阅读说明：本技术 业务事件的归因分析方法、装置、电子设备及存储介质 (Attribution analysis method and device of business event, electronic equipment and storage medium ) 是由 潘琪 于 2021-06-29 设计创作，主要内容包括：本发明涉及大数据技术,揭露了一种业务事件的归因分析方法,包括：获取预设业务事件的样本用户的行为数据,得到样本数据集；根据预设的事件类别和业务目标确定目标关注事件；根据所述预设的事件类别,从所述样本数据集中选择与所述目标关注事件具有前向关联的数据,得到影响事件；对所述影响事件进行归因分析,得到分析结果；基于所述分析结果确定对所述业务目标的优化经营策略。此外,本发明还涉及区块链技术,所述样本用户的行为数据可存储于区块链的节点。本发明还提出一种业务事件的归因分析装置、电子设备以及计算机可读存储介质。本发明可以解决对业务事件缺乏行为动因分析、且分析结果较差的问题。(The invention relates to big data technology, disclosing an attribution analysis method of business events, comprising: acquiring behavior data of a sample user of a preset service event to obtain a sample data set; determining a target attention event according to a preset event category and a service target; selecting data which is in forward correlation with the target attention event from the sample data set according to the preset event category to obtain an influence event; carrying out attribution analysis on the influence events to obtain an analysis result; and determining an optimized operation strategy for the business objective based on the analysis result. In addition, the invention also relates to a block chain technology, and the behavior data of the sample user can be stored in the node of the block chain. The invention also provides an attribution analysis device of the business event, an electronic device and a computer readable storage medium. The invention can solve the problems of lack of behavior cause analysis and poor analysis result of the business event.)

1. A method for attribution analysis of a business event, the method comprising:

acquiring behavior data of a sample user of a preset service event to obtain a sample data set;

determining a target attention event according to a preset event category and a service target;

selecting data which is in forward correlation with the target attention event from the sample data set according to the preset event category to obtain an influence event;

carrying out attribution analysis on the influence events to obtain an analysis result;

and determining an optimized operation strategy for the business objective based on the analysis result.

2. The method for attribution analysis of business events according to claim 1, wherein the obtaining of behavior data of sample users of preset business events to obtain a sample data set comprises:

determining sample users meeting preset conditions of preset business events;

and acquiring behavior data of the sample user in a specified time period from a preset database to obtain a sample data set.

3. The method for attribution analysis of business events according to claim 1, wherein the selecting data having a forward correlation with the target event of interest from the sample data set according to the preset event category, resulting in an impact event, comprises:

dividing the sample data set according to the preset event category and the event occurrence time to obtain a single event set;

and calculating the related possibility of each event in the single event set and the target attention event, and selecting the event corresponding to the related possibility greater than a preset threshold value to obtain an influence event.

4. The attribution analysis method of business events according to claim 1, wherein the attribution analysis of the impact events to obtain an analysis result comprises:

calculating attribution scores of each event in the influence events to the target attention events through a preset probability formula to obtain attribution scores of single events;

determining the optimal operation time of each event in the influence events based on a preset box separation analysis method to obtain the optimal operation time point of a single event;

determining a combined event behavior path based on the attribution score of the single event and the frequency of the single event;

and collecting the attribution score of the single event, the optimal operation time point of the single event and the combined event behavior path to obtain an analysis result.

5. The attribution analysis method of business events according to claim 4, wherein the calculating the attribution score of each event in the influence events to the target attention event through a preset probability formula to obtain the attribution score of a single event comprises:

calculating the occurrence probability of the target attention event when each event in the influence events occurs based on the conditional probability to obtain the influence probability;

calculating the occurrence probability of the target attention event when each event does not occur in the influence events based on the conditional probability to obtain the non-influence probability;

and calculating the attribution score of each event in the influence events by using a preset probability formula according to the influence probability and the non-influence probability to obtain the attribution score of a single event.

6. The attribution analysis method of business events according to claim 4, wherein the determining the optimal business time for each of the impact events based on a preset binning analysis method to obtain the optimal business time point for a single event comprises:

acquiring the number of days between each event in the influence events and the target attention event;

the number of days at intervals is subjected to box separation to obtain an optimal operation interval;

and determining the optimal operation time of the single event based on the optimal operation interval to obtain the optimal operation time point of the single event.

