CN112437198A - Intelligent outbound data processing method, device and storage medium - Google Patents
Intelligent outbound data processing method, device and storage medium Download PDFInfo
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- CN112437198A CN112437198A CN202011249488.3A CN202011249488A CN112437198A CN 112437198 A CN112437198 A CN 112437198A CN 202011249488 A CN202011249488 A CN 202011249488A CN 112437198 A CN112437198 A CN 112437198A
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
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- H04L51/02—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
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Abstract
The invention relates to the technical field of intelligent outbound call, in particular to an intelligent outbound call data processing method, an intelligent outbound call data processing device and a storage medium. The intelligent outbound data processing method comprises the following steps: when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to a service platform; obtaining outbound data which accords with outbound data generation conditions from the business data; extracting a first preset number of outbound data before sequencing and sending the data to the intelligent outbound system; taking the sequence of the outbound data as an outbound sequence to carry out outbound; through the mode, the data generation request is triggered when the residual outbound data is close to the exhausted state, so that the cancel of the write back and the underutilization of the line are avoided, the interval time between the outbound data generation time and the outbound time is shortened, and the working efficiency of the intelligent outbound system is improved; and the outbound data is pushed to the intelligent outbound system according to the priority, so that the outbound efficiency of the intelligent outbound system is improved.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of intelligent outbound call, in particular to an intelligent outbound call data processing method, an intelligent outbound call data processing device and a storage medium.
[ background of the invention ]
When the insurance policy is close to the payment date or when the insurance policy is close to the expiration date, the user needs to be reminded to pay, and the reminding is completed by the intelligent outbound system. In the prior art, outbound data needing to be reminded by an intelligent outbound system on the next day is generally generated uniformly for the service platform one day before, the data is uniformly synchronized to the intelligent outbound system, and the intelligent outbound system calls the outbound data on the next day. When the outbound data volume is less and the performance of the intelligent outbound system is more stable, the outbound data is quickly completed by outbound, so that the intelligent outbound system cannot fully utilize the line.
[ summary of the invention ]
The invention aims to provide an intelligent outbound data processing method, an intelligent outbound data processing device and a storage medium, which aim to solve the problem of underutilized lines caused by unstable performance of an intelligent outbound system in the prior art.
The technical scheme of the invention is as follows: an intelligent outbound data processing method is provided, which comprises the following steps:
when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to a service platform;
receiving the data generation request, and acquiring outbound data meeting outbound data generation conditions from service data;
acquiring the time difference between the current time and the expected calling time of each outbound data, sequencing the outbound data according to the sequence of the time differences from large to small, extracting a first preset number of outbound data before sequencing, and sending the extracted outbound data to the intelligent outbound system;
and taking the sequence of the outbound data as an outbound sequence, and carrying out outbound call on the mobile terminal corresponding to the user number in the outbound data.
Preferably, when the remaining outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to the service platform includes:
counting the outbound number of the intelligent outbound system at a preset time interval;
calculating the average outbound rate of the last time interval according to the outbound number of the last time interval;
acquiring the ratio of the residual outbound data volume to the average outbound rate, and taking the ratio as the residual outbound time;
and judging whether the residual outbound time is less than or equal to a preset residual time threshold value, and sending a data generation request to the service platform when the judgment result is yes.
Preferably, when the remaining outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to the service platform includes:
and when the residual outbound data volume of the intelligent outbound system is less than or equal to the residual data volume threshold value, sending a data generation request to the service platform.
Preferably, the receiving the data generation request and acquiring the outbound data meeting the outbound data generation condition from the service data includes:
receiving the data generation request, acquiring a policy with the current time and distance fee due date less than or equal to a first time threshold from the service data, and taking policy information corresponding to the policy as outbound data;
calculating the probability of paying the premium on time of each policy according to the historical payment records;
and deleting the outbound data corresponding to the policy with the probability of paying the premium on time being greater than or equal to the preset probability.
Preferably, before calculating the probability of paying the premium on time of each said policy according to the historical payment record, the method further comprises:
and when the data volume of the outbound data is less than or equal to a second preset number, adjusting the first time threshold value to be a second time threshold value, re-acquiring the policy of which the current time and distance fee due date is less than or equal to the second time threshold value from the service data, and taking policy information corresponding to the policy as the outbound data, wherein the second time threshold value is greater than the first time threshold value.
