A method and apparatus for evaluating the implementation effectiveness of a service operation.

Abstract

The present application discloses a method and device for evaluating the implementation effect of an operation business of a service. When evaluating the implementation effect of an operation business of a service, the embodiment of the present application adopts the user-side perception depth of the operation business in the service as an evaluation indicator for evaluation. The user-side perception depth of the operation business in the service is determined by the claim rate indicator of the service in a set unit time period. Since the implementation effect of the operation business in the service can be accurately determined based on the user-side total perception depth of the operation business in the service, the evaluation accuracy of the implementation effect of the operation business in the service is improved.

Description

Technical Field

[0001] The present application relates to the field of computer network technology, and in particular to a method and device for evaluating the implementation effect of a service operation business. Background Art

[0002] With the development of computer networks, various applications have emerged in computer networks to provide various services to users. In an application or a web page or website in a computer such as an application, different operating services can be launched online to implement the operating strategies of the operating services and provide corresponding services to users. For example, in an e-commerce service such as a house sale service, different operating services such as a house sale service commitment can be launched online to make a commitment to the house sale service and improve the quality of the house sale service provided to users.

[0003] When the operation service is put into operation, it is necessary to evaluate its implementation effect, specifically, to evaluate its quality penetration effect in the service and obtain evaluation information. This evaluation information can reflect the user's perception rate and perception depth of the operation service in the service, so as to determine the operation direction of the operation service in the subsequent implementation based on this. At present, when evaluating the implementation effect of the operation service in the service, the user's awareness rate is used as the evaluation indicator, and the user's awareness rate is determined by inquiring the user's return visit. This method of evaluating the implementation effect of the operation service in the service makes the evaluation accuracy low and cannot truly reflect the user's perception depth of the operation service in the service. Summary of the invention

[0004] In view of this, an embodiment of the present application provides a method and device for evaluating the implementation effect of an operation business of a service, which can improve the evaluation accuracy of evaluating the implementation effect of the operation business in the service.

[0005] The embodiment of the present application is implemented as follows:

[0006] A method for evaluating the implementation effect of a service operation business, the method comprising:

[0007] Operational business of launching the said service;

[0008] Obtaining a claim rate index of the service in a set unit time period, wherein the claim rate index is a probability value of maintaining user rights and interests according to the service after the user learns that the operation business of the service is online;

[0009] Based on the claim rate indicator, the implementation effect of the operating business in the service is evaluated.

[0010] Optionally, obtaining a claim rate indicator of the service in a set unit time period includes:

[0011] Obtain the measured claim rate and predicted natural claim rate of the previous unit time period of the set unit time period, input them into the set claim rate optimization model, perform prediction, and predict the predicted natural claim rate of the set unit time period;

[0012] Obtaining the operating claim rate of the service in the set unit time period;

[0013] The claim rate index of the service in the set unit time period is determined based on the difference between the operating claim rate in the set unit time period and the predicted natural claim rate.

[0014] Optionally, the obtaining of the measured claim rate and the predicted natural claim rate of the previous unit time period of the set unit time period, inputting them into a set claim rate optimization model for prediction, and predicting the predicted natural claim rate of the set unit time period includes:

[0015] The claim rate optimization model is a prediction model using a single exponential smoothing method, and the measured claim rate and the predicted natural claim rate of the previous unit time period are input into the claim rate optimization model;

[0016] The claim rate optimization model performs a weighted average calculation on the measured claim rate and the predicted natural claim rate of the previous unit time period according to the set smoothing coefficient to obtain a calculation result, and uses the obtained settlement result as a prediction to obtain the predicted natural claim rate in the set unit time period.

[0017] Optionally, obtaining the predicted natural claim rate for the previous unit time period includes:

[0018] Setting a historical time period including a plurality of unit time periods, wherein the last unit time period is included in the historical time period and is the last unit time period;

[0019] a. In the historical time period, two consecutive unit time periods are used as the first unit time period and the second unit time period in chronological order;

[0020] b. obtaining a measured claim rate and a predicted natural claim rate for a first unit time period, and when the first unit time period is the first unit time period in the historical period, setting the predicted claim rate for the first unit time period as the measured claim rate for the first unit time period;

[0021] c. Taking a weighted average of the measured claim rate and the predicted natural claim rate of the first unit time period according to the set smoothing coefficient, and calculating the predicted natural claim rate of the second unit time period;

[0022] d. After obtaining the measured claim rate of the second unit time period, take the second unit time period as the first unit time period, take the subsequent unit time period of the second unit time period as the second unit time period, and return to step c to continue the calculation until the second unit time period is the last unit time period in the historical time period.

