Mobile Terminal Recommendation Method, Device, and Readable Storage Medium

Abstract

The present application discloses a mobile terminal recommendation method, device, and readable storage medium. The mobile terminal recommendation method includes: obtaining usage data and after-sales data of a terminal to be evaluated, obtaining common information of the user associated with the terminal to be evaluated according to the usage data, and recommending a device corresponding to the common information to the associated user based on the usage data, the after-sales data, and the common information. The technical problem in the prior art that a new mobile terminal cannot be automatically recommended to a user is solved.

Description

Technical Field

[0001] This application relates to the technical field of big data applications, and in particular, to a method, device, and readable storage medium for recommending mobile terminals. Background Art

[0002] Currently, the field of big data applications is becoming more and more extensive. Among them, one of the fields of big data applications is the use of big data to understand and meet customer needs. Currently, in the prior art, when recommending a mobile terminal device replacement service to a user of a mobile terminal device, the user needs to actively initiate an operation to replace the mobile terminal device, and the user needs to input their personal interests themselves in order to give a new device recommendation suitable for the user. That is, in the prior art, it is impossible to automatically identify whether the user needs a mobile terminal device replacement service and automatically recommend a new device to the user. Therefore, there is a technical problem in the prior art that a new mobile terminal cannot be automatically recommended to the user. Summary of the Invention

[0003] The main purpose of this application is to provide a method, device, and readable storage medium for recommending mobile terminals, aiming to solve the technical problem in the prior art that a new mobile terminal cannot be automatically recommended.

[0004] To achieve the above object, an embodiment of this application provides a method for recommending a mobile terminal. The method for recommending a mobile terminal is applied to a mobile terminal recommendation device, and the method for recommending a mobile terminal includes:

[0005] Obtain the usage data and after-sales data of the terminal to be evaluated;

[0006] According to the usage data, obtain the common information of the user associated with the terminal to be evaluated;

[0007] Based on the usage data, the after-sales data, and the common information, recommend a device corresponding to the common information to the associated user.

[0008] Optionally, the step of recommending a device corresponding to the common information to the associated user based on the usage data, the after-sales data, and the common information includes:

[0009] Analyze the usage data and the after-sales data to obtain a comprehensive loss score of the mobile terminal;

[0010] Based on the comprehensive loss score, recommend a device corresponding to the common information to the associated user.

[0011] Optionally, the usage data includes a usage loss value and a usage loss weight value, and the after-sales data includes an after-sales loss value and an after-sales loss weight value.

[0012] Optionally, after the step of analyzing the usage data and the after-sales data to obtain the comprehensive loss score of the mobile terminal, the following steps are included:

[0013] Analyze the comprehensive loss score to determine the required device.

[0014] Optionally, the device may be a component or a whole machine.

[0015] Optionally, the usage data includes a usage loss value and a usage loss weight value, and the after-sales data includes an after-sales loss value and an after-sales loss weight value.

[0016] The steps of obtaining the usage data and the after-sales data of the terminal to be evaluated include:

[0017] Based on the mobile terminal device data in the preset sales end, determine the device usage time of the mobile terminal device;

[0018] Based on the device usage time, calculate the usage loss value and the usage loss weight value;

[0019] Based on the user behavior data in the preset after-sales end, determine the device health status of the mobile terminal device;

[0020] Based on the device health status, calculate the after-sales loss value and the after-sales loss weight value.

[0021] Optionally, the step of recommending the device corresponding to the common information to the associated user based on the usage data, the after-sales data, and the common information includes:

[0022] Query the mobile terminal device purchase record of the associated user to obtain the initial device;

[0023] Based on the user hobby information, screen the initial device to obtain the device, and based on the usage data and the after-sales data, recommend the device to the associated user.

[0024] Optionally, regularly detect the mobile terminal and recommend relevant replacement information.

[0025] This application also provides a mobile terminal recommendation device. The mobile terminal recommendation device is applied to a mobile terminal recommendation device. The mobile terminal recommendation device includes:

[0026] A first acquisition module for acquiring the usage data and the after-sales data of the terminal to be evaluated;

[0027] A second acquisition module for acquiring the common information of the associated user of the terminal to be evaluated according to the usage data;

[0028] A recommendation module, configured to recommend, to the associated user, a device corresponding to the common information based on the usage data, the after-sales data, and the common information.

[0029] Optionally, the recommendation module includes:

[0030] An analysis sub-module, configured to analyze the usage data and the after-sales data to obtain a comprehensive loss score of the mobile terminal;

[0031] A recommendation sub-module, configured to recommend, to the associated user, a device corresponding to the common information based on the comprehensive loss score.