7. The attribution analysis method of business events according to claim 4, wherein the determining a combined event behavior path based on the attribution score of a single event and the frequency of a single event comprises:

acquiring the event with the attribution score larger than a preset threshold value to obtain an attribution event;

obtaining events with the frequency greater than a preset threshold value in the influence events to obtain high-frequency events;

and combining and sequencing the attribution events and the high-frequency events according to the sequence of the occurrence time of the events to obtain a combined event behavior path.

8. An attribution analysis apparatus of business events, the apparatus comprising:

the system comprises a sample data acquisition module, a service event processing module and a service event processing module, wherein the sample data acquisition module is used for acquiring behavior data of a sample user of a preset service event to obtain a sample data set;

the target determination module is used for determining a target attention event according to a preset event type and a service target;

the influence event determining module is used for selecting data which is in forward correlation with the target attention event from the sample data set according to the preset event type to obtain an influence event;

the attribution analysis module is used for carrying out attribution analysis on the influence events to obtain an analysis result;

and the strategy optimization module is used for determining an optimized operation strategy for the business target based on the analysis result.

9. An electronic device, characterized in that the electronic device comprises:

at least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of attribution analysis of business events according to any one of claims 1 to 7.

10. A computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, implements the attribution analysis method for business events according to any one of claims 1 to 7.

Technical Field

The present invention relates to the field of big data technologies, and in particular, to an attribution analysis method and apparatus for a business event, an electronic device, and a computer-readable storage medium.

Background

In an actual service scene, a user often generates a plurality of behavior data, and the analysis of the data can provide a basis for business optimization. For example, in banking, a user may generate a large amount of behavior data when using online banking, and attribution analysis of the behavior data of the user may help the banking to better classify the user and determine the next operation policy.

The traditional data attribution analysis method generally adopts operation analysis models such as RFM (customer relationship management model), AARRR (user life cycle model) and the like, and the models mainly carry out different-dimension layering on users so as to carry out differentiated operation based on different customer groups. However, these models lack the mining of key behavior causes, are limited to solving the channel distribution problem of the advertisement effect, and have poor attribution analysis effect on the business operation.

Disclosure of Invention

The invention provides an attribution analysis method and device of a business event and a computer readable storage medium, and mainly aims to solve the problems that the business event is lack of behavior cause analysis and the analysis result is poor.

In order to achieve the above object, the present invention provides an attribution analysis method for a business event, including:

acquiring behavior data of a sample user of a preset service event to obtain a sample data set;

determining a target attention event according to a preset event category and a service target;

selecting data which is in forward correlation with the target attention event from the sample data set according to the preset event category to obtain an influence event;

carrying out attribution analysis on the influence events to obtain an analysis result;

and determining an optimized operation strategy for the business objective based on the analysis result.

Optionally, the obtaining of the behavior data of the sample user of the preset service event to obtain a sample data set includes:

determining sample users meeting preset conditions of preset business events;

and acquiring behavior data of the sample user in a specified time period from a preset database to obtain a sample data set.

Optionally, the selecting, according to the preset event category, data having a forward correlation with the target attention event from the sample data set to obtain an influence event includes:

dividing the sample data set according to the preset event category and the event occurrence time to obtain a single event set;

and calculating the related possibility of each event in the single event set and the target attention event, and selecting the event corresponding to the related possibility greater than a preset threshold value to obtain an influence event.

Optionally, the attribution analysis of the impact events to obtain an analysis result includes:

calculating attribution scores of each event in the influence events to the target attention events through a preset probability formula to obtain attribution scores of single events;

determining the optimal operation time of each event in the influence events based on a preset box separation analysis method to obtain the optimal operation time point of a single event;

determining a combined event behavior path based on the attribution score of the single event and the frequency of the single event;

and collecting the attribution score of the single event, the optimal operation time point of the single event and the combined event behavior path to obtain an analysis result.

Optionally, the calculating, by a preset probability formula, an attribution score of each event in the impact events to the target attention event to obtain an attribution score of a single event includes:

calculating the occurrence probability of the target attention event when each event in the influence events occurs based on the conditional probability to obtain the influence probability;

calculating the occurrence probability of the target attention event when each event does not occur in the influence events based on the conditional probability to obtain the non-influence probability;

and calculating the attribution score of each event in the influence events by using a preset probability formula according to the influence probability and the non-influence probability to obtain the attribution score of a single event.