[0023] Optionally, when the historical time period is a time period during which the operating service is not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period;

[0024] Or, when the historical time period includes the time period during which the operating business was not online and the time period during which the operating business was online, in response to the first unit time period being within the time period during which the operating business was online, obtaining the measured claim rate of the first unit time period includes: obtaining the operational claim rate of the first unit time period; in response to the first unit time period being within the time period during which the operating business was not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; in response to the second unit time period being within the time period during which the operating business was online, obtaining the policy claim rate of the second unit time period includes: obtaining the operational claim rate of the second unit time period; in response to the second unit time period being within the time period during which the operating business was not online, obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period.

[0025] Optionally, determining the claim rate index of the service in the set unit time period according to the difference between the operating claim rate and the predicted natural claim rate in the set unit time period includes:

[0026] Setting the set unit time period to be within the set detection time period;

[0027] According to the predicted natural claim rate and the corresponding operational claim rate of each continuous unit time period within the detection time period, the difference between the two is calculated, and all the differences of each continuous unit time period within the detection time period are obtained, and all the obtained differences are averaged to obtain the difference mean;

[0028] The obtained mean of the differences is used as an indicator of the claim rate of the service in a set unit time period.

[0029] Optionally, the evaluating the implementation effect of the operating business in the service according to the claim rate indicator further includes:

[0030] Obtaining user-side awareness rate of the operating service;

[0031] The implementation effect of the operating business in the service is evaluated based on the user-end awareness rate of the operating business and the claim rate indicator.

[0032] Optionally, obtaining the user terminal awareness rate of the operating service includes:

[0033] Obtaining from the user terminal running the service whether the user terminal is aware of the operation service information by querying the user terminal;

[0034] A statistical calculation is performed on whether all the acquired user terminals know the operation service information, and a probability value of the user terminals knowing the operation service is obtained.

[0035] Optionally, the evaluating the implementation effect of the operating business in the service according to the user terminal awareness rate and the claim rate indicator includes:

[0036] The implementation effect of the operating business in the service is determined by the evaluation value of the implementation effect of the operating business in the service, and the evaluation value of the implementation effect of the operating business in the service includes the user-side awareness rate and the user-side awareness level value, wherein the claim rate indicator serves as the user-side awareness level value of the implementation effect of the operating business in the service, and the user-side awareness rate serves as the user-side awareness rate of the implementation effect of the operating business in the service.

[0037] An electronic device, comprising:

[0038] processor;

[0039] A memory stores a program, wherein the program is configured to implement the implementation effect evaluation method of the operation business of the service as described in any one of the above when executed by the processor.

[0040] A non-transitory computer-readable storage medium storing instructions, characterized in that when the instructions are executed by a processor, the processor executes a method for evaluating the implementation effect of an operation business of a service as described in any one of the above.

[0041] A computer program product includes a computer program or instructions, which, when executed by a processor, implements the steps of the method for evaluating the implementation effect of the operation business of the service described in any one of the above.

[0042] As can be seen above, when evaluating the implementation effect of the operating business of the service, the embodiment of the present application adopts the user-side perception depth of the operating business in the service as an evaluation indicator for evaluation. The user-side perception depth of the operating business in the service is determined by the claim rate indicator of the service in a set unit time period. Since the accurate implementation effect of the operating business in the service can be determined based on the user-side total perception depth of the operating business in the service, the evaluation accuracy of the implementation effect of the operating business in the service is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flow chart of a method for evaluating the implementation effect of an operation business of a service provided in an embodiment of the present application;

[0044] Figure 2 A schematic diagram of the structure of an implementation effect evaluation device for an operation business of a service provided in an embodiment of the present application;

[0045] Figure 3 A schematic diagram of an electronic device provided according to another embodiment of the present application. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0048] The technical solution of the present application is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0049] From the background technology, it can be seen that the reason for the low accuracy of the implementation effect of the operation business in the service is: the user-side awareness rate is obtained by inquiring the user-side return visit, and the user-side awareness rate is used as the evaluation indicator. Since the user-side awareness rate is obtained by inquiry, firstly, it is too single, and the user-side is more random when inquiring, which makes it difficult to obtain an accurate user-side awareness rate; secondly, the inquiry method can only be used to know whether the user knows about the operation business, but the degree of user awareness and whether the user has used the operation business in the service after knowing it are not included. Therefore, it is impossible to accurately evaluate the quality penetration effect of the operation business in the service.

[0050] Therefore, in order to solve the above-mentioned problems, the embodiments of the present application use the user-side perception depth of the operating business in the service as an evaluation indicator for evaluation when evaluating the implementation effect of the operating business of the service. The user-side perception depth of the operating business in the service is determined by the claim rate indicator of the service in a set unit time period. Since the implementation effect of the operating business in the service can be accurately determined based on the user-side total perception depth of the operating business in the service, the evaluation accuracy of the implementation effect of the operating business in the service is improved.