Preferably, the obtaining of the time difference between the current time and the expected outgoing time of each outbound data, the sorting of the outbound data according to the sequence of the time differences from large to small, the extracting of the first preset number of outbound data before sorting, and the sending of the extracted outbound data to the intelligent outbound system includes:
generating a temporary data table according to the policy number, the user name, the user number, the fee due date, the user occupation and the area of the user in the outbound data;
obtaining expected outbound time of the outbound data, and adding the expected outbound time to the temporary data table;
calculating the time difference between the current time and the expected outbound time, and adding the time difference into the temporary data table;
sequencing the outbound data according to the sequence of the time difference from large to small to obtain a sequenced temporary data table;
determining a target calling time period of each outbound data according to occupation of a user and an area to which the user belongs, judging whether the target calling time of each outbound data is intersected with an estimated calling time period or not to obtain a first judgment result, and adding the first judgment result to the temporary data table, wherein the estimated calling time period is the first time from the current time to the current time;
and sequentially extracting the outbound data with the first preset number with the first judgment result of yes from front to back in the temporary data table, and sending the extracted outbound data to the intelligent outbound system.
Preferably, the step of using the sequence of the outbound data as an outbound sequence, after the outbound of the mobile terminal corresponding to the user number in the outbound data, further comprises:
when the calling-out result is calling failure, updating the calling failure times of the corresponding calling-out data;
when the call failure times are less than a first preset time, moving the outbound data to the last bit of the outbound sequence;
when the call failure times are larger than or equal to a second preset time, generating feedback records related to the outbound data, summarizing the feedback records and sending the summarized feedback records to the service platform;
and the second preset times is greater than the first preset times.
The other technical scheme of the invention is as follows: an intelligent outbound data processing apparatus is provided, comprising:
the data generation triggering module is used for sending a data generation request to the service platform when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition;
the data acquisition module is used for receiving the data generation request and acquiring outbound data meeting outbound data generation conditions from the service data;
the data screening module is used for acquiring the time difference between the current time and the expected calling time of each outbound data, sequencing the outbound data according to the sequence of the time differences from large to small, extracting a first preset number of outbound data before sequencing, and sending the extracted outbound data to the intelligent outbound system;
and the outbound module is used for taking the sequence of the outbound data as an outbound sequence and carrying out outbound on the mobile terminal corresponding to the user number in the outbound data.
The other technical scheme of the invention is as follows: an intelligent outbound data processing apparatus is provided, the apparatus comprising a processor, and a memory coupled to the processor, the memory storing program instructions; the processor is used for executing the program instructions stored in the memory to execute the intelligent outbound data processing method.
The other technical scheme of the invention is as follows: there is provided a storage medium storing program instructions which, when executed by a processor, implement the intelligent outbound data processing method described above.
The invention has the beneficial effects that: according to the intelligent outbound data processing method, the intelligent outbound data processing device and the storage medium, the data generation request is triggered when the remaining outbound data is near to the exhausted state, so that the problem that write back is cancelled when the intelligent outbound system cannot complete due to overstock of the outbound data in the intelligent outbound system is avoided, meanwhile, the problem that the intelligent outbound system does not fully utilize a line when the amount of the outbound data is too small is avoided, and the working efficiency of the intelligent outbound system is improved; by means of generating outbound data in real time, the interval time between outbound data generation time and calling time can be shortened, the probability that the policy is changed in the interval time is reduced, the problem that the service platform needs to send the policy state to the intelligent outbound system again due to the change of the policy state is avoided, the intelligent outbound system does not need to record fields such as the policy state, and the outbound efficiency of the intelligent outbound system is improved; after the service platform acquires the outbound data, the outbound data is pushed to the intelligent outbound system according to the priority, and the intelligent outbound system can outbound in sequence, so that the outbound efficiency of the intelligent outbound system is improved.
[ description of the drawings ]
FIG. 1 is a flow chart of an intelligent outbound data processing method according to a first embodiment of the present invention;
FIG. 2 is a flow chart of an intelligent outbound data processing method according to a second embodiment of the present invention;
FIG. 3 is a flowchart of an intelligent outbound data processing method according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an intelligent outbound data processing apparatus according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an intelligent outbound data processing apparatus according to a fifth embodiment of the present invention;
fig. 6 is a schematic structural diagram of a storage medium according to a sixth embodiment of the present invention.
