user terminal, server and storage medium |
- 2022
- 2022-07-27CNCN202210894131.3Apatent/CN115222456A/enactivePending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105761101A (en)* | 2016-02-04 | 2016-07-13 | 云南今日游情科技有限公司 | High-precision advertisement push system and method of mobile terminal based on mutual selection |
| CN106204123A (en)* | 2016-07-01 | 2016-12-07 | 深圳中兴网信科技有限公司 | The method for pushing of advertising message and device |
| CN107563836A (en)* | 2017-07-31 | 2018-01-09 | 上海与德科技有限公司 | Billboard leasing method, server and storage medium |
| CN108156228A (en)* | 2017-12-15 | 2018-06-12 | 维沃移动通信有限公司 | A kind of ad data method for pushing and device |
| CN110706012A (en)* | 2018-07-10 | 2020-01-17 | 官伟岩 | Automatic vending machine-based advertisement accurate delivery method |
| US20200098010A1 (en)* | 2018-09-20 | 2020-03-26 | PAG Financial International LLC | System and method for providing recommendations based on consumer location |
| CN110310155A (en)* | 2019-06-28 | 2019-10-08 | 河北工业职业技术学院 | Advertisement placement method, device and server |
| CN111582938A (en)* | 2020-05-09 | 2020-08-25 | 北京精准沟通传媒科技股份有限公司 | Advertisement putting method and device and electronic equipment |
| CN112396467A (en)* | 2020-11-30 | 2021-02-23 | 武汉星辰文汇科技有限公司 | Operator DSP (digital Signal processor) support system and method based on big data |
| CN112465572A (en)* | 2021-02-03 | 2021-03-09 | 广州宜推网络科技有限公司 | Advertisement push monitoring system based on big data |
| CN113129078A (en)* | 2021-05-10 | 2021-07-16 | 武汉极风世界网络科技有限责任公司 | Social software advertisement information delivery method based on feature recognition and data visualization analysis |
| CN114742582A (en)* | 2022-03-30 | 2022-07-12 | 深圳市东信时代信息技术有限公司 | Advertisement putting method based on user terminal, server and storage medium |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823355A (en)* | 2023-06-13 | 2023-09-29 | 广东健怡投资有限公司 | Advertising push methods, devices, equipment and storage media |
| CN117808535A (en)* | 2023-12-29 | 2024-04-02 | 深圳博十强志科技有限公司 | Advertisement putting method and system based on user big data analysis |
| CN118172112A (en)* | 2024-05-11 | 2024-06-11 | 江西旅游商贸职业学院 | Marketing strategy intelligent analysis system and method based on big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115222456A (en) | Marketing method, platform, equipment and medium based on big data user consumption preference | |
| CN106357517B (en) | Directional label generation method and device | |
| CN108550055B (en) | Advertisement information pushing method and system based on geographic position | |
| CN105208113A (en) | Information pushing method and device | |
| CN102073956A (en) | Data mining-based directional advertisement release method, system and equipment | |
| CN110956505B (en) | Advertisement inventory estimation method and related device | |
| CN110049079A (en) | Information push and model training method, device, equipment and storage medium | |
| CN110876123A (en) | Flow acquiring, providing, sharing, calibrating and transferring method and equipment | |
| CN104035926A (en) | Internet information release method and system | |
| CN110300084A (en) | A kind of IP address-based portrait method and apparatus | |
| CN110189157A (en) | Trade company's management method, system, electric terminal and storage medium | |
| CN108629054A (en) | Community method for pushing, device, computer installation and computer readable storage medium | |
| CN114461893B (en) | Information recommendation method, related device, equipment and storage medium | |
| CN111899053A (en) | Online and offline advertisement management system for merchants | |
| CN114626881A (en) | Advertising delivery control method, device, equipment, storage medium and program product | |
| JP2011191911A (en) | Advertisement distribution device, advertisement distribution system, advertisement distribution method and program | |
| CN112435073B (en) | Red packet sending method and red packet sending system | |
| CN114187054A (en) | Customer classification method, apparatus and storage medium | |
| JP2011022675A (en) | Advertisement charging device and method | |
| CN112579910A (en) | Information processing method, information processing apparatus, storage medium, and electronic device | |
| CN116188120A (en) | Method, device and system for recommending audio books and storage medium | |
| CN111476613A (en) | Shopping guide auxiliary method and device based on passenger flow analysis, server and storage medium | |
| US8386299B2 (en) | System and method for dynamically pricing electronic advertisements | |
| CN119006059A (en) | Method, equipment and medium for returning data in dynamic real-time access pool | |
| CN115545737A (en) | Advertisement putting strategy calibration method and device, storage medium and electronic equipment |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication | Application publication date:20221021 |