CN116664236A - Commodity management and control method, commodity management and control device, computer equipment and computer readable storage medium - Google Patents
Commodity management and control method, commodity management and control device, computer equipment and computer readable storage medium Download PDFInfo
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Abstract
The invention relates to the technical fields of cloud computing, monitoring intellectualization and financial science and technology, and discloses a commodity management and control method, a device, computer equipment and a computer readable storage medium, wherein the method comprises the following steps: acquiring client behavior data generated by a client aiming at least one equity commodity; evaluating the equity commodity according to the client behavior data to judge whether the client behavior data is illegal or not, and generating an evaluation result; determining a management and control strategy according to the evaluation result; and managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy. And the customer behavior data is utilized to automatically generate a management and control strategy to manage and control the customers or equity commodities, management and control personnel are not required to manually screen during the management and control process, management and control are automatically performed, management and control efficiency is improved, labor cost and time cost are reduced, human errors are reduced, and management and control accuracy and management and control quality are improved.
Description
Technical Field
The present invention relates to the technical field of cloud computing, monitoring and intellectualization and financial science and technology, and in particular, to a method and apparatus for controlling commodities, a computer device, and a computer readable storage medium.
Background
With the high-speed development of intelligent technology, shopping modes are various, and convenience and high efficiency of life of people are improved from traditional ground wire shopping to current online shopping. With the rise of online shopping, the financial industry also pushes out online commodities so as to facilitate customers to be able to place the commodity at any time and any place, and promote the yield of the financial commodity while providing convenience for the customers.
For example, for financial enterprises such as banks, insurance, etc., under the development of basic business, commodities such as bank cards, loans, online banking, stocks, money, funds, etc., are derived. The customers can browse and place orders for financial goods through software, public numbers or websites which are promoted by banks or insurance enterprises so as to meet the purchase demands of the goods. In order to increase commodity yield and save customers, financial enterprises such as banks and insurance will usually release some rights and interests. Clients receive offers when buying equity goods, and use lower prices to obtain higher value financial goods.
On the internet, there is a special exception group. The benefits of the equity commodities, such as a large number of vouchers, coupons and the like, are rapidly spread through public numbers, chat groups and the like, so that the coupons are used in a large number, and the activity funds of financial enterprises are lost. At present, rule parameters of equity commodities are manually adjusted through operation, and benefits such as coupons are limited to be overused by clients, but the efficiency of the method is low.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, a computer device and a computer readable storage medium for controlling commodities, which are used for solving the technical problem of low efficiency of the control mode of the benefit commodity in the prior art. To achieve one or a part or all of the above or other objects, the present invention provides a method, an apparatus, a computer device, and a computer readable storage medium for controlling commodities, in a first aspect:
a commodity management and control method comprising:
acquiring client behavior data generated by a client aiming at least one equity commodity;
evaluating the equity commodity according to the client behavior data to judge whether the client behavior data is illegal or not, and generating an evaluation result;
Determining a management and control strategy according to the evaluation result;
and managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
Second aspect:
a merchandise management device, the device comprising:
the acquisition module is used for acquiring client behavior data generated by a client aiming at least one equity commodity;
the evaluation module is used for evaluating the equity commodity according to the customer behavior data so as to judge whether the customer behavior data is illegal or not and generate an evaluation result;
the control module is used for determining a control strategy according to the evaluation result;
and the execution module is used for managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
Third aspect:
a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the article management method described above when the computer program is executed by the processor.
Fourth aspect:
a computer readable storage medium storing a computer program which when executed by a processor performs the steps of the article management method described above.
The implementation of the embodiment of the invention has the following beneficial effects:
when browsing, clicking and purchasing equity commodities, a client can generate client behavior data, and the operation of the client on each equity commodity can be known by acquiring the client behavior data, so that the selling condition of each equity commodity can be monitored. And evaluating the equity commodity according to the client behavior data to obtain information such as the selling quantity and the selling efficiency of the equity commodity, so as to judge whether the client behavior data has illegal behaviors and generate a corresponding evaluation result. Finally, determining a management and control strategy according to the evaluation result, and managing and controlling clients and/or equity commodities, so that abnormal client groups can not purchase equity commodities or reduce sales volume of equity commodities, and benefits such as coupons are prevented from being excessively used by clients; the management and control process does not need manual screening of management and control personnel, automatic management and control is achieved, management and control efficiency is improved, labor cost and time cost are reduced, human errors are reduced, and management and control accuracy and management and control quality are improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Wherein:
fig. 1 is a schematic diagram of an application scenario of a commodity management and control method in an embodiment.
Fig. 2 is a schematic diagram of another application scenario of a commodity management method according to an embodiment.