[ detailed description ] embodiments
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first", "second" and "third" in the present invention are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise. All directional indicators (such as up, down, left, right, front, and rear … …) in the embodiments of the present invention are only used to explain the relative positional relationship between the components, the movement, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indicator is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Fig. 1 is a flowchart illustrating an intelligent outbound data processing method according to a first embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 1 if the results are substantially the same. As shown in fig. 1, the intelligent outbound data processing method includes the steps of:
and S101, when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to the service platform.
In this embodiment, the outbound data is derived from the service data, such as the data of the policy to be received and the data of the reusable policy, and when the policy approaches the payment due date, or the policy exceeds the grace period and is not paid yet, or the policy approaches the final deadline of the reusable policy, the intelligent outbound system reminds the customer to pay the fee in time. The intelligent outbound system is an AI outbound robot, carries out intelligent calling according to the user number in the outbound data, and reminds the client by voice after connection. In an alternative embodiment, each outbound call data corresponds to a policy, and all or part of the policy information for the policy is recorded.
In this embodiment, service data such as policy data to be received and reusable policy data are stored on the service platform, the service platform provides a reach interface for the intelligent outbound call system, the intelligent outbound call system sends a data generation request to the service platform by using the reach interface, and the service platform sends outbound call data to the intelligent outbound call system through the reach interface.
In step S101, a remaining data amount threshold may be set, and when the remaining outbound data amount of the intelligent outbound system side is less than or equal to the remaining data threshold, the outbound data generation triggering condition is satisfied. Assuming that 1 million effective connections are established, the average outgoing time 20S and the average outgoing time 30S may cause different outgoing amounts of the AI per hour, and then, in step S101, the outgoing rate of the intelligent outgoing system may be monitored according to the estimated outgoing completion time of the remaining outgoing data amount as a trigger condition, the average outgoing rate of the intelligent outgoing system within a preset time range is obtained, the remaining outgoing time is calculated according to the ratio of the remaining outgoing data to the average outgoing rate, and when the remaining outgoing time is less than or equal to a preset remaining time threshold, the outgoing data generation trigger condition is satisfied.
And S102, receiving the data generation request, and acquiring the outbound data meeting the outbound data generation condition from the service data.
In step S102, the service platform receives the data generation request, and obtains outbound data meeting the conditions from the service data stored in the service platform, where the outbound data obtained in this step is preliminary outbound data and is not outbound data fed back to the intelligent outbound system, and the subsequent steps are further performed with screening.
In an alternative embodiment, the outbound data generating condition comprises: (i) the current time is less than or equal to the first time threshold from the fee due day, or (ii) the current time exceeds the fee due day. And (3) judging whether each policy meets the generation condition of the outbound data or not, acquiring the policy meeting (i) or (ii), and taking policy information of the policy as the outbound data.
Furthermore, the service platform can calculate the on-time payment premium rate of the policy according to the past period payment record aiming at each policy in the outbound data, and delete the policy of which the on-time payment premium rate is greater than the preset threshold value from the outbound data so as to improve the outbound efficiency.
S103, acquiring the time difference between the current time and the expected calling time of each outbound data, sequencing the outbound data according to the sequence of the time differences from large to small, extracting the outbound data of a first preset number before sequencing, and sending the extracted outbound data to the intelligent outbound system.
In this embodiment, not all outbound data meeting the outbound data generation rule are sent to the intelligent outbound system, and in order to ensure that the policy with high priority is called in time, the outbound data obtained in step S102 is screened and then sent to the intelligent outbound system for outbound. In this embodiment, the current time may be a current date, the expected expiration time is an expected expiration date, and then the time difference is calculated by day, and the time difference is a date difference, for example, the current time is 25 days in 9 months in 2020, the expected expiration time is 30 days in 9 months in 2020, and the time difference is a date difference between 25 days in 9 months in 2020 and 30 days in 9 months in 2020, which is-5 days; the current time is 9, 25 and 2020, the expected exhalation time is 9, 20 and 2020, and the time difference is the date difference between 9, 25 and 9, 20 and 2020, namely +5 days; that is, the earlier the expected expiration time of the outbound data, the greater the time difference, a positive integer of the time difference indicating that the current time has exceeded the expected expiration time, and a negative integer of the time difference indicating that the current time has not exceeded the expected expiration time. For a plurality of outbound data with the same expected outbound time, the time difference is also the same, when the outbound data are sorted according to the sequence from large to small of the time difference, the outbound data are sorted in parallel, for example, outbound data 1 is arranged in a first sequence (sequence number 1), outbound data 2, outbound data 3 and outbound data 4 are arranged in a second sequence (sequence numbers are 2,3 and 4 respectively), and outbound data 2, outbound data 3 and outbound data 4 are parallel outbound data. If the parallel outbound data exist in the outbound data sequence, acquiring the policy effective time of the outbound data, and adjusting the outbound data sequence of the parallel outbound data according to the order of the policy effective time from morning to evening. And when parallel outbound data also exist in the outbound data sequence adjusted according to the policy validation time, directly determining the final sequence from small to large according to the sequence number.
