CN111383083A - Micro-add marketing service system based on big data - Google Patents
Micro-add marketing service system based on big data Download PDFInfo
- Publication number
- CN111383083A CN111383083A CN202010483995.7A CN202010483995A CN111383083A CN 111383083 A CN111383083 A CN 111383083A CN 202010483995 A CN202010483995 A CN 202010483995A CN 111383083 A CN111383083 A CN 111383083A
- Authority
- CN
- China
- Prior art keywords
- user
- marketing
- product
- time
- information
- 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.)
- Granted
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
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
Abstract
The invention discloses a micro-adding marketing service system based on big data, which is used for solving the problems that the traditional marketing service system cannot stop pushing inferior marketing products in time and is recommended too frequently, so that a user has conflict psychology and the use of the system is influenced; the system solves the problem that a user cannot suspend receiving marketing product pushing according to actual requirements, and comprises a data acquisition module, a server, a marketing analysis module and a marketing recommendation module; according to the invention, the verification connection value is obtained by analyzing the evaluation information of the marketing product purchased by the user, and the product verification personnel verifies and stops recommending correspondingly, so that the pushing of inferior marketing products can be reduced in time; the recommended interval duration of the user is obtained through conversion of the pushing interval value, so that the product information of the marketing product is reasonably pushed to the user, the watching duration of the user is counted and the pause pushing duration of the user is obtained through conversion, and the user can conveniently and reasonably pause to receive the pushing of the marketing product.
Description
Technical Field
The invention relates to the technical field of micro-add marketing service, in particular to a micro-add marketing service system based on big data.
Background
In recent years, the information and globalization trends based on the internet and the mobile internet have deeply changed our life, production and competition modes. With the advent of the big data age, the demand for marketing is also rising; marketing refers to the enterprise discovery or excavates accurate consumer demand, removes to promote and sell the product from the construction of whole atmosphere and the construction of self product form, mainly digs the connotation of product deeply, accords with accurate consumer's demand to let the consumer understand the process that this product and then purchase deeply. The traditional marketing service system cannot stop pushing inferior marketing products in time, and the poor marketing products are recommended too frequently, so that the users have conflict psychology and the use of the poor marketing products is influenced; the user cannot pause receiving the marketing product push according to actual needs.
Disclosure of Invention
The invention aims to solve the problems that the traditional marketing service system cannot stop pushing inferior marketing products in time and the use of the traditional marketing service system is influenced due to the conflict psychology of users caused by too frequent recommendation; the user can not pause to receive the pushing of the marketing product according to the actual demand, and provides a micro marketing service system based on big data; according to the invention, the verification connection value is obtained by analyzing the evaluation information of the marketing product purchased by the user, the marketing product purchased by the user is sent to the corresponding product verification personnel through the verification connection value, and the verification is carried out and the corresponding recommendation is stopped through the product verification personnel, so that the pushing of inferior marketing products can be timely reduced; the recommending interval duration of the user is obtained through conversion of the pushing interval value, so that the product information of the marketing product is reasonably pushed to the user, the user counts the watching duration of the user and obtains the pausing pushing duration of the user through sending a pausing recommending request instruction and checking the corresponding marketing product according to conversion of a certain proportion, and the user can reasonably pause to receive the pushing of the marketing product.
The purpose of the invention can be realized by the following technical scheme: a micro-add marketing service system based on big data comprises a data acquisition module, a server, a marketing analysis module and a marketing recommendation module;
the data acquisition module is used for acquiring marketing information of marketing products and sending the marketing information to the server, and the marketing information comprises names of the marketing products, purchasing user data corresponding to the marketing products and logistics real-time data; the purchasing user data comprises user account information and all evaluation information of the user on the marketing product, wherein the user account information comprises a user account name and a mobile phone number; the evaluation information comprises evaluation time, evaluation characters, evaluation shot marketing product pictures and evaluation scores of the purchased marketing products;
the marketing analysis module is used for analyzing marketing information of marketing products, and the specific analysis steps are as follows:
the method comprises the following steps: acquiring purchasing user data, marking the user as a verification user when the user evaluation score is lower than a set threshold value, and acquiring all evaluation information of the user;
step two: screening all the evaluation information, acquiring the evaluation information of the user within three months before the current time of the system, and counting the total evaluation times and the time and times when the evaluation score is lower than a set threshold value;
step three: sequencing the moments with the evaluation scores lower than the set threshold according to the time sequence, calculating the grading interval duration of two adjacent moments, summing all the grading interval durations to obtain the total grading interval duration, marking the total evaluation duration as A1, marking the total evaluation times as A2, and marking the times with the evaluation scores lower than the set threshold as A3;
step four: using formulas
Obtaining a verification connection value AZ of the user, wherein b1, b2, b3, b4 and b5 are all preset proportionality coefficients;
step five: when the verification connection value is larger than the set threshold value, no operation is performed; when the verification connection value is less than or equal to the set threshold, performing verification connection processing, wherein the specific processing steps are as follows:
s1: acquiring personnel information of a product verifier, calculating a distance difference between the position of the product verifier and the position of a verification user, and marking the distance difference as Ak, k for representing the product verifier;
