CN114143402A - AI outbound method, device, computer equipment and storage medium - Google Patents
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Abstract
The application is applicable to the technical field of artificial intelligence, and provides an AI outbound method, an AI outbound device, a computer device and a storage medium, wherein the method comprises the following steps: integrating to obtain a data record corresponding to each user based on user data from different sources, matching the user outbound number in the outbound list with the user outbound number in the data record, and determining a target data record where the target number is located when the target number is matched; acquiring task priority of an outbound task corresponding to an outbound list, and determining a first upper limit threshold of outbound times based on the task priority; acquiring the outbound frequency of a target user corresponding to the target data record, and determining a second upper limit threshold of the outbound frequency based on the outbound frequency; and triggering the outbound operation of the target number when the outbound statistical frequency corresponding to the target user is determined to be in the set range based on the first upper limit threshold and the second upper limit threshold. According to the scheme, the service experience is improved while the reaching rate of the client can be guaranteed.
Description
Technical Field
The application belongs to the technical field of artificial intelligence, and particularly relates to an AI outbound method, an AI outbound device, computer equipment and a storage medium.
Background
AI (Artificial Intelligence) services are widely used in various service industries due to their characteristics of high efficiency, low cost, etc. Especially in the application field of AI outbound service, the services of service promotion, customer extension, customer maintenance and the like can be realized through the AI outbound of the telephone, thereby greatly reducing the number of customer service personnel and lowering the labor cost.
In the existing AI outbound management and control, an outbound management and control system directly and sequentially triggers outbound operation according to an outbound list directly based on the current service requirement, but causes frequent AI outbound behaviors of different subordinate companies or service departments to the same client in a short time. The same customer is contacted by different departments or different subordinate subsidiaries of the same company at the same time, and even if the service projects and processes of the customer in different departments or different subsidiaries are different, the customer can be harassed, the service experience is greatly discounted, and the complaint risk can be improved.
Disclosure of Invention
The embodiment of the application provides an AI outbound method, an AI outbound device, computer equipment and a storage medium, which are used for solving the problems that in the existing AI outbound management and control, outbound operation is directly triggered by an outbound management and control system according to an outbound list based on the current service requirement, harassment can be caused to a client, and service experience is reduced.
A first aspect of an embodiment of the present application provides an AI outbound method, including:
integrating to obtain data records corresponding to each user based on user data from different sources, wherein each data record comprises at least one user outbound number;
matching the user outbound numbers in the outbound list with the user outbound numbers in the data records one by one, and determining the target data record where the target number is located when the target number is matched;
acquiring the task priority of an outbound task corresponding to the outbound list, and determining a first upper limit threshold of outbound times based on the task priority;
acquiring the outbound frequency of a target user corresponding to the target data record, and determining a second upper limit threshold of the outbound frequency based on the outbound frequency;
and triggering the outbound operation of the target number when the outbound statistic times corresponding to the target user is determined to be in a set range based on the first upper threshold and the second upper threshold.
Optionally, the outbound statistics number includes an outbound cumulative number and a number of outbound times reached by the trigger in the outbound cumulative number, and the triggering the outbound operation of the target number when the outbound statistics number corresponding to the target user is determined to be within a set range based on the first upper threshold and the second upper threshold includes:
acquiring the cumulative outbound times of the target user and the number of touch outbound times in the time interval of the current moment;
and triggering the outbound operation of the target number when the cumulative number of outbound calls is judged to be smaller than the first upper threshold and the number of outbound touch times is judged to be smaller than the second upper threshold.
Optionally, after the obtaining of the cumulative number of outbound calls of the target user and the number of outbound calls touched within the time interval of the current time, the method further includes:
and when the cumulative number of the outbound calls is judged to be smaller than the first upper threshold and the number of the outbound touch times is judged to be larger than the second upper threshold, taking out the target number from an outbound waiting queue corresponding to the outbound list and reinserting the target number to a target position in the outbound waiting queue.