In this embodiment, the expected outbound time is used as a screening condition of the priority, the expected outbound time is an optimal outbound time, and the expected outbound time may be N days before the payment due date, where N is a positive integer greater than or equal to 0. In specific practice, due to unstable outbound performance, many policy policies do not complete outbound operation at the expected outbound time, and this embodiment preferentially calls outbound data with an expected outbound time earlier.
And S104, taking the sequence of the outbound data as an outbound sequence, and carrying out outbound call on the mobile terminal corresponding to the user number in the outbound data.
In step S104, the intelligent outbound system receives the outbound data sent by the service platform, and since the outbound data is arranged according to priority, the intelligent outbound system directly calls in sequence.
In the embodiment, the data generation request is triggered when the remaining outbound data is close to the exhausted state, so that the problem that the write back of the outbound data is cancelled when the intelligent outbound system cannot complete due to overstock of the intelligent outbound system is avoided, and meanwhile, the problem that the intelligent outbound system does not fully utilize the line when the outbound data amount is too small is avoided, and the working efficiency of the intelligent outbound system is improved; by means of generating outbound data in real time, the interval time between outbound data generation time and calling time can be shortened, the probability that the policy is changed in the interval time is reduced, the problem that the service platform needs to send the policy state to the intelligent outbound system again due to the change of the policy state is avoided, the intelligent outbound system does not need to record fields such as the policy state, and the outbound efficiency of the intelligent outbound system is improved; after the service platform acquires the outbound data, the outbound data is pushed to the intelligent outbound system according to the priority, and the intelligent outbound system can outbound in sequence, so that the outbound efficiency of the intelligent outbound system is improved.
In a first optional embodiment, step S101 further comprises:
and S1011, counting the outbound number of the intelligent outbound system at preset time intervals.
And S1012, calculating the average outbound rate of the previous time interval according to the outbound number of the previous time interval.
And S1013, acquiring the ratio of the residual outbound data volume to the average outbound rate, and taking the ratio as the residual outbound time.
And S1014, judging whether the residual outbound time is less than or equal to a preset residual time threshold, and sending a data generation request to the service platform when the judgment result is yes.
In step S1011, the time interval may be 1 hour, 30 minutes, or 10 minutes; in step S1012, the previous time interval is the statistical period closest to the current time; in step S1013, the time required for calling out the remaining outbound data volume is estimated according to the average outbound rate of the previous time interval, where the time is the remaining outbound time; in step S1014, when the remaining outbound time is less than or equal to the preset remaining time threshold, a data generation request is sent to the service platform.
In a second alternative embodiment, step S102 further comprises:
and S1021, the service platform receives the data generation request, acquires the policy with the current time and distance fee due date less than or equal to the first time threshold from the service data, and takes policy information corresponding to the policy as outbound data.
And S1022, calculating the probability of paying the premium on time according to the historical payment records.
And S1023, deleting the outbound data corresponding to the policy with the probability of paying the premium on time being greater than or equal to the preset probability.
In step S1022, the historical payment record may represent the payment behavior of the user, for example, the user pays before receiving the reminder of the charge-promoting message, the user pays immediately after receiving the call of the charge-promoting call of the intelligent outbound system, the user pays in the grace period, and the user pays in the revisable period.