FIG. 3 is an overall flow chart of a method of controlling merchandise in one embodiment.
FIG. 4 is a schematic diagram of a commodity control method applying a decision model according to one embodiment.
Fig. 5 is a block diagram of a commodity control apparatus according to an embodiment.
FIG. 6 is a schematic diagram of a computer device in one embodiment.
FIG. 7 is another schematic structural diagram of a computer device in one embodiment.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is to be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with one another without conflict.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to be limiting of the invention.
The embodiment of the invention provides a commodity management and control method. Can be applied in the application scenario shown in fig. 1, including the terminal 001 and the server 002. The terminal 001 is connected to the server 002 in communication, and can exchange data. When a client uses a terminal 001 to access a page for selling equity commodity such as software, a website or a public number, and when the client operates the equity commodity, the terminal 001 obtains client behavior data generated for the equity commodity, evaluates the equity commodity according to the client behavior data, judges whether the client behavior data is illegal, and generates an evaluation result. And then the terminal 001 uploads the evaluation result to the server 002, the server 002 determines a management and control strategy according to the evaluation result, and manages and controls the clients and/or the equity commodities according to the management and control strategy. When the client needs to be managed, the server 002 may transmit a management instruction to the terminal 001, and the management instruction is executed by the terminal 001, and the server 002 may also directly manage the account number of the client.
In another application scenario, as shown in fig. 2, a plurality of terminals 001 are each connected to a server 002. When a client uses the terminal 001 to access a page for selling the equity commodity such as software, a website, or a public number, and when the client operates the equity commodity, the terminal 001 obtains client behavior data generated for the equity commodity, and the terminal 001 is used for uploading the client behavior data to the server 002. The server 002 evaluates the equity commodity according to the client behavior data, judges whether the client behavior data is illegal, and generates an evaluation result. And determining a management and control strategy according to the evaluation result, and managing and controlling the clients and/or the equity commodities according to the management and control strategy. The terminal 001 feeds back the control result to the corresponding client based on the control of the server 002. The management and control result, such as account number, is sealed, login cannot be continued, and then, for example, the equity commodity is put off the shelf, purchase cannot be continued, and the like.
Specifically, the terminal 001 may be, but not limited to, various smartphones, personal computers, notebook computers, tablet computers, intelligent control panels, portable wearable devices or other devices capable of implementing network connection, and the server 002 may be implemented by an independent server or a server cluster formed by a plurality of servers, which is not limited in this embodiment.
For financial enterprises such as banks, insurance, etc., under the development of basic business, commodities such as bank cards, loans, online banking, stocks, currencies, funds, etc., are derived. The customers can browse and place orders for financial goods through software, public numbers or websites which are promoted by banks or insurance enterprises so as to meet the purchase demands of the goods. In order to increase commodity yield and save customers, financial enterprises such as banks and insurance will usually release some rights and interests. Clients receive offers when buying equity goods, and use lower prices to obtain higher value financial goods.
On the internet, there is a special exception group. The benefits of the equity commodities, such as a large number of vouchers, coupons and the like, are rapidly spread through public numbers, chat groups and the like, so that the coupons are used in a large number, and the activity funds of financial enterprises are lost. At present, rule parameters of equity commodities are manually adjusted through operation, and benefits such as coupons are limited to be excessively used by clients. But this approach is inefficient and costly to operate.
Based on this, the commodity management and control method provided by the embodiment of the present invention, as shown in fig. 3, includes:
101. Customer behavior data generated by a customer for at least one equity commodity is obtained.
In one embodiment, the customer is only concerned with the equity merchandise, i.e., only the customers who are behaving towards the equity merchandise, and the customers who are behaving towards other merchandise may not be monitored. In another embodiment, all customers are monitored and from all the activities of each customer, the generated activity data for the equity commodity is collected.
In one embodiment, the equity merchandise is a special merchandise, such as merchandise with offers, merchandise sold at a limited time, etc., relative to the normal merchandise. For easy understanding, for example, for financial enterprises such as banks and insurance, a loan commodity and an insurance commodity which are paid out at a time limit cannot be purchased any more when the term is exceeded. And the fund commodity is supported by group purchase, splice purchase and the like which are pushed out by financial enterprises such as banks, insurance and the like.
When browsing, clicking and ordering equity commodity through software, website or public number, the customer monitors each action of the customer, and then customer behavior data can be generated. In an embodiment, the customer behavior data at least includes an ordering behavior of the equity commodity, and information such as whether a coupon is used, whether a full decrease is formed, whether the equity commodity is purchased, and whether the purchase quantity of the equity commodity is equal to or smaller than a predetermined value when the equity commodity is purchased by the customer can be monitored through the ordering behavior. Therefore, whether the clients buying equity goods or generating the client behavior data belong to the abnormal client group can be judged by utilizing the client behavior data. Wherein, the abnormal guest group refers to clients who use illegal means to obtain a large number of coupons or utilize the privilege vulnerability of the equity commodity, so that profit of the equity commodity is damaged.