s2, obtaining the coincidence value Wk of the product verifier by using a formula Wk = Ak × b6+ Dk × b8-Ck × b7, wherein b6, b7 and b8 are all preset proportionality coefficients, Ck is the number of the product verifier to be verified, and Dk is a basic value of the product verifier;
s3: selecting the product verifier with the maximum matching value Wk and marking the product verifier as the selected verifier; simultaneously adding one to the number to be verified of the product verification personnel;
s4: the position and the number of the selected verification personnel are sent to a mobile phone terminal of the verification user;
step six: after the verification user receives the position and the number of the verification person through the mobile phone terminal, the verification user sends the marketing product to the position of the selected verification person through express delivery and sends the sent express bill number to the mobile phone terminal of the selected verification person;
step seven: the selected verifying personnel receives the marketing product sent by the verifying user and verifies the marketing product with the rating information of the verifying user; then, selecting a verifier to send a product problem instruction or a user problem instruction to the marketing analysis module through the mobile phone terminal; meanwhile, the number of the selected personnel to be verified is reduced by one;
step eight: generating a recommendation stopping instruction of the marketing product after the marketing analysis module receives the product problem instruction; when the marketing analysis module receives a user problem instruction, no operation is performed;
step nine: the marketing analysis module sends a recommendation stopping instruction to the marketing recommendation module;
the marketing recommendation module is used for pushing the product information of the marketing product to a WeChat account of a user, and stopping recommending the marketing product after the marketing recommendation module receives a recommendation stopping instruction of the marketing product; after receiving a push instruction of a user, the marketing recommendation module pushes product information of a marketing product to a WeChat account of the user; and after the marketing recommendation module receives the pause instruction and the pause pushing time, recording the time of receiving the pause instruction, and when the time difference between the time of receiving the pause instruction and the current time of the system is equal to the pause pushing time, pushing the product information of the marketing product to the WeChat account of the user by the marketing recommendation module.
Preferably, the product verification module is used for submitting staff information for registration, sending the staff information which is successfully registered to the server, and marking the staff as a product verification staff, wherein the staff information comprises the name, the position, the age and the time of job entry of the staff;
after receiving the personnel information, the server calculates a basic value, and the specific calculation steps are as follows:
SS 1: calculating the time difference between the working time and the current time of the system to obtain the working time of the product verification personnel, and marking the working time as Tk, wherein the unit is day;
SS 2: recording the age of a product verifier as Nk;
SS 3: using formulas
And obtaining a basic value Dk of the product verifier, wherein both b9 and b10 are preset proportionality coefficients.
Preferably, the system also comprises a registration login module, a user acquisition module, a user analysis module and a marketing adjustment module; the registration login module is used for submitting user information for registration through the mobile phone terminal and sending the user information which is successfully registered to the server for storage; the user information comprises a name, a mobile phone number and a position;
the user acquisition module is used for acquiring product information operation data of a user on a marketing product and sending the operation data to the user analysis module through the server; the operation data comprises the moment when the user receives the product information, the moment when the user clicks, the closing moment, the neglecting moment of the user and the neglecting times; the neglect moment is the moment when the user directly ignores the product information;
the user analysis module receives the operation data and analyzes the operation data, and the specific analysis is as follows:
w1: screening the operation data of the user, acquiring the operation data within 10 days before the current time of the system and marking the operation data as analysis data;
w2: counting the product information received by the user in the analysis data, counting the times of clicking time and the times of neglecting of the user, and respectively marking as E1 and E2;
w3: calculating time difference of the moment when the user receives the product information, the user clicking moment and the closing moment respectively to obtain receiving duration and checking duration respectively; the receiving time length is the time difference between the moment of receiving the product information and the moment of clicking by the user, and the checking time length is the time difference between the moment of clicking by the user and the moment of closing; summing all the receiving time lengths to obtain a total receiving time length and marking the total receiving time length as E3; summing all the viewing durations to obtain a total viewing duration and marking the total viewing duration as E4;
w4: calculating the time difference between the moment when the user receives the product information and the neglect moment of the corresponding user to obtain the neglect duration of the user; summing all the neglected durations to obtain a neglected total duration E5;
w5: using formulas
Acquiring a pushing interval value EZ of the user; wherein v1, v2, v3, v4 and v5 are all preset fixed values of proportionality coefficients;
w6: the user analysis module sends the pushing interval value of the user to the marketing adjustment module;
the marketing adjustment module is used for adjusting the time when the product information of the marketing product is pushed to the WeChat account of the user, and is specifically shown in the following steps that when the marketing adjustment module receives the pushing interval value of the user, the pushing interval duration TS of the user is obtained by using a formula TS = EZ × t1, wherein t1 is a duration conversion proportion coefficient, the marketing adjustment module obtains the time when the marketing recommendation module last sends the marketing product information to the user and calculates the time difference with the current time of the system, when the time difference is equal to the pushing interval duration, the pushing instruction of the user is generated and sent to the marketing recommendation module, and after the marketing recommendation module receives the pushing instruction, the product information of the marketing product is pushed to the WeChat account of the user.