Further, the first time threshold may be dynamically changed, and the data amount of the obtained outbound data may be adjusted by adjusting the first time threshold, where the data amount of the first time threshold of 5 days may be greater than the data amount of the first time threshold of 3 days. For example, when a quarter month ends, the number of outbound data is large, if the outbound data is acquired according to the first time threshold which is generally set, the data size is too large, the calculation amount of the service platform is increased, and at this time, the first time threshold may be appropriately decreased (for example, the first time threshold is 1 day). For another example, when the amount of the outbound data acquired according to the first time threshold set in a general case is small, the intelligent outbound system cannot be fully utilized, the first time threshold may be appropriately increased (for example, the first time threshold is 10 days), and a part of the policy which is relatively late from the payment day of the fee is outbound in advance.
Then, after step S1021 and before step S1022, the method further includes:
s1021', when the data volume of the outbound data is smaller than or equal to a second preset number, adjusting the first time threshold to be a second time threshold, re-acquiring the policy of which the current time and distance fee due date is smaller than or equal to the second time threshold from the service data, and taking policy information corresponding to the policy as the outbound data, wherein the second time threshold is larger than the first time threshold.
In step S1021', the second time threshold may be determined as the first time threshold +1 day, and the policy that the current time and distance fee due payment day is less than or equal to the second time threshold may be obtained again from the service data; if the data volume is less than or equal to a second preset quantity, determining a second time threshold as the first time threshold +2 days, and acquiring the insurance policy of which the current time and distance fee due payment day is less than or equal to the second time threshold from the service data again; until the amount of data is greater than a second preset amount.
Fig. 2 is a flowchart illustrating an intelligent outbound data processing method according to a second embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 2 if the results are substantially the same. As shown in fig. 2, the intelligent outbound data processing method includes the steps of:
s201, when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to the service platform.
And S202, receiving the data generation request, and acquiring outbound data meeting outbound data generation conditions from the service data.
Step S201 and step S202 correspond to step S101 and step S102, respectively, of the first embodiment, and refer to the description of the first embodiment specifically.
S203, generating a temporary data table according to the insurance policy number, the user name, the user number, the fee due date, the user occupation and the area to which the user belongs in the outbound data.
In step S203, the service platform temporarily stores the obtained outbound data, for example, in the form of a data table, the fields of the data table include a policy number, a user name, a user number, a fee due date, and the like, and the temporary data table in this step is an initial temporary data table.
S204, obtaining the expected outbound time of the outbound data, and adding the expected outbound time into the temporary data table.
The desired outbound time in this step is specifically described in step S103 in the first embodiment.
S205, calculating the time difference between the current time and the expected outbound time, and adding the time difference into the temporary data table.
S206, sorting the outbound data according to the sequence of the time difference from large to small to obtain a sorted temporary data table.
S207, determining a target calling time period of each outbound data according to occupation of a user and an area to which the user belongs, judging whether the target calling time of each outbound data is intersected with an estimated calling time period to obtain a first judgment result, and adding the first judgment result to the temporary data table, wherein the estimated calling time period is the first time from the current time to the current time.
In this step, the area to which the user belongs is an area attribute of a city in which the user is located, for example, south or north. Northern cities have different working time in winter and summer, and northern cities have different working time in south. The user occupation includes doctors, teachers, lawyers, programmers, free occupations and the like, for example, the user occupation is doctors, doctors generally have outpatients in the morning, operations are generally scheduled in the afternoon, calls can be made in the noon and afternoon only in the noon and afternoon, and the target calling time is 11:30 in the morning to 12:30 in the afternoon. Due to the fact that the occupation of the user is different from the area where the user belongs, the target calling time periods corresponding to the user are different.
And S208, sequentially extracting the outbound data with the first preset number from front to back in the temporary data table, wherein the first judgment result is that the outbound data is the first preset number, and sending the extracted outbound data to the intelligent outbound system.
In the step, the outbound data with intersection of the target calling time and the estimated calling time period is extracted and sent to the intelligent outbound system, so that the outbound call completing rate is improved, and the customer complaint rate is reduced.
And S209, taking the sequence of the outbound data as an outbound sequence, and carrying out outbound to the mobile terminal corresponding to the user number in the outbound data.
Step S209 corresponds to step S104 of the first embodiment, and refer to the description of the first embodiment specifically.
In this embodiment, since a real-time data generation manner is adopted, the outbound data sent to the intelligent outbound system will complete the call in the next time period, except for the expected outbound time, it is further considered whether the estimated call time period is matched with the target call time period of the user, if the outbound is performed in an unmatched time period, the user experience is reduced, the outbound efficiency of the intelligent outbound system is not improved, and the service platform directly delays the data temporarily when acquiring the outbound data.