Wherein, each customer corresponds to a customer behavior data, and a customer behavior data corresponds to a plurality of equity commodities. For example, if a client orders 10 equity commodities, the client behavior data of the client includes 10 equity commodities, and each equity commodity corresponds to one equity commodity.
The method for acquiring the customer behavior data is not particularly limited in this embodiment, and in order to facilitate understanding, in an embodiment, the customer behavior data is acquired in real time. For example, when a client A of a banking enterprise browses loan goods, browsing behavior data of the client A is generated, the client A clicks one loan goods later and enters a detail page of the loan goods, namely clicking behavior data of the client A is generated, and all behavior data of the client A are stored in an associated mode, namely, the client behavior data of the client A updated in real time is obtained.
In another embodiment, the customer behavior data is retrieved from storage space. For example, after a new loan product is offered, the bank sets the new loan product as a equity commodity, and sells 1 ten thousand copies in a limited amount. The behavioral data generated by each customer for the new loan product, i.e., customer behavioral data, is then stored continually. Every 10 hours, the customer behavior data stored before is called from the storage space, or every 1000 copies are sold, the customer behavior data stored before is called from the storage space, so as to obtain the customer behavior data.
102. And evaluating the equity commodity according to the client behavior data to judge whether the client behavior data is illegal or not, and generating an evaluation result.
Whether the client behavior data violates rules or not refers to whether the client violates rules or not, namely, the operation mode in the abnormal client group is judged to be illegal, so that the method is favorable for finding out the illegal client, managing and controlling the illegal client, and reducing the cost loss of the equity commodity. Specifically, for example, in one embodiment, the bank pushes out a equity commodity: and (3) loan A, namely, reducing the corresponding price through the clicking amount of friends, and if the total number of clicking links of friends is greater than 100, reducing the price of loan A by 100 yuan. The abnormal group may constitute a temporary team clicking on the links sent to each other so that the bank does not have new users to see loan a. At this time, the client behavior data can be evaluated, if the client behavior data of a plurality of clients are displayed and the clicked link is always a client group, the client behavior data can be judged to be illegal, so that the client corresponding to the client behavior data is judged to be the illegal client, and a corresponding evaluation result is generated.
The specific evaluation process and the condition for judging the violation of the customer behavior data are not limited in this embodiment, and it is only required to judge whether the customer corresponding to the customer behavior data belongs to an abnormal customer group through evaluation.
In one embodiment, the evaluation result is used to represent whether the customer behavior data is illegal; in another embodiment, the evaluation result is used to reflect the violation condition of the customer behavior data, and the violation process reflected by the proportion customer behavior data, the information of the violating customer contained in the customer behavior data, and the like, which is not limited specifically. The aim is to determine the corresponding control strategy according to the evaluation result. For easy understanding, for example, for financial enterprises such as banks and insurance, if the evaluation result is used for reflecting whether the customer behavior data is illegal, if the evaluation result is that the behavior is illegal, a management and control policy for sealing the corresponding customer account number can be determined, or a management and control policy for prohibiting the corresponding customer account number from purchasing equity commodities can be determined.
103. And determining a management and control strategy according to the evaluation result.
In an embodiment, the management and control policies are preset and stored in the storage space, each management and control policy corresponds to a policy identifier, and the evaluation result contains the policy identifier. After the evaluation result is obtained, searching the strategy identification which is the same as the strategy identification contained in the evaluation result in the storage space, and then calling the corresponding management and control strategy. In another embodiment, the policing policy is generated temporarily. For example, the neural network model is trained in advance, so that the neural network model can export the control strategy according to the evaluation result. The neural network model may be a management and control strategy that is most suitable for evaluating results and is called from a plurality of preset management and control strategies; the neural network model can also be used for carrying out text analysis according to the evaluation result to obtain corresponding strategy response, namely the neural network model is a model with text processing and response functions.
104. And managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
And after the control strategy is determined, controlling according to the control strategy. The management and control can be performed on a customer account of a customer, for example, the account used by the customer is subjected to number sealing, the intelligent equipment used by the customer is limited to be subjected to ordering, the account used by the customer is forbidden to trigger preferential and the like; the control may also be performed on the equity commodity, for example, putting the equity commodity down, adjusting the price of the equity commodity, reducing the number of the equity commodity sold, etc., which is not limited in this embodiment.
