CN114817306A

CN114817306A - Data processing method, device, server and readable storage medium

Info

Publication number: CN114817306A
Application number: CN202210451222.XA
Authority: CN
Inventors: 王广川; 卿力; 吴海英; 罗仕杰; 赵飞; 蒋宁; 石硕
Original assignee: Mashang Xiaofei Finance Co Ltd
Current assignee: Mashang Xiaofei Finance Co Ltd
Priority date: 2022-04-24
Filing date: 2022-04-24
Publication date: 2022-07-29

Abstract

The application discloses a data processing method, a data processing device, a server and a readable storage medium, and belongs to the technical field of computers. The data processing method comprises the following steps: acquiring a plurality of lists to be processed, wherein each list to be processed is an effective identification list; determining the suggested return visit date of each list to be processed according to the first effective identification time of each list to be processed; and sequencing the plurality of lists to be processed according to the suggested return visit date of each list to be processed to obtain a first list sequence to be processed, wherein the first list sequence to be processed is used for the agent to return visit according to the sequence of the first list sequence to be processed. By adopting the embodiment of the application, the conversion rate of the effective identification list can be improved.

Description

Data processing method, device, server and readable storage medium

Technical Field

The application belongs to the technical field of computers, and particularly relates to a data processing method, a data processing device, a server and a readable storage medium.

Background

After a round of dialing, a large number of lists can generate some effective identification lists, namely lists which are answered or considered for transaction. The lists belong to lists with certain values, but the number of the effective identification lists is also large, if the lists are selected and dialed by an agent, irregular dialing easily causes user dislike, and due to the fact that the lists are large in number and cannot be visited back completely, high-quality lists with higher handling intentions cannot be dialed preferentially, waste of the high-quality lists is caused, and the conversion rate of the effective identification lists is reduced.

Disclosure of Invention

The embodiment of the application provides a data processing method, a data processing device, a server and a readable storage medium, which are used for improving the conversion rate of an effective identification list.

In a first aspect, a data processing method is provided, including:

acquiring a plurality of lists to be processed, wherein each list to be processed is an effective identification list;

determining the suggested return visit date of each list to be processed according to the first effective identification time of each list to be processed;

and sequencing the plurality of lists to be processed according to the suggested return visit date of each list to be processed to obtain a first list sequence to be processed, wherein the first list sequence to be processed is used for the agent to return visit according to the sequence of the first list sequence to be processed.

In a second aspect, there is provided a data processing apparatus, the apparatus comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a plurality of lists to be processed, and each list to be processed is an effective identification list;

the determining module is used for determining the suggested return visit date of each list to be processed according to the first effective identification time of each list to be processed;

and the sorting module is used for sorting the plurality of lists to be processed according to the suggested return visit date of each list to be processed to obtain a first list sequence to be processed, and the first list sequence to be processed is used for the agent to return visits according to the sequence of the first list sequence to be processed.

In a third aspect, a server is provided, comprising a processor, a memory, and a program or instructions stored on the memory and executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method according to the first aspect.

In a fourth aspect, a readable storage medium is provided, on which a program or instructions are stored, which when executed by a processor, implement the steps of the method according to the first aspect.

In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and the processor is configured to execute a program or instructions to implement the steps of the method according to the first aspect.

In the embodiment of the application, firstly, a plurality of lists to be processed are obtained, each list to be processed is an effective identification list, then, the suggested return visit date of each list to be processed is determined according to the first effective identification time of each list to be processed, because the first effective identification time is the time when a user with strong will is marked when the user is dialed for the first time, the user can be indicated to be idle in the time period, the user is returned in the time period which is closer to the first effective identification time, namely, the user is returned by a regular time, the return visit success rate is improved, finally, the plurality of lists to be processed are sequenced according to the suggested return visit date of each list to be processed, a first list sequence to be processed is obtained, the seat can return visits according to the sequence of the list sequence, and the effect that under the condition that the number of the lists to be processed is large and the return visits cannot be all, the seat can preferentially return to the user with a strong handling intention, the return visit success rate is improved, and the conversion rate of the effective identification list is further improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

FIG. 1 is a flow chart of a data processing method provided by an embodiment of the present application;

FIG. 2 is a schematic diagram of a data processing apparatus provided by an embodiment of the present application;

fig. 3 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described clearly below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present disclosure.

The terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one. In addition, "and/or" in the specification and claims means at least one of connected objects, a character "/" generally means that a preceding and succeeding related objects are in an "or" relationship.

Because the effective identification lists needing return visit of each agent every day are thousands of, the existing return visits are selected and dialed by the agents, and lack of unified standard, the conversion rate of the effective identification lists is low, and the return visit success rate can not be guaranteed because the time and frequency of the dialing of the agents are random. In order to solve the problems, the scheme provides a data processing method, users with strong handling intentions are preferentially revisited by sequencing effective identification lists, and meanwhile, the specific time of the revisiting of the seat is planned, so that the revisiting is more regular, and further the conversion rate of the effective identification lists is improved.

The data processing method, the data processing apparatus, the server, and the readable storage medium provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

As shown in fig. 1, an embodiment of the present application provides a data processing method, which may include the contents shown in S101 to S103.

In S101, a plurality of to-be-processed lists are acquired. And each list to be processed is an effective identification list.

Wherein a list of valid identifiers refers to a list that should be handled or considered for inclusion. For example, during the first visit to the user by the agent, the user's account is answered or considered for transaction, in which case the agent adds a valid identifier to the list.

The number of the obtained lists to be processed may be any number preset, and may be set according to historical data or specific conditions.

It should be noted that all lists can be stored in MySQL (relational database management system), and an effective identification list and a total list within a certain activity specified time period can be queried through SQL statements (Structured Query Language) for subsequent use.

The data processing method provided by the application can be executed periodically, for example, at 5 am every day, the list is not dialed or revisited, a plurality of lists to be processed can be obtained, and the back visit work of the seat can be facilitated after a series of subsequent processing is carried out on the plurality of lists to be processed. The agent refers to a staff of the visiting user or the revising user and is mainly responsible for work such as making and receiving calls and the like.

In S102, a suggested return visit date of each to-be-processed list is determined according to the first valid identification time of each to-be-processed list.

The first effective identification time refers to the time when the effective identification list marks the effective identification for the first time.

The suggested revisitation date of each to-be-processed list may be one or more, and is not limited herein. And the suggested return visit date of the list to be processed is used for suggesting the agent to return visit to the list to be processed on the date.

And the time of the first effective identification time of the list to be processed is close to or the same as the time of the suggested return visit date of the list to be processed. For example, the first valid identification time of the to-be-processed list is 1 month 15 am 9 am, and the suggested return visit date of the to-be-processed list may be 1 month 18 am 8 am 50, or 1 month 18 am 9 am.

The first effective identification time of the list to be processed is used for indicating that the probability that the user is successfully revisited at the time of the time is high, and the user is revisited at the time close to the time of the first effective identification time, so that the revisiting success rate can be improved.

Furthermore, due to the fact that effective identification time of different to-be-processed lists is different, suggested return visit dates of different to-be-processed lists are different, return visit sequence of different to-be-processed lists is further distinguished, and conversion rate of effective identification lists is improved.

In S103, the plurality of lists to be processed are sorted according to the suggested return visit date of each list to be processed, so as to obtain a first list sequence to be processed.

And the first list sequence to be processed is used for the agent to return visit according to the sequence of the first list sequence to be processed.

In the first list to be processed, the list ranked earlier in the sequence indicates that the handling of the list is stronger, and the list ranked later in the sequence indicates that the handling of the list is weaker. When the list sequence to be processed includes more lists, under the condition that the agent cannot return all the lists, the conversion rate of the effective identification list can be further improved by preferentially returning the users with strong handling willingness.