Fig. 3 is a flowchart illustrating an intelligent outbound data processing method according to a third embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 3 if the results are substantially the same. As shown in fig. 3, the intelligent outbound data processing method includes the steps of:
s301, when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to the service platform.
S302, receiving the data generation request, and acquiring outbound data meeting outbound data generation conditions from the service data.
And S303, acquiring the time difference between the current time and the expected calling time of each outbound data, sequencing the outbound data according to the sequence of the time differences from large to small, extracting the outbound data of a first preset number before sequencing, and sending the extracted outbound data to the intelligent outbound system.
S304, taking the sequence of the outbound data as an outbound sequence, and carrying out outbound call on the mobile terminal corresponding to the user number in the outbound data.
Steps S301 to S304 of the present embodiment correspond to steps S101 to S104 of the first embodiment, respectively, and reference may be made to the description of the first embodiment.
S305, when the calling out result is that the calling is failed, updating the calling failure times of the corresponding calling out data.
In this step, when the outbound result is a call failure, the number of call failures of the corresponding outbound data is added by 1.
S306, when the call failure times are less than a first preset time, the outbound data are moved to the last bit of the outbound sequence.
The first preset number of times in step S306 is a preset number of times for determining whether the user missed calls, and the first preset number of times may be set to 2 times or 3 times, and when the number of times of call failure is less than the first preset number of times, it indicates that the user missed calls more likely, and places the corresponding outbound data in the last digit of the call sequence of this round, and continues the call.
S307, when the call failure times are larger than or equal to a second preset time, generating feedback records related to the outbound data, summarizing the feedback records, and sending the summarized feedback records to the service platform, wherein the second preset time is larger than the first preset time.
The second preset number in step S307 is a preset number used for determining whether the user masks the number of the intelligent outbound system, and when the number of call failure is greater than the second preset number, it indicates that the possibility that the user masks the number of the intelligent outbound system is high, at this time, continuing to call increases the customer complaint rate and the outbound cost, and the outbound data whose number of call failure is greater than the second preset number is fed back to the service platform, and the service platform receives the feedback and then does not add the policy corresponding to the customer to the outbound data.
Further, when the call fails and the call failure times are greater than the first preset times and less than the second preset times, the call is not performed in the current round.
Further, after step S307, the following steps are also included:
s308, uploading the temporary data table and the feedback record to a block chain, so that the block chain encrypts and stores the temporary data table and the feedback record.
In step S308, corresponding digest information is obtained based on the temporary data table and the feedback record, specifically, the digest information is obtained by performing hash processing on the temporary data table and the feedback record, for example, using sha256S algorithm. Uploading summary information to the blockchain can ensure the safety and the fair transparency of the user. The user equipment may download the summary information from the blockchain to verify whether the temporary data table and the feedback record are tampered. The blockchain referred to in this example is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm, and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
Fig. 4 is a schematic structural diagram of an intelligent outbound data processing apparatus according to a fourth embodiment of the present invention. As shown in fig. 4, the intelligent outbound data processing apparatus 40 includes: the system comprises a data generation triggering module 41, a data acquisition module 42, a data screening module 43 and an outbound module 44, wherein the data generation triggering module 41 is used for sending a data generation request to a service platform when the remaining outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition; a data obtaining module 42, configured to receive the data generation request, and obtain outbound data meeting an outbound data generation condition from the service data; the data screening module 43 is configured to acquire a time difference between a current time and an expected outgoing time of each outbound data, sort the outbound data according to a descending order of the time difference, extract a first preset number of outbound data before sorting, and send the extracted outbound data to the intelligent outbound system; and the outbound module 44 is used for taking the sequence of the outbound data as an outbound sequence and carrying out outbound on the mobile terminal corresponding to the user number in the outbound data.
Further, the data generation triggering module 41 is specifically configured to count the outbound number of the intelligent outbound system at preset time intervals; calculating the average outbound rate of the last time interval according to the outbound number of the last time interval; acquiring the ratio of the residual outbound data volume to the average outbound rate, and taking the ratio as the residual outbound time; and judging whether the residual outbound time is less than or equal to a preset residual time threshold value, and sending a data generation request to the service platform when the judgment result is yes.