Through the steps, when a customer browses, clicks and purchases equity commodities, the customer behavior data can be generated, and the operation of the customer on each equity commodity can be known by acquiring the customer behavior data, so that the selling condition of each equity commodity can be monitored. And evaluating the equity commodity according to the client behavior data to obtain information such as the selling quantity and the selling efficiency of the equity commodity, so as to judge whether the client behavior data has illegal behaviors and generate a corresponding evaluation result. Finally, determining a management and control strategy according to the evaluation result, and managing and controlling clients and/or equity commodities, so that abnormal client groups can not purchase equity commodities or reduce sales volume of equity commodities, and benefits such as coupons are prevented from being excessively used by clients; the management and control process does not need manual screening of management and control personnel, automatic management and control is achieved, management and control efficiency is improved, labor cost and time cost are reduced, human errors are reduced, and management and control accuracy and management and control quality are improved.
In another implementation manner of the embodiment of the present application, the evaluating the equity commodity according to the customer behavior data to determine whether the customer behavior data is illegal, and generating an evaluation result includes:
201. and evaluating the number of the orders of the clients for the rights and interests commodities according to the client behavior data of one client, and generating the evaluation result.
In one embodiment, individual customers are evaluated individually in evaluating equity merchandise. For example, in one embodiment, an insurance enterprise pushes out equity goods: and vehicle risk A. According to the client behavior data of each client, the situation that a single client purchases the car insurance A is counted, and if a certain client purchases a plurality of car insurance A in a short time, the client behavior data is judged to be illegal, and an illegal evaluation result is generated.
202. And evaluating the ordering behaviors of the clients according to the client behavior data of the clients aiming at one right commodity, and generating the evaluation result.
In one embodiment, when evaluating the equity merchandise, customer behavior data of a plurality of customers are put together to be compared with each other for evaluation. For example, in one embodiment, an insurance enterprise pushes out equity goods: and (5) life insurance B. The equity merchandise group purchase can be discounted. At this time, according to the customer behavior data of a plurality of customers, the purchasing situation of the personal insurance B is counted, if the same or several customers appear in a plurality of group-buying customer groups, it can be determined that the corresponding customer behavior data is illegal, and there may be a bill or off-line transaction behavior, so as to generate an illegal evaluation result.
It should be noted that, in one embodiment, the step 201 and the step 202 are and/or are related, that is, in one embodiment, both the step 201 and the step 202 are performed; in another embodiment, only step 201 or only step 202 is performed, and this embodiment is not particularly limited.
Through the steps, the rights commodity is evaluated, the evaluation can be performed according to single customer behavior data, the evaluation can be performed according to a plurality of customer behavior data, and the final evaluation result can be obtained by fusing each evaluation result after the evaluation is performed in two modes. The multiple evaluation modes are beneficial to improving the probability and accuracy of finding abnormal guest groups, so that a more applicable control strategy is obtained, the control efficiency is improved, and the operation cost is reduced.
In another implementation manner of the embodiment of the present application, the evaluating, for one of the equity commodities, the ordering behaviors of the plurality of clients according to the client behavior data of the plurality of clients, and generating the evaluation result includes:
301. judging whether the quantity of the client behavior data for generating the ordering behavior for one equity commodity is larger than a preset purchase quantity threshold or not in a preset time window.
The time window is set according to specific situations, and this embodiment is not limited specifically. For example, in one embodiment, the time window is 20 minutes, and in another embodiment, the time window is 60 minutes.
And judging whether a large number of clients generate client behavior data comprising ordering behaviors aiming at a benefit commodity within a certain time period. Whether a large number of clients are represented by the purchase amount threshold may be 10 ten thousand or 1000, which is not particularly limited in this embodiment. The method aims at reflecting that a certain equity commodity is gushed into a large number of purchases in a short time through a set time window and a purchase amount threshold, so that clients in an abnormal guest group can be easily evaluated.
To facilitate understanding, for example, in one embodiment, a banking enterprise pushes out equity goods: loan X. After the customer behavior data is obtained, it is detected that the loan X is 3 tens of thousands of times in 10 minutes. At this point, it is determined that there are multiple customers who complete the ordering of loan X during the time window. Thereby performing step 302.
If yes, go to step 302, otherwise, go to step 303.
302. And generating the evaluation result which corresponds to the rights commodity and is abnormal.
Because the evaluation is carried out on a single equity commodity, when a large number of purchases are made in a short time of a certain equity commodity, an evaluation result for the equity commodity is generated, and the evaluation result represents that the equity commodity is abnormal.
303. Step 301 is skipped to determine the next equity commodity.
If one equity commodity is within the time window period, the ordering of the equity commodity is completed without the customer behavior data of a plurality of customers, and then the next equity commodity is judged.