Optionally, the determining the optimal operation time of each event in the impact events based on a preset binning analysis method to obtain the optimal operation time point of a single event includes:

acquiring the number of days between each event in the influence events and the target attention event;

the number of days at intervals is subjected to box separation to obtain an optimal operation interval;

and determining the optimal operation time of the single event based on the optimal operation interval to obtain the optimal operation time point of the single event.

Optionally, the determining a combined event behavior path based on the attribution score of the single event and the frequency of the single event comprises:

acquiring the event with the attribution score larger than a preset threshold value to obtain an attribution event;

obtaining events with the frequency greater than a preset threshold value in the influence events to obtain high-frequency events;

and combining and sequencing the attribution events and the high-frequency events according to the sequence of the occurrence time of the events to obtain a combined event behavior path.

In order to solve the above problem, the present invention also provides an attribution analyzing apparatus for business events, the apparatus comprising:

the system comprises a sample data acquisition module, a service event processing module and a service event processing module, wherein the sample data acquisition module is used for acquiring behavior data of a sample user of a preset service event to obtain a sample data set;

the target determination module is used for determining a target attention event according to a preset event type and a service target;

the influence event determining module is used for selecting data which is in forward correlation with the target attention event from the sample data set according to the preset event type to obtain an influence event;

the attribution analysis module is used for carrying out attribution analysis on the influence events to obtain an analysis result;

and the strategy optimization module is used for determining an optimized operation strategy for the business target based on the analysis result.

In order to solve the above problem, the present invention also provides an electronic device, including:

a memory storing at least one instruction; and

and the processor executes the instructions stored in the memory to realize the attribution analysis method of the business event.

In order to solve the above problem, the present invention further provides a computer-readable storage medium, which stores at least one instruction, where the at least one instruction is executed by a processor in an electronic device to implement the attribution analysis method for a business event described above.

The method and the system perform deep mining on the behavior cause of the user who performs attribution analysis on the event to form the preset service, improve the accuracy of the analysis result, find the combination of the behavior cause and the behavior of the user who generates the service target, and provide suggestions for specific operation strategies after the user group is divided; meanwhile, the influence events related to the target events can be expanded according to the service scenes, the setting of the service targets is very flexible, the problem of initialization configuration of the operation strategies of different targets under various service scenes can be solved, and data assistance is provided for fine operation and promotion of target conversion. Therefore, the attribution analysis method, the attribution analysis device, the electronic equipment and the computer readable storage medium for the business events can solve the problems that the business events lack behavior cause analysis and the analysis result is poor.

Drawings

Fig. 1 is a schematic flow chart of an attribution analysis method for a business event according to an embodiment of the present invention;

FIG. 2 is a functional block diagram of an attribution analysis device for business events according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of an electronic device implementing the attribution analysis method for a business event according to an embodiment of the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

The embodiment of the application provides an attribution analysis method for a business event. The main body of the attribution analysis method for the business event includes, but is not limited to, at least one of electronic devices, such as a server and a terminal, capable of being configured to execute the method provided by the embodiment of the present application. In other words, the attribution analysis method for the business event may be performed by software or hardware installed in the terminal device or the server device, and the software may be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.

Referring to fig. 1, a schematic flow chart of an attribution analysis method for a business event according to an embodiment of the present invention is shown. In this embodiment, the attribution analysis method for the business event includes:

and S1, acquiring behavior data of a sample user of the preset service event to obtain a sample data set.

The embodiment of the invention can provide an optimization strategy for the operation of subsequent services by performing attribution analysis on the behavior data of the sample user. Taking the banking business as an example, in the process of banking business, attribution analysis may be required to be performed on some resultant action events or milestone phase events so as to better improve business objectives and user experience, for example, why a user opens an account, why a user changes from a second type of account to a first type of account, under what circumstances a certain service is used, how a user grows into a loyal customer, and the like, and according to the information, a corresponding business strategy may be formulated to improve the banking business service.

The sample user refers to a user meeting a certain preset condition in a preset business event, such as a user who newly opens an account in a business event of opening an account in a certain bank branch. The behavior data are all behavior actions generated by the user in the process of executing the business event, such as the account opening time of the user, whether the user opens a mobile phone bank after account opening, and the like.

In detail, the obtaining of the behavior data of the sample user of the preset service event to obtain the sample data set includes:

determining sample users meeting preset conditions of preset business events;

and acquiring behavior data of the sample user in a specified time period from a preset database to obtain a sample data set.

The preset condition is a condition related to a business target of the preset business event, and if the business target is to improve the financial and purchase rate of a new account opening user, the corresponding preset condition can be the new account opening user of the bank.

Optionally, to further emphasize the privacy and security of the behavior data of the sample user, the behavior data of the sample user may also be obtained from a node of a block chain.

And S2, determining a target attention event according to the preset event type and the business target.

The preset event category in the embodiment of the invention is a plurality of specific service event data sets which are correspondingly sorted out according to the core service function of the actual service and the corresponding service data. As in banking, the business event categories may include a basic account, credit card, financing, loan, LC, bank insurance, issuance, equity, transaction category, browsing category, status category, contact category 12 broad category.

Optionally, the preset event category may be further specifically divided into a target attention event and a forward correlation influence event. For example, when the target interest event is the first purchase of financing, the forward association impact event may include APP financing page browsing, credit card activation, life payment behavior, bank payment binding, wechat public number binding, and the like. Furthermore, the target attention event is a key event which is concerned by a business party, such as a business result event like 'first-class account opening', 'credit card activation', 'current financial purchasing', 'loan application', and the like; the forward correlation influence event is an action event closely related to the target attention event, such as a page browsing event, a payment action and the like, or an operation-related marketing event, such as a touch point, a push, an outbound and the like.

In the embodiment of the invention, the business target is a specific business target related to an actual business, and the target event of interest is a specific event corresponding to the business target and belonging to the preset event category, namely a specific action implemented by the user, and if the business target is to improve the first financial rate of the user, the target event of interest is a data record of any financial product which can be used for the user to purchase a non-current bank deposit for the first time.

In detail, the determining a target event of interest according to a preset event category and a service objective includes:

acquiring a service target based on a preset service event requirement;

and searching a category corresponding to the service target in preset event categories, and determining a target attention event from the sample data set according to the category.

And S3, selecting data which are forward related to the target attention event from the sample data set according to the preset event type, and obtaining an influence event.

In detail, the selecting, according to the preset event category, data having a forward correlation with the target attention event from the sample data set to obtain an influence event includes:

dividing the sample data set according to the preset event category and the event occurrence time to obtain a single event set;

and calculating the related possibility of each event in the single event set and the target attention event, and selecting the event corresponding to the related possibility greater than a preset threshold value to obtain an influence event.

In the embodiment of the invention, the step of dividing the sample data set according to the preset event category and the event occurrence time is that the sample data set is divided according to the preset event category to obtain a sub-event set; and selecting the events with the occurrence time before the target attention event in the sub-event set to obtain the influence events.

Further, the calculating of the related possibility of each event in the single event set and the target attention event is a correlation coefficient calculated by a preset correlation formula, and the correlation coefficient is used as the related possibility of the corresponding event.

In the embodiment of the present invention, the correlation formula is:

where r (X, Y) is a correlation coefficient, X is one event in the single event set and is the target event of interest, Cov (X, Y) is a covariance of data X and data Y, σ_XIs the standard deviation, σ, of the data X_YIs the standard deviation of the data Y.

And S4, performing attribution analysis on the influence events to obtain an analysis result.

In detail, the attribution analysis of the impact events to obtain an analysis result includes:

calculating attribution scores of each event in the influence events to the target attention events through a preset probability formula to obtain attribution scores of single events;

determining the optimal operation time of each event in the influence events based on a preset box separation analysis method to obtain the optimal operation time point of a single event;

determining a combined event behavior path based on the attribution score of the single event and the frequency of the single event;

and collecting the attribution score of the single event, the optimal operation time point of the single event and the combined event behavior path to obtain an analysis result.

In the embodiment of the invention, the analysis result is obtained by acquiring all events contained in the combined event behavior path, correspondingly finding the attribution score and the optimal operation time point corresponding to each event, and sequencing the obtained data into a table according to the path sequence to obtain the analysis result.

Further, the calculating, by a preset probability formula, the attribution score of each event in the influence events to the target attention event to obtain the attribution score of a single event includes:

calculating the occurrence probability of the target attention event when each event in the influence events occurs based on the conditional probability to obtain the influence probability;

calculating the occurrence probability of the target attention event when each event does not occur in the influence events based on the conditional probability to obtain the non-influence probability;

and calculating the attribution score of each event in the influence events by using a preset probability formula according to the influence probability and the non-influence probability to obtain the attribution score of a single event.