In one possible embodiment of the present application, for each to-be-processed list, a specific implementation manner of determining the suggested return visit date of the to-be-processed list according to the first valid identification time of the to-be-processed list may include: if the time of the first effective identification time of the list to be processed is before the preset time, determining the suggested return visit date of the list to be processed according to a first rule; and if the time of the first effective identification time of the list to be processed is behind the preset time, determining the suggested return visit date of the list to be processed according to a second rule. The time interval of two adjacent revisits set by the first rule is a first time interval, the time interval of two adjacent revisits set by the second rule is a second time interval, and the first time interval is different from the second time interval.

The preset time may be any time in a day, may be set by a technician according to experience, or may be set according to historical data.

In this embodiment, different revisit rules are formulated by distinguishing the first valid identification time of the list, for example, if the first valid identification time of the list is before 1 pm, the revisit rule is adopted to perform the revisit, and if the first valid identification time of the list is after 1 pm or 1 pm, the revisit rule is adopted to perform the revisit rule. The effective identification list has uniform suggested return visit time, namely, the user is returned by a regular time, and the return visit success rate is improved.

Wherein the first time interval and the second time interval may be determined based on the number of revisits. The second time interval includes a first sub-time interval and a second sub-time interval, the second sub-time interval being greater than the first sub-time interval, the first sub-time interval being a time interval used for determining the suggested return date N times before, and the second sub-time interval being a time interval used for determining the suggested return date N times before.

In a specific embodiment of the present application, the first time interval may be 2n days, where n is the number of revisits of the list to be processed; the first sub-time interval can be m days, m is the number of revisits of the list to be processed, m is smaller than or equal to 2, the second sub-time interval can be 2m-2 days, m is the number of revisits of the list to be processed, and m is larger than 2;

in an embodiment, the first revisit times used when determining the suggested revisit dates of the to-be-processed list according to the first rule are all the same, and the first revisit times are fixed values set in advance, for example, may be set by technicians according to experience; the second revisit times used when determining the suggested revisit dates of the list to be processed according to the second rule are all the same, and the second revisit times are fixed values set in advance, for example, can be set by technicians according to experience. Further, the first revisit times and the second revisit times may be the same or different.

In another embodiment, each to-be-processed list corresponds to a revisit number, and the revisit number of the to-be-processed list is labeled together when the agent performs the first effective identification on the to-be-processed list.

According to the embodiment of the application, the time intervals used by the two rules for determining the recommended return visit date are different, so that the recommended return visit dates determined under different rules are staggered, the condition that the return visits are concentrated at a certain time is avoided, the condition that the seat cannot effectively return visits is avoided, and the return visit success rate is further improved.

The suggested return visit times are explained in detail below using lists a1 to a12 as examples. Specifically, if the first valid identification time of the list is 1 pm, the return visit is performed according to the rule of 2:2:2 (i.e., return visit every 2 days, and final return visit every 2 days), and if the first valid identification time of the list is 1 pm, the return visit is performed according to the rule of 1:1:2:2 (i.e., return visit every 1 day, return visit every 2 days, and final return visit every 2 days) after 1 pm. Specifically, it can be as shown in table 1.

TABLE 1

In a possible embodiment of the present application, the step of sorting the plurality of lists to be processed according to the suggested return visit date of each list to be processed to obtain the first list sequence to be processed may include the following steps.

Step one, determining a first return visit score of each list to be processed according to the target suggested return visit date of each list to be processed. Wherein the target suggested return visit date is the date closest to the current time. For example, a suggestion of a certain to-be-processed list is periodically revisited, so that the suggestion revisiting date of the to-be-processed list includes a plurality of suggestion revisiting dates, and the target suggestion revisiting date is the date closest to the current time in the plurality of suggestion revisiting dates.

In the above embodiment, at least one suggested return visit date of each to-be-processed list is determined according to the first effective identification time, in this example, different scores are added to each to-be-processed list according to the suggested return visit date closest to the current time, so that multiple to-be-processed lists can be further sorted, a better priority ranking is obtained, and the conversion rate of the effective identification list is further improved.