Optionally, after the triggering the outbound operation of the target number when the number of outbound statistics corresponding to the target user is determined to be within a set range based on the first upper threshold and the second upper threshold, the method further includes:
carrying out outbound monitoring on the triggered outbound operation;
and if the outbound operation is successfully monitored, updating the outbound accumulated times of the target user corresponding to the target number and the number of the contact outbound times of the target user in the time interval of the current moment.
Optionally, after the outbound monitoring is performed on the triggered outbound operation, the method further includes:
if the outbound operation fails, acquiring a return parameter of the outbound operation which fails to operate;
identifying an outbound abnormal type corresponding to the outbound operation based on the return parameters, and counting the failure times of the outbound operation of the target number under the outbound abnormal type;
and when the failure times exceed a failure threshold value, carrying out failure marking on the target number.
Optionally, the obtaining of the outbound frequency of the target user corresponding to the target data record and determining a second upper threshold of the outbound frequency based on the outbound frequency include:
acquiring the planned completion time of the outbound task;
dividing the plan completion time into a target number of time intervals, and setting the outbound frequency of a target user corresponding to the target data record in different time intervals;
and determining the second upper threshold of the outbound frequency of the target user in different time intervals based on the outbound frequency.
Optionally, the integrating, based on the user data from different sources, to obtain the data record corresponding to each user includes:
extracting user identity information and user contact information in the user data;
and associating the user identity information and the user contact information of the same user to the same data item to obtain a data record corresponding to each user.
A second aspect of the embodiments of the present application provides an AI outbound device, including:
the data integration module is used for integrating to obtain data records corresponding to each user based on user data from different sources, wherein each data record comprises at least one user outbound number;
the matching module is used for matching the user outbound numbers in the outbound list with the user outbound numbers in the data records one by one, and determining the target data record where the target number is located when the target number is matched;
the first acquisition module is used for acquiring the task priority of the outbound task corresponding to the outbound list and determining a first upper limit threshold of the outbound times based on the task priority;
the second acquisition module is used for acquiring the outbound frequency of the target user corresponding to the target data record and determining a second upper limit threshold of the outbound frequency based on the outbound frequency;
and the outbound module is used for triggering the outbound operation of the target number when the outbound statistical frequency corresponding to the target user is determined to be in a set range based on the first upper limit threshold and the second upper limit threshold.
Optionally, the outbound statistics number includes an outbound cumulative number and a reach outbound number in the outbound cumulative number, and the outbound module is specifically configured to:
acquiring the cumulative outbound times of the target user and the number of touch outbound times in the time interval of the current moment;
and triggering the outbound operation of the target number when the cumulative number of outbound calls is judged to be smaller than the first upper threshold and the number of outbound touch times is judged to be smaller than the second upper threshold.
Optionally, the outbound module is further specifically configured to:
and when the cumulative number of the outbound calls is judged to be smaller than the first upper threshold and the number of the outbound touch times is judged to be larger than the second upper threshold, taking out the target number from an outbound waiting queue corresponding to the outbound list and reinserting the target number to a target position in the outbound waiting queue.
Optionally, the second obtaining module is specifically configured to:
acquiring the planned completion time of the outbound task;
dividing the plan completion time into a target number of time intervals, and setting the outbound frequency of a target user corresponding to the target data record in different time intervals;
and determining the second upper threshold of the outbound frequency of the target user in different time intervals based on the outbound frequency.
Optionally, the apparatus further comprises: an outbound monitoring module to:
carrying out outbound monitoring on the triggered outbound operation;
and if the outbound operation is successfully monitored, updating the outbound accumulated times of the target user corresponding to the target number and the number of the contact outbound times of the target user in the time interval of the current moment.
Optionally, the outbound monitoring module is further configured to:
if the outbound operation fails, acquiring a return parameter of the outbound operation which fails to operate;
identifying an outbound abnormal type corresponding to the outbound operation based on the return parameters, and counting the failure times of the outbound operation of the target number under the outbound abnormal type;
and when the failure times exceed a failure threshold value, carrying out failure marking on the target number.