[0032] Optionally, the recommendation module further includes:

[0033] A determination sub-module, configured to analyze the comprehensive loss score to determine the required device.

[0034] Optionally, the first acquisition module includes:

[0035] A first determination sub-module, configured to determine the device usage time of the mobile terminal device based on the mobile terminal device data in the preset sales end;

[0036] A first calculation sub-module, configured to calculate the usage loss value and the usage loss weight value based on the device usage time;

[0037] A second determination sub-module, configured to determine the device health status of the mobile terminal device based on the user behavior data in the preset after-sales end;

[0038] A second calculation sub-module, configured to calculate the after-sales loss value and the after-sales loss weight value based on the device health status.

[0039] Optionally, the recommendation module further includes:

[0040] A query sub-module, configured to query the purchase record of the mobile terminal device of the associated user to obtain an initial device;

[0041] A screening sub-module, configured to screen the initial device based on the user hobby information to obtain the device, and recommend the device to the associated user based on the usage data and the after-sales data.

[0042] Optionally, the mobile terminal recommendation device further includes:

[0043] ]>A detection sub-module, configured to periodically detect the mobile terminal and recommend relevant replacement information.

[0044] The present application further provides a mobile terminal recommendation device, which includes: a memory, a processor, and a program of the mobile terminal recommendation method stored on the memory and executable on the processor. When the program of the mobile terminal recommendation method is executed by the processor, the steps of the mobile terminal recommendation method as described above can be implemented.

[0045] The present application further provides a readable storage medium, on which a program for implementing the mobile terminal recommendation method is stored. When the program of the mobile terminal recommendation method is executed by the processor, the steps of the mobile terminal recommendation method as described above are implemented.

[0046] The present application first obtains the usage data and after-sales data of the terminal to be evaluated, and then, based on the usage data, obtains the common information of the user associated with the terminal to be evaluated. Furthermore, based on the usage data, the after-sales data, and the common information, the device corresponding to the common information is recommended to the associated user. That is, in the present application, first, the usage data and after-sales data of the terminal to be evaluated are obtained, and then, based on the usage data, the common information of the user associated with the terminal to be evaluated is obtained. Furthermore, based on the usage data, the after-sales data, and the common information, the recommendation of the device corresponding to the common information to the associated user is performed. That is, by obtaining the usage data, after-sales data, and common information of the terminal to be evaluated, the present application can automatically recommend the device corresponding to the common information to the associated user. Therefore, the technical problem in the prior art that a new mobile terminal cannot be automatically recommended to a user is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application and used together with the specification to explain the principles of the present application.

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0049] Figure 1 It is a schematic flowchart of the usage embodiment based on the mobile terminal recommendation method of the present application;

[0050] Figure 2 It is a schematic flowchart of the after-sales embodiment based on the mobile terminal recommendation method of the present application;

[0051] Figure 3 It is a schematic diagram of the device structure of the hardware operating environment involved in the method of the embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] It should be understood that the specific embodiments described herein are merely for explaining this application and are not used to limit this application.

[0053] An embodiment of this application provides a method for recommending a mobile terminal. The method for recommending a mobile terminal based on a mobile terminal is applied to a device for recommending a mobile terminal based on a mobile terminal. In the usage embodiment of the method for recommending a mobile terminal based on a mobile terminal in this application, with reference to Figure 1 , the method for recommending a mobile terminal based on a mobile terminal includes:

[0054] Step S10, obtaining usage data and after-sales data of the terminal to be evaluated;

[0055] In this embodiment, it should be noted that the usage data includes a usage loss value and a usage loss weight value, and the after-sales data includes an after-sales loss value and an after-sales loss weight value. To obtain the usage data and after-sales data of the terminal to be evaluated, specifically, based on the mobile terminal device data in a preset sales end, the usage loss value and the usage loss weight value are calculated through a preset usage data algorithm, and based on the user behavior data in a preset after-sales end, the after-sales loss value and the after-sales loss weight value are calculated through a preset after-sales data algorithm.

[0056] Among them, the preset sales end includes an offline sales end or an online sales end. The mobile terminal device data includes data such as the device activation time and the total value of the device. The usage loss value is the usage value lost by the mobile terminal device due to use or the percentage value of the value in the total value of the mobile terminal device. The usage loss weight value is a measurement value for evaluating the proportion of the usage loss value in the total value lost by the mobile terminal device. The preset after-sales end includes an offline sales end or an online sales end. The user behavior data includes relevant data such as detection, reservation, consultation, and repair. The after-sales loss value is the after-sales value lost by the mobile terminal device due to detection and repair or the percentage value of the after-sales value in the total value of the mobile terminal device. The after-sales loss weight value is a measurement value for evaluating the proportion of the after-sales loss value in the total value lost by the mobile terminal device. Among them, the total value lost by the mobile terminal device includes the usage loss value and the detection and repair loss value, and the usage loss value is the usage loss value. The preset usage data algorithm includes a usage loss value algorithm and a usage loss weight value algorithm.