Preferably, the system further comprises a pause recommending module, wherein the pause recommending module is used for stopping receiving the product information of the marketing product sent by the marketing recommending module by the user, and the specific receiving stopping step is as follows:
WW 1: a user sends a pause recommendation request instruction, a viewing starting time and a viewing ending time to a pause recommendation module through a mobile phone terminal;
WW 2: after the pause recommending module receives the pause recommending request instruction and the watching starting time and the watching finishing time, the pause recommending module generates a push instruction at the watching starting time and sends the push instruction to the pause recommending module;
WW 3: after receiving the push instruction, the pause recommending module pushes the product information of the marketing product to a WeChat account of the user, and meanwhile, the pause recommending module collects the active duration of the product information of the marketing product viewed by the user;
WW4, marking the active time length as TZ, when the active time length TZ is larger than the set threshold value, generating a pause instruction, and obtaining the pause push time length ZS of the user by using a formula ZS = TZ × t2, wherein t2 is a time length conversion scale coefficient;
WW 5: and the pause recommending module sends the pause instruction and the pause pushing duration to the marketing recommending module.
Compared with the prior art, the invention has the beneficial effects that:
1. the data acquisition module acquires marketing information of a marketing product and sends the marketing information to the server, the marketing analysis module is used for analyzing the marketing information of the marketing product, a verification connection value of a user is obtained by using a formula, when the verification connection value is smaller than or equal to a set threshold value, verification connection processing is carried out, and a selected verifier sends a product problem instruction or a user problem instruction to the marketing analysis module through a mobile phone terminal; the marketing analysis module sends a recommendation stopping instruction to the marketing recommendation module; after the marketing recommendation module receives a recommendation stopping instruction of the marketing product, stopping recommending the marketing product; the method comprises the steps that evaluation information of marketing products purchased by a user is analyzed to obtain a verification connection value, the marketing products purchased by the user are sent to corresponding product verification personnel through the verification connection value, and the verification is carried out and the corresponding recommendation stopping is carried out through the product verification personnel, so that the pushing of inferior marketing products can be timely reduced, and the problem that the existing marketing service system cannot timely stop pushing the inferior marketing products is solved;
2. the user analysis module receives the operation data and analyzes the operation data, and a formula is used for obtaining a pushing interval value of the user; the user analysis module sends the pushing interval value of the user to the marketing adjustment module; the marketing adjustment module adjusts the moment when the product information of the marketing product is pushed to the WeChat account of the user; the pushing interval value of the user is obtained by analyzing the operation data corresponding to the product information of the marketing product received by the user, and the recommending interval duration of the user is obtained by converting the pushing interval value, so that the product information of the marketing product is reasonably pushed to the user, and the phenomenon that the user is influenced by the conflicting psychology caused by the fact that the existing marketing system recommends too frequently is avoided;
the pause recommending module is used for stopping receiving the product information of the marketing product sent by the marketing recommending module by a user, and sending a pause recommending request instruction, a watching starting time and a watching ending time to the pause recommending module by the user through a mobile phone terminal; after the pause recommending module receives the pause recommending request instruction and the watching starting time and the watching finishing time, the pause recommending module generates a push instruction at the watching starting time and sends the push instruction to the pause recommending module; the marketing recommendation module receives the pause instruction and the push pause time and records the time of receiving the pause instruction, and when the time difference between the time of receiving the pause instruction and the current time of the system is equal to the push pause time, the marketing recommendation module pushes the product information of the marketing product to a WeChat account of the user; the user counts the watching time length of the user and converts the watching time length according to a certain proportion to obtain the time length of the user for temporarily stopping to receive the marketing product push conveniently and reasonably by sending a temporarily stopping recommendation request instruction and checking the corresponding marketing product.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a micro marketing service system based on big data includes a data acquisition module, a server, a marketing analysis module, a marketing recommendation module, a suspension recommendation module, a registration login module, a user acquisition module, a user analysis module, and a marketing adjustment module;
the data acquisition module is used for acquiring marketing information of marketing products and sending the marketing information to the server, wherein the marketing information comprises names of the marketing products, purchasing user data corresponding to the marketing products and logistics real-time data; the purchasing user data comprises user account information and all evaluation information of the user on the marketing product, wherein the user account information comprises a user account name and a mobile phone number; the evaluation information comprises evaluation time, evaluation characters, evaluation shot marketing product pictures and evaluation scores of the purchased marketing products;
the marketing analysis module is used for analyzing marketing information of marketing products, and the specific analysis steps are as follows:
the method comprises the following steps: acquiring purchasing user data, marking the user as a verification user when the user evaluation score is lower than a set threshold value, and acquiring all evaluation information of the user;
step two: screening all the evaluation information, acquiring the evaluation information of the user within three months before the current time of the system, and counting the total evaluation times and the time and times when the evaluation score is lower than a set threshold value;
step three: sequencing the moments with the evaluation scores lower than the set threshold according to the time sequence, calculating the grading interval duration of two adjacent moments, summing all the grading interval durations to obtain the total grading interval duration, marking the total evaluation duration as A1, marking the total evaluation times as A2, and marking the times with the evaluation scores lower than the set threshold as A3;