Optionally, the data integration module is specifically configured to:
extracting user identity information and user contact information in the user data;
and associating the user identity information and the user contact information of the same user to the same data item to obtain a data record corresponding to each user.
A third aspect of embodiments of the present application provides a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method according to the first aspect when executing the computer program.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, in which a computer program is stored, which, when executed by a processor, performs the steps of the method according to the first aspect.
A fifth aspect of the present application provides a computer program product, which, when run on a terminal, causes the terminal to perform the steps of the method of the first aspect described above.
As can be seen from the above, in the embodiment of the present application, according to user data from different sources, data records corresponding to each user and including at least one outbound number are integrated and formed, a limit threshold of the outbound frequency is determined based on the priority of the outbound task and the outbound frequency of the target user, and whether the outbound operation is triggered or not is determined by combining the cumulative number of outbound calls of the target user and the number of outbound frequency triggered within the time interval of the current time, so as to implement frequency management and control of the AI outbound service, improve global unified management and control of the AI outbound frequency of different channels, and improve service experience while ensuring the customer reach rate.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a first flowchart of an AI outbound method according to an embodiment of the present application;
fig. 2 is a flowchart ii of an AI outbound method according to an embodiment of the present application;
fig. 3 is a structural diagram of an AI outbound device according to an embodiment of the present application;
fig. 4 is a block diagram of a computer device according to an embodiment of the present disclosure.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
In particular implementations, the terminals described in embodiments of the present application include, but are not limited to, other portable devices such as mobile phones, laptop computers, or tablet computers having touch sensitive surfaces (e.g., touch screen displays and/or touch pads). It should also be understood that in some embodiments, the device is not a portable communication device, but is a desktop computer having a touch-sensitive surface (e.g., a touch screen display and/or touchpad).
In the discussion that follows, a terminal that includes a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and/or joystick.
The terminal supports various applications, such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disc burning application, a spreadsheet application, a gaming application, a telephone application, a video conferencing application, an email application, an instant messaging application, an exercise support application, a photo management application, a digital camera application, a web browsing application, a digital music player application, and/or a digital video player application.
Various applications that may be executed on the terminal may use at least one common physical user interface device, such as a touch-sensitive surface. One or more functions of the touch-sensitive surface and corresponding information displayed on the terminal can be adjusted and/or changed between applications and/or within respective applications. In this way, a common physical architecture (e.g., touch-sensitive surface) of the terminal can support various applications with user interfaces that are intuitive and transparent to the user.
It should be understood that, the sequence numbers of the steps in this embodiment do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic of the process, and should not constitute any limitation to the implementation process of the embodiment of the present application.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Referring to fig. 1, fig. 1 is a first flowchart of an AI outbound method according to an embodiment of the present application. As shown in fig. 1, an AI outbound method includes the steps of:
Wherein, each data record comprises at least one user calling number.
When integrating user data from different sources, user identity information and user contact information in the user data can be extracted, and user contact information corresponding to the same user identity information is integrated into the same data content, so that a data record corresponding to each user is obtained.
That is, based on the user data from different sources, the data records corresponding to each user are obtained by integration, including: and extracting user identity information and user contact information in the user data, and associating the user identity information and the user contact information of the same user to the same data item to obtain a data record corresponding to each user.
The user identity information is, for example, a user identity card number, and is used for identifying that different data records correspond to different users; in the user data from different sources, the same user corresponds to different user contact modes to a great extent, and the user contact mode information is, for example, a user fixed telephone, a mobile phone number and the like, and forms at least one outbound number corresponding to the user.
The data structure in the integrated data record may include a subscriber identification code and at least one subscriber outbound number of the current subscriber. When the outbound operation is triggered based on the user outbound number contained in the data record in the follow-up process, the outbound times of AI outbound operation triggered by at least one user outbound number in the data record can be accumulated to obtain the information of the outbound accumulated times, the outbound touch times and the like. The number of outbound touches is the number of successful outbound after the AI outbound operation is executed based on at least one contact way of the user. After the data are obtained, the data can be associated with the data records of the corresponding users so as to control the outbound operation times of the same user in real time and provide reference for whether to continue to allow the outbound of the same user subsequently.