[0057] Among them, the usage data includes a usage loss value and a usage loss weight value, and the after-sales data includes an after-sales loss value and an after-sales loss weight value.

[0058] The step of obtaining the usage data and after-sales data of the terminal to be evaluated includes:

[0059] Step S11: Determine the device usage time of the mobile terminal device based on the mobile terminal device data in the preset sales end.

[0060] In this embodiment, the mobile terminal device data includes data such as device activation time and total device value. Based on the mobile terminal device data in the preset sales end, determine the device usage time of the mobile terminal device. Specifically, first obtain the current time through the time display in the mobile terminal device, and then based on the device activation time, perform a subtraction operation on the current time and the device activation time to obtain the usage time of the mobile terminal device. For example, assume that the device activation time is July 8, 2016, and the current time is July 8, 2019, then the usage time of the mobile terminal device is 36 months. Among them, assume that the usage time of the mobile terminal device is 35 months and X days and less than 36 months, then it is determined as 36 months.

[0061] Step S12: Calculate the usage loss value and usage loss weight value of the mobile terminal device based on the device usage time.

[0062] In this embodiment, calculate the usage loss value and usage loss weight value of the mobile terminal device based on the device usage time. Specifically, based on the device usage time, calculate the usage loss value through the usage loss value algorithm and calculate the usage loss weight value through the usage loss weight value algorithm. That is, by inputting the device usage time into the usage weight relation formula corresponding to the usage weight correspondence and the usage loss relation formula corresponding to the usage loss correspondence, and then obtain the usage loss weight value and the usage loss value. And if the device usage time is 0, both the usage loss weight value and the usage loss value are 0. For example, assume that the usage loss value algorithm is that for every 6 - month increase, the usage loss value increases by 5%, and the usage loss weight value algorithm is that for every ⑥ - month increase, the usage loss weight value increases by 1. If the device usage time is 24 months, then the usage loss value is 20% and the usage loss weight value is 4.

[0063] Step S13: Determine the device health status of the mobile terminal device based on the user behavior data in the preset after - sales end.

[0064] In this embodiment, based on the user behavior data in the preset after-sales end, the device health status of the mobile terminal device is determined. Specifically, based on the detection and repair times in the user behavior data, the device health status of the mobile terminal device is determined by a preset determiner. Among them, when the detection and repair times of the mobile terminal device is 0, the device health status of the mobile terminal device is 100%. And the preset determiner includes the corresponding relationship formula between the detection and repair times and the device health status of the mobile terminal device. That is, when the detection and repair times are input into the preset determiner, the preset judge can output the device health status of the mobile terminal device. For example, assume that the corresponding relationship formula is that when the detection and repair times increase by 1 time, the device health status of the mobile terminal device decreases by 5%. If the detection and repair times are 2 times, the device health status of the mobile terminal device is 90%.

[0065] Step S14, based on the device health status, calculate the after-sales loss value and the after-sales loss weight value of the mobile terminal device.

[0066] In this embodiment, based on the device usage time, calculate the usage loss value and the usage loss weight value of the mobile terminal device. Specifically, based on the device usage time, calculate the after-sales loss value through the after-sales loss value algorithm and calculate the after-sales loss weight value through the after-sales loss weight value algorithm. That is, by inputting the device health status into the after-sales weight relationship formula corresponding to the after-sales weight correspondence and the after-sales loss relationship formula corresponding to the after-sales loss correspondence, the after-sales loss weight value and the after-sales loss value are obtained. And if the device health status is 100%, both the usage loss weight value and the usage loss value are 0. For example, assume that the after-sales loss value algorithm is that when the device health status drops by 10%, the after-sales loss value increases by 5%, and the usage loss weight value algorithm is that when the device health status drops by 10%, the usage loss weight value increases by 1. If the device health status is 80%, it means that the device health status has dropped by 20%, then the after-sales loss value is 10% and the usage loss weight value is 2.

[0067] Step S20, according to the usage data, obtain the common information of the user associated with the terminal to be evaluated;

[0068] In this embodiment, according to the usage data, the common information of the user associated with the terminal to be evaluated is obtained, where the associated user is the user of the terminal to be evaluated. Specifically, the usage data of each software in the mobile terminal device is statistically analyzed by a preset statistical module, where the usage data of each software includes the usage duration information of each software. Further, by analyzing the ranking of the usage duration of each software, the common information corresponding to the terminal to be evaluated is obtained, where the common information refers to the type of user hobbies. For example, assuming that in the usage duration information of each software, the usage duration ranking of the camera software and the video playback software is the user name and the after-sales name, the common information is that the user hobby type is taking pictures and watching videos.