For example, in one embodiment, a banking enterprise pushes out equity goods: loan B, loan M, and loan N. After the judgment of step 301 is performed for the loan B, if the judgment result is no, the judgment of step 301 is performed for the loan M; if the determination result is yes, step 302 is executed, if the determination result is no, step 301 is executed for loan N, and so on, until the ownership interest commodity is traversed.
Through the steps, the method detects the behavior data of a plurality of clients by setting the time window, judges the ordering condition of a certain equity commodity, has simple logic, is easy to change the setting conditions of the time window and the like, is beneficial to timely and accurately generating the evaluation result and timely finding out the abnormal guest group.
In another implementation of the embodiment of the present application, before the obtaining the customer behavior data generated by the customer for the at least one equity commodity, the method further includes:
and at least at the node of the issuing of the equity commodity, embedding the point in advance.
The buried point is also called buried point analysis, and is a data acquisition method, which refers to a related technology and implementation process of capturing, processing and transmitting user behaviors or events on an operation node by adding a program code for data acquisition to a functional program code on the operation node where data needs to be acquired.
Through the steps, the client behavior data is captured by embedding points at the nodes of the equity commodity, so that the method is convenient and quick, and is beneficial to reducing the data acquisition and capture cost and improving the timeliness of capturing the client behavior data.
In another implementation manner of the embodiment of the present application, the obtaining the client behavior data generated by the client for at least one equity commodity includes:
401. and responding to the node trigger signal of the buried point, and acquiring feedback data.
402. And determining each feedback data corresponding to the same customer as the customer behavior data.
In an embodiment, when a customer operates a node of the equity commodity, the node trigger signal is triggered, so that data is captured, then the captured data is transmitted in a feedback data form, and then the captured data is judged to be customer behavior data, so that the customer behavior data can be obtained and updated in time, the selling condition of the equity commodity can be effectively monitored, and benefit damage to the equity commodity caused by an abnormal customer group is reduced.
When clicking is performed on the ordering node of the same equity commodity by the same customer, the node triggering signals are triggered twice, so that two feedback data are obtained, and the customer behavior data of the customer comprise two ordering behavior data of the same equity commodity.
Through the content, the client behavior data is acquired by utilizing the buried points preset in advance, so that the real-time performance and accuracy of the client behavior data acquisition are improved, redundant data are not easy to appear in the client behavior data, and the accuracy of the evaluation result is improved.
In another implementation of the embodiment of the present application, the customer behavior data includes location data, client IP data, equity commodity purchase data, and historical behavior data.
In one embodiment, the positioning data is obtained through LBS positioning means, specifically, LBS (Location Based Services, location based service) positioning is to obtain the current location of the positioning device by using various positioning technologies, and provide information resources and basic services to the positioning device through the mobile internet. The client IP refers to the IP of intelligent equipment used by a client; the equity commodity purchase data includes at least one of a purchase time of equity commodity, a purchase price of equity commodity, a purchased total number of each equity commodity, and a purchased total number of equity commodity.
The historical behavior data is data of a commodity purchased before the customer, and it should be noted that in an embodiment, the historical behavior data includes not only data related to the commodity purchased before the customer but also data related to the commodity purchased before the customer. For example, in an application scenario, the historical behavior data in the customer behavior data is information of all goods purchased by the customer a on loan software issued by a bank. Historical behavior data may be retrieved from memory space.
The determining a management and control strategy according to the evaluation result comprises the following steps:
501. And determining the control strategy for limiting the client behavior by using at least one of the positioning data, the client IP data and the historical behavior data according to the evaluation result.
In one embodiment, when the evaluation result is illegal, the client behavior is limited by using the positioning data, the client IP data and/or the historical behavior data. Specifically, the purchasing behavior of the client may be limited, or the behavior of the client logging into the website or the software may be limited, which is not particularly limited in this embodiment.
For easy understanding, for example, for the fund software issued by a bank, when the evaluation result determines that the client a belongs to an abnormal client group, the geographic position of the client a is known by using the positioning data, the position of the client a is verified by using the client IP data, and after the determination, a management and control policy for sealing the account number of the client a is generated.
For another example, for the fund software issued by the bank, when the evaluation result determines that the client a belongs to the abnormal customer group, whether the client a is subjected to the number sealing or purchase limiting processing is determined according to the historical behavior data of the client a, and if so, a management and control policy for limiting the purchase rights and interests commodity behavior of the client a is generated.
502. And determining the control strategy for limiting the equity commodity ordering by utilizing at least the equity commodity purchasing data in the client behavior data according to the evaluation result.