The user data of different sources is, for example, user purchase data, user subscription intention data, user transaction data, etc. of different sources.
The different sources of user data are, for example, user data originating from different subsidiaries, user data originating from different business departments.
Specifically, in different application fields, the system has massive service and sales data, and sources of the massive service and sales data are different. May originate from different business departments, different subordinate subsidiaries, or from different distribution channels. For example, in the application field of insurance, the mass service and sale data channels are sourced from different dangerous species sales departments or different subordinate insurance companies, and for example, the service and sale data channels are divided into new channels, agent channels, mobile channels and the like.
In the step, data in different departments and different subordinate subsidiaries are integrated by providing a platform type management mode, and a data record corresponding to each user is created by extracting relevant information of the customer to form usable list information.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
And 102, matching the user outbound numbers in the outbound list with the user outbound numbers in the data records one by one, and determining the target data record where the target number is located when the target number is matched.
The target data record is one or more data records determined from the integrated data records based on the user outbound number matching operation, and specifically, the target data record includes a target number consistent with any user outbound number in the outbound list.
Each outbound list corresponds to an outbound task, and the number which needs to be outbound currently is recorded in the outbound list. And calling the numbers out to realize the task requirement corresponding to the current calling-out list.
The retrieval of the outbound list may be submitted by a source entity corresponding to a different source of user data. For example, the calling-out list submitted by the subordinate subsidiary company or subordinate department, so as to implement unified management and control on the calling-out operation of the user through the platform.
In this step, when the user outbound numbers in the outbound list are matched with the user outbound numbers in the data record one by one, the specific matching may be:
based on the data source information of different user outbound numbers in the data records, screening out the data records matched with the source information of the current outbound list according to the source information of the outbound list, realizing the preliminary screening of the data records, and then matching the user outbound numbers in the outbound list with the user outbound numbers in the data records one by one on the basis of the screened data records.
The data records matched with the source information of the current outbound list comprise data records consistent with the source information of the current outbound list and data records of the same type as the source information of the current outbound list. The source information of the current outbound list is similar to that of the current outbound list, which may be obtained by classifying different data sources in advance, and determining whether the source information of the current outbound list is similar to that of the current outbound list according to the classified classes. For example, the user's outbound number and the current outbound list contained in the data record are both from the insurance agency. Or, for example, if the outbound number of the user included in the data record is from the production insurance agency sales department and the outbound list is from the life insurance agency sales department, the source information of the two is considered as the same source information.
In the process, because the data records come from different channels, and at least one telephone number of the same user is summarized in one data record, the telephone numbers are further matched on the basis of the preliminarily screened data records, so that the target data record containing the current outbound number is accurately matched from the mass data records, the data matching time is shortened, and the processing efficiency is improved.
And 103, acquiring the task priority of the outbound task corresponding to the outbound list, and determining a first upper limit threshold of the outbound times based on the task priority.
The outbound list corresponds to different outbound task requirements. For example, the following are: sales, service, return visit, etc. And different tasks can be further divided into task demands at different stages, for example, the sales task includes: outbound call to get a guest, appointment, renewal, etc.
And determining the task priority of the outbound task corresponding to the outbound list according to the task purpose. The determination of the priority may be made in terms of how much benefit is generated. For example, a task may be determined to be higher in order to remind a renewal, a fee payment, etc., and a lower in order if the task is to remind a user to participate in a lottery, a weather forecast trip reminder, etc.
And setting the outbound frequency threshold value for judging whether the outbound is currently called or not according to different priorities. Therefore, when the task purposes of the outbound tasks corresponding to the outbound list are different, the outbound frequency threshold value can float, so that important outbound calls can be successfully dialed out to a certain extent.