[0051] The meaning of the claim rate indicator is: reflecting the probability value of maintaining the user's rights and interests according to the service commitment of the service after the user learns that the service's operating business is online. The claim rate indicator can evaluate the depth of users' knowledge of the operating business and reflect the real purpose and value of the operating business in the service.

[0052] In the embodiment of the present application, the service may be a house sale service, and the service operation business is various service commitment operation strategies in the house sale service, which is not limited here. The service may also be a goods sale service, and the service operation business is various service commitment operation strategies in the goods sale service, etc.

[0053] Furthermore, the above method also includes: obtaining the user-side awareness rate of the operating business; and evaluating the implementation effect of the operating business in the service according to the user-side awareness rate of the operating business and the claim rate index. That is, the implementation effect of the operating business in the service is determined by combining two parts, one of which is the user-side awareness rate of the operating business in the service, and the other is the user-side perception depth of the operating business in the service. This combination method determines the implementation effect of the operating business in the service, and is applied to services with low claim rate indicators, such as house buying and selling services, and the evaluation effect is better.

[0054] Figure 1 A flowchart of a method for evaluating the implementation effect of an operation business of a service provided in an embodiment of the present application, wherein the specific steps include:

[0055] Step 101, launching the operation business of the service;

[0056] Step 102: Obtain a claim rate index of the service in a set unit time period, wherein the claim rate index is a probability value of maintaining user rights and interests according to the service after the user learns that the operation business of the service is online;

[0057] Step 103: Evaluate the implementation effect of the operating business in the service according to the claim rate indicator.

[0058] In the method, obtaining the claim rate index of the service in a set unit time period includes:

[0059] Obtain the measured claim rate and predicted natural claim rate of the previous unit time period of the set unit time period, input them into the set claim rate optimization model, perform prediction, and predict the predicted natural claim rate of the set unit time period;

[0060] Obtaining the operating claim rate of the service in the set unit time period;

[0061] The claim rate index of the service in the set unit time period is determined based on the difference between the operating claim rate in the set unit time period and the predicted natural claim rate.

[0062] Among them, when the operating business has not yet been put into operation in the previous unit time period, the measured claim rate of the previous unit time period is the actual natural claim rate of the previous unit time period; when the operating business has been put into operation in the previous unit time period, the measured claim rate of the previous unit time period is the operational claim rate of the previous unit time period.

[0063] Specifically, the natural claim rate reflects the claim rate of the service when the operating business is not implemented, that is, the probability value of the service maintaining the rights and interests of the user end when the operating business of the service is not online. This is mainly affected by natural objective factors during the service implementation process. There are two types of natural claim rates, one is the actual natural claim rate, which represents the actual measured natural claim rate, and the other is the predicted claim rate, which represents the predicted natural claim rate. The operational claim rate reflects the claim rate when the operating business is implemented, which is not only affected by natural objective factors, but also by the implementation of the operating business.

[0064] Here, the difference between the predicted natural claim rate and the operational claim rate for a set unit time period can be directly used as the claim rate indicator for the operating business in the set unit time period.

[0065] The set compensation rate optimization model is a prediction model using a first-order exponential smoothing method, and the compensation rate optimization model adopts the formula: F(t+1)=αY(t)+(1-α)F(t);

[0066] Among them, Y(t) is the measured claim rate of the previous unit time period, F(t) is the predicted natural claim rate of the previous unit time period, α is the smoothing coefficient, which is set according to the empirical value and can be set to 0.3 here, and F(t+1) is the calculated predicted natural claim rate in the set unit time period.

[0067] That is to say, the predicted natural claim rate in the set unit time period includes:

[0068] The measured claim rate and the predicted natural claim rate of the previous unit time period are weighted averaged according to the set smoothing coefficient to obtain a calculation result, and the calculation result is used as a prediction to obtain the predicted natural claim rate in the set unit time period.

[0069] In this method, in order to make the predicted natural claim rate of the set unit time period more accurate, a historical time period can be set, the historical time period includes multiple unit time periods, the previous unit time period is the last unit time period in the historical time period, and the obtaining of the natural claim rate of the previous unit time period also includes:

[0070] a. In the historical time period, two consecutive unit time periods are used as the first unit time period and the second unit time period in chronological order;

[0071] b. obtaining a measured claim rate and a predicted natural claim rate for a first unit time period, and when the first unit time period is the first unit time period in the historical period, setting the predicted natural claim rate for the first unit time period as the measured claim rate for the first unit time period;

[0072] c. Taking a weighted average of the measured claim rate and the predicted natural claim rate of the first unit time period according to the set smoothing coefficient to obtain the predicted natural claim rate of the second unit time period;

[0073] d. After obtaining the measured claim rate of the second unit time period, take the second unit time period as the first unit time period, take the subsequent unit time period of the second unit time period as the second unit time period, and return to step c for calculation until the second unit time period is the last unit time period in the historical time period.