For example, the target recommended return visit date is 240 points of the to-be-processed list on the current day, the target recommended return visit date is 160 points of the to-be-processed list on the next day, the target recommended return visit date is 80 points of the to-be-processed list on the third day, and the target recommended return visit date is not added to the to-be-processed list on the fourth day and later. Specifically, the current time may be 2021-01-1105: 00, as shown in Table 2.

TABLE 2

Effective identification list	Suggested return visit time	First return visit score	Description of the invention
				A1	2021-01-12 09:00	+160	Return visit of tomorrow
A2	2021-01-11 09:00	+240	Return visit today
				A3	2021-01-12 09:00	+160	Return visit of tomorrow
A4	2021-01-11 09:00	+240	Return visit today
				A5	2021-01-12 09:00	+160	Return visit of tomorrow
A6	2021-01-11 09:00	+240	Return visit today
				A7	2021-01-11 14:00	+240	Return visit today
A8	2021-01-11 14:00	+240	Return visit today
				A9	2021-01-12 14:00	+160	Return visit of tomorrow
A10	2021-01-11 14:00	+240	Return visit today
				A11	2021-01-12 14:00	+160	Return visit of tomorrow
A12	2021-01-11 14:00	+240	Return visit today

And step two, determining the conversion rate score of each list to be processed according to the list conversion rate of each list to be processed, wherein the list conversion rate is the ratio of each list to be processed in the total list within the preset time period of the preset activity corresponding to the list to be processed.

The preset activity refers to an activity triggered by a certain service, for example, a plurality of users trigger a certain service on a platform or a page, but the users do not handle the service for various reasons, and at this time, the platform or the page can collect lists corresponding to the part of users together to form a service activity, that is, the preset activity described in the present application. Since the duration of the preset activity may be long, the generated list may be many, and the application only intercepts a period of the activity, that is, the preset period, for example, the preset period may be from one to twenty times of a month, or from monday to friday of a week, etc. The general list refers to all lists acquired by the platform or the web page within a preset time period of the preset activity, for example, all lists for triggering the first service on the platform from the first number of the last month to the twenty-fifth number. After obtaining the general list, the agent accesses the general list, wherein the user list which is answered or considered to transact the service is an effective identification list, namely a to-be-processed list in the application, and the conversion rate value of the to-be-processed list refers to the ratio of the to-be-processed list to the general list.

It should be noted that all the lists can be stored in MySQL, the to-be-processed list and the total list within a preset time period of a preset activity can be queried through SQL statements, and the conversion rate of the list can be determined through the to-be-processed list and the total list, that is, the ratio of the to-be-processed list to the total list is the conversion rate score of the to-be-processed list.

Because the to-be-processed lists can be marked from some specified time periods of different activities, each to-be-processed list has a corresponding list conversion rate, if the list conversion rate in a certain time period is higher, the requirement of the user in the certain time period of the activity is higher, the conversion rate of the part of the list is possibly higher, and therefore the conversion rate scores of the part of the list are correspondingly higher.

For example, a list with 80% conversion score is 800 for that list and 50% conversion score is 500 for that list. In particular, it can be shown in table 3, wherein the conversion score is the product of the conversion of the list and 1000.

TABLE 3

And thirdly, sequencing the plurality of lists to be processed according to the first target score of each list to be processed to obtain a first list sequence to be processed. And the first target score of the to-be-processed list is the sum of the first revisit score and the conversion rate score of the to-be-processed list.

The step of determining the first return score of each to-be-processed list and the step of determining the conversion rate score of each to-be-processed list have no fixed sequence, the first return score may be determined first and then the conversion rate score may be determined, the conversion rate score may be determined first and then the first return score may be determined, and the first return score and the conversion rate score may be determined at the same time, specifically based on actual application.

The scores of the lists to be processed are added to obtain a first target score of each list to be processed, then the first target scores are sequenced, an arrangement sequence of the lists to be processed, namely a first list sequence to be processed, is obtained, and revisit is performed according to the first list sequence to be processed, so that the conversion rate of the lists can be further improved, users with high requirements can get revisit preferentially, the requirements are met preferentially, and the revisit success rate is improved.