Further, the data obtaining module 42 is specifically configured to receive the data generation request, obtain, from the service data, a policy that a current time and a due date of the fee are less than or equal to a first time threshold, and use policy information corresponding to the policy as outbound data; calculating the probability of paying the premium on time of each policy according to the historical payment records; and deleting the outbound data corresponding to the policy with the probability of paying the premium on time being greater than or equal to the preset probability. Furthermore, the data obtaining module 42 is further configured to, when the data volume of the outbound data is less than or equal to a second preset number, adjust the first time threshold to a second time threshold, re-obtain the policy that the current time-distance fee due to payment day is less than or equal to the second time threshold from the service data, and use policy information corresponding to the policy as the outbound data, where the second time threshold is greater than the first time threshold.
Further, the data filtering module 43 is specifically configured to generate a temporary data table according to the policy number, the user name, the user number, the fee due date, the user occupation, and the area to which the user belongs in the outbound data; obtaining expected outbound time of the outbound data, and adding the expected outbound time to the temporary data table; calculating the time difference between the current time and the expected outbound time, and adding the time difference into the temporary data table; sequencing the outbound data according to the sequence of the time difference from large to small to obtain a sequenced temporary data table; determining a target calling time period of each outbound data according to occupation of a user and an area to which the user belongs, judging whether the target calling time of each outbound data is intersected with an estimated calling time period or not to obtain a first judgment result, and adding the first judgment result to the temporary data table, wherein the estimated calling time period is the first time from the current time to the current time; and sequentially extracting the outbound data with the first preset number with the first judgment result of yes from front to back in the temporary data table, and sending the extracted outbound data to the intelligent outbound system.
Further, the outbound module 44 is further configured to update the call failure times of the corresponding outbound data when the outbound result is a call failure; when the call failure times are less than a first preset time, moving the outbound data to the last bit of the outbound sequence; when the call failure times are larger than or equal to a second preset time, generating feedback records related to the outbound data, summarizing the feedback records and sending the summarized feedback records to the service platform; and the second preset times is greater than the first preset times.
Fig. 5 is a schematic structural diagram of an intelligent outbound data processing apparatus according to a fifth embodiment of the present invention. As shown in fig. 5, the intelligent outbound data processing apparatus 50 includes a processor 51 and a memory 52 coupled to the processor 51.
The memory 52 stores program instructions for implementing the intelligent outbound data processing method of any of the embodiments described above.
The processor 51 may also be referred to as a CPU (Central Processing Unit). The processor 51 may be an integrated circuit chip having signal processing capabilities. The processor 51 may also be a 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, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a storage medium according to a sixth embodiment of the invention. The storage medium of the embodiment of the present invention stores program instructions 61 capable of implementing all the above-mentioned intelligent outbound data processing methods, where the program instructions 61 may be stored in the storage medium in the form of a software product, and include several instructions to enable a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the methods according to the embodiments of the present invention. The aforementioned storage device includes: various media capable of storing program codes, such as a usb disk, a mobile hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or terminal devices, such as a computer, a server, a mobile phone, and a tablet.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or 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.
In addition, functional units in the embodiments of the present invention 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 above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
While the foregoing is directed to embodiments of the present invention, it will be understood by those skilled in the art that various changes may be made without departing from the spirit and scope of the invention.
Claims (10)
1. An intelligent outbound data processing method, comprising:
when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition, sending a data generation request to a service platform;
receiving the data generation request, and acquiring outbound data meeting outbound data generation conditions from service data;
acquiring the time difference between the current time and the expected calling time of each outbound data, sequencing the outbound data according to the sequence of the time differences from large to small, extracting a first preset number of outbound data before sequencing, and sending the extracted outbound data to the intelligent outbound system;
and taking the sequence of the outbound data as an outbound sequence, and carrying out outbound call on the mobile terminal corresponding to the user number in the outbound data.
2. The intelligent outbound data processing method according to claim 1, wherein when the remaining outbound data volume of the intelligent outbound system satisfies the outbound data generation triggering condition, sending a data generation request to the service platform, comprises:
counting the outbound number of the intelligent outbound system at a preset time interval;
calculating the average outbound rate of the last time interval according to the outbound number of the last time interval;
acquiring the ratio of the residual outbound data volume to the average outbound rate, and taking the ratio as the residual outbound time;
and judging whether the residual outbound time is less than or equal to a preset residual time threshold value, and sending a data generation request to the service platform when the judgment result is yes.
