CN115297163A - Shopping guide background operation optimization system - Google Patents
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- CN115297163A CN115297163A CN202210776925.XA CN202210776925A CN115297163A CN 115297163 A CN115297163 A CN 115297163A CN 202210776925 A CN202210776925 A CN 202210776925A CN 115297163 A CN115297163 A CN 115297163A
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- 241001178520 Stomatepia mongo Species 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 claims description 3
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Abstract
The invention provides a shopping guide background operation optimization system, which utilizes a network service unit to realize the access and data transmission of a user; the background server processes and verifies the data and then can send the data further; the scheduled task unit realizes the timing data checking and judgment; the processor realizes the creation of a storage queue of data, and ensures the smoothness of data transmission; furthermore, operators can flexibly modify the task rules of the background server, so that data transmission can be optimized anytime and anywhere, and the accuracy of data transmission is ensured.
Description
Technical Field
The invention relates to the technical field of intelligent marketing, in particular to a shopping guide background operation optimization system.
Background
In the marketing of modern society, due to diversification of data in the information age, marketing modes in a human management mode are limited, for example, equipment resources cannot be reasonably utilized, and managers cannot grasp various dynamic data in real time. Moreover, the existing marketing system can collect user information, but lacks analysis and subdivision on user groups; the automatic marketing tool is lacked, and the working efficiency is low; lack of management, tracking, and evaluation of activity plans; the effective information interaction and management of three parties, namely a user, an employee and a manager, are lacked.
In addition, the traditional marketing system has a single data acquisition mode, is insufficient in data analysis depth, and does not show the analysis result in detail. Moreover, transaction information, user information, orders and the like are manually input, and the manual input mode cannot cover various channels and marketing performances of marketing information, and cannot count conditions of customers in stores, service conditions of products by the customers and the like, so that information loss is caused, and marketing means and market promotion are influenced. In addition, manual input requires a lot of manpower and time, is time-consuming and labor-consuming, has low efficiency, cannot accurately collect and process various information, and gives timely feedback.
Moreover, the traditional marketing system only monitors and counts the marketing data of the products, simplifies the judging mode and the processing mode, and is difficult to combine the products with the sales condition according to the preference and the tendency of the user. Often, one order only has one commodity association, and whether the preference and the commodity setting of a client are reasonable or not is not known, for example, timely and accurate pushing service for the client cannot be realized, so that the development of a large batch of marketing activities is limited, and the service expansion is limited. At present, a marketing method aiming at interactive behaviors of a user, an employee and a manager does not exist in a marketing system.
Moreover, the traditional marketing system cannot stop pushing inferior marketing products in time, and the pushing is too frequent, so that the users have conflict psychology and the use of the products is influenced; the user cannot pause receiving the marketing product push according to actual needs.
The traditional marketing process usually includes that a marketer designs materials, selects configurable parameters such as marketing audiences (target groups) and budgets, puts the materials on a social media platform, the platform displays the materials according to an internal strategy, and updates the configurable parameters such as the audiences and the budgets according to statistical data information fed back by the putting platform, such as browsing amount, downloading amount and actual cost, until the putting process is finished. This is a typical sequence decision process, and the goal of marketing is to make the actual cost as low as possible, and the conversion rate (which may be the amount of downloads or the amount of browsing) at the target audience as high as possible. After the material is delivered, bidding and recommendation are carried out among a large number of delivered materials in the platform, and display is carried out finally, but the strategy of the platform cannot be directly obtained, so that the delivery of the material is a continuous and dynamically-changing process indirectly, and a deliverer needs to decide how to deliver the material next time by means of intuition and experience.
Disclosure of Invention
In order to overcome the problems, the invention aims to provide a shopping guide background operation method, which realizes the optimization of a shopping guide daily operation system.
In order to achieve the above object, the present invention provides a shopping guide background operation optimization system, which includes:
the network service unit is used for accessing the background server by a user and transmitting data to the background server according to the access record of the user;
the background server receives the data and processes the data; and verifying the data validity; then writing the data into the memory;
a task planning unit for regularly checking the data in the memory and judging whether the sending condition is satisfied; if yes, sending a signal to a processor;
and the processor creates a storage queue for the data meeting the sending condition and sends the data to the network service unit in the form of the storage queue.
In some embodiments, the background server also has a task rule module to set the sending condition to be met by the data.
In some embodiments, after the operator modifies the task rule in the background server according to the transmitted data, the background server writes the modified data into the memory.
In some embodiments, the modified data is in json format.
In some embodiments, the backend server serializes the data in json format, verifies the validity of the data, and then writes the data to memory.
In some embodiments, the memory employs a mongo DB.
In some embodiments, the task planning unit determines the sending condition to be met according to the data set by the task rule module.
In some embodiments, the network service unit transmits data via https protocol.
In some embodiments, the planned task unit employs cron technology.
The shopping guide background operation optimization system realizes the intercommunication among users, backgrounds and operators; the network service unit is used for realizing the access and data transmission of the user; the background server processes and verifies the data and then can send the data further; the planning task unit realizes the timing inspection data and judgment; the processor realizes the creation of a storage queue of data, and ensures the smoothness of data transmission; furthermore, operators can flexibly modify the task rules of the background server, so that data transmission can be optimized anytime and anywhere, the accuracy of data transmission is ensured, and intelligent management of shopping guide daily operation is realized.
Drawings
FIG. 1 is a block diagram of a shopping guide background operation optimization system according to an embodiment of the present invention
FIG. 2 is a schematic flow chart of a shopping guide background operation optimization method according to an embodiment of the present invention
Detailed Description
In order to make the disclosure of the present invention more comprehensible, the present invention is further described with reference to the following embodiments. The invention is of course not limited to this particular embodiment, and general alternatives known to those skilled in the art are also covered by the scope of the invention.