step four: using formulas
Obtaining a verification connection value AZ of the user, wherein b1, b2, b3, b4 and b5 are all preset proportionality coefficients;
step five: when the verification connection value is larger than the set threshold value, no operation is performed; when the verification connection value is less than or equal to the set threshold, performing verification connection processing, wherein the specific processing steps are as follows:
s1: acquiring personnel information of a product verifier, calculating a distance difference between the position of the product verifier and the position of a verification user, and marking the distance difference as Ak, k for representing the product verifier;
s2, obtaining the coincidence value Wk of the product verifier by using a formula Wk = Ak × b6+ Dk × b8-Ck × b7, wherein b6, b7 and b8 are all preset proportionality coefficients, Ck is the number of the product verifier to be verified, and Dk is a basic value of the product verifier;
s3: selecting the product verifier with the maximum matching value Wk and marking the product verifier as the selected verifier; simultaneously adding one to the number to be verified of the product verification personnel;
s4: the position and the number of the selected verification personnel are sent to a mobile phone terminal of the verification user;
step six: after the verification user receives the position and the number of the verification person through the mobile phone terminal, the verification user sends the marketing product to the position of the selected verification person through express delivery and sends the sent express bill number to the mobile phone terminal of the selected verification person;
step seven: the selected verifying personnel receives the marketing product sent by the verifying user and verifies the marketing product with the rating information of the verifying user; then, selecting a verifier to send a product problem instruction or a user problem instruction to the marketing analysis module through the mobile phone terminal; meanwhile, the number of the selected personnel to be verified is reduced by one;
step eight: generating a recommendation stopping instruction of the marketing product after the marketing analysis module receives the product problem instruction; when the marketing analysis module receives a user problem instruction, no operation is performed;
step nine: the marketing analysis module sends a recommendation stopping instruction to the marketing recommendation module;
the marketing recommendation module is used for receiving a push instruction of a user and pushing product information of a marketing product to a WeChat account of the user, and when the marketing recommendation module receives a recommendation stopping instruction of the marketing product, the marketing product is stopped from being recommended.
The product verification module is used for submitting personnel information for registration by a worker, sending the personnel information which is successfully registered to the server, and marking the worker as a product verification worker, wherein the personnel information comprises the name, the position, the age and the time of job entry of the worker;
after receiving the personnel information, the server calculates a basic value, and the specific calculation steps are as follows:
SS 1: calculating the time difference between the working time and the current time of the system to obtain the working time of the product verification personnel, and marking the working time as Tk, wherein the unit is day;
SS 2: recording the age of a product verifier as Nk;
SS 3: using formulas
And obtaining a basic value Dk of the product verifier, wherein both b9 and b10 are preset proportionality coefficients.
The registration login module is used for submitting user information for registration through the mobile phone terminal and sending the user information which is successfully registered to the server for storage; the user information comprises a name, a mobile phone number and a position;
the user acquisition module is used for acquiring product information operation data of a user on a marketing product and sending the operation data to the user analysis module through the server; the operation data comprises the moment when the user receives the product information, the user clicking moment, the closing moment, the user ignoring moment and the ignoring times; the neglect moment is the moment when the user directly ignores the product information;
the user analysis module receives the operation data and analyzes the operation data, and the specific analysis is as follows:
w1: screening the operation data of the user, acquiring the operation data within 10 days before the current time of the system and marking the operation data as analysis data;
w2: counting the product information received by the user in the analysis data, counting the times of clicking time and the times of neglecting of the user, and respectively marking as E1 and E2;
w3: calculating time difference of the moment when the user receives the product information, the user clicking moment and the closing moment respectively to obtain receiving duration and checking duration respectively; the receiving time length is the time difference between the moment of receiving the product information and the moment of clicking by the user, and the checking time length is the time difference between the moment of clicking by the user and the moment of closing; summing all the receiving time lengths to obtain a total receiving time length and marking the total receiving time length as E3; summing all the viewing durations to obtain a total viewing duration and marking the total viewing duration as E4;
w4: calculating the time difference between the moment when the user receives the product information and the neglect moment of the corresponding user to obtain the neglect duration of the user; summing all the neglected durations to obtain a neglected total duration E5;
w5: using formulas
Acquiring a pushing interval value EZ of the user; wherein v1, v2, v3, v4 and v5 are all preset fixed values of proportionality coefficients;
w6: the user analysis module sends the pushing interval value of the user to the marketing adjustment module;
the marketing adjustment module is used for adjusting the time when the product information of the marketing product is pushed to the WeChat account of the user, and is specifically shown in the following steps that when the marketing adjustment module receives the pushing interval value of the user, the pushing interval duration TS of the user is obtained by using a formula TS = EZ × t1, wherein t1 is a duration conversion proportion coefficient, the marketing adjustment module obtains the time when the marketing recommendation module last sends the marketing product information to the user and calculates the time difference with the current period of the system, when the time difference is equal to the pushing interval duration, the pushing instruction of the user is generated and sent to the marketing recommendation module, and after the marketing recommendation module receives the pushing instruction, the product information of the marketing product is pushed to the WeChat account of the user.