And 104, acquiring the outbound frequency of the target user corresponding to the target data record, and determining a second upper limit threshold of the outbound frequency based on the outbound frequency.
The determination of the upper threshold of the outbound times may be to obtain the outbound frequency of the user corresponding to the target data record in the same day or one hour in the past, and determine the outbound times corresponding to the outbound frequency that can be accepted in the current certain time length or time interval as the second upper threshold.
Specifically, in an embodiment, the obtaining the outbound frequency of the target user corresponding to the target data record, and determining the second upper threshold of the outbound frequency based on the outbound frequency includes:
acquiring the planned completion time of the outbound task; dividing the plan completion time into a target number of time intervals, and setting the outbound frequency of a target user corresponding to the target data record in different time intervals; and determining a second upper threshold of the outbound frequency of the target user in different time intervals based on the outbound frequency.
In practical application, when the outbound rule is set in the time dimension, the specific outbound frequency is, for example, the weekly frequency, the daily frequency, and the hourly frequency.
The second upper limit threshold is an upper limit value of the short-time outbound frequency determined based on the outbound frequency. In the subsequent processing step, the second upper threshold is used for specifically limiting the outbound frequency in a certain time interval so as to avoid the user trouble caused by the fact that the outbound operation is excessively triggered in a short time.
And 105, triggering the outbound operation of the target number when the outbound statistic times corresponding to the target user is determined to be in the set range based on the first upper threshold and the second upper threshold.
Before the outbound operation of the outbound number is triggered, it needs to be determined that the cumulative number of outbound times of the target user does not exceed the upper limit of the outbound times, and the outbound times in the current time interval does not exceed the upper limit.
Specifically, the outbound operation is performed by a robot or manually followed when the outbound operation is triggered.
According to the process, the controllability of the frequency of the AI service is improved through the AI service outbound scheme of frequency control, the frequency of the contact clients from different channels can be controlled in a better frequency mode, and an AI service scene more in line with the actual situation is provided.
The external call counting times comprise external call accumulated times and touch external call times in the external call accumulated times. Specifically, the triggering of the outbound operation of the target number when determining that the outbound statistic times corresponding to the target user is within the set range based on the first upper threshold and the second upper threshold includes:
acquiring the cumulative number of outbound calls of a target user and the number of touch outbound calls within a time interval of the current moment; and when the cumulative number of the outbound calls is judged to be smaller than a first upper limit threshold and the number of the outbound call touch times is judged to be smaller than a second upper limit threshold, the outbound operation of the target number is triggered.
The cumulative number of outgoing calls is the cumulative number of outgoing calls made to all telephone numbers contained in the target data record.
The calculation of the number of touch out calls of the target user corresponding to the target data record in the time interval of the current time is the accumulation of the number of successful out calls of all the user out call numbers contained in the target data record in the time interval of the current time.
When the target user is called out, the used telephone number may be an unused null number, or the call-out is not successful due to communication failure and the like. Unsuccessful calling operation is not counted in, so as to ensure the effectiveness of calling frequency control.
Further, after obtaining the cumulative number of outbound calls of the target user and the number of outbound calls touched within the time interval of the current time, the method further comprises:
and when the cumulative number of outbound calls is judged to be less than a first upper threshold and the number of outbound touch times is judged to be greater than a second upper threshold, taking out the target number from the outbound waiting queue corresponding to the outbound list and reinserting the target number to the target position in the outbound waiting queue.
The target position of the outbound waiting queue is, for example, the tail position of the queue, or a calculated queue position in the queue.
The process realizes that the outbound numbers waiting for outbound, the total number of outbound times does not exceed the limit, but the outbound frequency in a short time is too high, queue up again for waiting to ensure that the corresponding outbound operation is executed at a proper time point, improves the service experience while ensuring the reaching rate of customers, and further reduces the incidence rate of complaints.