[0069] Step S30: Based on the usage data, the after-sales data, and the common information, recommend to the associated user the device corresponding to the common information.

[0070] In this embodiment, based on the usage data, the after-sales data, and the common information, recommend to the associated user the device corresponding to the common information. Specifically, based on the usage data and the after-sales data, the comprehensive loss degree of the terminal to be evaluated is obtained. When the comprehensive loss degree reaches the preset comprehensive loss degree, recommend to the user the mobile terminal to be recommended corresponding to the user hobby information, where the preset comprehensive loss degree is a quantity related to the comfort of the user using the mobile terminal device. If the comprehensive loss degree is too large, the comfort of the user using the mobile terminal device is poor. That is, when the comprehensive loss degree reaches the preset comprehensive loss degree, the comfort of the user using the mobile terminal device is poor. Specifically, when the comprehensive loss degree reaches the preset comprehensive loss degree, recommend to the user to replace the mobile terminal device through recommendation methods such as sending text messages, making phone calls, and recommending in physical stores, and recommend to the user the mobile terminal to be recommended corresponding to the user hobby information. For example, assuming that the user hobby information is that the user likes taking pictures, recommend to the user a mobile terminal device with a more powerful camera function as the user's actual favorite model.

[0071] Among them, the step of recommending to the associated user the mobile terminal to be recommended corresponding to the user hobby information based on the usage data, the after-sales data, and the user hobby information includes:

[0072] Step S31: Query the purchase record of the mobile terminal device of the associated user to obtain the initial device.

[0073] In this embodiment, query the purchase records of the mobile terminal devices of the associated user to obtain the initial devices. Specifically, query the purchase types of the user's mobile terminal devices, where the purchase types include color types, size types, etc. Based on the purchase types, obtain the initial devices. For example, assume the user has 5 mobile phone purchase records and has purchased sky-blue mobile phones each time. Then the initial device is a sky-blue mobile phone.

[0074] Step S32: Based on the user preference information, screen the initial devices to obtain the devices, and based on the usage data and the after-sales data, recommend the devices to the associated user.

[0075] In this embodiment, it should be noted that the devices can be components or whole machines, such as mobile phone screens, mobile phone batteries, mobile phone whole machines, etc.

[0076] Based on the user preference information, screen the initial devices to obtain the devices, and based on the usage data and the after-sales data, recommend the devices to the associated user. Specifically, based on the user preference information, screen the initial devices, that is, screen the mobile terminals related to the common information in the initial devices, and then obtain the devices. Further, recommend the devices corresponding to the common information to the user through recommendation methods such as text message recommendation and phone call recommendation.

[0077] In addition, in this embodiment, the mobile terminal will also be periodically detected and relevant replacement information will be recommended. Specifically, obtain a preset time period and start timing. Then, every time a preset time period passes, the mobile terminal will be detected once, and based on the detection results, the mobile terminal will be scored to obtain the score corresponding to the mobile terminal. If the score is less than the preset score threshold, relevant replacement information will be recommended to the associated user of the mobile terminal.

[0078] In this embodiment, the usage data and after-sales data of the terminal to be evaluated are first obtained. Then, based on the usage data, the common information of the user associated with the terminal to be evaluated is obtained. Further, based on the usage data, the after-sales data, and the common information, the device corresponding to the common information is recommended to the associated user. That is, in this embodiment, first, the usage data and after-sales data of the terminal to be evaluated are obtained. Then, based on the usage data, the common information of the user associated with the terminal to be evaluated is obtained. Further, based on the usage data, the after-sales data, and the common information, the device corresponding to the common information is recommended to the associated user. That is, by obtaining the usage data, after-sales data, and common information of the terminal to be evaluated, this embodiment can automatically recommend the device corresponding to the common information to the associated user. Therefore, the technical problem in the prior art that a new mobile terminal cannot be automatically recommended to the user is solved.