[0074] In this way, after an iterative calculation of the predicted natural claim rate for a set unit time period over a historical time period, the predicted natural claim rate for the unit time period is more accurate.

[0075] In the above process, depending on whether the operating business is online, the measured claim rate of the first unit time period and the measured claim rate of the second unit time period are divided into two situations:

[0076] In the first case, when the historical time period is a time period during which the operating service is not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period;

[0077] The second situation: when the historical time period includes the time period when the operating business is not online and the time period when the operating business is online, in response to the first unit time period being within the time period when the operating business is online, obtaining the measured claim rate of the first unit time period includes: obtaining the operational claim rate of the first unit time period; in response to the first unit time period being within the time period when the operating business is not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; in response to the second unit time period being within the time period when the operating business is online, obtaining the policy claim rate of the second unit time period includes: obtaining the operational claim rate of the second unit time period; in response to the second unit time period being within the time period when the operating business is not online, obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period.

[0078] In this way, if the second situation is implemented, the operating business can still be predicted for a long historical period from the time it has never been put into operation to the time after it is put into operation, and the claim rate indicator can be calculated based on this, making the evaluation more accurate.

[0079] In the embodiment of the present application, the unit time period can be set to one week, and the historical time period can be set to half a year, which is not limited here.

[0080] In the method, determining the claim rate index of the service in the set unit time period according to the difference between the predicted natural claim rate and the operational claim rate in the set unit time period includes:

[0081] Setting the set unit time period to be within the set detection time period;

[0082] According to the predicted natural claim rate and the corresponding operational claim rate of each continuous unit time period within the detection time period, the difference between the two is calculated, and all the differences of each continuous unit time period within the detection time period are obtained, and all the obtained differences are averaged to obtain the difference mean;

[0083] The obtained mean of the differences is used as an indicator of the claim rate of the service in a set unit time period.

[0084] In this way, since the claim rate index of the operating business in the set unit time period is obtained based on the average of the claim rate indexes of multiple unit time periods, it is more accurate and can accurately reflect the user-side awareness of the operating business of the service in the set unit time period.

[0085] The embodiment of the present application uses a claim rate optimization model to predict the predicted natural claim rate for a set unit time period. The measured claim rates of each week in the past six months can be used to predict the predicted natural claim rate for the future week through a single exponential smoothing method. The embodiment of the present application then compares the predicted natural claim rate for the future week with the operational claim rate for the future week for the same period to obtain the difference, and repeats the above process within the detection time period to calculate the average difference in claim rates for each future week within the detection time period, so as to evaluate whether the user-side awareness of the operational service has been significantly improved after it goes online.

[0086] It can be seen that the embodiment of the present application adopts a comparison of the difference between the operating claim rate of a set unit time period and the predicted natural claim rate to determine the claim rate index of the set unit time period, thereby realizing a contemporaneous comparison during the implementation of the operating business, and solving the problem of using a claim rate comparison method before and after the implementation of the operating business without considering the impact of changes in natural laws over time.

[0087] The claim rate optimization model of the embodiment of the present application adopts a single exponential smoothing method to perform a weighted average of the actual natural claim rates of continuous unit time periods within the historical time period, that is, the predicted natural claim rate at time t+1 is the weighted average of the predicted natural claim rate at time t and the measured claim rate at time t, where t is the previous unit time period. The longer the historical time period is set, the longer the time interval between a certain unit time period in the historical time period and the set unit time period, and the more the weight presentation index of the certain unit time period decreases in the natural claim rate of the set unit time period. This can avoid the exponential impact of time fluctuations on the predicted natural claim rate of the set unit time period on the one hand, and on the other hand, it can also make the prediction of the predicted natural claim rate of the set unit time period more accurate.

[0088] The claim rate optimization model of the embodiment of the present application can be set to a weekly unit time period, that is, it is calculated in a weekly dimension, using the actual natural claim rate of each week in the past six months, using a single exponential smoothing method to predict the predicted natural claim rate of each week, and then using the measured claim rate and predicted natural claim rate of the previous week, using a single exponential smoothing method to predict the predicted natural claim rate of the set week. This makes the amount of data in the prediction process very sufficient, including the measured claim rate before and after the operation of the operating business goes online, effectively avoiding the problem of large fluctuations in the predicted natural claim rate caused by fluctuations in the operating environment of the operating business in different periods.