In one embodiment, when the evaluation result is illegal, determining a management and control strategy according to the rights and interests commodity purchase data in the customer behavior data. For easy understanding, for example, in an application scenario, when the evaluation result determines that the client a belongs to an abnormal customer group, according to the equity commodity purchasing data of the client a, the client a never purchases the equity commodity of the bank before, and at this time, a management and control policy for limiting the client a to purchase part of equity commodity is generated; if the weight ratio of the equity commodity to the commodity purchased before the client A is higher than 50% according to the equity commodity purchase data of the client A, a management and control strategy for limiting the client A to purchase all equity commodities is generated.
It should be noted that, in one embodiment, step 501 and step 502 are and/or are related, that is, in one embodiment, both step 501 and step 502 are performed; in another embodiment, only step 501 or only step 502 is performed, and this embodiment is not particularly limited.
Through the steps, the management and control strategy is determined according to the positioning data, the client IP data, the equity commodity purchasing data, the historical behavior data and the like in the client behavior data, so that the accuracy of the management and control strategy is improved, the client or equity commodity is accurately managed and controlled by the management and control strategy with higher accuracy, and the management and control effect is improved.
In another implementation manner of the embodiment of the present application, the management and control policy includes:
and putting off the equity commodity according to the equity commodity purchase data.
In one embodiment, the management and control policy includes off-shelf equity merchandise. Wherein, the commodity can be put under the shelf part of the equity commodity, also can put under the shelf of the equity commodity. Specifically, the equity commodity under the shelf is determined by equity commodity purchase data.
In another implementation manner of the embodiment of the present application, the controlling, according to the control policy, the customer account number corresponding to the customer behavior data includes:
601. and shielding the corresponding client according to the client IP data.
In one embodiment, the management and control policy is to mask the client, so that the client corresponding to the client behavior data is masked by using the client IP data, so that the client cannot access the equity commodity purchasing page.
602. And terminating the ordering action of the equity commodity according to the client IP data and the equity commodity purchase data.
In one embodiment, the client IP data and the equity commodity purchase data are utilized to obtain equity commodities that the corresponding client is buying and has purchased, thereby terminating the client from ordering the equity commodities that are buying and have purchased for the intelligent device using the IP address as the client IP data.
It should be noted that, in an embodiment, the step 601 and the step 602 are and/or are related, that is, in an embodiment, both the step 601 and the step 602 are performed; in another embodiment, only the step 601 or only the step 602 is performed, and this embodiment is not particularly limited.
Through the steps, the client behavior data is used for evaluation, and whether the client is an abnormal client group or not is judged. And when the client is judged to be an abnormal client group, the control strategy is determined by utilizing part of data in the client behavior data, so that the control is performed, the client behavior data is repeatedly used, and the data statistics work is reduced.
In another implementation manner of the embodiment of the present application, as shown in fig. 4, the determining a management and control policy according to the evaluation result includes:
And processing the evaluation result by using a pre-trained decision model to determine the control strategy, wherein the decision model is trained by using historical customer behavior data.
In one embodiment, a decision model is utilized to determine a policing policy. And the decision model is trained using historical customer behavior data. As shown in FIG. 4, in one embodiment, the equity commodities include video equity commodities, entertainment equity commodities, dining equity commodities, etc., and the collector collects and stores data of the behavior generated by the customer for the equity commodities to obtain historical customer behavior data. And then taking the historical customer behavior data as input of a decision model, and training the decision model. In particular, the decision model may be a language analysis model or a GPT model (natural language processing model). The training model can select a proper strategy from preset management and control strategies according to the client behavior data, such as verification strategies, and the client is required to provide real personal information, conduct real-name authentication and the like; and further such as limited purchase policies, off shelf policies, etc.
Through the above, the decision model is trained by using the truly generated customer behavior data, so that the training efficiency and training effect of the decision model are improved, and the quality of the management and control strategy output by the decision model in the using process is improved.
In summary, the equity commodity is evaluated by using the client behavior data, and whether the equity commodity is in a normal selling state is judged. And evaluating the client behavior data of one client and a plurality of clients respectively to generate an evaluation result. The method is beneficial to improving the probability of finding abnormal guest groups. In addition, by means of setting time windows, buried points and the like, the evaluation difficulty and the customer behavior data acquisition difficulty are reduced, and the overall management and control efficiency is improved.