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It is to be noted that the drawings are not to precise scale and are not intended to limit the scope of the invention.
Referring to fig. 1, the shopping guide background operation optimization system of the present embodiment includes: the system comprises a network service unit, a background server, a planning task unit and a processor.
Specifically, the user accesses the background server. And the network service unit transmits data to the background server according to the access record of the user. Here, the network service unit transmits data through https protocol. The background server receives the data and processes the data; moreover, the background server verifies the validity of the data; the data is then written to memory. Preferably, the memory adopts mongo DB. It should be noted here that the data validity refers to whether the data conforms to a preset data rule.
Here, the task scheduling unit checks the data in the memory at regular time intervals to determine whether or not the transmission condition is satisfied. If so, a signal is sent to the processor. Preferably, the scheduled task unit may use a cron technology processor to create a storage queue for data satisfying the sending condition, and send the data to the network service unit in the form of the storage queue.
In addition, the background server can also be provided with a task rule module for setting the sending condition to be met by the data, so that the task planning unit judges according to the sending condition to be met by the data set by the task rule module.
Further, after the operator modifies the task rule in the background server according to the transmitted data, the background server writes the modified data into the memory.
In this embodiment, preferably, the modified data is in json format. Here, the backend server may first perform json format serialization on the data, then verify the validity of the data, and then write the data into the memory.
Referring to fig. 2, an example of an operation flow of the shopping guide background operation optimization system of the embodiment is as follows:
step 5, a task planning unit checks the data in the memory at regular time and judges whether the sending condition is met; if yes, sending a signal to a processor and executing step 6;
and 6, the processor creates a storage queue for the data meeting the sending condition and sends the data to the network service unit in a storage queue form.
In conclusion, the shopping guide background operation optimization system realizes the intercommunication among users, the background and the operators; the network service unit is used for realizing the access and data transmission of the user; the background server processes and verifies the data and then can further send the data; the planning task unit realizes the timing inspection data and judgment; the processor realizes the creation of a storage queue of data, and ensures the smoothness of data transmission; furthermore, operators can flexibly modify the task rules of the background server, so that data transmission can be optimized anytime and anywhere, the accuracy of data transmission is ensured, and intelligent management of shopping guide daily operation is realized.
Although the present invention has been described with reference to preferred embodiments, which are illustrated for the purpose of illustration only and not for the purpose of limitation, it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (9)
1. A shopping guide background operation optimization system, comprising:
the network service unit transmits data to the background server according to the access record of the user;
the background server receives the data and processes the data; and verifying the data validity; then writing the data into the memory;
a task planning unit for regularly checking the data in the memory and judging whether the sending condition is satisfied; if yes, sending a signal to a processor;
and the processor creates a storage queue for the data meeting the sending condition and sends the data to the network service unit in the form of the storage queue.
2. The shopping guide background operation optimization system according to claim 1, wherein the background server further comprises a task rule module for setting a sending condition to be met by the data.
3. The shopping guide background operation optimization system according to claim 2, wherein after the operator modifies the task rules in the background server according to the transmitted data, the background server writes the modified data into the memory.
4. The shopping guide back-office operation optimization system of claim 3, wherein the modified data is in json format.
5. The shopping guide background operation optimization system according to claim 1 or 3, wherein the background server serializes the data in json format, verifies the validity of the data, and then writes the data into the memory.
6. The shopping guide daily intelligent operation system according to claim 5, wherein the memory adopts mongo DB.
7. The shopping guide background operation optimization system according to claim 1, wherein the task planning unit performs the determination according to the sending condition to be satisfied by the data set by the task rule module.
8. The shopping guide background operation optimization system of claim 1, wherein the network service unit transmits data via https protocol.
9. The shopping guide background operation optimization system according to claim 1, wherein the planning task unit employs cron technology.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210776925.XA CN115297163A (en) | 2022-07-04 | 2022-07-04 | Shopping guide background operation optimization system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210776925.XA CN115297163A (en) | 2022-07-04 | 2022-07-04 | Shopping guide background operation optimization system |
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| CN115297163A true CN115297163A (en) | 2022-11-04 |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108600336A (en) * | 2018-04-03 | 2018-09-28 | 广州市宝比万像软件科技有限公司 | Scenic spot integrated synthesis service platform |
| CN110189206A (en) * | 2019-06-04 | 2019-08-30 | 苏州程旅网络科技有限公司 | Asynchronous ordering system and ordering method from the background |
| CN112734485A (en) * | 2021-01-13 | 2021-04-30 | 上海群之脉信息科技有限公司 | User intelligent operation system |
| CN112765109A (en) * | 2021-01-20 | 2021-05-07 | 商客通尚景科技（上海）股份有限公司 | Queue type data storage analysis method and system |
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2022
- 2022-07-04 CN CN202210776925.XA patent/CN115297163A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108600336A (en) * | 2018-04-03 | 2018-09-28 | 广州市宝比万像软件科技有限公司 | Scenic spot integrated synthesis service platform |
| CN110189206A (en) * | 2019-06-04 | 2019-08-30 | 苏州程旅网络科技有限公司 | Asynchronous ordering system and ordering method from the background |
| CN112734485A (en) * | 2021-01-13 | 2021-04-30 | 上海群之脉信息科技有限公司 | User intelligent operation system |
| CN112765109A (en) * | 2021-01-20 | 2021-05-07 | 商客通尚景科技（上海）股份有限公司 | Queue type data storage analysis method and system |
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