[0079] Further, referring to Figure 2 , based on the usage embodiment in the present application, in another embodiment of the mobile terminal recommendation method, the step of recommending the to-be-recommended mobile terminal corresponding to the user hobby information to the associated user based on the usage data, the after-sales data, and the user hobby information includes:

[0080] Step A10: Analyze the usage data and the after-sales data to obtain the comprehensive loss score of the mobile terminal;

[0081] In this embodiment, the usage data and the after-sales data are analyzed to obtain the comprehensive loss score of the mobile terminal device. Among them, the usage data includes a usage loss value and a usage loss weight value, and the after-sales data includes an after-sales loss value and an after-sales loss weight value. Specifically, first, the usage loss weight value and the after-sales loss weight value are added to obtain a total loss weight value, and the proportions of the usage loss weight value and the after-sales loss weight value in the total loss weight value are calculated respectively to obtain a usage loss weight proportion and an after-sales loss weight proportion. Then, the sum of the product of the usage loss value and the usage loss weight proportion and the product of the after-sales loss value and the after-sales loss weight proportion is calculated to obtain a comprehensive loss value. Further, by inputting the comprehensive loss value into a preset scoring device, the comprehensive loss score is obtained. Among them, the preset scoring device includes the relationship formula between the comprehensive loss value and the comprehensive loss score. For example, assume that the comprehensive loss value is X%, and the comprehensive loss score is (100 - X) points, where the value of X is greater than or equal to 0 and less than or equal to 100.

[0082] Among them, the usage data includes a usage loss value and a usage loss weight value, and the after-sales data includes an after-sales loss value and an after-sales loss weight value,

[0083] The step of analyzing the usage data and the after-sales data to obtain the comprehensive loss score of the mobile terminal includes:

[0084] Step A11: Determine whether the after-sales loss weight value is zero. When the after-sales loss weight value is zero, analyze the usage loss value to obtain the comprehensive loss score;

[0085] In this embodiment, determine whether the after-sales loss weight value is zero. When the after-sales loss weight value is zero, analyze the usage data to obtain the comprehensive loss score. Specifically, determine whether the after-sales loss weight value is zero. When the after-sales loss weight value is zero, that is, when the number of detection and repair times of the mobile terminal device is 0, at this time, the after-sales loss weight value is 0, then the usage loss value is the comprehensive loss value. Further, analyze the usage data to obtain the comprehensive loss score, that is, input the comprehensive loss value into a preset score calculator to obtain the comprehensive loss score. Among them, the preset score calculator includes the relationship formula between the comprehensive loss value and the comprehensive loss score. For example, assume that the comprehensive loss value is X%, and the comprehensive loss score is (100 - X) points, where the value of X is greater than or equal to 0 and less than or equal to 100.

[0086] Step A12: When the after-sales loss weight value is not zero, analyze and calculate the usage loss weight value and the after-sales loss weight value to obtain the usage loss weight ratio and the after-sales loss weight ratio;

[0087] In this embodiment, when the after-sales loss weight value is not zero, analyze and calculate the usage loss weight value and the after-sales loss weight value to obtain the usage loss weight ratio and the after-sales loss weight ratio. Specifically, when the after-sales loss weight value is not zero, that is, when the number of detection and repair times of the mobile terminal device is not 0, at this time, the after-sales loss weight value is not 0, then calculate the sum of the usage loss weight value and the after-sales loss weight value to obtain the total loss weight value. Further, calculate the ratios of the usage loss weight value and the after-sales loss weight value in the total loss weight value respectively to obtain the usage loss weight ratio and the after-sales loss weight ratio. For example, assume that the usage loss weight value is 9 and the after-sales loss weight value is 1, then the total loss weight value is 10. Therefore, the usage loss weight ratio is 90% and the after-sales weight ratio is 10%.

[0088] Step A13: Calculate the comprehensive loss value according to the usage loss value and the usage loss weight ratio, and the after-sales loss value and the after-sales loss weight ratio;

[0089] In this embodiment, based on the usage loss value and the usage loss weight ratio, as well as the after-sales loss value and the after-sales loss weight ratio, a comprehensive loss value is obtained through calculation. Specifically, based on the usage loss value and the usage loss weight ratio, as well as the after-sales loss value and the after-sales loss weight ratio, the sum of the product of the usage loss value and the usage loss weight ratio and the product of the after-sales loss value and the after-sales loss weight ratio is calculated to obtain the comprehensive loss value. For example, assume that the usage loss value is 20%, the usage loss weight ratio is 80%, the after-sales loss value is 10%, and the after-sales loss weight ratio is 20%. Then the comprehensive loss value is (20% * 80% + 10% * 20%), that is, the comprehensive loss value is 18%.

[0090] Step A14, analyze the comprehensive loss value to obtain the comprehensive loss score.

[0091] In this embodiment, analyze the comprehensive loss value to obtain the comprehensive loss score. Specifically, input the comprehensive loss value into a preset score calculator to obtain the comprehensive loss score. Among them, the preset score calculator includes the relationship formula between the comprehensive loss value and the comprehensive loss score. For example, assume that the comprehensive loss value is X%, and the comprehensive loss score is (100 - X) points, where the value of X is greater than or equal to 0 and less than or equal to 100.

[0092] Among them, after the step of analyzing the usage data and the after-sales data to obtain the comprehensive loss score of the mobile terminal, it includes:

[0093] Step B10, analyze the comprehensive loss score to determine the required equipment.