The pause recommending module is used for stopping receiving the product information of the marketing product sent by the marketing recommending module by the user, and the specific receiving stopping step is as follows:
WW 1: a user sends a pause recommendation request instruction, a viewing starting time and a viewing ending time to a pause recommendation module through a mobile phone terminal;
WW 2: after the pause recommending module receives the pause recommending request instruction and the watching starting time and the watching finishing time, the pause recommending module generates a push instruction at the watching starting time and sends the push instruction to the pause recommending module;
WW 3: after receiving the push instruction, the pause recommending module pushes the product information of the marketing product to a WeChat account of the user, and meanwhile, the pause recommending module collects the active duration of the product information of the marketing product viewed by the user;
WW4, marking the active time length as TZ, when the active time length TZ is larger than the set threshold value, generating a pause instruction, and obtaining the pause push time length ZS of the user by using a formula ZS = TZ × t2, wherein t2 is a time length conversion scale coefficient;
WW 5: the marketing recommendation module receives the pause instruction and the push pause time and records the time of receiving the pause instruction, and when the time difference between the time of receiving the pause instruction and the current time of the system is equal to the push pause time, the marketing recommendation module pushes the product information of the marketing product to a WeChat account of the user;
the symbols in the formula are all numerical values of the symbols, and then the numerical values are substituted into the formula for calculation;
when the system is used, the data acquisition module acquires marketing information of a marketing product and sends the marketing information to the server, the marketing analysis module is used for analyzing the marketing information of the marketing product to acquire purchasing user data, and when the user evaluation score is lower than a set threshold value, the user is marked as a verification user, and simultaneously all evaluation information of the user is acquired; screening all the evaluation information, acquiring the evaluation information of the user within three months before the current time of the system, and counting the total evaluation times and the time and times when the evaluation score is lower than a set threshold value; sequencing the moments with the evaluation scores lower than a set threshold value according to the time sequence, calculating the scoring interval duration of two adjacent moments, summing all the scoring interval durations to obtain the total scoring interval duration, and utilizing a formula
Obtaining a verification connection value AZ of the user, and when the verification connection value is larger than a set threshold value, not performing any operation; when the verification connection value is smaller than or equal to the set threshold value, verification connection processing is carried out, after the verification user receives the position and the number of the verification person through the mobile phone terminal, the verification user sends the marketing product to the position of the selected verification person through express delivery and sends the sent express delivery order number to the mobile phone terminal of the selected verification person; the selected verifying personnel receives the marketing product sent by the verifying user and verifies the marketing product with the rating information of the verifying user; then, selecting a verifier to send a product problem instruction or a user problem instruction to the marketing analysis module through the mobile phone terminal; generating a recommendation stopping instruction of the marketing product after the marketing analysis module receives the product problem instruction; the marketing analysis module sends a recommendation stopping instruction to the marketing recommendation module; the marketing recommendation module is used for receiving a push instruction of a user and pushing product information of a marketing product to a WeChat account of the user, and when the marketing recommendation module receives a recommendation stopping instruction of the marketing product, the marketing product is stopped from being recommended; obtaining a verification connection value by analyzing the evaluation information of the marketing product purchased by the userThe marketing products purchased by the users are sent to corresponding product verification personnel through the verification connection values, and the verification is carried out by the product verification personnel and the corresponding recommendation stopping is carried out, so that the pushing of inferior marketing products can be reduced in time, and the problem that the existing marketing service system cannot stop the pushing of the inferior marketing products in time is solved; the user analysis module receives the operation data, analyzes the operation data, screens the operation data of the user, acquires the operation data within 10 days before the current time of the system and marks the operation data as analysis data; counting product information received by a user in the analysis data, counting the times and the neglect times of the user click time, and respectively calculating the time difference of the time when the user receives the product information, the user click time and the closing time to respectively obtain a receiving time and a checking time; summing all the receiving time lengths to obtain the total receiving time length; summing all the checking durations to obtain a total checking duration, and calculating the time difference between the moment when the user receives the product information and the neglecting moment of the corresponding user to obtain the neglecting duration of the user; summing all the neglected durations to obtain the neglected total duration; using formulas
Acquiring a pushing interval value EZ of the user;
the user analysis module sends the pushing interval value of the user to the marketing adjustment module; the marketing adjustment module adjusts the moment when the product information of the marketing product is pushed to the WeChat account of the user; the pushing interval value of the user is obtained by analyzing the operation data corresponding to the product information of the marketing product received by the user, and the recommending interval duration of the user is obtained by converting the pushing interval value, so that the product information of the marketing product is reasonably pushed to the user, and the phenomenon that the user is influenced by the conflicting psychology caused by the fact that the existing marketing system recommends too frequently is avoided; the pause recommending module is used for stopping receiving the product information of the marketing product sent by the marketing recommending module by the user, and sending a pause recommending request instruction, the watching starting time and the watching ending time to the pause recommending module by the user through the mobile phone terminal; after the pause recommending module receives the pause recommending request instruction and the watching starting time and the watching finishing time, the pause recommending module generates a push instruction at the watching starting time and sends the push instruction to the pause recommending module; after receiving the push instruction, the pause recommending module pushes the product information of the marketing product to a WeChat account of the user, and meanwhile, the pause recommending module collects the active duration of the product information of the marketing product viewed by the user;