3. The intelligent outbound data processing method according to claim 1, wherein when the remaining outbound data volume of the intelligent outbound system satisfies the outbound data generation triggering condition, sending a data generation request to the service platform, comprises:
and when the residual outbound data volume of the intelligent outbound system is less than or equal to the residual data volume threshold value, sending a data generation request to the service platform.
4. The intelligent outbound data processing method according to claim 1, wherein said receiving the data generation request and obtaining outbound data meeting outbound data generation conditions from the service data comprises:
receiving the data generation request, acquiring a policy with the current time and distance fee due date less than or equal to a first time threshold from the service data, and taking policy information corresponding to the policy as outbound data;
calculating the probability of paying the premium on time of each policy according to the historical payment records;
and deleting the outbound data corresponding to the policy with the probability of paying the premium on time being greater than or equal to the preset probability.
5. The intelligent outbound data processing method of claim 4 wherein prior to calculating the probability of paying the premium on time for each said policy based on historical payment records, further comprising:
and when the data volume of the outbound data is less than or equal to a second preset number, adjusting the first time threshold value to be a second time threshold value, re-acquiring the policy of which the current time and distance fee due date is less than or equal to the second time threshold value from the service data, and taking policy information corresponding to the policy as the outbound data, wherein the second time threshold value is greater than the first time threshold value.
6. The intelligent outbound data processing method according to claim 4, wherein the obtaining of the time difference between the current time and the expected outbound time of each outbound data, the sorting of the outbound data according to the descending order of the time difference, the extracting of the first preset number of outbound data before sorting, and the sending of the extracted outbound data to the intelligent outbound system comprises:
generating a temporary data table according to the policy number, the user name, the user number, the fee due date, the user occupation and the area of the user in the outbound data;
obtaining expected outbound time of the outbound data, and adding the expected outbound time to the temporary data table;
calculating the time difference between the current time and the expected outbound time, and adding the time difference into the temporary data table;
sequencing the outbound data according to the sequence of the time difference from large to small to obtain a sequenced temporary data table;
determining a target calling time period of each outbound data according to occupation of a user and an area to which the user belongs, judging whether the target calling time of each outbound data is intersected with an estimated calling time period or not to obtain a first judgment result, and adding the first judgment result to the temporary data table, wherein the estimated calling time period is the first time from the current time to the current time;
and sequentially extracting the outbound data with the first preset number with the first judgment result of yes from front to back in the temporary data table, and sending the extracted outbound data to the intelligent outbound system.
7. The intelligent outbound data processing method according to claim 1, wherein said sorting of said outbound data as an outbound sequence, after outbound to a mobile terminal corresponding to a user number in said outbound data, further comprising:
when the calling-out result is calling failure, updating the calling failure times of the corresponding calling-out data;
when the call failure times are less than a first preset time, moving the outbound data to the last bit of the outbound sequence;
when the call failure times are larger than or equal to a second preset time, generating feedback records related to the outbound data, summarizing the feedback records and sending the summarized feedback records to the service platform;
and the second preset times is greater than the first preset times.
8. An intelligent outbound data processing apparatus, comprising:
the data generation triggering module is used for sending a data generation request to the service platform when the residual outbound data volume of the intelligent outbound system meets the outbound data generation triggering condition;
the data acquisition module is used for receiving the data generation request and acquiring outbound data meeting outbound data generation conditions from the service data;
the data screening module is used for acquiring the time difference between the current time and the expected calling time of each outbound data, sequencing the outbound data according to the sequence of the time differences from large to small, extracting a first preset number of outbound data before sequencing, and sending the extracted outbound data to the intelligent outbound system;
and the outbound module is used for taking the sequence of the outbound data as an outbound sequence and carrying out outbound on the mobile terminal corresponding to the user number in the outbound data.
9. An intelligent outbound data processing apparatus, comprising a processor, and a memory coupled to the processor, the memory storing program instructions; the processor is configured to execute the program instructions stored by the memory to perform the intelligent outbound data processing method of any of claims 1 to 7.
10. A storage medium storing program instructions which, when executed by a processor, implement the intelligent outbound data processing method of any one of claims 1 to 7.
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