[0094] Among them, the step of analyzing the comprehensive loss score to determine the required equipment includes:

[0095] Step B11, analyze the comprehensive loss value to obtain the initial comprehensive loss score of the mobile terminal device;

[0096] In this embodiment, when the mobile terminal device has not replaced hardware parts, analyze the comprehensive loss value to obtain the initial comprehensive loss score of the mobile terminal device. Specifically, input the comprehensive loss value into a preset score calculator to obtain the initial comprehensive loss score. Among them, the preset score calculator includes the relationship formula between the comprehensive loss value and the initial comprehensive loss score. For example, assume that the comprehensive loss value is X%, and the initial comprehensive loss score is (100 - X) points, where the value of X is greater than or equal to 0 and less than or equal to 100.

[0097] Step AB12: Obtain the hardware replacement information in the preset after-sales terminal, and analyze the hardware replacement information to obtain the compensation value corresponding to the initial comprehensive loss score;

[0098] In this embodiment, it should be noted that the hardware replacement information includes information such as hardware type and hardware value. Obtain the hardware replacement information in the preset after-sales terminal, and analyze the hardware replacement information to obtain the compensation value corresponding to the initial comprehensive loss score. Specifically, obtain the hardware replacement information in the preset after-sales terminal, compare the replacement hardware value with the current value of the original hardware to obtain the value increment, and compare the value increment with the original total value of the mobile terminal device to obtain the compensation value corresponding to the initial comprehensive loss score. For example, assume that the replacement hardware value is 100, the original hardware value is 100, the comprehensive loss value is 20%, then the current value of the original hardware is 80, the value increment is 20. If the original total value of the mobile terminal device is 1000, and when the comprehensive loss value is 0, the initial comprehensive loss score is 100 points, then the compensation value is 2 points.

[0099] Among them, the steps of obtaining the hardware replacement information in the preset after-sales terminal, and analyzing the hardware replacement information to obtain the compensation value corresponding to the initial comprehensive loss score include:

[0100] Step B121: Obtain the hardware replacement information in the preset after-sales terminal, and analyze the hardware replacement information to obtain the replacement hardware value in the hardware replacement information;

[0101] In this embodiment, it should be noted that the hardware replacement information includes information such as hardware type and hardware value. Obtain the hardware replacement information in the preset after-sales terminal, and analyze the hardware replacement information to obtain the replacement hardware value in the hardware replacement information. Specifically, send an information acquisition request to the preset after-sales terminal, where the information acquisition request includes user information, and then obtain the hardware replacement information. Then, extract the replacement hardware value information in the hardware replacement information to obtain the replacement hardware value in the hardware replacement information.

[0102] Step B122: Compare the replacement hardware value with the current value of the original hardware corresponding to the hardware replacement information to obtain the hardware replacement value increment;

[0103] In this embodiment, the replacement hardware value is compared with the current value of the original hardware corresponding to the hardware replacement information to obtain the value increment of hardware replacement. For example, assume that the replacement hardware value is 100, the original hardware value is 100, and the comprehensive loss value is 20%. Then the current value of the original hardware is 80, and the value increment is 20. If the same hardware is replaced after-sales, and at this time, the comprehensive loss value is 40%, so the increased value of the damage value is 20%. The current value of the hardware used for this replacement is 80, and the value increment of the after-sales secondary replacement is also 20.

[0104] Step B123: Compare the value increment of hardware replacement with the original total value of the mobile terminal device to obtain the compensation value corresponding to the initial comprehensive loss score.

[0105] In this embodiment, the value increment of hardware replacement is compared with the original total value of the mobile terminal device to obtain the compensation value corresponding to the initial comprehensive loss score. Specifically, calculate the ratio of the value increment of hardware replacement to the original total value of the mobile terminal device, and multiply the ratio by 100 points to obtain the compensation value corresponding to the initial comprehensive loss score.

[0106] Step B13: Calculate the initial comprehensive loss score and the compensation value to obtain the comprehensive loss score.

[0107] In this embodiment, the initial comprehensive loss score and the compensation value are calculated to obtain the comprehensive loss score. Specifically, perform an addition operation on the initial comprehensive loss score and the compensation value to obtain the comprehensive loss score. For example, assume that the initial comprehensive loss score is 80 points, the usage compensation value for the secondary replacement of the used hardware is 1 point, and the after-sales compensation value for the secondary replacement of the after-sales hardware is 2 points. Then the comprehensive loss score is 83 points.

[0108] Step A20: Based on the comprehensive loss score, recommend the device corresponding to the common information to the associated user.