the method comprises the steps of marking active duration as TZ, generating a pause instruction when the active duration TZ is larger than a set threshold value, obtaining pause push duration ZS of a user by using a formula ZS = TZ × t2, sending the pause instruction and the pause push duration to a marketing recommendation module by the pause recommendation module, recording the moment of receiving the pause instruction after the marketing recommendation module receives the pause instruction and the pause push duration, pushing product information of a marketing product to a WeChat account of the user by the marketing recommendation module when the time difference between the moment of receiving the pause instruction and the current time of a system is equal to the pause push duration, sending a pause recommendation request instruction by the user, checking the corresponding marketing product, counting the watching duration of the user, converting the pause push duration of the user according to a certain proportion, and facilitating the user to reasonably pause and receive the push of the marketing product.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. A micro-add marketing service system based on big data is characterized by comprising a data acquisition module, a server, a marketing analysis module and a marketing recommendation module;
the data acquisition module is used for acquiring marketing information of marketing products and sending the marketing information to the server; the marketing analysis module is used for analyzing marketing information of marketing products, and the specific analysis steps are as follows:
the method comprises the following steps: acquiring purchasing user data, marking the user as a verification user when the user evaluation score is lower than a set threshold value, and acquiring all evaluation information of the user;
step two: screening all the evaluation information, acquiring the evaluation information of the user within three months before the current time of the system, and counting the total evaluation times and the time and times when the evaluation score is lower than a set threshold value;
step three: sequencing the moments with the evaluation scores lower than the set threshold according to the time sequence, calculating the grading interval duration of two adjacent moments, summing all the grading interval durations to obtain the total grading interval duration, marking the total evaluation duration as A1, marking the total evaluation times as A2, and marking the times with the evaluation scores lower than the set threshold as A3;
step four: using formulas
Obtaining a verification connection value AZ of the user, wherein b1, b2, b3, b4 and b5 are all preset proportionality coefficients;
step five: when the verification connection value is larger than the set threshold value, no operation is performed; when the verification connection value is less than or equal to the set threshold, performing verification connection processing, wherein the specific processing steps are as follows:
s1: acquiring personnel information of a product verifier, calculating a distance difference between the position of the product verifier and the position of a verification user, and marking the distance difference as Ak, k for representing the product verifier;
s2, obtaining the coincidence value Wk of the product verifier by using a formula Wk = Ak × b6+ Dk × b8-Ck × b7, wherein b6, b7 and b8 are all preset proportionality coefficients, Ck is the number of the product verifier to be verified, and Dk is a basic value of the product verifier;
s3: selecting the product verifier with the maximum matching value Wk and marking the product verifier as the selected verifier; simultaneously adding one to the number to be verified of the product verification personnel;
s4: the position and the number of the selected verification personnel are sent to a mobile phone terminal of the verification user;
step six: after the verification user receives the position and the number of the verification person through the mobile phone terminal, the verification user sends the marketing product to the position of the selected verification person through express delivery and sends the sent express bill number to the mobile phone terminal of the selected verification person;
step seven: the selected verifying personnel receives the marketing product sent by the verifying user and verifies the marketing product with the rating information of the verifying user; then, selecting a verifier to send a product problem instruction or a user problem instruction to the marketing analysis module through the mobile phone terminal; meanwhile, the number of the selected personnel to be verified is reduced by one;
step eight: generating a recommendation stopping instruction of the marketing product after the marketing analysis module receives the product problem instruction; when the marketing analysis module receives a user problem instruction, no operation is performed;
step nine: the marketing analysis module sends a recommendation stopping instruction to the marketing recommendation module;
the marketing recommendation module is used for pushing the product information of the marketing product to a WeChat account of a user, and stopping recommending the marketing product after the marketing recommendation module receives a recommendation stopping instruction of the marketing product; after receiving a push instruction of a user, the marketing recommendation module pushes product information of a marketing product to a WeChat account of the user; and after the marketing recommendation module receives the pause instruction and the pause pushing time, recording the time of receiving the pause instruction, and when the time difference between the time of receiving the pause instruction and the current time of the system is equal to the pause pushing time, pushing the product information of the marketing product to the WeChat account of the user by the marketing recommendation module.
2. The big data-based micro-add marketing service system according to claim 1, wherein the product verification module is configured to submit staff information for registration and send the staff information that is successfully registered to the server, and mark the staff as a product verifier, wherein the staff information includes the name, location, age, and time of job entry of the staff;
after receiving the personnel information, the server calculates a basic value, and the specific calculation steps are as follows:
SS 1: calculating the time difference between the working time and the current time of the system to obtain the working time of the product verification personnel, and marking the working time as Tk, wherein the unit is day;
SS 2: recording the age of a product verifier as Nk;
SS 3: using formulas
And obtaining a basic value Dk of the product verifier, wherein both b9 and b10 are preset proportionality coefficients.