[0089] In this method, the claim rate index obtained mainly describes the user-side awareness of the implementation effect of the operation business in the service. Therefore, in order to make the evaluation of the implementation effect of the operation business in the service more accurate, it is also necessary to evaluate the user-side awareness of the implementation effect of the operation business in the service. Specifically, the evaluation value of the implementation effect of the operation business in the application is composed of two parts, one is the user-side awareness rate of the operation business, and the other is the user-side perception depth of the operation business. The user-side perception depth of the operation business is determined by the claim rate index.

[0090] In the method, evaluating the implementation effect of the operating business in the service based on the claim claim rate index also includes: obtaining the user-side awareness rate of the operating business; and evaluating the implementation effect of the operating business in the service based on the user-side awareness rate of the operating business and the claim claim rate index.

[0091] The acquiring of the user terminal awareness rate of the operating service includes:

[0092] Obtaining from the user terminal running the service whether the user terminal is aware of the operation service information by querying the user terminal;

[0093] A statistical calculation is performed on whether all the acquired user terminals know the operation service information, and a probability value of the user terminals knowing the operation service is obtained.

[0094] In this case, in the method, evaluating the implementation effect of the operating business in the service according to the user terminal awareness rate and the claim rate indicator includes:

[0095] The implementation effect of the operating business in the service is determined by the evaluation value of the implementation effect of the operating business in the service, and the evaluation value of the implementation effect of the operating business in the service includes the user-side awareness rate and the user-side awareness level value, wherein the claim rate indicator serves as the user-side awareness level value of the implementation effect of the operating business in the service, and the user-side awareness rate serves as the user-side awareness rate of the implementation effect of the operating business in the service.

[0096] The following is a specific example to illustrate the embodiments of the present application in detail.

[0097] In this specific example, the service is a house buying and selling service, and the operating business set up is a second-hand service commitment strategy. The second-hand service commitment strategy needs to be put online and the implementation effect of the second-hand service commitment strategy needs to be evaluated, that is, the quality penetration effect of the second-hand service commitment strategy in the house buying and selling service needs to be evaluated.

[0098] The first step is to obtain the user-side awareness rate of the second-hand service commitment strategy in the house buying and selling service.

[0099] The second step is to obtain the claim rate indicator of the house buying and selling service in a set unit time period.

[0100] Claim rate index = number of claim work orders for houses that meet service commitments in second-hand house sales / total transaction volume of houses that meet service commitments in second-hand house sales.

[0101] In this step, it is taken as an example that the second-hand service commitment strategy was not put into operation in the previous unit time period, and the measured claim rate of the previous unit time period is the actual natural claim rate of the previous unit time period.

[0102] The implementation process of this step includes:

[0103] The actual natural claim rate and predicted natural claim rate of the previous unit time period are obtained, and input into the set claim rate optimization model for prediction, so as to obtain the predicted natural claim rate of the set unit time period;

[0104] Obtain the operating claim rate of the house buying and selling service in a set unit time period;

[0105] Based on the difference between the predicted natural claim rate and the operational claim rate in the set unit time period, the claim rate indicator of the house buying and selling service in the set unit time period is determined.

[0106] Here, the actual natural claim rate refers to the claim rate before the second-hand service commitment strategy is launched, which is mainly affected by natural objective factors.

[0107] The predicted natural claim rate is obtained by using the exponential smoothing method, and the formula used is:

[0108] F(t+1)=αY(t)+(1-α)F(t);

[0109] Among them, Y(t) is the actual natural claim rate in the previous unit time period, F(t) is the predicted natural claim rate in the previous unit time period, α is the smoothing coefficient, which is set according to the empirical value, 0<α<1, and F(t+1) is the calculated natural claim rate in the set unit time period.

[0110] Let F1 be the actual natural claim rate in the first week of the historical time period (half year), that is, F1 = Y1. Therefore,

[0111] The natural claim rate for the second week is: F(2) = αY(1) + (1-α)F(1) = αY(1) + (1-α)Y(1) = Y(1);

[0112] The natural claim rate in the third week is: F(3) = αY(2) + (1-α)F(2) = αY(2) + (1-α)Y(1);

[0113] The natural claim rate for the fourth week is: F(4) = αY(3) + (1-α)F(3) = αY(3) + α(1-α)Y(2) + (1-α) 2 Y(1);

[0114] …;

[0115] By analogy, any F(t+1) is the weighted average of the actual natural claim rates of all previous unit time periods. The key is to choose an appropriate smoothing coefficient α.

[0116] Setting the unit time period to the 26th week, the predicted natural claim rate is 0.527%, as shown in Table 1.

[0117]

[0118]

[0119] Table 1

[0120] From the comparison of the squares of the errors in Table 1, it can be seen that when α = 0.3, the predicted natural claim rate is better.

[0121] Similarly, the predicted natural claim rate for each week can be predicted.

[0122] Of course, after the second-hand service commitment strategy is launched in the 27th week, the predicted natural claim rate can continue to be predicted for each week after the 27th week. In the specific prediction, the measured claim rate of the previous unit time period is used as the operational claim rate of the previous unit time period. In this case, according to the calculation rules, the predicted natural claim rate of each week after the 27th week still includes the relevant information of the actual natural claim rate of each week before the 26th week, so it still reflects the change in the claim rate indicator of the second-hand service commitment strategy from before it was launched to after it was launched.

[0123] The operational claim rate refers to the claim rate after the second-hand service commitment strategy is launched. It is affected by natural and objective factors as well as the operation of the strategy.

[0124] The new user side knows that the strategy was implemented in the 26th week. After three months of implementation, the implementation effect was evaluated. The comparison of the operational claim rate and the predicted natural claim rate in the same week is shown in Table 2:

[0125]

[0126]

[0127] Table 2

[0128] Table 2 is used to perform a significance test on the mean to determine whether the second-hand service commitment strategy has significantly improved the user-side awareness depth. If it has significantly improved, the mean of the improvement is avg(Y)-avg(F).

[0129] In this step, since the second-hand service commitment strategy has been put into operation in the 27th week, the measured claim rate of the previous week and the predicted natural claim rate are used to predict the predicted natural claim rate of subsequent weeks. The measured claim rate of the previous week is the operational claim rate actually measured in the previous week.

[0130] The third step is to evaluate the implementation effect of the operation business in the service based on the user-end awareness rate of the operation business and the claim rate index in a set unit time period.

[0131] Figure 2 A schematic diagram of the structure of an implementation effect evaluation device for an operation business of a service provided in an embodiment of the present application, as shown in the figure, includes: an operation unit, an acquisition unit and an evaluation unit, wherein:

[0132] An operation unit, used for launching and operating the service;

[0133] An acquisition unit, used to acquire a claim rate index of the service in a set unit time period, wherein the claim rate index is a probability value of maintaining user rights and interests according to the service after the user learns that the operation business of the service is online;

[0134] An evaluation unit is used to evaluate the implementation effect of the operating business in the service according to the claim rate indicator.

[0135] In the device, the acquisition unit is also used to obtain the measured claim rate and the predicted natural claim rate of the previous unit time period of the set unit time period, input them into the set claim rate optimization model, perform prediction, and predict the predicted natural claim rate of the set unit time period; obtain the operating claim rate of the service in the set unit time period; and determine the claim rate index of the service in the set unit time period based on the difference between the operating claim rate and the predicted natural claim rate of the set unit time period.

[0136] In the device, the acquisition unit is also used to obtain the measured claim rate and the predicted natural claim rate of the previous unit time period of the set unit time period, input them into the set claim rate optimization model, and perform prediction. The predicted natural claim rate of the set unit time period includes: the claim rate optimization model is a prediction model using a single exponential smoothing method, and the measured claim rate and the predicted natural claim rate of the previous unit time period are input into the claim rate optimization model; the claim rate optimization model performs a weighted average calculation on the measured claim rate and the predicted natural claim rate of the previous unit time period according to the set smoothing coefficient to obtain a calculation result, and the obtained settlement result is used as a prediction to obtain the predicted natural claim rate in the set unit time period.

[0137] In the device, the acquisition unit is also used for acquiring the predicted natural claim rate of the previous unit time period, including: setting a historical time period including multiple unit time periods, the previous unit time period is included in the historical time period and is the last unit time period; a. In the historical time period, two consecutive unit time periods are used as the first unit time period and the second unit time period in chronological order; b. Obtaining the measured claim rate and the predicted natural claim rate of the first unit time period, when the first unit time period is the first unit time period in the historical period, setting the predicted claim rate of the first unit time period as the measured claim rate of the first unit time period; c. Taking the measured claim rate and the predicted natural claim rate of the first unit time period as the weighted average according to the set smoothing coefficient, and calculating the predicted natural claim rate of the second unit time period; d. After obtaining the measured claim rate of the second unit time period, taking the second unit time period as the first unit time period, taking the subsequent unit time period of the second unit time period as the second unit time period, and returning to step c to continue the calculation until the second unit time period is the last unit time period in the historical time period.

[0138] Specifically, when the historical time period is a time period during which the operating service is not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period;

[0139] Or, when the historical time period includes the time period during which the operating business was not online and the time period during which the operating business was online, in response to the first unit time period being within the time period during which the operating business was online, obtaining the measured claim rate of the first unit time period includes: obtaining the operational claim rate of the first unit time period; in response to the first unit time period being within the time period during which the operating business was not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; in response to the second unit time period being within the time period during which the operating business was online, obtaining the policy claim rate of the second unit time period includes: obtaining the operational claim rate of the second unit time period; in response to the second unit time period being within the time period during which the operating business was not online, obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period.

[0140] In the device, the acquisition unit is also used to set the set unit time period within the set detection time period; according to the predicted natural claim rate and the corresponding operational claim rate of each continuous unit time period within the detection time period, the difference between the two is calculated to obtain all the differences of each continuous unit time period within the detection time period, and all the obtained differences are averaged to obtain the difference mean; the obtained difference mean is used as the claim rate indicator of the service in the set unit time period.

[0141] In the device, the acquisition unit is further used to acquire the user-end awareness rate of the operating service; and evaluate the implementation effect of the operating service in the service according to the user-end awareness rate of the operating service and the claim rate index.

[0142] Specifically, the acquisition unit is also used to obtain the user terminal awareness rate of the operation service, including: obtaining whether the user terminal running the service knows the operation service information by inquiry; performing statistical calculations on whether all the user terminals obtained know the operation service information, and obtaining the probability value of the user terminal knowing the operation service.

[0143] Furthermore, the acquisition unit is also used to evaluate the implementation effect of the operating business in the service based on the user-side awareness rate and the claim claim rate index, including: the implementation effect of the operating business in the service is determined by an evaluation value of the implementation effect of the operating business in the service, and the evaluation value of the implementation effect of the operating business in the service includes a user-side awareness rate and a user-side awareness level value, wherein the claim claim rate index serves as the user-side awareness level value of the implementation effect of the operating business in the service, and the user-side awareness rate serves as the user-side awareness rate of the implementation effect of the operating business in the service.

[0144] In another embodiment of the present application, an electronic device is also provided, characterized in that it includes an electronic device, including: a processor; a memory, storing a program, and the program is configured to implement an implementation effect evaluation method of the operating business of the service as described above when executed by the processor.

[0145] In another embodiment of the present application, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores instructions, which, when executed by a processor, cause the processor to execute a method for evaluating the implementation effect of an operational business of a service in the aforementioned embodiment. Figure 3 A schematic diagram of an electronic device provided by another embodiment of the present application. Figure 3As shown, another embodiment of the present application further provides an electronic device, which may include a processor 301, wherein the processor 301 is used to execute the steps of the implementation effect evaluation method of the above-mentioned service operation business. Figure 3 It can also be seen that the electronic device provided in the above embodiment also includes a non-transitory computer-readable storage medium 302, on which a computer program is stored. When the computer program is run by the processor 301, the steps of the implementation effect evaluation method of the operation business of the above-mentioned service are executed.

[0146] Specifically, the non-transitory computer-readable storage medium 302 can be a general storage medium, such as a mobile disk, a hard disk, FLASH, a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), or a portable compact disk read-only memory (CD-ROM), etc. When the computer program on the non-transitory computer-readable storage medium 302 is executed by the processor 301, it can trigger the processor 601 to execute the various steps of the above-mentioned method for evaluating the implementation effect of an operation business of a service.

[0147] In practical applications, the non-transitory computer-readable storage medium 302 may be included in the device / apparatus / system described in the above embodiment, or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, each step in the above method for evaluating the implementation effect of an operation business of a service can be executed.

[0148] Yet another embodiment of the present application provides a computer program product, including a computer program or instructions, which, when executed by a processor, implements each step of the above-mentioned method for evaluating the implementation effect of an operation business of a service.

[0149] The flow chart and block diagram in the accompanying drawings of the present application show the possible architecture, function and operation of the system, method and computer program product according to the various embodiments disclosed in the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the box can also occur in the order of the standards in different figures. For example, the boxes represented by two connections can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0150] Those skilled in the art will appreciate that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations or combinations are not explicitly described in the present application. In particular, without departing from the spirit and teachings of the present application, the features described in the various embodiments and / or claims of the present application may be combined and / or combined in a variety of ways, and all of these combinations and / or combinations fall within the scope disclosed in the present application.

[0151] Specific embodiments are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core ideas of the present application, and is not used to limit the present application. For those skilled in the art, changes can be made in the specific implementation methods and application scopes according to the ideas, spirits and principles of the present application, and any modifications, equivalent substitutions, improvements, etc. made by them should be included in the scope of protection of the present application.

Claims

1. A method for evaluating the implementation effect of a service operation business, characterized in that: The method comprises: Operational business of launching the said service; Obtaining a claim rate index of the service in a set unit time period, wherein the claim rate index is a probability value of maintaining user rights and interests according to the service after the user learns that the operation business of the service is online; Based on the claim rate indicator, evaluate the implementation effect of the operating business in the service. Wherein, obtaining the claim rate index of the service in a set unit time period includes: Obtain the measured claim rate and predicted natural claim rate of the previous unit time period of the set unit time period, input them into the set claim rate optimization model, perform prediction, and predict the predicted natural claim rate of the set unit time period; Obtaining the operating claim rate of the service in the set unit time period; Determine the claim rate index of the service in the set unit time period according to the difference between the operating claim rate in the set unit time period and the predicted natural claim rate, The measured claim rate and predicted natural claim rate of the previous unit time period of the set unit time period are obtained, and input into the set claim rate optimization model for prediction. The predicted natural claim rate of the set unit time period is predicted to include: The claim rate optimization model is a prediction model using a single exponential smoothing method, and the measured claim rate and the predicted natural claim rate of the previous unit time period are input into the claim rate optimization model; The claim rate optimization model performs weighted average calculation on the measured claim rate and the predicted natural claim rate of the previous unit time period according to the set smoothing coefficient to obtain a calculation result, and uses the obtained settlement result as a prediction to obtain the predicted natural claim rate in the set unit time period.

2. The method according to claim 1, characterized in that The obtaining of the predicted natural claim rate for the previous unit time period includes: Setting a historical time period including a plurality of unit time periods, wherein the last unit time period is included in the historical time period and is the last unit time period; a. In the historical time period, two consecutive unit time periods are used as the first unit time period and the second unit time period in chronological order; b. obtaining a measured claim rate and a predicted natural claim rate for a first unit time period, and when the first unit time period is the first unit time period in the historical period, setting the predicted claim rate for the first unit time period as the measured claim rate for the first unit time period; c. Taking a weighted average of the measured claim rate and the predicted natural claim rate of the first unit time period according to the set smoothing coefficient, and calculating the predicted natural claim rate of the second unit time period; d. After obtaining the measured claim rate of the second unit time period, take the second unit time period as the first unit time period, take the subsequent unit time period of the second unit time period as the second unit time period, and return to step c to continue the calculation until the second unit time period is the last unit time period in the historical time period.

3. The method according to claim 2, characterized in that When the historical time period is a time period during which the operating service is not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period; Or, when the historical time period includes the time period during which the operating business was not online and the time period during which the operating business was online, in response to the first unit time period being within the time period during which the operating business was online, obtaining the measured claim rate of the first unit time period includes: obtaining the operational claim rate of the first unit time period; in response to the first unit time period being within the time period during which the operating business was not online, obtaining the measured claim rate of the first unit time period includes: obtaining the actual natural claim rate of the first unit time period; in response to the second unit time period being within the time period during which the operating business was online, obtaining the policy claim rate of the second unit time period includes: obtaining the operational claim rate of the second unit time period; in response to the second unit time period being within the time period during which the operating business was not online, obtaining the measured claim rate of the second unit time period includes: obtaining the actual natural claim rate of the second unit time period.

4. The method according to claim 1, characterized in that Determining the claim rate index of the service in the set unit time period according to the difference between the operating claim rate in the set unit time period and the predicted natural claim rate includes: Setting the set unit time period to be within the set detection time period; According to the predicted natural claim rate and the corresponding operational claim rate of each continuous unit time period within the detection time period, the difference between the two is calculated, and all the differences of each continuous unit time period within the detection time period are obtained, and all the obtained differences are averaged to obtain the difference mean; The obtained mean of the differences is used as an indicator of the claim rate of the service in a set unit time period.

5. The method according to claim 1, characterized in that The evaluating the implementation effect of the operating business in the service according to the claim rate indicator also includes: Obtaining user-side awareness rate of the operating service; The implementation effect of the operating business in the service is evaluated based on the user-end awareness rate of the operating business and the claim rate indicator.

6. The method according to claim 5, characterized in that The evaluating the implementation effect of the operation business in the service according to the user terminal awareness rate and the claim rate indicator includes: The implementation effect of the operating business in the service is determined by the evaluation value of the implementation effect of the operating business in the service, and the evaluation value of the implementation effect of the operating business in the service includes the user-side awareness rate and the user-side awareness level value, wherein the claim rate indicator serves as the user-side awareness level value of the implementation effect of the operating business in the service, and the user-side awareness rate serves as the user-side awareness rate of the implementation effect of the operating business in the service.

7. An electronic device, characterized in that: An electronic device comprising: processor; A memory storing a program, wherein the program is configured to implement the implementation effect evaluation method of the service operation business according to any one of claims 1 to 6 when executed by the processor.

8. A non-transitory computer-readable storage medium storing instructions, characterized in that: When the instructions are executed by a processor, the processor executes the method for evaluating the implementation effect of the operation business of the service according to any one of claims 1 to 6.

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