[0109] In this embodiment, based on the comprehensive loss score, the device corresponding to the common information is recommended to the associated user. The preset comprehensive loss score is a quantity related to the comfort of the user using the mobile terminal device. If the comprehensive loss score is less than the preset comprehensive loss score, the comfort of the user using the mobile terminal device is poor. That is, when the comprehensive loss value of the mobile terminal device is less than the preset comprehensive loss value, the comfort of the user using the mobile terminal device is poor. Specifically, when the comprehensive loss score is less than the preset comprehensive loss score, the user is recommended to replace the mobile terminal device through recommendation methods such as sending text messages, making phone calls, and recommending in physical stores, and the user's actual preferred model corresponding to the user's hobby information is recommended to the user. For example, assuming that the user's hobby information is that the user likes taking pictures, the user's actual preferred model recommended to the user is a mobile terminal device with a more powerful camera function.

[0110] In this embodiment, by analyzing the usage data and the after-sales data, the comprehensive loss score of the mobile terminal is obtained. Then, based on the comprehensive loss score, the device corresponding to the common information is recommended to the associated user. That is, after analyzing the usage data and the after-sales data to obtain the comprehensive loss score in this embodiment, a comparison is made between the comprehensive loss score and the preset comprehensive score. When the comprehensive loss score is less than the preset comprehensive loss score, the device corresponding to the common information is recommended to the associated user. This embodiment provides a method for determining whether the user needs a mobile terminal to be recommended, and based on the judgment result, the device can be automatically recommended to the associated user. Therefore, it lays a foundation for solving the technical problem in the prior art that the new mobile terminal cannot be automatically recommended to the user.

[0111] Refer to Figure 3 , Figure 3 which is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of the present application.

[0112] As Figure 3 shown, the mobile terminal recommendation device may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0113] Optionally, the mobile terminal recommendation device may further include a target user interface, a network interface, a camera, an RF (Radio Frequency) circuit, sensors, an audio circuit, a WiFi module, and so on. The target user interface may include a display screen and an input unit such as a keyboard. Optionally, the target user interface may further include a standard wired interface and a wireless interface. The network interface may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0114] Those skilled in the art can understand that Figure 3 the structure of the mobile terminal recommendation device shown in does not limit the mobile terminal recommendation device. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0115] Such as Figure 3 As shown, in the memory 1005, which is a computer-readable storage medium, there may be an operating system, a network communication module, and a mobile terminal recommendation program. The operating system is a program that manages and controls the hardware and software resources of the mobile terminal recommendation device and supports the operation of the mobile terminal recommendation program and other software and / or programs. The network communication module is used to implement communication between components inside the memory 1005 and communication between other hardware and software in the mobile terminal recommendation system.

[0116] In Figure 3 the mobile terminal recommendation device shown, the processor 1001 is used to execute the mobile terminal recommendation program stored in the memory 1005 to implement the steps of the mobile terminal recommendation method described in any one of the above.

[0117] The specific implementation manner of the mobile terminal recommendation device in this application is basically the same as that of each embodiment of the above mobile terminal recommendation method, and will not be elaborated here.

[0118] This application embodiment also provides a mobile terminal recommendation device. The mobile terminal recommendation device is applied to a mobile terminal recommendation device, and the mobile terminal recommendation device includes:

[0119] A first acquisition module, configured to acquire usage data and after-sales data of the terminal to be evaluated;

[0120] A second acquisition module, configured to acquire the common information of the user associated with the terminal to be evaluated according to the usage data;

[0121] A recommendation module, configured to recommend devices corresponding to the common information to the associated user based on the usage data, the after-sales data, and the common information.

[0122] Optionally, the recommendation module includes:

[0123] An analysis sub-module, configured to analyze the usage data and the after-sales data to obtain a comprehensive loss score of the mobile terminal;

[0124] A recommendation sub-module, configured to recommend the device corresponding to the common information to the associated user based on the comprehensive loss score.

[0125] Optionally, the recommendation module further includes:

[0126] A determination sub-module, configured to analyze the comprehensive loss score to determine the required device.

[0127] Optionally, the first acquisition module includes:

[0128] A first determination sub-module, configured to determine the device usage time of the mobile terminal device based on the mobile terminal device data in the preset sales end;

[0129] A first calculation sub-module, configured to calculate the usage loss value and the usage loss weight value based on the device usage time;

[0130] A second determination sub-module, configured to determine the device health status of the mobile terminal device based on the user behavior data in the preset after-sales end;

[0131] A second calculation sub-module, configured to calculate the after-sales loss value and the after-sales loss weight value based on the device health status.

[0132] Optionally, the recommendation module further includes:

[0133] A query sub-module, configured to query the mobile terminal device purchase record of the associated user to obtain an initial device;

[0134] A screening sub-module, configured to screen the initial device based on the user hobby information to obtain the device, and recommend the device to the associated user based on the usage data and the after-sales data.