3. The big data-based micro-add marketing service system according to claim 1, further comprising a registration login module, a user collection module, a user analysis module and a marketing adjustment module; the registration login module is used for submitting user information for registration through the mobile phone terminal and sending the user information which is successfully registered to the server for storage; the user information comprises a name, a mobile phone number and a position;
the user acquisition module is used for acquiring product information operation data of a user on a marketing product and sending the operation data to the user analysis module through the server; the operation data comprises the moment when the user receives the product information, the moment when the user clicks, the closing moment, the neglecting moment of the user and the neglecting times; the neglect moment is the moment when the user directly ignores the product information;
the user analysis module receives the operation data and analyzes the operation data, and the specific analysis is as follows:
w1: screening the operation data of the user, acquiring the operation data within 10 days before the current time of the system and marking the operation data as analysis data;
w2: counting the product information received by the user in the analysis data, counting the times of clicking time and the times of neglecting of the user, and respectively marking as E1 and E2;
w3: calculating time difference of the moment when the user receives the product information, the user clicking moment and the closing moment respectively to obtain receiving duration and checking duration respectively; the receiving time length is the time difference between the moment of receiving the product information and the moment of clicking by the user, and the checking time length is the time difference between the moment of clicking by the user and the moment of closing; summing all the receiving time lengths to obtain a total receiving time length and marking the total receiving time length as E3; summing all the viewing durations to obtain a total viewing duration and marking the total viewing duration as E4;
w4: calculating the time difference between the moment when the user receives the product information and the neglect moment of the corresponding user to obtain the neglect duration of the user; summing all the neglected durations to obtain a neglected total duration E5;
w5: using formulas
Acquiring a pushing interval value EZ of the user; wherein v1, v2, v3, v4 and v5 are all preset fixed values of proportionality coefficients;
w6: the user analysis module sends the pushing interval value of the user to the marketing adjustment module;
the marketing adjustment module is used for adjusting the time when the product information of the marketing product is pushed to the WeChat account of the user, and is specifically shown in the following steps that when the marketing adjustment module receives the pushing interval value of the user, the pushing interval duration TS of the user is obtained by using a formula TS = EZ × t1, wherein t1 is a duration conversion proportion coefficient, the marketing adjustment module obtains the time when the marketing recommendation module last sends the marketing product information to the user and calculates the time difference with the current time of the system, when the time difference is equal to the pushing interval duration, the pushing instruction of the user is generated and sent to the marketing recommendation module, and after the marketing recommendation module receives the pushing instruction, the product information of the marketing product is pushed to the WeChat account of the user.
4. The big-data-based micro-add marketing service system according to claim 1, further comprising a pause recommending module, wherein the pause recommending module is used for stopping receiving the product information of the marketing product sent by the marketing recommending module by the user, and the specific receiving stopping step is as follows:
WW 1: a user sends a pause recommendation request instruction, a viewing starting time and a viewing ending time to a pause recommendation module through a mobile phone terminal;
WW 2: after the pause recommending module receives the pause recommending request instruction and the watching starting time and the watching finishing time, the pause recommending module generates a push instruction at the watching starting time and sends the push instruction to the pause recommending module;
WW 3: after receiving the push instruction, the pause recommending module pushes the product information of the marketing product to a WeChat account of the user, and meanwhile, the pause recommending module collects the active duration of the product information of the marketing product viewed by the user;
WW4, marking the active time length as TZ, when the active time length TZ is larger than the set threshold value, generating a pause instruction, and obtaining the pause push time length ZS of the user by using a formula ZS = TZ × t2, wherein t2 is a time length conversion scale coefficient;
WW 5: and the pause recommending module sends the pause instruction and the pause pushing duration to the marketing recommending module.