After revisiting the sorted list to be processed, some lists are revisited and some lists are not revisited, and under the condition, real-time optimization can be performed on the sorting of the list to be processed.

In one possible embodiment of the present application, the data processing method may further include: obtaining a revisited list in a plurality of lists to be processed, and determining a second target score of the revisited list, wherein the second target score of the revisited list is a difference value between a first target score and a first preset score of the list to be processed corresponding to the revisited list; and updating the first list sequence to be processed according to the second target score of the revisited list to obtain a second list sequence to be processed.

Wherein, the revisited list comprises successful revisited and unsuccessful revisited. The first predetermined score may be any value, and may be set by a technician based on experience or historical data.

That is, if the list is revisited, the score of the list is decreased no matter whether the revisiting is successful or not, so that the list which is not revisited is ranked forward, the revisiting probability of the list which is not revisited is increased, the overall conversion rate of the list is improved, and the revisiting efficiency is improved.

It should be noted that some lists in the first to-be-processed list sequence have been revisited, that is, become a revisited list, and obtain a second target score of the revisited list, and the score of the list that has not been revisited in the first to-be-processed list sequence is not changed, or is the first target score thereof, at this time, the first target score of the revisited list and the second target score of the revisited list may be sorted from large to small to obtain a new sequence, that is, the second to-be-processed list sequence. The position of the list which is not revisited in the first list sequence to be processed in the second list sequence to be processed may be further forward, so as to increase the revisiting probability of the list which is not revisited, and improve the overall conversion rate of the list.

For example, the current day's revisited list is subtracted by 200 points, and the non-revisited list score is unchanged. Specifically, it can be as shown in table 4.

TABLE 4

Effective identification list	Has come back to visit on the same day	First predetermined value	Description of the invention
				A1	Whether or not	0	No return visit and no point reduction on the same day
A2	Whether or not	0	No return visit and no point reduction on the same day
				A3	Whether or not	0	No return visit and no point reduction on the same day
A4	Is that	200	The day is visited again, and the score is reduced by 200
				A5	Is that	200	The day is visited again, and the score is reduced by 200
A6	Is that	200	The day is visited again, and the score is reduced by 200
				A7	Whether or not	0	No return visit and no point reduction on the same day
A8	Whether or not	0	No return visit and no point reduction on the same day
				A9	Whether or not	0	No return visit and no point reduction on the same day
A10	Is that	200	The day is visited again, and the score is reduced by 200
				A11	Is that	200	The day is visited again, and the score is reduced by 200
A12	Is that	200	The day is visited again, and the score is reduced by 200

In one possible embodiment of the present application, the data processing method may further include: acquiring the successful revisit times of the revisit list, and determining a second revisit score of the revisit list; determining a third target score of the revisited list according to a second revisited score of the revisited list, wherein the third target score of the revisited list is a difference value between the second target score and the second revisited score of the revisited list; and updating the second list sequence to be processed according to the third target score of the revisited list to obtain a third list sequence to be processed.

Some of the revisited lists may be successfully revisited, some of the revisited lists fail to be revisited, and a user who is successfully revisited may also handle the service once, that is, the number of times of successful revisiting of the list corresponding to the user is 1, some users may need to revisit n times to handle the service, that is, the number of times of successful revisiting of the list corresponding to the user is n, that is, the number of times of successful revisiting of a certain list means how many times of successful revisiting of a certain list.

In this embodiment, the list that has been revisited successfully may also be revisited, and if the revisited list is revisited, it indicates that the user corresponding to the list still does not handle the service when the agent revisits the list for the first time, so that the score of the list needs to be further reduced, so that other lists are more opportunistically revisited, thereby increasing the conversion rate of the list and reducing the revisited times of the agent.

The updating mode of the second list sequence to be processed is the same as that of the first list sequence to be processed, that is, the scores of the current plurality of lists to be processed can be sorted from large to small to obtain a new list sequence to be processed.