[0135] Optionally, the mobile terminal recommendation device further includes:

[0136] A detection sub-module, configured to periodically detect the mobile terminal and recommend relevant replacement information.

[0137] The specific implementation manners of the mobile terminal recommendation device in this application are basically the same as those of the embodiments of the above mobile terminal recommendation method, and will not be elaborated herein.

[0138] An embodiment of the present application provides a readable storage medium, and the readable storage medium stores one or more programs, and the one or more programs can also be executed by one or more processors to implement the steps of the mobile terminal recommendation method described in any one of the above.

[0139] The specific implementation manner of the readable storage medium of the present application is basically the same as that of each embodiment of the above mobile terminal recommendation method, and will not be described in detail here.

[0140] The above are only the preferred embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent scope of the present application.

Claims

1. A mobile terminal recommendation method, characterized in that, The mobile terminal recommendation method includes: Obtaining the usage data and after-sales data of the terminal to be evaluated. The usage data includes a usage loss value and a usage loss weight value, and the after-sales data includes an after-sales loss value and an after-sales loss weight value, including: determining the device usage time of the mobile terminal device based on the mobile terminal device data in the preset sales terminal; calculating the usage loss value and the usage loss weight value based on the device usage time; determining the device health status of the mobile terminal device based on the user behavior data in the preset after-sales terminal; calculating the after-sales loss value and the after-sales loss weight value based on the device health status. The usage loss value is the usage value lost by the mobile terminal device due to use, or the usage loss value is the percentage value of the usage value lost by the mobile terminal device due to use in the total value of the mobile terminal device. The usage loss weight value is a measurement value for evaluating the proportion of the usage loss value in the total value lost by the mobile terminal device. The after-sales loss value is the after-sales value lost by the mobile terminal device due to inspection and repair, or the after-sales loss value is the percentage value of the after-sales value lost by the mobile terminal device due to inspection and repair in the total value of the mobile terminal device. The after-sales loss weight value is a measurement value for evaluating the proportion of the after-sales loss value in the total value lost by the mobile terminal device. Obtaining the common information of the user associated with the terminal to be evaluated according to the usage data. Based on the usage data, the after-sales data, and the common information, recommending the device corresponding to the common information to the associated user, including: Analyzing the usage data and the after-sales data to obtain a comprehensive loss score of the mobile terminal. Based on the comprehensive loss score, recommending the device corresponding to the common information to the associated user, including: Judging whether the after-sales loss weight value is zero. When the after-sales loss weight value is zero, analyzing the usage loss value to obtain the comprehensive loss score. When the after-sales loss weight value is not zero, analyzing and calculating the usage loss weight value and the after-sales loss weight value to obtain the usage loss weight ratio and the after-sales loss weight ratio. Calculating a comprehensive loss value according to the usage loss value and the usage loss weight ratio, and the after-sales loss value and the after-sales loss weight ratio. Analyzing the comprehensive loss value to obtain the comprehensive loss score. When the comprehensive loss score is less than the preset comprehensive loss score, recommending the device corresponding to the common information to the associated user.

2. The mobile terminal recommendation method according to claim 1, wherein After the step of analyzing the usage data and the after-sales data to obtain a comprehensive loss score of the mobile terminal, it includes: Analyzing the comprehensive loss score to determine the required device.

3. The mobile terminal recommendation method according to claim 1, wherein The device is a spare part or a whole machine.

4. The mobile terminal recommendation method according to claim 1, wherein, The step of recommending the device corresponding to the common information to the associated user based on the usage data, the after-sales data, and the common information includes: Querying the mobile terminal device purchase record of the associated user to obtain the initial device. Based on the user's hobby information, screen the initial devices to obtain the devices, and recommend the devices to the associated users based on the usage data and the after-sales data.

5. The mobile terminal recommendation method according to claim 1, wherein, Regularly detect the mobile terminal and recommend relevant replacement information.

6. A mobile terminal recommendation device, characterized in that, The mobile terminal recommendation device includes: a memory, a processor, and a program stored on the memory for implementing the mobile terminal recommendation method. The memory is used to store a program for implementing the mobile terminal recommendation method. The processor is used to execute the program for implementing the mobile terminal recommendation method to implement the steps of the mobile terminal recommendation method according to any one of claims 1 to 5.

7. A readable storage medium, characterized in that, A program for implementing the mobile terminal recommendation method is stored on the readable storage medium, and the program for implementing the mobile terminal recommendation method is executed by the processor to implement the steps of the mobile terminal recommendation method according to any one of claims 1 to 5.

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