5. The big-data-based micro-add marketing service system according to claim 1, wherein the marketing information comprises a name of a marketing product, purchasing user data corresponding to the marketing product, and logistics real-time data; the purchasing user data comprises user account information and all evaluation information of the user on the marketing product, wherein the user account information comprises a user account name and a mobile phone number; the evaluation information includes evaluation time, evaluation characters, evaluation shot marketing product pictures and evaluation scores for purchasing marketing products.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010483995.7A CN111383083B (en) | 2020-06-01 | 2020-06-01 | Micro-add marketing service system based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010483995.7A CN111383083B (en) | 2020-06-01 | 2020-06-01 | Micro-add marketing service system based on big data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111383083A true CN111383083A (en) | 2020-07-07 |
| CN111383083B CN111383083B (en) | 2020-09-25 |
Family
ID=71219158
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010483995.7A Active CN111383083B (en) | 2020-06-01 | 2020-06-01 | Micro-add marketing service system based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111383083B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112381973A (en) * | 2020-11-11 | 2021-02-19 | 快优智能技术有限公司 | Electronic lock control system capable of being expanded for multiple times |
| CN112669481A (en) * | 2020-12-16 | 2021-04-16 | 重庆电子工程职业学院 | Management equipment for product marketing propaganda |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8073811B2 (en) * | 2007-12-12 | 2011-12-06 | Google Inc. | Online content collaboration model |
| CN105138639A (en) * | 2015-08-24 | 2015-12-09 | 成都秋雷科技有限责任公司 | Webpage advertisement screening method |
| CN105225133A (en) * | 2015-10-13 | 2016-01-06 | 广西中烟工业有限责任公司 | One how micro-letter account cigarette marketing operation management system |
| CN107809420A (en) * | 2017-09-30 | 2018-03-16 | 谢彩红 | A kind of advertisement intelligent hold-up interception method |
| CN108335175A (en) * | 2018-02-11 | 2018-07-27 | 吴小军 | Novel electric business platform and investment management system based on economic heath development |
| CN108733748A (en) * | 2018-04-04 | 2018-11-02 | 浙江大学城市学院 | A kind of cross-border product quality risk fuzzy prediction method based on comment on commodity public sentiment |
| CN110264238A (en) * | 2019-05-09 | 2019-09-20 | 浙江华坤道威数据科技有限公司 | A kind of visualization marketing management system based on big data |
-
2020
- 2020-06-01 CN CN202010483995.7A patent/CN111383083B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8073811B2 (en) * | 2007-12-12 | 2011-12-06 | Google Inc. | Online content collaboration model |
| CN105138639A (en) * | 2015-08-24 | 2015-12-09 | 成都秋雷科技有限责任公司 | Webpage advertisement screening method |
| CN105225133A (en) * | 2015-10-13 | 2016-01-06 | 广西中烟工业有限责任公司 | One how micro-letter account cigarette marketing operation management system |
| CN107809420A (en) * | 2017-09-30 | 2018-03-16 | 谢彩红 | A kind of advertisement intelligent hold-up interception method |
| CN108335175A (en) * | 2018-02-11 | 2018-07-27 | 吴小军 | Novel electric business platform and investment management system based on economic heath development |
| CN108733748A (en) * | 2018-04-04 | 2018-11-02 | 浙江大学城市学院 | A kind of cross-border product quality risk fuzzy prediction method based on comment on commodity public sentiment |
| CN110264238A (en) * | 2019-05-09 | 2019-09-20 | 浙江华坤道威数据科技有限公司 | A kind of visualization marketing management system based on big data |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112381973A (en) * | 2020-11-11 | 2021-02-19 | 快优智能技术有限公司 | Electronic lock control system capable of being expanded for multiple times |
| CN112669481A (en) * | 2020-12-16 | 2021-04-16 | 重庆电子工程职业学院 | Management equipment for product marketing propaganda |
| CN112669481B (en) * | 2020-12-16 | 2022-10-21 | 重庆电子工程职业学院 | Management equipment for product marketing propaganda |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111383083B (en) | 2020-09-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108269123B (en) | Advertisement putting control method and device | |
| CN111383083B (en) | Micro-add marketing service system based on big data | |
| US20050021396A1 (en) | Method of assessing the cost effectiveness of advertising | |
| CN109615442B (en) | RTB real-time bidding method based on incentive video advertisement | |
| CN111340538B (en) | Enterprise informatization management cloud platform based on marketing big data | |
| CN111383094A (en) | Product service full-chain driving method, equipment and readable storage medium | |
| CN108694372A (en) | A kind of net cast customer service attitude evaluation method and device | |
| CN111553633A (en) | Engineering cost management system and method | |
| CN113886449A (en) | Big data information analysis system based on Internet of things | |
| CN115983911A (en) | Experience type interactive marketing advertisement delivery system | |
| CN111652659B (en) | VR product evaluation system based on big data | |
| CN114757694A (en) | Advertisement video information pushing system | |
| CN109919659A (en) | Method for pushing, device and the computer equipment of advertisement clearing scheme | |
| JP2014219707A (en) | Advertisement distribution system and point granting method | |
| CN116342177B (en) | BIM-based whole-process cost consultation service management system | |
| CN115730858B (en) | Cultural product design intelligent management platform based on big data | |
| EP3279857A1 (en) | Comment analysis system, comment analysis method, and program for comment analysis | |
| CN116308537A (en) | Advertisement targeted delivery management system based on information flow big data | |
| CN115689655A (en) | Intelligent efficient automatic global analysis SCRM marketing system | |
| CN113099260B (en) | Live broadcast processing method, live broadcast platform, system, medium and electronic device | |
| CN113205364B (en) | User management system and method based on specific scene appeal | |
| CN104205147A (en) | System for collecting and analyzing information regarding advertisement exposure using communication terminal | |
| CN111401718A (en) | One-stop management system and method for building industry | |
| Jordanoski et al. | Report on the state of application of Digital Economy Society Index (DESI) in Western Balkan economies | |
| KR20140047237A (en) | Donation estimating system using location based service gps and the way of bussiness as social company from using it |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |