Reverse dispatching method, device, equipment and storage medium based on reach data

Abstract

The embodiments of the present invention provide a reverse dispatching method, apparatus, device and storage medium based on reach data, the method comprising: obtaining dispatching data and reach data for a delivery person; determining a first correlation between reach data and dispatch conversion data, and determining a second correlation between delivery distance and dispatch conversion data; adjusting the dispatch quantity of the delivery person according to the first correlation and the second correlation, and dispatching the delivery person using the adjusted dispatch quantity. By comprehensively considering the impact of the delivery distance and reach data of the delivery person on the dispatch conversion data, the dispatch quantity of the delivery person is reversely dispatched, which improves delivery efficiency and ensures the degree of activation of the delivery person for the delivery order to ensure the quality of task completion, while also indirectly improving user satisfaction based on the involved reach data.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a reverse dispatching method based on reach data, a reverse dispatching device based on reach data, a corresponding electronic device, and a corresponding computer storage medium. Background Art

[0002] The automatic order dispatch system is used to distribute the corresponding orders to the delivery personnel after receiving the order information to complete the dispatch of the orders.

[0003] Current automated dispatch systems are primarily based on logistics systems or delivery route optimization. These systems primarily track the locations of logistics vehicles or couriers in real time, determine the optimal route or the courier closest to the target location, and dispatch orders to ensure that orders reach users as quickly as possible. However, these systems only consider the optimization of location routes and the efficiency of receiving target tasks, and do not address the quality of task completion. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention are proposed to provide a reverse dispatching method based on reach data, a reverse dispatching device based on reach data, a corresponding electronic device, and a corresponding computer storage medium that overcome the above problems or at least partially solve the above problems.

[0005] An embodiment of the present invention discloses a reverse dispatching method based on reach data, which is applied to a dispatching system. The method includes:

[0006] Obtaining dispatch data and reach data for delivery personnel; the dispatch data includes delivery distance and dispatch conversion data used to indicate the degree of activation of delivery personnel for delivery orders; the reach data is used to indicate the service status of delivery personnel for delivery orders;

[0007] Determining a first correlation between the reach data and the dispatch conversion data, and determining a second correlation between the delivery distance and the dispatch conversion data;

[0008] According to the first correlation and the second correlation, the dispatch quantity of the delivery personnel is adjusted, and the adjusted dispatch quantity is used to dispatch orders to the delivery personnel.

[0009] Optionally, the dispatch data includes the dispatch volume of the delivery personnel, and the activation degree of the delivery personnel for the delivery orders is determined based on the dispatch conversion rate;

[0010] Obtain dispatch conversion data for delivery personnel, including:

[0011] Obtain the number of activated orders from the delivery personnel's order volume;

[0012] The delivery personnel's order conversion rate is calculated by using the ratio of the activation quantity of the order and the number of orders dispatched by the delivery personnel.

[0013] Optionally, the reach data includes a reach consistency rate used to indicate the service quality of the delivery personnel for the delivery order, and obtaining the reach data for the delivery personnel includes:

[0014] Obtaining delivery personnel contact user data and smart object contact user data; wherein the delivery personnel contact user data is used to indicate the delivery personnel's manual service situation, and the smart object contact user data is used to indicate the total number of users that the delivery personnel needs to contact;

[0015] The delivery personnel's reach consistency rate is calculated by using the consistent order volume of the delivery personnel's reach user data and the smart object's reach user data, and the ratio of the delivery personnel's reach user data.

[0016] Optionally, the dispatch conversion data includes a dispatch conversion rate, and the reach data includes a reach consistency rate; the first correlation is determined based on a first correlation coefficient between the reach consistency rate and the dispatch conversion rate, and the second correlation is determined based on a second correlation coefficient between the delivery distance and the dispatch conversion rate;

[0017] Determining the first correlation between the reach data and the order conversion data, and determining the second correlation between the delivery distance and the order conversion data, includes:

[0018] The reach consistency rate and the order conversion rate are used to calculate a first correlation coefficient based on a correlation coefficient method, which is used to characterize the degree of correlation between the reach data and the order conversion data;

[0019] And / or, the delivery distance and the dispatch conversion rate are used to calculate a second correlation coefficient based on a correlation coefficient method to characterize the degree of correlation between the delivery distance and the dispatch conversion data.

[0020] Optionally, the first correlation is determined based on a first correlation coefficient, and the second correlation is determined based on a second correlation coefficient; and adjusting the number of orders assigned to the delivery personnel based on the first correlation and the second correlation includes:

[0021] Based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient are used to set the order dispatch weight;

[0022] The dispatch quantity of the delivery personnel is dynamically adjusted based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0023] Optionally, the dispatch conversion data includes a dispatch conversion rate, and the dynamically adjusting the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches a dispatch quantity threshold includes:

[0024] Obtaining the dispatch volume corresponding to the highest dispatch conversion rate in the dispatch data for the delivery personnel, and using the dispatch volume corresponding to the highest dispatch conversion rate as the dispatch volume threshold;

[0025] The dispatch quantity of the delivery personnel is dynamically adjusted based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0026] Optionally, dynamically adjusting the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches a dispatch quantity threshold includes:

[0027] After adjusting the dispatch volume of the delivery personnel to reach the dispatch volume threshold, obtaining again the dispatch volume corresponding to the highest dispatch conversion rate in the dispatch data for the delivery personnel, and using the dispatch volume corresponding to the highest dispatch conversion rate as the dispatch volume threshold;

[0028] Again based on the correlation coefficient method, the first correlation coefficient is calculated using the reach consistency rate and the dispatch conversion rate, and the second correlation coefficient is calculated using the dispatch distance and dispatch conversion data;

[0029] Again based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient are used to set the dispatch weight, and again based on the dispatch weight, the dispatch quantity of the delivery personnel is dynamically adjusted until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0030] The embodiment of the present invention further discloses a reverse dispatching device based on reach data, which is applied to a dispatching system. The device includes:

[0031] A data acquisition module is used to obtain dispatch data and reach data for delivery personnel; the dispatch data includes delivery distance and dispatch conversion data used to indicate the degree of activation of delivery personnel for delivery orders; the reach data is used to indicate the service status of delivery personnel for delivery orders;

[0032] a correlation determination module, configured to determine a first correlation between the reach data and the dispatch conversion data, and to determine a second correlation between the dispatch distance and the dispatch conversion data;

[0033] An order dispatching module is used to adjust the order dispatching quantity of the delivery personnel according to the first correlation and the second correlation, and use the adjusted order dispatching quantity to dispatch orders to the delivery personnel.

[0034] Optionally, the dispatch data includes the number of dispatches by the delivery personnel, and the degree of activation of the delivery personnel for the delivery orders is determined based on the dispatch conversion rate; the data acquisition module includes:

[0035] An activation quantity acquisition submodule, used to obtain the activation quantity of orders from the delivery personnel's dispatch quantity;

[0036] The dispatch conversion rate generating submodule is used to calculate the dispatch conversion rate of the delivery personnel by using the ratio of the activation quantity of the order and the dispatch quantity of the delivery personnel.

[0037] Optionally, the reach data includes a reach consistency rate used to indicate the service quality of the delivery personnel for the delivery order, and the data acquisition module includes:

[0038] The user data acquisition submodule is used to obtain the user data reached by the delivery personnel and the user data reached by the smart object; wherein the user data reached by the delivery personnel is used to represent the manual service situation of the delivery personnel, and the user data reached by the smart object is used to represent the total number of users that the delivery personnel needs to reach;

[0039] The reach consistency rate generation submodule is used to calculate the reach consistency rate of the delivery personnel by using the consistent order volume of the delivery personnel's reach user data and the smart object's reach user data, and the ratio of the delivery personnel's reach user data.

[0040] Optionally, the dispatch conversion data includes a dispatch conversion rate, and the reach data includes a reach consistency rate; the first correlation is determined based on a first correlation coefficient between the reach consistency rate and the dispatch conversion rate, and the second correlation is determined based on a second correlation coefficient between the delivery distance and the dispatch conversion rate;

[0041] The correlation determination module 502 includes:

[0042] A first correlation coefficient calculation submodule, configured to calculate, based on a correlation coefficient method, a first correlation coefficient for describing the degree of correlation between the reach data and the dispatch conversion data, using the reach consistency rate and the dispatch conversion rate;

[0043] The second correlation coefficient calculation submodule is used to use the delivery distance and the delivery order conversion rate to calculate a second correlation coefficient based on the correlation coefficient method to characterize the degree of correlation between the delivery distance and the delivery order conversion data.

[0044] Optionally, the first correlation is determined based on a first correlation coefficient, and the second correlation is determined based on a second correlation coefficient; and the dispatch module includes:

[0045] a dispatch weight setting submodule, configured to set a dispatch weight using the first correlation coefficient and the second correlation coefficient based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation;

[0046] The dynamic adjustment submodule is used to dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0047] Optionally, the dispatch conversion data includes a dispatch conversion rate, and the dynamic adjustment submodule includes:

[0048] a dispatch quantity threshold determination unit, configured to obtain the dispatch quantity corresponding to the highest dispatch conversion rate in the dispatch data for the delivery personnel, and use the dispatch quantity corresponding to the highest dispatch conversion rate as the dispatch quantity threshold;

[0049] A dynamic adjustment unit is used to dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0050] Optionally, the dynamic adjustment unit includes:

[0051] The order quantity threshold re-determination subunit is used to obtain the order quantity corresponding to the highest order conversion rate in the order data for the delivery personnel after the order quantity of the delivery personnel is adjusted to reach the order quantity threshold, and use the order quantity corresponding to the highest order conversion rate as the order quantity threshold;

[0052] The correlation coefficient re-determination sub-unit is used to calculate the first correlation coefficient again based on the correlation coefficient method using the reach consistency rate and the dispatch conversion rate, and to calculate the second correlation coefficient using the delivery distance and the dispatch conversion data;

[0053] The sub-unit is dynamically adjusted again, and is used to set the dispatch weight based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, and to dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight again until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0054] An embodiment of the present invention also discloses an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of any one of the reverse dispatching methods based on reach data are implemented.

[0055] An embodiment of the present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods for reverse dispatching based on reach data are implemented.

[0056] The embodiments of the present invention include the following advantages:

[0057] In an embodiment of the present invention, based on a first correlation between reach data indicating the service status of the delivery personnel for the delivery order and dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, and a second correlation between the determined delivery distance and the dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, the dispatch quantity of the delivery personnel is dynamically adjusted, and the delivery personnel are dispatched using the adjusted dispatch quantity. By comprehensively considering the impact of the delivery personnel's delivery distance and reach data on the dispatch conversion data, the dispatch quantity of the delivery personnel is reversely dispatched. While improving delivery efficiency and ensuring the degree of activation of the delivery personnel for the delivery order to ensure the quality of task completion, user satisfaction is also indirectly improved based on the involved reach data. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a flowchart of the steps of an embodiment of a reverse dispatching method based on reach data of the present invention;

[0059] Figure 2 This is a flowchart of another embodiment of a reverse dispatching method based on reach data of the present invention;

[0060] Figure 3 This is a schematic diagram of a process for dispatching orders based on conversion rates provided by an embodiment of the present invention;

[0061] Figure 4 This is a schematic diagram of an application scenario of reverse dispatching based on reach data provided by an embodiment of the present invention;

[0062] Figure 5 It is a structural block diagram of an embodiment of a reverse dispatching device based on reach data of the present invention. DETAILED DESCRIPTION

[0063] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0064] The current automatic dispatching system is mainly built based on the logistics system or the optimization system of the delivery route. It can mainly complete the dispatch by tracking the location of logistics vehicles or couriers in real time, determining the optimal route or the courier closest to the target location, and ensuring that the order can be delivered to the user as quickly as possible.

[0065] In one example of an automated dispatch system based on a logistics system or an optimized delivery route, a city can be divided into grids, with the location and availability of personnel in each grid marked. When assigning target tasks, the target task location can be matched with the location of each personnel. A dispatch module then sends the task to the most compatible personnel, ensuring timely response. However, this approach only considers the optimization of the location path and the efficiency of task acceptance, and does not address the quality of task completion. Regarding the construction of an automated dispatch system, in another example, a terminal data management module can integrate customer order information and personnel status information to match and screen personnel. This involves individual reputation ratings, attendance status, real-time latitude and longitude, and order data. However, this approach only provides simple statistics on the personnel's personal reputation and company attributes, without providing data-level statistics on the personnel's service quality, thus failing to form a closed data loop.

[0066] From the above, it can be seen that the current automatic dispatching system based on the logistics system or the optimization system of the delivery path does not involve the quality of completion of the target task, nor does it involve the construction of a system for reverse dispatching based on the delivery person's contact data.

[0067] One of the core ideas of the embodiments of the present invention is to propose a method for reverse dispatching orders based on the delivery staff's reach data, based on the first correlation between the reach data used to represent the delivery staff's service status for the delivery order and the dispatch conversion data used to represent the delivery staff's activation level for the delivery order, and the second correlation between the determined delivery distance and the dispatch conversion data used to represent the delivery staff's activation level for the delivery order, the delivery staff's dispatch volume is reversely dispatched taking into account the impact of the delivery staff's delivery distance and reach data on the dispatch conversion data. While improving the delivery efficiency and ensuring the delivery staff's activation level for the delivery order to ensure the quality of task completion, the user satisfaction is indirectly improved based on the reach data involved.

[0068] Reference Figure 1 , shows a flowchart of an embodiment of a reverse dispatching method based on reach data of the present invention, which is applied to a dispatching system and may specifically include the following steps:

[0069] Step 101: Obtain dispatch data and contact data for delivery personnel;

[0070] Dispatch data refers to the real-time and historical delivery data recorded and counted by delivery personnel. This data may include the delivery volume and distance covered by the delivery personnel, as well as dispatch conversion data, which indicates the degree of activation of delivery personnel for delivery orders. This activation level can be used to assess the quality of delivery personnel's task completion. Reach data can be used to indicate the service performance of delivery personnel for delivery orders.

[0071] In an embodiment of the present invention, in order to improve delivery efficiency and ensure the degree of activation of delivery orders by delivery personnel to ensure the quality of task completion, it is also possible to indirectly improve user satisfaction based on the reach data involved. When adjusting the delivery personnel's order volume, the delivery data and reach data for the delivery personnel can be obtained, so as to introduce the delivery distance and delivery conversion data in the delivery data, as well as the reach data.

[0072] It should be noted that the recording and statistics of the delivery personnel's real-time delivery data and historical delivery data, as well as the acquisition of the delivery personnel's dispatch data and contact data, are all carried out with the knowledge and permission of the delivery personnel, which is in line with the protection of the delivery personnel's personal privacy; delivery personnel can refer to door-to-door service personnel in any door-to-door service industry, such as takeaway personnel in the takeaway industry, express delivery personnel in the express delivery industry and errand running industry, etc., and the embodiments of the present invention are not limited to this.

[0073] Step 102: determining a first correlation between reach data and order conversion data, and determining a second correlation between delivery distance and order conversion data;

[0074] After obtaining the dispatch data and reach data for the delivery personnel, that is, introducing the delivery distance and the dispatch conversion data used to represent the degree of activation of the delivery personnel for the delivery order, and the reach data used to represent the service status of the delivery personnel for the delivery order, since the degree of activation represented by the dispatch conversion data can be used to determine the quality of the delivery personnel's task completion, in order to ensure the degree of activation of the delivery personnel for the delivery order and ensure the quality of task completion, in the process of adjusting the delivery personnel's dispatch volume, the degree of influence of other data / factors on the dispatch conversion data can be determined, so that based on the adjustment of other data / factors, the dispatch conversion data can be adjusted accordingly.

[0075] Specifically, when judging the degree of influence of other data / factors on the dispatch conversion data, the other data / factors may be relevant data that can reflect the delivery situation during the order delivery process, such as delivery data, reach data, etc. At this time, it can be expressed as a judgment on the degree of influence of reach data on the dispatch conversion data, as well as a judgment on the degree of influence of delivery distance on the dispatch conversion data.

[0076] The degree of influence can be determined based on the degree of correlation, which refers to the effect of an increase and / or decrease in one data point on another data point. The degree of correlation can be determined based on the correlation. In this case, a first correlation between reach data and dispatch conversion data can be determined, as well as a second correlation between delivery distance and dispatch conversion data. Based on the first and second correlations, the impact of the delivery personnel's delivery distance and reach data on the dispatch conversion data can be comprehensively considered.

[0077] Step 103: Adjust the dispatch quantity of the delivery personnel based on the first correlation and the second correlation, and use the adjusted dispatch quantity to dispatch orders to the delivery personnel.

[0078] After determining the first correlation between reach data and dispatch conversion data, and determining the second correlation between delivery distance and dispatch conversion data, the degree of influence of reach data on dispatch conversion data and the degree of influence of delivery distance on dispatch conversion data are now clear. When adjusting the dispatch quantity of the delivery personnel, the dispatch quantity of the dispatch personnel can be adjusted in the direction that can ensure the quality of task completion based on the determined degree of influence, that is, based on the first correlation and the second correlation, and the dispatch quantity of the delivery personnel can be reversed.

[0079] In an embodiment of the present invention, based on a first correlation between reach data indicating the service status of the delivery personnel for the delivery order and dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, and a second correlation between the determined delivery distance and the dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, the dispatch quantity of the delivery personnel is dynamically adjusted, and the delivery personnel are dispatched using the adjusted dispatch quantity. By comprehensively considering the impact of the delivery personnel's delivery distance and reach data on the dispatch conversion data, the dispatch quantity of the delivery personnel is reversely dispatched. While improving delivery efficiency and ensuring the degree of activation of the delivery personnel for the delivery order to ensure the quality of task completion, user satisfaction is also indirectly improved based on the involved reach data.

[0080] Reference Figure 2 , shows a flowchart of another embodiment of a reverse dispatching method based on reach data of the present invention, which is applied to a dispatching system and may specifically include the following steps:

[0081] Step 201: Obtain the delivery distance, order conversion rate, and reach consistency rate for the delivery personnel;

[0082] In an embodiment of the present invention, in order to improve delivery efficiency and ensure the degree of activation of delivery orders by delivery personnel to ensure the quality of task completion, it is also possible to indirectly improve user satisfaction based on the reach data involved. When adjusting the delivery personnel's order volume, the delivery data and reach data for the delivery personnel can be obtained, so as to introduce the delivery distance and delivery conversion data in the delivery data, as well as the reach data.

[0083] Dispatch and reach data can be obtained from a pre-established delivery data repository, which can be used to store both real-time and historical data. It should be noted that data storage and retrieval are performed with the knowledge and permission of delivery personnel, ensuring the protection of their privacy.

[0084] The acquired delivery distance refers to the real-time and historical delivery data recorded and counted by delivery personnel. This recorded and counted delivery data may include the delivery volume, delivery distance, and order conversion data, which indicates the degree of activation of delivery personnel for delivery orders. This activation level can be used to determine the quality of delivery personnel's task completion. The acquired reach data can be used to indicate the delivery personnel's service performance for delivery orders.

[0085] Among them, the dispatch conversion data used to indicate the degree of activation of delivery orders by delivery personnel can be mainly expressed as the dispatch conversion rate, which can be achieved based on the ratio of the activation volume of delivery orders to the dispatch volume, that is, the proportion of activation volume in the dispatch volume. As for the overall dispatch conversion rate, the overall dispatch conversion rate can be expressed as the ratio of the total number of orders activated by all delivery personnel to the number of orders dispatched to all couriers, that is, the total delivery volume; and for the dispatch conversion rate of a certain delivery personnel, it can be expressed as obtaining the number of order activations in the dispatch volume of the delivery personnel, and using the ratio of the order activation volume and the dispatch volume of the delivery personnel to calculate the dispatch conversion rate of the delivery personnel.

[0086] In actual applications, the delivery distance of the delivery personnel can usually be obtained by calling the map API (Application Programming Interface) to obtain the longitude and latitude between the delivery personnel's station and the delivery address, and the delivery distance of the delivery personnel and the average delivery distance of the delivery personnel can be calculated through the distance measurement interface.

[0087] The reach data can refer to the situation in which the delivery personnel deliver the required delivery tasks to the users. It can be used to indicate the service situation of the delivery personnel for the delivery orders. It can usually include the reach rate used to evaluate the delivery situation of the delivery orders, and the reach consistency rate used to indicate the service quality of the delivery personnel for the delivery orders. Among them, the reach rate can be expressed as the ratio of the outbound volume to the delivery volume. The outbound volume can be used to estimate the number of delivered orders, which refers to the number of outbound orders; and the reach consistency rate can be expressed as the ratio of the delivery personnel's reach user data (i.e., manual reach user data) to the smart object reach user data (i.e., smart reach user data). The manual reach user data is used to indicate the manual service situation of the delivery personnel. Its manual reach user method is usually expressed as the number of orders that the delivery personnel reach the user by phone. The smart reach user data can usually be expressed as the number of orders that the smart customer service robot or the smart platform virtual image reaches the user. Since it is the order data of the user reached through the AI ​​(Artificial Intelligence) outbound call platform, the smart object reach user data is usually the total number of users that the delivery personnel need to reach.

[0088] At this time, the delivery personnel's user contact data and smart object's user contact data can be obtained, and the delivery personnel's contact consistency rate can be calculated by using the consistent order volume of the delivery personnel's user contact data and the smart object's user contact data and the ratio of the delivery personnel's user contact data. The calculated contact consistency rate can be used to determine whether the delivery personnel's manual user contact data is consistent with the smart object's user contact data. The higher the consistency rate, the more manual service situations the delivery personnel have, and the higher the service quality of the delivery personnel.

[0089] Step 202: Using the reach consistency rate and the order conversion rate, a first correlation coefficient is calculated based on the correlation coefficient method to characterize the correlation between the reach data and the order conversion data.

[0090] In order to ensure the degree of activation of delivery personnel for delivery orders and the quality of task completion, when adjusting the delivery personnel's order quantity, the degree of influence of other data / factors on the order conversion data can be determined, so that the order conversion data can be adjusted accordingly based on the adjustment of other data / factors.

[0091] Specifically, when judging the degree of influence of other data / factors on the dispatch conversion data, the other data / factors may be relevant data that can reflect the delivery situation during the order delivery process, such as delivery data, reach data, etc. At this time, it can be expressed as a judgment on the degree of influence of reach data on the dispatch conversion data, as well as a judgment on the degree of influence of delivery distance on the dispatch conversion data.

[0092] The degree of influence can be determined based on the degree of correlation. The degree of correlation refers to the effect of an increase and / or decrease in a certain data on another data. The degree of correlation can be determined based on the correlation. The correlation can be determined based on the correlation coefficient. The correlation coefficient r represents the linear correlation between two variables. If r is greater than 0, it indicates a positive correlation between the two variables. If r is less than 0, it indicates a negative correlation between the two variables. The absolute value of the correlation coefficient r is usually between 1 and -1. The closer the absolute value of r is to 1, the stronger the linear correlation between the two variables.

[0093] In order to determine the degree of influence of the reach consistency rate on the order conversion rate, the first correlation between the reach data and the order conversion rate can be determined at this time. The first correlation can be mainly determined based on the first correlation coefficient of the reach consistency rate and the order conversion rate. Based on the value of the determined first correlation coefficient and the positive and negative correlation, the reach data and the order conversion data, specifically the degree of correlation between the reach consistency rate and the order conversion rate, can be determined.

[0094] In practical applications, the calculation of the first correlation coefficient can be achieved based on the correlation coefficient method.

[0095] Specifically, the formula of the correlation coefficient method can be Formula 1:

[0096]

[0097] When calculating the first correlation coefficient r1, n in Formula 1 can refer to the number of dispatch personnel, X i It can refer to the delivery personnel's contact consistency rate, Refers to the average of the delivery personnel’s contact consistency rate, Y i It can refer to the delivery personnel's order conversion rate. Refers to the average order conversion rate of delivery personnel.

[0098] In an embodiment of the present invention, the weights among the reach consistency rate, delivery distance, and conversion rate can be determined by the correlation coefficient method, i.e., Formula 1, to avoid subjective human operations and improve work efficiency.

[0099] Step 203: Using the delivery distance and the order conversion rate, a second correlation coefficient is calculated based on a correlation coefficient method to characterize the degree of correlation between the delivery distance and the order conversion rate.

[0100] In order to determine the degree of influence of delivery distance on the dispatch conversion rate, the second correlation between delivery distance and dispatch conversion data can be determined at this time. The second correlation can be mainly determined based on the second correlation coefficient between delivery distance and dispatch conversion rate. Based on the value of the determined second correlation coefficient and the positive and negative correlation, the delivery distance and dispatch conversion data, specifically the degree of correlation between delivery distance and dispatch conversion rate, can be determined.

[0101] In practical applications, the calculation of the first correlation coefficient can be achieved based on the correlation coefficient method.

[0102] Specifically, the formula of the correlation coefficient method can be Formula 1:

[0103]

[0104] When calculating the second correlation coefficient r2, n in Formula 1 can refer to the number of dispatch personnel, X i It can refer to the delivery distance of the delivery personnel. Refers to the average delivery distance of the delivery personnel, Y i It can refer to the delivery personnel's order conversion rate. Refers to the average order conversion rate of delivery personnel.

[0105] Step 204: Based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient are used to set the dispatch weight;

[0106] After determining the first correlation between reach data and dispatch conversion data, and determining the second correlation between delivery distance and dispatch conversion data, the degree of influence of reach data on dispatch conversion data and the degree of influence of delivery distance on dispatch conversion data are now clear. When adjusting the dispatch quantity of the delivery personnel, the dispatch quantity of the dispatch personnel can be adjusted in the direction that can ensure the quality of task completion based on the determined degree of influence, that is, based on the first correlation and the second correlation, and the dispatch quantity of the delivery personnel can be reversed.

[0107] Specifically, based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient can be used to set the dispatch weight, so as to dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold, thereby achieving the purpose of adjusting the dispatch quantity of the dispatch personnel in the direction that can ensure the quality of task completion.

[0108] Step 205: Dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0109] The values ​​of the first correlation coefficient and the second correlation coefficient used can be expressed as the size relationship between the first relative coefficient and the second correlation coefficient. At this time, the first correlation coefficient and the second correlation coefficient used as dispatch weights can be dynamically adjusted according to different size relationships and positive and negative correlations until the dispatch quantity of the adjusted delivery personnel reaches the dispatch quantity threshold, so that the adjusted dispatch quantity can be used to dispatch orders to the corresponding delivery personnel.

[0110] According to different size relationships and positive and negative correlations, the first correlation coefficient and the second correlation coefficient, which serve as the dispatch weight, are dynamically adjusted, which can be manifested in the following six situations:

[0111] (1) When the first correlation coefficient r1>the second correlation coefficient r2, and r1 and r2 are both positively correlated, it means that the higher the delivery personnel's reach consistency rate, the higher the delivery conversion rate, and the shorter the delivery personnel's delivery distance, the higher the delivery conversion rate. However, the positive impact of the delivery personnel's reach consistency rate on the delivery conversion rate is greater than the impact of the delivery distance on the delivery conversion rate. At this time, the dispatch volume can be adjusted based on r1 as the main condition. Since the first correlation coefficient determines the degree of correlation between the reach consistency rate and the delivery conversion rate, more orders can be allocated to delivery personnel with a higher reach consistency rate. At the same time, the delivery conversion rate can be monitored in real time. If the monitored delivery conversion rate increases, more orders can be allocated to delivery personnel with a higher reach consistency rate until the dispatch volume of this delivery personnel is adjusted to the dispatch threshold, and the allocation of orders to this delivery personnel is stopped.

[0112] The specific formula can be expressed as shown in Formula 2:

[0113]

[0114] Among them, r1 can refer to the first correlation coefficient between the reach consistency rate and the dispatch conversion rate, r2 can refer to the second correlation coefficient between the delivery distance and the dispatch conversion rate, a1 can refer to the reach consistency rate of the delivery personnel, and b1 can refer to the delivery distance of the delivery personnel. It can refer to the average delivery distance of the delivery personnel.

[0115] (2) When the first correlation coefficient r1 is less than the second correlation coefficient r2, and both r1 and r2 are positively correlated, it means that the higher the delivery personnel's reach consistency rate, the higher the delivery conversion rate, and the shorter the delivery personnel's delivery distance, the higher the delivery conversion rate. However, the positive impact of the delivery personnel's delivery distance on the delivery conversion rate is greater than the impact of the reach consistency rate on the delivery conversion rate. At this time, the dispatch volume can be adjusted based on r2 as the main condition. Since the second correlation coefficient determines the degree of correlation between the delivery distance and the delivery conversion rate, more orders can be allocated to delivery personnel with a longer delivery distance. At the same time, the delivery conversion rate can be monitored in real time. If the monitored delivery conversion rate increases, more orders can be allocated to delivery personnel with a longer delivery distance until the dispatch volume of this delivery personnel is adjusted to the dispatch threshold, and the allocation of orders to this delivery personnel is stopped.

[0116] The specific formula can be expressed as shown in Formula 3:

[0117]

[0118] Among them, r1 can refer to the first correlation coefficient between the reach consistency rate and the dispatch conversion rate, r2 can refer to the second correlation coefficient between the delivery distance and the dispatch conversion rate, a1 can refer to the reach consistency rate of the delivery personnel, and b1 can refer to the delivery distance of the delivery personnel. It can refer to the average delivery distance of the delivery personnel.

[0119] (3) When the first correlation coefficient r1 is greater than the second correlation coefficient r2, and r1 and r2 are both negatively correlated, it means that the higher the delivery personnel's reach consistency rate, the lower the delivery conversion rate, and the shorter the delivery personnel's delivery distance, the lower the delivery conversion rate, and the positive impact of the delivery personnel's reach consistency rate on the delivery conversion rate is greater than the impact of the delivery distance on the delivery conversion rate. At this time, the dispatch quantity can be adjusted based on r1 as the main condition. Since the first correlation coefficient determines the degree of correlation between the reach consistency rate and the delivery conversion rate, the number of orders assigned to delivery personnel with a higher reach consistency rate can be reduced at this time, and the delivery conversion rate can be monitored in real time. If the monitored delivery conversion rate increases, more orders can be further reduced for delivery personnel with a higher reach consistency rate until the dispatch quantity of this delivery personnel is adjusted to the dispatch threshold, and the dispatch of orders to this delivery personnel is stopped.

[0120] The specific formula can be expressed as shown in Formula 4:

[0121]

[0122] Among them, r1 can refer to the first correlation coefficient between the reach consistency rate and the dispatch conversion rate, r2 can refer to the second correlation coefficient between the delivery distance and the dispatch conversion rate, a1 can refer to the reach consistency rate of the delivery personnel, and b1 can refer to the delivery distance of the delivery personnel. It can refer to the average delivery distance of the delivery personnel.

[0123] (4) When the first correlation coefficient r1 is less than the second correlation coefficient r2, and r1 and r2 are both negatively correlated, it means that the higher the delivery personnel's reach consistency rate, the lower the delivery conversion rate, and the closer the delivery personnel's delivery distance, the lower the delivery conversion rate, and the positive impact of the delivery personnel's delivery distance on the delivery conversion rate is greater than the impact of the reach consistency rate on the delivery conversion rate. At this time, the dispatch quantity can be adjusted based on r2 as the main condition. Since the second correlation coefficient determines the degree of correlation between the delivery distance and the delivery conversion rate, the number of orders assigned to the delivery personnel with a closer delivery distance can be reduced at this time, and the delivery conversion rate can be monitored in real time. If the monitored delivery conversion rate increases, more orders can be further reduced for the delivery personnel with a closer delivery distance until the dispatch quantity of this delivery personnel is adjusted to the dispatch threshold, and the dispatch of orders to this delivery personnel is stopped.

[0124] The specific formula can be expressed as shown in Formula 5:

[0125]

[0126] Among them, r1 can refer to the first correlation coefficient between the reach consistency rate and the dispatch conversion rate, r2 can refer to the second correlation coefficient between the delivery distance and the dispatch conversion rate, a1 can refer to the reach consistency rate of the delivery personnel, and b1 can refer to the delivery distance of the delivery personnel. It can refer to the average delivery distance of the delivery personnel.

[0127] (5) When the first correlation coefficient r1 is greater than the second correlation coefficient r2, and r1 is positively correlated and r2 is negatively correlated, it means that the higher the delivery personnel's reach consistency rate, the higher the delivery conversion rate, and the shorter the delivery personnel's delivery distance, the lower the delivery conversion rate, and the positive impact of the delivery personnel's reach consistency rate on the delivery conversion rate is greater than the impact of the delivery distance on the delivery conversion rate. At this time, the dispatch volume can be adjusted based on r1 as the main condition. Since the first correlation coefficient determines the degree of correlation between the reach consistency rate and the delivery conversion rate, more orders can be allocated to delivery personnel with a higher reach consistency rate. At the same time, the delivery conversion rate can be monitored in real time. If the monitored delivery conversion rate increases, more orders can be allocated to delivery personnel with a higher reach consistency rate until the dispatch volume of this delivery personnel is adjusted to the dispatch threshold, and the allocation of orders to this delivery personnel is stopped.

[0128] The specific formula can be expressed as shown in Formula 6:

[0129]

[0130] Among them, r1 can refer to the first correlation coefficient between the reach consistency rate and the dispatch conversion rate, r2 can refer to the second correlation coefficient between the delivery distance and the dispatch conversion rate, a1 can refer to the reach consistency rate of the delivery personnel, and b1 can refer to the delivery distance of the delivery personnel. It can refer to the average delivery distance of the delivery personnel.

[0131] (6) When the first correlation coefficient r1 is less than the second correlation coefficient r2, and r1 is negatively correlated and r2 is positively correlated, it means that the higher the delivery personnel's reach consistency rate, the lower the delivery conversion rate, but the closer the delivery personnel's delivery distance, the higher the delivery conversion rate, and the positive impact of the delivery personnel's delivery distance on the delivery conversion rate is greater than the impact of the reach consistency rate on the delivery conversion rate. At this time, the dispatch quantity can be adjusted based on r2 as the main condition. Since the second correlation coefficient determines the degree of correlation between the delivery distance and the delivery conversion rate, more orders can be allocated to delivery personnel with a closer delivery distance, and the delivery conversion rate can be monitored in real time. If the monitored delivery conversion rate increases, more dispatch quantities can be added to the delivery personnel with a closer delivery distance until the dispatch quantity of this delivery personnel is adjusted to the dispatch threshold, and the dispatch of orders to this delivery personnel is stopped.

[0132] The specific formula can be expressed as shown in Formula 7:

[0133]

[0134] Among them, r1 can refer to the first correlation coefficient between the reach consistency rate and the dispatch conversion rate, r2 can refer to the second correlation coefficient between the delivery distance and the dispatch conversion rate, a1 can refer to the reach consistency rate of the delivery personnel, and b1 can refer to the delivery distance of the delivery personnel. It can refer to the average delivery distance of the delivery personnel.

[0135] In actual applications, the determination of the order quantity threshold to be adjusted can be expressed as obtaining the order quantity corresponding to the highest order conversion rate in the order data for the delivery personnel, and using the order quantity corresponding to the highest order conversion rate as the order quantity threshold, so as to dynamically adjust the order quantity of the delivery personnel based on the order weight until the adjusted order quantity reaches the order quantity threshold.

[0136] In a preferred embodiment, since the delivery conversion rate of each delivery personnel is counted in real time, the currently determined order volume threshold is not necessarily the latest threshold. At this time, after adjusting the delivery personnel's order volume to reach the order volume threshold, the order volume corresponding to the highest order conversion rate in the delivery personnel's order data can be obtained again, and the order volume corresponding to the highest order conversion rate is used as the order volume threshold; and based on the correlation coefficient method again, the first correlation coefficient is calculated using the reach consistency rate and the order conversion rate, and the second correlation coefficient is calculated using the delivery distance and the order conversion data, and then, based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient are used to set the order weight, and the delivery personnel's order volume is dynamically adjusted based on the order weight again until the adjusted order volume reaches the order volume threshold.

[0137] For example, assuming that the initial dispatch volume of a delivery person is 100 orders, the reach consistency rate is 0.9, the first correlation coefficient r1 between the delivery person's reach consistency rate and the delivery person's dispatch conversion rate is 0.7, the second correlation coefficient r2 between the delivery person's delivery distance and the delivery person's dispatch conversion rate is 0.4, and the delivery person's delivery distance b1 is 5 kilometers, and the average delivery distance of the delivery person is If the distance is 4 kilometers, the adjusted dispatch volume is: 100*(1+0.9*0.7+(0.4 / 0.7)*((5-4) / 5)=170. Assuming the dispatch threshold is 200, since the first correlation coefficient r1>the second correlation coefficient r2, and r1 and r2 are both less than 1, that is, r1 and r2 are negatively correlated, then the dispatch volume can be adjusted based on r1 as the main condition, and the number of assigned orders can be reduced for delivery personnel with a higher reach consistency rate. At the same time, the delivery conversion rate can be monitored in real time. If the monitored delivery conversion rate increases, more orders can be reduced for delivery personnel with a higher reach consistency rate until the dispatch volume of this delivery personnel is adjusted to the dispatch threshold, and the allocation of orders to this delivery personnel is stopped.

[0138] In an embodiment of the present invention, based on a first correlation between reach data indicating the service status of the delivery personnel for the delivery order and dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, and a second correlation between the determined delivery distance and the dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, the dispatch quantity of the delivery personnel is dynamically adjusted, and the delivery personnel are dispatched using the adjusted dispatch quantity. By comprehensively considering the impact of the delivery personnel's delivery distance and reach data on the dispatch conversion data, the dispatch quantity of the delivery personnel is reversely dispatched. While improving delivery efficiency and ensuring the degree of activation of the delivery personnel for the delivery order to ensure the quality of task completion, user satisfaction is also indirectly improved based on the involved reach data.