In the embodiment of the application, according to user data of different sources, data records corresponding to each user and containing at least one outbound number are integrated and formed, the limiting threshold of the outbound frequency is determined based on the priority of the outbound task and the outbound frequency of the target user, the outbound accumulated frequency of the target user and the contact outbound frequency in the time interval of the current moment are combined, whether outbound operation is triggered is judged, frequency management and control of AI outbound service are achieved, global unified management and control of AI outbound frequency of different channels are improved, and service experience is improved while the contact rate of the client is guaranteed.
The embodiment of the application also provides different implementation modes of the AI outbound method.
Referring to fig. 2, fig. 2 is a second flowchart of an AI outbound method according to the embodiment of the present application. As shown in fig. 2, an AI outbound method includes the steps of:
Wherein, each data record comprises at least one user calling number.
The implementation process of this step is the same as that of step 101 in the foregoing embodiment, and is not described here again.
The implementation process of this step is the same as that of step 102 in the foregoing embodiment, and is not described here again.
The implementation process of this step is the same as the implementation process of step 103 in the foregoing embodiment, and is not described here again.
And 204, acquiring the outbound frequency of the target user corresponding to the target data record, and determining a second upper limit threshold of the outbound frequency based on the outbound frequency.
The implementation process of this step is the same as that of step 104 in the foregoing embodiment, and is not described here again.
The implementation process of this step is the same as that of step 105 in the foregoing embodiment, and is not described here again.
And step 206, carrying out outbound monitoring on the triggered outbound operation.
And step 207, if the outbound operation is successfully monitored, updating the outbound accumulated times of the target user corresponding to the target number and the touch outbound times of the target user in the time interval of the current moment.
In the step, the accumulated times of the external call reaching the touch are accumulated, the real-time updating of the accumulated times of the external call is realized, and meanwhile, the counting of the triggering time of the external call operation is convenient for implementing the counting of the external call frequency.
Wherein, after the outbound monitoring is carried out to the triggered outbound operation, the method further comprises the following steps:
if the outbound operation fails, acquiring a return parameter of the outbound operation with failed operation; based on the return parameters, identifying the outbound abnormal type corresponding to the outbound operation, and counting the failure times of the outbound operation of the target number under the outbound abnormal type; and when the failure times exceed the failure threshold value, carrying out failure marking on the target number.
The abnormal type of the outbound call is, for example, a call dialing prompt that the call is not in a service area, a call dialing prompt that the call is stopped, a call is hung up within 1 second after the call is made, an outbound call failure caused by a system power failure, and the like.
And aiming at the outbound operation with the result of being judged as failure, judging the outbound abnormal type of the target number, counting the failure times of the target number in different outbound abnormal types, and determining whether the target number is still the effective outbound number according to the failure times.
Specifically, when the total number of times of the outbound operation of the target number under different types of outbound exception exceeds a threshold, the number is considered not to be effectively associated with the target user, and then the number is subjected to invalidation labeling to indicate that the number is an invalidated number or an invalid number.
Or, when the total number of times of the outbound operation of the target number in one or a plurality of outbound exception types exceeds a threshold value, the number is considered not to be effectively connected to the target user, and then the number is subjected to failure marking to indicate that the number is a failure number or an invalid number.
The user contact modes capable of being touched can be effectively screened out, resource waste is reduced, and labor cost is saved while the touch rate is guaranteed.
In the embodiment of the application, according to user data of different sources, data records corresponding to each user and containing at least one outbound number are integrated and formed, the limiting threshold of the outbound frequency is determined based on the priority of the outbound task and the outbound frequency of the target user, the outbound accumulated frequency of the target user and the number of outbound frequency touched within the time interval of the current moment are combined, whether outbound operation is triggered is judged, frequency control of AI outbound service is achieved, outbound monitoring is conducted on the outbound operation, data updating and screening of invalid outbound numbers are achieved, overall unified control over AI outbound frequency of different channels is improved, and service experience is improved while the customer reach rate is guaranteed.
Referring to fig. 3, fig. 3 is a structural diagram of an AI outbound device provided in the embodiment of the present application, and only a part related to the embodiment of the present application is shown for convenience of description.