The embodiment of the application also discloses a commodity management and control device, as shown in fig. 5, which comprises:
the acquisition module 1 is used for acquiring client behavior data generated by a client aiming at least one equity commodity;
the evaluation module 2 is used for evaluating the equity commodity according to the customer behavior data so as to judge whether the customer behavior data is illegal or not and generate an evaluation result;
the control module 3 is used for determining a control strategy according to the evaluation result;
and the execution module 4 is used for managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
Through the above, when the client browses, clicks and purchases the equity commodity, the acquisition module 1 can acquire the client behavior data, and the evaluation module 2 can learn the operation of the client on each equity commodity through the client behavior data, so that the selling condition of each equity commodity can be monitored. And evaluating the equity commodity according to the client behavior data, and obtaining information such as the selling quantity and the selling efficiency of the equity commodity, so as to judge whether the client behavior data has illegal behaviors and generate a corresponding evaluation result. Finally, the management and control module 3 determines a management and control strategy according to the evaluation result, and manages and controls clients and/or equity commodities, so that abnormal client groups can not purchase equity commodities or reduce sales volume of equity commodities, and benefits such as coupons are prevented from being excessively used by clients; the management and control process does not need manual screening of management and control personnel, automatic management and control is achieved, management and control efficiency is improved, labor cost and time cost are reduced, human errors are reduced, and management and control accuracy and management and control quality are improved.
In another embodiment of the present application, the evaluation module 2 includes a monomer unit for evaluating, with respect to the customer behavior data of a customer, the number of orders of the customer for each of the equity commodities, and generating the evaluation result;
and/or a multi-body unit, which is used for evaluating the ordering behaviors of the clients according to the client behavior data of the clients for one benefit commodity and generating the evaluation result.
In another embodiment of the present application, the evaluation module 2 includes a determining unit, configured to determine whether the number of customer behavior data for generating the ordering behavior for one of the equity commodities is greater than a preset purchase amount threshold within a preset time window;
if yes, generating the evaluation result which corresponds to the right commodity and is abnormal.
In another embodiment of the present application, the apparatus further includes a point burying module for burying a point in advance at least at a node of the issuing of the equity commodity;
the acquiring module 1 includes an acquiring unit, configured to acquire feedback data in response to a node trigger signal of a buried point, and determine the feedback data as the customer behavior data.
In another embodiment of the present application, the customer behavior data includes location data, client IP data, equity commodity purchase data, and historical behavior data;
the management and control module 3 includes a behavior limiting unit, configured to determine, according to the evaluation result, the management and control policy for limiting the behavior of the client by using at least one of the positioning data, the client IP data, and the historical behavior data;
and/or a commodity limiting unit, configured to determine, according to the evaluation result, the management and control policy for limiting the issuing of the equity commodity by using at least one of the customer behavior data and the equity commodity purchase data.
In another embodiment of the present application, the execution module 4 includes a shielding unit, configured to shield a corresponding client according to the client IP data;
and/or the ordering unit is used for terminating the ordering action of the equity commodity according to the client IP data and the equity commodity purchase data.
In another embodiment of the present application, the control module 3 includes a model unit for processing the evaluation result by using a pre-trained decision model, and determining the control strategy, where the decision model is trained by using historical customer behavior data.
Through the content, the equity commodity is evaluated by using the client behavior data, and whether the equity commodity is in a normal selling state is judged. And evaluating the client behavior data of one client and a plurality of clients respectively to generate an evaluation result. The method is beneficial to improving the probability of finding abnormal guest groups. In addition, by means of setting time windows, buried points and the like, the evaluation difficulty and the customer behavior data acquisition difficulty are reduced, and the overall management and control efficiency is improved.
The specific limitation of the commodity control device can be referred to the limitation of the commodity control method hereinabove, and the detailed description thereof is omitted. The modules in the commodity control device may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes non-volatile and/or volatile storage media and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is for communicating with an external client via a network connection. The computer program, when executed by a processor, performs functions or steps on the server side of a commodity control method.