[0139] In order to make those skilled in the art aware of the reverse dispatching method based on reach data proposed in this application, refer to Figure 3 , shows a schematic diagram of an application scenario of reverse dispatching based on reach data provided by an embodiment of the present invention, and the following description is given in conjunction with this application scenario:

[0140] Currently, after a carrier's SIM card order is generated, it's typically allocated to logistics partners based on a certain percentage. Once the SIM card order arrives at a delivery point, it's randomly assigned to a delivery person, or the delivery person grabs the order themselves. The delivery person then calls the user to schedule a visit and completes the face-to-face activation service. This entire process lacks an effective dispatch system, and activation is entirely dependent on the delivery person's discretion. If a delivery person intentionally tries to mislead a user into abandoning activation, unnecessary card resources are likely to be wasted.

[0141] The current automatic dispatching system is mainly based on the logistics system or the construction of an optimized delivery route system. That is, by real-time tracking of the location of logistics vehicles or couriers, the optimal route or the delivery personnel closest to the target location is found to complete the dispatch and ensure that the order reaches the user as quickly as possible. However, the reverse dispatching system based on the delivery personnel's contact consistency rate involves less, which is not conducive to the evaluation of the completion quality of the target task.

[0142] One of the core ideas of the embodiments of the present invention is to propose a method for reverse dispatching orders based on the delivery personnel's reach data. By comprehensively considering the delivery distance of the delivery personnel and the impact of the reach data on the dispatch conversion data, the delivery personnel's dispatch volume is reversely dispatched. While improving delivery efficiency and ensuring the delivery personnel's activation level for delivery orders to ensure the quality of task completion, it also indirectly improves user satisfaction based on the reach data involved.

[0143] The reverse dispatching method based on reach data proposed in the embodiment of the present invention can be applied to any door-to-door service industry, such as a dispatching scenario based on reach data and the courier's outbound call data. In this application scenario, a dispatching system 310 is involved. This dispatching system can be constructed based on a system for reverse dispatching based on reach data. This dispatching system can communicate with a pre-established delivery data information library 311, a map API interface 312 required to be called, and an AI outbound call platform 313.

[0144] In this application scenario, each courier has the ability to reach users and activate SIM cards face-to-face, thus forming the courier's reach rate and conversion rate. The courier's reach rate can be expressed as the reach consistency rate used to indicate the courier's service quality for delivery orders, and the courier's conversion rate can be expressed as the degree of activation of the courier for delivery orders.

[0145] Among them, the reach consistency rate can be calculated by the consistent order volume of the courier reach user data and the smart object reach user data, and the ratio of the courier reach user data. It is mainly used to determine whether the courier reach user data is consistent with the smart object reach user data. The higher the consistency rate, the more manual service situations of the courier and the higher the service quality. In actual applications, the smart reach user data can usually be expressed as the number of orders that the intelligent customer service robot or the smart platform virtual image reaches the user. Since it is the order data of the user reached through the AI ​​(Artificial Intelligence) outbound call platform 313, the smart object reach user data is usually the total number of users that the delivery personnel need to reach. At this time, it can be expressed as obtaining AI outbound call data from the outbound call platform 313. The obtained AI outbound call data can refer to the smart object reach user data, and the courier reach user data can be obtained from the pre-established delivery data information library 311.

[0146] The courier conversion rate can be expressed as a delivery person's order conversion rate. This can be expressed by obtaining the number of order activations within the courier's order volume, and then calculating the courier's order conversion rate using the ratio of order activations to the courier's order volume. In practical applications, the delivery volume and activation volume required to calculate the courier conversion rate can be obtained from the pre-established delivery data information library 311.

[0147] In an embodiment of the present invention, in order to improve delivery efficiency and ensure the degree of activation of delivery orders by delivery personnel to ensure the quality of task completion, it is also possible to indirectly improve user satisfaction based on the reach data involved. When adjusting the delivery personnel's order volume, the delivery data and reach data for the delivery personnel can be obtained, so as to introduce the delivery distance and delivery conversion data in the delivery data, as well as the reach data.

[0148] The delivery distance can be obtained by calling the map API 312, that is, the longitude and latitude between the delivery station and the delivery address are obtained through the map API 312, and the delivery distance of the delivery personnel and the average delivery distance of the delivery personnel are calculated through the distance measurement interface.

[0149] Then, the correlation coefficient method can be used to determine the weight values ​​between the reach consistency rate and the dispatch distance and the dispatch conversion rate, and dynamically adjust the dispatch ratio until the dispatch conversion rate reaches the highest within the dispatch volume threshold, which is usually the dispatch volume threshold.

[0150] In specific terms, it can be manifested as establishing a database of courier dispatch volume and dispatch conversion rate information; obtaining the longitude and latitude between the courier's station and the delivery address through the AutoNavi Map API interface, and calculating the courier's delivery distance through the distance measurement interface; then recording the difference between the AI ​​outbound call data and the courier's user reach data; at this time, the number of orders received when the courier's conversion rate is the highest can be calculated as the threshold for the courier's order volume, and using the correlation coefficient method, determine the correlation r1 between the courier's reach consistency rate and the courier's conversion rate, as well as the correlation r2 between the courier's delivery distance and the courier's conversion rate. Then, the dispatch weight can be set according to the correlation, and the dispatch volume can be dynamically adjusted until the dispatch volume threshold is reached and the adjustment ends.

[0151] The dynamic adjustment of the dispatch weights by setting the correlation can refer to the dispatch dimension parameters and algorithm parameters configured by Formulas 2 to 7 in the method embodiments, so as to dynamically adjust the first correlation coefficient and the second correlation coefficient as the dispatch weights according to different size relationships and positive and negative correlations, so as to ensure that the dispatch quantity of the dispatch personnel is adjusted in the direction of the task completion quality, and the dispatch quantity of the delivery personnel is dispatched in the opposite direction.

[0152] As an example, when the first correlation coefficient r1> the second correlation coefficient r2, and r1 and r2 are both positively correlated, the order quantity can be adjusted based on r1 as the main condition. At this time, more orders can be allocated to couriers with higher reach consistency rates, and the courier conversion rate can be monitored in real time. If the conversion rate of the monitored courier increases, more orders can be allocated to the courier with higher reach consistency rates until the order quantity of this courier is adjusted to the order threshold, and the order allocation for this courier is stopped. In another example, when the first correlation coefficient r1< the second correlation coefficient r2, and r1 and r2 are both positively correlated, the order quantity can be adjusted based on r2 as the main condition. At this time, more orders can be allocated to couriers with longer delivery distances, and the courier conversion rate can be monitored in real time. If the conversion rate of the monitored courier increases, more orders can be allocated to couriers with longer delivery distances until the order quantity of this courier is adjusted to the order threshold, and the order allocation for this courier is stopped. As another example, when the first correlation coefficient r1> the second correlation coefficient r2, and r1 and r2 are both negatively correlated, the order quantity can be adjusted based on r1 as the main condition. At this time, the number of orders assigned to couriers with higher reach consistency rates can be reduced, and the courier conversion rate can be monitored in real time. If the conversion rate of the monitored couriers increases, more orders can be further reduced for couriers with higher reach consistency rates until the order quantity for this courier is adjusted to the order threshold, and the order assignment for this courier is stopped. In another example, when the first correlation coefficient r1< the second correlation coefficient r2, and r1 and r2 are both negatively correlated, the order quantity can be adjusted based on r2 as the main condition. At this time, more orders can be further reduced for couriers with shorter delivery distances until the order quantity for this courier is adjusted to the order threshold, and the order assignment for this courier is stopped. In another example, when the first correlation coefficient r1>the second correlation coefficient r2, and r1 is positively correlated and r2 is negatively correlated, the dispatch volume can be adjusted based on r1 as the main condition. At this time, more orders can be allocated to couriers with higher reach consistency rates, and the courier conversion rate can be monitored in real time. If the conversion rate of the monitored courier increases, more dispatch volumes can be added to the courier with higher reach consistency rates until the dispatch volume of this courier is adjusted to the dispatch threshold, and the allocation of orders to this courier is stopped.In another example, when the first correlation coefficient r1 is less than the second correlation coefficient r2, and r1 is negatively correlated and r2 is positively correlated, the order quantity can be adjusted based on r2 as the main condition. At this time, more orders can be allocated to couriers with closer delivery distances, and the courier conversion rate can be monitored in real time. If the conversion rate of the monitored couriers increases, more orders can be allocated to couriers with closer delivery distances until the order quantity of this courier is adjusted to the order dispatch threshold, and the allocation of orders to this courier is stopped.

[0153] In a preferred embodiment, since the delivery conversion rate of each delivery personnel is counted in real time, the currently determined order volume threshold is not necessarily the latest threshold. At this time, after adjusting the delivery personnel's order volume to reach the order volume threshold, the order volume corresponding to the highest order conversion rate in the delivery personnel's order data can be obtained again, and the order volume corresponding to the highest order conversion rate is used as the order volume threshold; and based on the correlation coefficient method again, the first correlation coefficient is calculated using the reach consistency rate and the order conversion rate, and the second correlation coefficient is calculated using the delivery distance and the order conversion data, and then, based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient are used to set the order weight, and the delivery personnel's order volume is dynamically adjusted based on the order weight again until the adjusted order volume reaches the order volume threshold.

[0154] In an embodiment of the present invention, by comparing and analyzing user reach data and AI outbound call system data, that is, monitoring the reach consistency rate data, the courier's dispatch volume can be dynamically adjusted to improve the conversion rate of number card orders, effectively avoid couriers intentionally inducing users to give up activating number cards, resulting in a waste of card resources, and can also reduce the situation where random dispatch or couriers grab orders, resulting in couriers with higher conversion rates not being able to get orders, solve the problem of couriers randomly grabbing orders, and through the dispatch system, within the dispatch volume threshold range, dynamically adjust the dispatch volume based on the set weights to continuously adjust the number of couriers dispatching orders, so that orders always flow to couriers with higher conversion rates, avoiding the problem of grabbing but not delivering. And by comprehensively considering the impact of the courier's delivery distance and reach consistency rate on the conversion rate, the courier's dispatch volume is reversely dispatched, while improving delivery efficiency and ensuring the courier's activation level (i.e., conversion rate) of the delivery order to ensure the quality of task completion, it also indirectly improves user satisfaction based on the involved reach consistency rate.

[0155] It should be noted that for the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0156] Reference Figure 5 , shows a structural block diagram of an embodiment of a reverse dispatching device based on reach data of the present invention, which is applied to a dispatching system and may specifically include the following modules:

[0157] Data acquisition module 501 is used to obtain dispatch data and reach data for delivery personnel; dispatch data includes delivery distance and dispatch conversion data used to indicate the degree of activation of delivery personnel for delivery orders; reach data is used to indicate the service performance of delivery personnel for delivery orders;

[0158] A correlation determination module 502 is configured to determine a first correlation between reach data and order conversion data, and a second correlation between delivery distance and order conversion data;

[0159] The dispatch module 503 is used to adjust the dispatch quantity of the delivery personnel according to the first correlation and the second correlation, and use the adjusted dispatch quantity to dispatch orders to the delivery personnel.

[0160] In one embodiment of the present invention, the dispatch data includes the number of dispatch orders by the delivery personnel, and the degree of activation of the delivery personnel for the delivery orders is determined based on the dispatch conversion rate. The data acquisition module 501 may include the following submodules:

[0161] The activation quantity acquisition submodule is used to obtain the activation quantity of orders from the delivery personnel's dispatch quantity;

[0162] The dispatch conversion rate generation submodule is used to calculate the dispatch conversion rate of the delivery personnel by using the ratio of the activation quantity of orders and the dispatch quantity of the delivery personnel.

[0163] In one embodiment of the present invention, the reach data includes a reach consistency rate used to indicate the service quality of the delivery personnel for the delivery order. The data acquisition module 501 may include the following submodules:

[0164] The user data acquisition submodule is used to obtain the user data reached by the delivery personnel and the user data reached by the smart objects. The user data reached by the delivery personnel is used to indicate the manual service situation of the delivery personnel, and the user data reached by the smart objects is used to indicate the total number of users that the delivery personnel need to reach.

[0165] The reach consistency rate generation sub-module is used to calculate the reach consistency rate of the delivery personnel by using the consistent order volume of the delivery personnel's reach user data and the smart object's reach user data, and the ratio of the delivery personnel's reach user data.

[0166] In one embodiment of the present invention, the dispatch conversion data includes the dispatch conversion rate, and the reach data includes the reach consistency rate; the first correlation is determined based on a first correlation coefficient between the reach consistency rate and the dispatch conversion rate, and the second correlation is determined based on a second correlation coefficient between the delivery distance and the dispatch conversion rate;

[0167] The correlation determination module 502 may include the following submodules:

[0168] A first correlation coefficient calculation submodule is used to calculate a first correlation coefficient for describing the degree of correlation between the reach data and the dispatch conversion data based on a correlation coefficient method using the reach consistency rate and the dispatch conversion rate;

[0169] The second correlation coefficient calculation submodule is used to use the delivery distance and the dispatch conversion rate to calculate a second correlation coefficient based on the correlation coefficient method to characterize the degree of correlation between the delivery distance and the dispatch conversion data.

[0170] In one embodiment of the present invention, the first correlation is determined based on the first correlation coefficient, and the second correlation is determined based on the second correlation coefficient; the dispatch module 503 may include the following submodules:

[0171] A dispatch weight setting submodule, configured to set the dispatch weight using the first correlation coefficient and the second correlation coefficient based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation;

[0172] The dynamic adjustment submodule is used to dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0173] In one embodiment of the present invention, the dispatch conversion data includes the dispatch conversion rate, and the dynamic adjustment submodule may include the following units:

[0174] a dispatch quantity threshold determination unit, configured to obtain the dispatch quantity corresponding to the highest dispatch conversion rate in the dispatch data for the delivery personnel, and use the dispatch quantity corresponding to the highest dispatch conversion rate as the dispatch quantity threshold;

[0175] The dynamic adjustment unit is used to dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0176] In one embodiment of the present invention, the dynamic adjustment unit may include the following subunits:

[0177] The order quantity threshold re-determination subunit is used to obtain the order quantity corresponding to the highest order conversion rate in the order data for the delivery personnel after the order quantity of the delivery personnel is adjusted to reach the order quantity threshold, and use the order quantity corresponding to the highest order conversion rate as the order quantity threshold;

[0178] The correlation coefficient re-determination sub-unit is used to calculate the first correlation coefficient again based on the correlation coefficient method using the reach consistency rate and the dispatch conversion rate, and to calculate the second correlation coefficient using the delivery distance and the dispatch conversion data;

[0179] The sub-unit is dynamically adjusted again, and is used to set the dispatch weight based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, and dynamically adjust the dispatch quantity of the delivery personnel based on the dispatch weight again until the adjusted dispatch quantity reaches the dispatch quantity threshold.

[0180] In an embodiment of the present invention, based on a first correlation between reach data indicating the service status of the delivery personnel for the delivery order and dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, and a second correlation between the determined delivery distance and the dispatch conversion data indicating the degree of activation of the delivery personnel for the delivery order, the dispatch quantity of the delivery personnel is dynamically adjusted, and the delivery personnel are dispatched using the adjusted dispatch quantity. By comprehensively considering the impact of the delivery personnel's delivery distance and reach data on the dispatch conversion data, the dispatch quantity of the delivery personnel is reversely dispatched. While improving delivery efficiency and ensuring the degree of activation of the delivery personnel for the delivery order to ensure the quality of task completion, user satisfaction is also indirectly improved based on the involved reach data.

[0181] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0182] An embodiment of the present invention further provides an electronic device, including:

[0183] It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the various processes of the above-mentioned reverse dispatching method embodiment based on contact data and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0184] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned reverse dispatching method embodiment based on contact data are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0185] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0186] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatus, or computer program products. Thus, embodiments of the present invention may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0187] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0188] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0189] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0190] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0191] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "includes," or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0192] The above is a detailed introduction to a reverse dispatching method based on reach data, a reverse dispatching device based on reach data, a corresponding electronic device and a corresponding computer storage medium provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A reverse dispatching method based on reach data, characterized in that: Applied to an order dispatching system, the method includes: Obtaining dispatch data and reach data for delivery personnel; the dispatch data includes delivery distance and dispatch conversion data used to indicate the degree of activation of delivery personnel for delivery orders; the reach data is used to indicate the service status of delivery personnel for delivery orders; Determining a first correlation between the reach data and the dispatch conversion data, and determining a second correlation between the delivery distance and the dispatch conversion data; Adjusting the dispatch quantity of the delivery personnel according to the first correlation and the second correlation, and dispatching orders to the delivery personnel using the adjusted dispatch quantity; The dispatch conversion data includes a dispatch conversion rate, and the reach data includes a reach consistency rate; the first correlation is determined based on a first correlation coefficient between the reach consistency rate and the dispatch conversion rate, and the second correlation is determined based on a second correlation coefficient between the dispatch distance and the dispatch conversion rate; Determining the first correlation between the reach data and the order conversion data, and determining the second correlation between the delivery distance and the order conversion data, includes: The reach consistency rate and the order conversion rate are used to calculate a first correlation coefficient based on a correlation coefficient method, which is used to characterize the degree of correlation between the reach data and the order conversion data; and / or, using the delivery distance and the dispatch conversion rate, calculating a second correlation coefficient based on a correlation coefficient method for describing the degree of correlation between the delivery distance and dispatch conversion data; the dispatch data includes the number of dispatches by the delivery personnel, and the degree of activation of the delivery personnel for delivery orders is determined based on the dispatch conversion rate; Obtain dispatch conversion data for delivery personnel, including: Obtain the number of activated orders from the delivery personnel's order volume; The delivery personnel's order conversion rate is calculated by using the ratio of the activation volume of the order and the number of orders dispatched by the delivery personnel; The reach data includes a reach consistency rate used to represent the service quality of the delivery personnel for the delivery order. Acquiring the reach data for the delivery personnel includes: Obtaining delivery personnel contact user data and smart object contact user data; wherein the delivery personnel contact user data is used to indicate the delivery personnel's manual service situation, and the smart object contact user data is used to indicate the total number of users that the delivery personnel needs to contact; The delivery personnel's reach consistency rate is calculated by using the consistent order volume of the delivery personnel's reach user data and the smart object's reach user data, and the ratio of the delivery personnel's reach user data.

2. The method according to claim 1, characterized in that The first correlation is determined based on a first correlation coefficient, and the second correlation is determined based on a second correlation coefficient; and adjusting the number of orders assigned to the delivery personnel based on the first correlation and the second correlation includes: Based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient are used to set the order dispatch weight; The dispatch quantity of the delivery personnel is dynamically adjusted based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

3. The method according to claim 2, characterized in that The dispatch conversion data includes a dispatch conversion rate, and the dynamically adjusting the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches a dispatch quantity threshold includes: Obtaining the dispatch volume corresponding to the highest dispatch conversion rate in the dispatch data for the delivery personnel, and using the dispatch volume corresponding to the highest dispatch conversion rate as the dispatch volume threshold; The dispatch quantity of the delivery personnel is dynamically adjusted based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold.

4. The method according to claim 2 or 3, characterized in that The dynamically adjusting the dispatch quantity of the delivery personnel based on the dispatch weight until the adjusted dispatch quantity reaches the dispatch quantity threshold includes: After adjusting the dispatch volume of the delivery personnel to reach the dispatch volume threshold, obtaining again the dispatch volume corresponding to the highest dispatch conversion rate in the dispatch data for the delivery personnel, and using the dispatch volume corresponding to the highest dispatch conversion rate as the dispatch volume threshold; Again based on the correlation coefficient method, the first correlation coefficient is calculated using the reach consistency rate and the dispatch conversion rate, and the second correlation coefficient is calculated using the dispatch distance and dispatch conversion data; Again based on the values ​​of the first correlation coefficient and the second correlation coefficient and the positive and negative correlation, the first correlation coefficient and the second correlation coefficient are used to set the dispatch weight, and again based on the dispatch weight, the dispatch quantity of the delivery personnel is dynamically adjusted until the adjusted dispatch quantity reaches the dispatch quantity threshold.

5. A reverse dispatching device based on reach data, characterized in that: Applied to an order dispatching system, the device comprises: A data acquisition module is used to obtain dispatch data and reach data for delivery personnel; the dispatch data includes delivery distance and dispatch conversion data used to indicate the degree of activation of delivery personnel for delivery orders; the reach data is used to indicate the service status of delivery personnel for delivery orders; a correlation determination module, configured to determine a first correlation between the reach data and the dispatch conversion data, and to determine a second correlation between the dispatch distance and the dispatch conversion data; an order dispatching module, configured to adjust the order dispatch quantity of the delivery personnel according to the first correlation and the second correlation, and dispatch orders to the delivery personnel using the adjusted order dispatch quantity; The dispatch conversion data includes the dispatch conversion rate, and the reach data includes the reach consistency rate. The first correlation is determined based on a first correlation coefficient between the reach consistency rate and the dispatch conversion rate, and the second correlation is determined based on a second correlation coefficient between the delivery distance and the dispatch conversion rate. The relevance determination module includes the following submodules: A first correlation coefficient calculation submodule is used to calculate a first correlation coefficient for describing the degree of correlation between the reach data and the dispatch conversion data based on a correlation coefficient method using the reach consistency rate and the dispatch conversion rate; A second correlation coefficient calculation submodule is used to calculate a second correlation coefficient based on the correlation coefficient method using the delivery distance and the order conversion rate to characterize the degree of correlation between the delivery distance and the order conversion data; The dispatch data includes the dispatch volume of the delivery personnel, and the activation degree of the delivery personnel for the delivery orders is determined based on the dispatch conversion rate; the data acquisition module includes: An activation quantity acquisition submodule, used to obtain the activation quantity of orders from the delivery personnel's dispatch quantity; A dispatch conversion rate generating submodule is configured to calculate the dispatch conversion rate of a delivery person by using the ratio of the activation quantity of the order and the dispatch quantity of the delivery person; The reach data includes a reach consistency rate used to represent the service quality of the delivery personnel for the delivery order, and the data acquisition module includes: The user data acquisition submodule is used to obtain the user data reached by the delivery personnel and the user data reached by the smart object; wherein the user data reached by the delivery personnel is used to represent the manual service situation of the delivery personnel, and the user data reached by the smart object is used to represent the total number of users that the delivery personnel needs to reach; The reach consistency rate generation submodule is used to calculate the reach consistency rate of the delivery personnel by using the consistent order volume of the delivery personnel's reach user data and the smart object's reach user data, and the ratio of the delivery personnel's reach user data.

6. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of the reverse dispatching method based on reach data as described in any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the reverse dispatching method based on reach data as described in any one of claims 1 to 4.

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