The AI outbound device 300 includes:
a data integration module 301, configured to integrate, based on user data from different sources, data records corresponding to each user, where each data record includes at least one user outbound number;
a matching module 302, configured to match the outbound numbers of the users in the outbound list with the outbound numbers of the users in the data records one by one, and determine a target data record where the target number is located when the target number is matched;
a first obtaining module 303, configured to obtain a task priority of an outbound task corresponding to the outbound list, and determine a first upper threshold of outbound times based on the task priority;
a second obtaining module 304, configured to obtain the outbound frequency of the target user corresponding to the target data record, and determine a second upper threshold of the outbound frequency based on the outbound frequency;
and the outbound module 305 is configured to trigger an outbound operation of the target number when it is determined that the outbound statistical frequency corresponding to the target user is within a set range based on the first upper threshold and the second upper threshold.
The outbound counting number includes an outbound cumulative number and a reach outbound number in the outbound cumulative number, and the outbound module 305 is specifically configured to:
acquiring the cumulative outbound times of the target user and the number of touch outbound times in the time interval of the current moment;
and triggering the outbound operation of the target number when the cumulative number of outbound calls is judged to be smaller than the first upper threshold and the number of outbound touch times is judged to be smaller than the second upper threshold.
The outbound module 305 is further specifically configured to:
and when the cumulative number of the outbound calls is judged to be smaller than the first upper threshold and the number of the outbound touch times is judged to be larger than the second upper threshold, taking out the target number from an outbound waiting queue corresponding to the outbound list and reinserting the target number to a target position in the outbound waiting queue.
The second obtaining module 304 is specifically configured to:
acquiring the planned completion time of the outbound task;
dividing the plan completion time into a target number of time intervals, and setting the outbound frequency of a target user corresponding to the target data record in different time intervals;
and determining the second upper threshold of the outbound frequency of the target user in different time intervals based on the outbound frequency.
Wherein the apparatus further comprises:
an outbound monitoring module to:
carrying out outbound monitoring on the triggered outbound operation;
and if the outbound operation is successfully monitored, updating the outbound accumulated times of the target user corresponding to the target number and the number of the contact outbound times of the target user in the time interval of the current moment.
Wherein, the outbound monitoring module is further configured to:
if the outbound operation fails, acquiring a return parameter of the outbound operation which fails to operate;
identifying an outbound abnormal type corresponding to the outbound operation based on the return parameters, and counting the failure times of the outbound operation of the target number under the outbound abnormal type;
and when the failure times exceed a failure threshold value, carrying out failure marking on the target number.
The data integration module 301 is specifically configured to:
extracting user identity information and user contact information in the user data;
and associating the user identity information and the user contact information of the same user to the same data item to obtain a data record corresponding to each user.
The AI outbound device provided in the embodiment of the present application can implement each process of the above-mentioned AI outbound method, and can achieve the same technical effect, and is not described here again to avoid repetition.
Fig. 4 is a block diagram of a computer device according to an embodiment of the present disclosure. As shown in the figure, the computer apparatus 4 of this embodiment includes: at least one processor 40 (only one shown in fig. 4), a memory 41, and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, the steps of any of the various method embodiments described above being implemented when the computer program 42 is executed by the processor 40.
The computer device 4 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The computer device 4 may include, but is not limited to, a processor 40, a memory 41. Those skilled in the art will appreciate that fig. 4 is merely an example of a computer device 4 and is not intended to limit computer device 4 and may include more or fewer components than those shown, or some of the components may be combined, or different components, e.g., the computer device may also include input output devices, network access devices, buses, etc.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. The memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the computer device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the computer device 4. The memory 41 is used for storing the computer program and other programs and data required by the computer device. The memory 41 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The present application realizes all or part of the processes in the method of the above embodiments, and may also be implemented by a computer program product, when the computer program product runs on a terminal, the steps in the above method embodiments may be implemented when the terminal executes the computer program product.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. An AI outbound method comprising:
integrating to obtain data records corresponding to each user based on user data from different sources, wherein each data record comprises at least one user outbound number;
matching the user outbound numbers in the outbound list with the user outbound numbers in the data records one by one, and determining the target data record where the target number is located when the target number is matched;
acquiring the task priority of an outbound task corresponding to the outbound list, and determining a first upper limit threshold of outbound times based on the task priority;
acquiring the outbound frequency of a target user corresponding to the target data record, and determining a second upper limit threshold of the outbound frequency based on the outbound frequency;
and triggering the outbound operation of the target number when the outbound statistic times corresponding to the target user is determined to be in a set range based on the first upper threshold and the second upper threshold.