It should be noted that the second score of the revisited list is determined based on the number of successful revisits of the list, and the score of the list decreases by a certain value when the agent successfully revisits the list once, and the score of the list further decreases when the agent successfully revisits the list again.

Specifically, each time the agent successfully accesses a certain list, the score of the list is subtracted by a certain value, the subtracted value may be linearly related to the number of successful revisits, for example, the revisit score is 20f, f is the number of successful revisits, and the score may also be nonlinearly related to the number of successful revisits, and the greater the number of revisits, the user still does not handle the service, which indicates that the user has a lower possibility of handling the service, at this time, the subtracted amount may be increased, for example, one successful revisit, the score of the list is subtracted by 20, two successful revisits, the score of the list is subtracted by 40, the three successful revisits, and the score of the list is subtracted by 100. Specifically, it can be as shown in table 5.

TABLE 5

In one possible embodiment of the present application, the data processing method may further include: and deleting transacted lists in the plurality of lists to be processed, and updating the third list sequence to be processed to obtain a fourth list sequence to be processed.

The list is handled, namely after the seat successfully visits the list to be processed, the user corresponding to the list handles the service, and the list is called as the handled list at this time.

Because the probability that the user transacting the service continues to transact the service recently is low, the list of the user is deleted, so that other un-transacted lists are ranked ahead, the sequence of the list is updated in real time, and the return visit conversion rate of each day is improved.

For example, if the list is a transacted list, the list is deleted from the list sequence to be processed.

The final sorting of the list to be processed is shown in table 6 after the addition and subtraction of the above steps.

TABLE 6

Specifically, the list to be processed with the recommended revisitation time 2021-01-11 is sorted from top to bottom by score as shown in table 7.

TABLE 7

The list to be processed with suggested revisitation times 2021-01-12 is sorted by score from top to bottom as shown in Table 8.

TABLE 8

By the data processing method, list sequencing shown in tables 7 and 8 can be obtained, and workers can return visits to users corresponding to the lists to be processed according to the sequencing, so that the return visit success rate is improved, the seat can preferentially return visits to the users with strong handling intentions under the condition that the lists to be processed are large in quantity and cannot be completely returned, the return visit success rate is improved, and the conversion rate of the effective identification lists is further improved. In the process of revisiting the list, the sequence of the list to be processed can be updated in real time according to various factors such as whether revisiting is performed, the number of times of revising is successful, whether the list is transacted and the like. The method carries out unified score calculation on the plurality of lists to be processed, can flexibly adjust the return visit frequency and improve the return visit success rate. And different score rules can be added at any time, and the scores of the recommended dialing can be calculated in a multi-dimensional manner only by updating the sequence of the list after the scores are calculated, so that the recommended dialing is more refined and accurate.

After the plurality of lists to be processed are processed, the next batch of lists to be processed can be obtained continuously, and the steps are repeated until all the scores of all the effective identification lists are calculated.

As shown in fig. 2, an embodiment of the present application further provides a data processing apparatus, where the data processing apparatus may include: an acquisition module 201, a determination module 202 and a sorting module 203.

The acquiring module 201 is configured to acquire a plurality of to-be-processed lists, where each to-be-processed list is an effective identifier list; the determining module 202 is configured to determine a suggested return visit date of each to-be-processed list according to the first valid identifier time of each to-be-processed list; the sorting module 203 is configured to sort the plurality of lists to be processed according to the suggested return visit date of each list to be processed, so as to obtain a first list sequence to be processed, where the first list sequence to be processed is used for the agent to return visit according to the sequence of the first list sequence to be processed.

In this embodiment, the obtaining module 201 obtains a plurality of to-be-processed lists, each of which is an effective identification list, the determining module 202 determines a suggested revisit date of each of the to-be-processed lists according to a first effective identification time of each of the to-be-processed lists, since the first effective identification time is a time when a user having a strong intention is marked when the user is dialed for the first time, it can be said that the user is idle in the time period, and revisit the user in a time period closer to the first effective identification time, that is, revisit the user by a regular time, to increase the revisit success rate, the sorting module 203 sorts the plurality of to-be-processed lists according to the suggested revisit date of each of the to-be-processed lists, to obtain a first sequence of the to-be-processed lists, which is used for a seat to revisit according to the sort order of the list sequence, the method and the system realize that the seat can preferentially return the users with stronger handling willingness under the condition that the number of the lists to be processed is large and the lists cannot be returned completely, improve the return visit success rate and further improve the conversion rate of the effective identification lists.

Optionally, the determining module 202 is configured to: if the time of the first effective identification time of the list to be processed is before the preset time, determining the suggested return visit date of the list to be processed according to a first rule; and if the time of the first effective identification time of the list to be processed is behind the preset time, determining the suggested return visit date of the list to be processed according to a second rule, wherein the time interval of two adjacent return visits set by the first rule is a first time interval, the time interval of two adjacent return visits set by the second rule is a second time interval, and the first time interval is different from the second time interval.

Optionally, the first time interval and the second time interval are both determined based on the number of return visits; the second time interval includes a first sub-time interval and a second sub-time interval, the second sub-time interval is larger than the first sub-time interval, the first sub-time interval is used for determining the suggested return visit date for the previous N times, and the second sub-time interval is used for determining the suggested return visit date for other times except the previous N times.

Optionally, the sorting module 203 is configured to: determining a first return visit score of each list to be processed according to a latest recommended return visit date of a target of each list to be processed from the current moment, wherein the target recommended return visit date is closest to the current moment; determining the conversion rate score of each to-be-processed list according to the list conversion rate of each to-be-processed list, wherein the list conversion rate is the ratio of each effective identification to-be-processed list in a total list within a preset time period of a preset activity corresponding to the effective identification to-be-processed list; and sequencing the plurality of lists to be processed according to the first target score of each list to be processed to obtain a first list sequence to be processed, wherein the first target score of the list to be processed is the sum of the first revisit score and the conversion rate score of the list to be processed.

Optionally, the data processing apparatus may further include: the device comprises a second acquisition module and a first updating module.

The second obtaining module is used for obtaining a revisited list in the plurality of lists to be processed and determining a second target score of the revisited list, wherein the second target score of the revisited list is a difference value between a first target score and a first preset score of the list to be processed corresponding to the revisited list; and the first updating module is used for updating the first list sequence to be processed according to the second target score of the revisited list in the plurality of lists to be processed to obtain a second list sequence to be processed.

Optionally, the data processing apparatus may further include: the device comprises a third acquisition module, a second determination module and a second updating module.

The third obtaining module is used for obtaining the successful revisit times of the revisit lists in the multiple lists to be processed and determining second revisit scores of the revisit lists in the multiple lists to be processed; the second determining module is used for determining a third target score of the revisited list according to a second revisited score of the revisited list, wherein the third target score of the revisited list is a difference value between the second target score of the revisited list and the second revisited score; and the second updating module is used for updating the second list sequence to be processed according to the third target score of the revisited list to obtain a third list sequence to be processed.

Optionally, the data processing apparatus may further include: and a third updating module.

And the third updating module is used for deleting the transacted lists in the plurality of lists to be processed and updating the third list sequence to be processed to obtain a fourth list sequence to be processed.

The data processing device in the embodiment of the present application may be a device, and may also be a component, an integrated circuit, or a chip in a server.

The data processing apparatus provided in the embodiment of the present application can implement each process implemented in the method embodiment of fig. 1, and is not described here again to avoid repetition.

Optionally, as shown in fig. 3, an embodiment of the present application further provides a server 300, which includes a processor 301, a memory 302, and a program or an instruction stored in the memory 302 and capable of running on the processor 301, and when the program or the instruction is executed by the processor 301, the program or the instruction implements each process of the embodiment of the data processing method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.

The embodiments of the present application also provide a readable storage medium, on which a program or instructions are stored, and when the program or instructions are executed by a processor, the program or instructions implement the processes of the embodiments of the data processing method provided in any of the above embodiments. And the same technical effect can be achieved, and in order to avoid repetition, the description is omitted.

The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and so on.

The embodiment of the present application further provides a chip, where the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to execute a program or an instruction to implement each process of the embodiment of the data processing method provided in the foregoing embodiment, and the same technical effect can be achieved, and in order to avoid repetition, details are not repeated here.

It should be understood that the chips mentioned in the embodiments of the present application may also be referred to as system-on-chip, system-on-chip or system-on-chip, etc.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Further, it should be noted that the scope of the methods and apparatus of the embodiments of the present application is not limited to performing the functions in the order illustrated or discussed, but may include performing the functions in a substantially simultaneous manner or in a reverse order based on the functions involved, e.g., the methods described may be performed in an order different than that described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present application.

While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the invention is not limited to the precise embodiments described above, which are meant to be illustrative and not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.

Claims

1. A data processing method, comprising:

2. The method according to claim 1, wherein specific implementation manners for determining the suggested return visit date of the to-be-processed list according to the first valid identification time of the to-be-processed list are as follows:

if the time of the first effective identification time of the list to be processed is before the preset time, determining the suggested return visit date of the list to be processed according to a first rule;

if the time of the first effective identification time of the list to be processed is behind the preset time, determining the suggested return visit date of the list to be processed according to a second rule,

the time interval of two adjacent revisits set by the first rule is a first time interval, the time interval of two adjacent revisits set by the second rule is a second time interval, and the first time interval is different from the second time interval.

3. The method of claim 2, wherein the first time interval and the second time interval are each determined based on a number of revisits;

the second time interval includes a first sub-time interval and a second sub-time interval, the second sub-time interval is larger than the first sub-time interval, the first sub-time interval is used for determining the date of the suggested return visit for the previous N times, and the second sub-time interval is used for determining the date of the suggested return visit for other times except the previous N times.

4. The method of claim 1, wherein the sorting the plurality of to-be-processed lists according to the suggested revisit date of each to-be-processed list to obtain a first sequence of to-be-processed lists comprises:

determining a first return visit score of each list to be processed according to a target suggested return visit date of each list to be processed, wherein the target suggested return visit date is closest to the current moment;

determining the conversion rate score of each to-be-processed list according to the list conversion rate of each to-be-processed list, wherein the list conversion rate is the ratio of each to-be-processed list to the total list in a preset activity preset time period corresponding to the list conversion rate;

and sequencing the plurality of lists to be processed according to the first target score of each list to be processed to obtain a first list sequence to be processed, wherein the first target score of the list to be processed is the sum of the first return visit score and the conversion rate score of the list to be processed.

5. The method of claim 4, further comprising:

obtaining a revisited list in the plurality of lists to be processed, and determining a second target score of the revisited list, wherein the second target score of the revisited list is a difference value between a first target score and a first preset score of the list to be processed corresponding to the revisited list;

and updating the first list sequence to be processed according to the second target score of the revisited list to obtain a second list sequence to be processed.

6. The method of claim 5, further comprising:

acquiring the number of successful revisits of the revisited list, and determining a second revisit score of the revisited list;

determining a third target score of the revisited list according to a second revisited score of the revisited list, wherein the third target score of the revisited list is a difference value between the second target score of the revisited list and the second revisited score;

and updating the second list sequence to be processed according to the third target score of the revisited list to obtain a third list sequence to be processed.

7. The method of claim 6, further comprising:

deleting the transacted lists in the plurality of lists to be processed, and updating the third list sequence to be processed to obtain a fourth list sequence to be processed.

8. A data processing apparatus, characterized in that the apparatus comprises:

9. A server, characterized in that the server comprises a processor, a memory and a program or instructions stored on the memory and executable on the processor, which program or instructions, when executed by the processor, implement the steps of the method according to any of claims 1-7.

10. A readable storage medium, characterized in that it stores thereon a program or instructions which, when executed by a processor, implement the steps of the method according to any one of claims 1-7.