In one embodiment, a computer device is provided, which may be a client, the internal structure of which may be as shown in FIG. 7. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is for communicating with an external server via a network connection. The computer program, when executed by a processor, performs the functions or steps of a commodity control method client side.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
acquiring client behavior data generated by a client aiming at least one equity commodity;
Evaluating the equity commodity according to the client behavior data to judge whether the client behavior data is illegal or not, and generating an evaluation result;
determining a management and control strategy according to the evaluation result;
and managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
When the processor executes the computer program, the operation of the client for each equity commodity can be known by acquiring the client behavior data, so that the selling condition of each equity commodity can be monitored. And evaluating the equity commodity according to the client behavior data to obtain information such as the selling quantity and the selling efficiency of the equity commodity, so as to judge whether the client behavior data has illegal behaviors and generate a corresponding evaluation result. Finally, determining a management and control strategy according to the evaluation result, and managing and controlling clients and/or equity commodities, so that abnormal client groups can not purchase equity commodities or reduce sales volume of equity commodities, and benefits such as coupons are prevented from being excessively used by clients; the management and control process does not need manual screening of management and control personnel, automatic management and control is achieved, management and control efficiency is improved, labor cost and time cost are reduced, human errors are reduced, and management and control accuracy and management and control quality are improved.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring client behavior data generated by a client aiming at least one equity commodity;
evaluating the equity commodity according to the client behavior data to judge whether the client behavior data is illegal or not, and generating an evaluation result;
determining a management and control strategy according to the evaluation result;
and managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
The stored computer program, when executed, can learn the operation of the client for each equity commodity by acquiring the client behavior data, thereby being capable of monitoring the selling condition of each equity commodity. And evaluating the equity commodity according to the client behavior data to obtain information such as the selling quantity and the selling efficiency of the equity commodity, so as to judge whether the client behavior data has illegal behaviors and generate a corresponding evaluation result. Finally, determining a management and control strategy according to the evaluation result, and managing and controlling clients and/or equity commodities, so that abnormal client groups can not purchase equity commodities or reduce sales volume of equity commodities, and benefits such as coupons are prevented from being excessively used by clients; the management and control process does not need manual screening of management and control personnel, automatic management and control is achieved, management and control efficiency is improved, labor cost and time cost are reduced, human errors are reduced, and management and control accuracy and management and control quality are improved.
It should be noted that, the functions or steps implemented by the computer readable storage medium or the computer device may correspond to the relevant descriptions of the server side and the client side in the foregoing method embodiments, and are not described herein for avoiding repetition.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (10)
1. A method of article management comprising:
acquiring client behavior data generated by a client aiming at least one equity commodity;
evaluating the equity commodity according to the client behavior data to judge whether the client behavior data is illegal or not, and generating an evaluation result;
Determining a management and control strategy according to the evaluation result;
and managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
2. The method of claim 1, wherein evaluating the equity commodity according to the customer behavior data to determine whether the customer behavior data is illegal and generating an evaluation result comprises:
evaluating the number of orders of the client for each equity commodity according to the client behavior data of the client, and generating an evaluation result;
and/or evaluating the ordering behaviors of the clients according to the client behavior data of the clients aiming at one benefit commodity, and generating the evaluation result.
3. The article management and control method according to claim 2, wherein the evaluating the ordering behavior of the plurality of customers based on the customer behavior data of the plurality of customers for one of the equity articles, and generating the evaluation result, comprises:
judging whether the quantity of the client behavior data for generating the ordering behavior aiming at one equity commodity is larger than a preset purchase quantity threshold value or not in a preset time window;
If yes, generating the evaluation result which corresponds to the right commodity and is abnormal.
4. A method of article management as recited in any of claims 1-3, wherein prior to said obtaining customer behavior data generated by a customer for at least one equity article, the method further comprises:
pre-burying points at least at the node of the issuing of the equity commodity;
the obtaining the customer behavior data generated by the customer for at least one equity commodity comprises:
responding to node trigger signals of the buried points to acquire feedback data;
and determining each feedback data corresponding to the same customer as the customer behavior data.
5. A method of article management as recited in any of claims 1-3, wherein said customer behavior data includes location data, client IP data, equity article purchase data, and historical behavior data;
the determining a management and control strategy according to the evaluation result comprises the following steps:
determining the control strategy for limiting the client behavior by using at least one of the positioning data, the client IP data and the historical behavior data according to the evaluation result;
and/or determining the management and control strategy for limiting the issuing of the equity commodity by utilizing at least one of the customer behavior data and the equity commodity purchasing data according to the evaluation result.
6. The method of claim 5, wherein the controlling the customer account corresponding to the customer behavior data according to the control policy includes:
shielding the corresponding clients according to the client IP data;
and/or terminating the ordering action of the equity commodity according to the client IP data and the equity commodity purchase data.
7. A method of controlling commodities according to any one of claims 1 to 3, wherein said determining a control strategy based on said evaluation results comprises:
and processing the evaluation result by using a pre-trained decision model to determine the control strategy, wherein the decision model is trained by using historical customer behavior data.
8. A merchandise management device, the device comprising:
the acquisition module is used for acquiring client behavior data generated by a client aiming at least one equity commodity;
the evaluation module is used for evaluating the equity commodity according to the customer behavior data so as to judge whether the customer behavior data is illegal or not and generate an evaluation result;
the control module is used for determining a control strategy according to the evaluation result;
And the execution module is used for managing and controlling the equity commodity and/or the customer account corresponding to the customer behavior data according to the management and control strategy.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the article management method according to any one of claims 1 to 7.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of the article management method of any one of claims 1 to 7.
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| CN202310651144.2A CN116664236A (en) | 2023-06-02 | 2023-06-02 | Commodity management and control method, commodity management and control device, computer equipment and computer readable storage medium |
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