2. The method according to claim 1, wherein the outbound statistics number includes an outbound cumulative number and a reach outbound number among the outbound cumulative number, and the triggering the outbound operation of the target number when the outbound statistics number corresponding to the target user is determined to be within a set range based on the first upper threshold and the second upper threshold includes:
acquiring the cumulative outbound times of the target user and the number of touch outbound times in the time interval of the current moment;
and triggering the outbound operation of the target number when the cumulative number of outbound calls is judged to be smaller than the first upper threshold and the number of outbound touch times is judged to be smaller than the second upper threshold.
3. The method according to claim 2, wherein after obtaining the cumulative number of outbound calls of the target user and the number of outbound calls reached within the time interval of the current time, further comprising:
and when the cumulative number of the outbound calls is judged to be smaller than the first upper threshold and the number of the outbound touch times is judged to be larger than the second upper threshold, taking out the target number from an outbound waiting queue corresponding to the outbound list and reinserting the target number to a target position in the outbound waiting queue.
4. The method according to claim 1, wherein the obtaining of the outbound frequency of the target user corresponding to the target data record, and determining a second upper threshold of the outbound frequency based on the outbound frequency, comprises:
acquiring the planned completion time of the outbound task;
dividing the plan completion time into a target number of time intervals, and setting the outbound frequency of a target user corresponding to the target data record in different time intervals;
and determining the second upper threshold of the outbound frequency of the target user in different time intervals based on the outbound frequency.
5. The method according to claim 1, wherein after triggering the outbound operation of the target number when determining that the outbound statistic times corresponding to the target subscriber is within a set range based on the first upper threshold and the second upper threshold, the method further comprises:
carrying out outbound monitoring on the triggered outbound operation;
and if the outbound operation is successfully monitored, updating the outbound accumulated times of the target user corresponding to the target number and the number of the contact outbound times of the target user in the time interval of the current moment.
6. The method of claim 5, wherein after the outbound monitoring of the triggered outbound operation, further comprising:
if the outbound operation fails, acquiring a return parameter of the outbound operation which fails to operate;
identifying an outbound abnormal type corresponding to the outbound operation based on the return parameters, and counting the failure times of the outbound operation of the target number under the outbound abnormal type;
and when the failure times exceed a failure threshold value, carrying out failure marking on the target number.
7. The method of claim 1, wherein the integrating the data records corresponding to each user based on the user data from different sources comprises:
extracting user identity information and user contact information in the user data;
and associating the user identity information and the user contact information of the same user to the same data item to obtain a data record corresponding to each user.
8. An AI outbound device, comprising:
the data integration module is used for integrating to obtain data records corresponding to each user based on user data from different sources, wherein each data record comprises at least one user outbound number;
the matching module is used for matching the user outbound numbers in the outbound list with the user outbound numbers in the data records one by one, and determining the target data record where the target number is located when the target number is matched;
the first acquisition module is used for acquiring the task priority of the outbound task corresponding to the outbound list and determining a first upper limit threshold of the outbound times based on the task priority;
the second acquisition module is used for acquiring the outbound frequency of the target user corresponding to the target data record and determining a second upper limit threshold of the outbound frequency based on the outbound frequency;
and the outbound module is used for triggering the outbound operation of the target number when the outbound statistical frequency corresponding to the target user is determined to be in a set range based on the first upper limit threshold and the second upper limit threshold.
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 implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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