Wherein the preset probability formula is as follows:

wherein score (A) is a attribution score of a single event A of the impact events, P (B | A) is the impact probability, i.e., the probability that the target event of interest B occurred when the single event A of the impact events occurred,is the non-influence probability, i.e. the probability that the target attention event B occurs when a single event a does not occur in the influence events.

Further, the determining the optimal operation time of each event in the influence events based on a preset binning analysis method to obtain the optimal operation time point of a single event includes:

acquiring the number of days between each event in the influence events and the target attention event;

the number of days at intervals is subjected to box separation to obtain an optimal operation interval;

and determining the optimal operation time of the single event based on the optimal operation interval to obtain the optimal operation time point of the single event.

According to the method and the device, the occurrence time of each event in the influence events is obtained and is calculated with the occurrence time of the target attention event to obtain the number of interval days, the number of interval days is sorted from small to large, the sorted result is divided into a plurality of subsets, namely the optimal operation interval according to an equidistant box dividing method, and the smooth data value in each optimal operation interval is calculated based on the average value of boxes to obtain the optimal operation time.

Further, the determining a combined event behavior path based on the attribution score of the single event and the frequency of the single event comprises:

acquiring the event with the attribution score larger than a preset threshold value to obtain an attribution event;

obtaining events with the frequency greater than a preset threshold value in the influence events to obtain high-frequency events;

and combining and sequencing the attribution events and the high-frequency events according to the sequence of the occurrence time of the events to obtain a combined event behavior path.

The influence events are sorted from large to small according to the attribution score, and the events corresponding to the attribution scores larger than a preset threshold value are selected from the influence events to obtain the attribution events; sorting the influence events according to the event occurrence frequency from large to small, selecting events with attribution scores larger than a preset threshold value from the influence events, and removing repeated events from the attribution events to obtain high-frequency events; and acquiring the occurrence time of each event in the attribution event and the high-frequency event, and sequencing according to the occurrence time to obtain a combined event behavior path.

And S5, determining an optimized operation strategy for the business target based on the analysis result.

In detail, the embodiment of the present invention determines an optimized business strategy of the business objective based on the attribution score of a single event in the analysis result, combining events of high frequency, and combining event behavior paths, and ensures the achievement of the final business objective.

For example, in an operation scene that a sample data set is a new opened ten-yuan account of a bank branch, due operation analysis shows that a user WeChat public number binding event has obvious influence (due score of 74%) on promotion of financial first purchasing of a user, and for repurchase, the influence of the WeChat binding event is weak, so that a corresponding marketing strategy can be provided for the user who does not yet perform financial first purchasing when binding the WeChat public number, so that the user is stimulated to perform financial first purchasing, user stickiness is improved, and service conversion is realized.

The method and the system perform deep mining on the behavior cause of the user who performs attribution analysis on the event to form the preset service, improve the accuracy of the analysis result, find the combination of the behavior cause and the behavior of the user who generates the service target, and provide suggestions for specific operation strategies after the user group is divided; meanwhile, the influence events related to the target events can be expanded according to the service scenes, the setting of the service targets is very flexible, the problem of initialization configuration of the operation strategies of different targets under various service scenes can be solved, and data assistance is provided for fine operation and promotion of target conversion. Therefore, the attribution analysis method, the attribution analysis device, the electronic equipment and the computer readable storage medium for the business events can solve the problems that the business events lack behavior cause analysis and the analysis result is poor.

Fig. 2 is a functional block diagram of an attribution analysis device for business events according to an embodiment of the present invention.

The attribution analyzing apparatus 100 of business events according to the present invention may be installed in an electronic device. According to the implemented functions, the attribution analysis device 100 for business events may include a sample data acquisition module 101, a targeting module 102, an impact event determination module 103, an attribution analysis module 104 and a policy optimization module 105. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.

In the present embodiment, the functions regarding the respective modules/units are as follows:

the sample data obtaining module 101 is configured to obtain behavior data of a sample user of a preset service event, and obtain a sample data set.

The sample user refers to a user meeting a certain preset condition in a preset business event, such as a user who newly opens an account in a business event of opening an account in a certain bank branch. The behavior data are all behavior actions generated by the user in the process of executing the business event, such as the account opening time of the user, whether the user opens a mobile phone bank after account opening, and the like.

In detail, the sample data obtaining module 101 is specifically configured to:

determining sample users meeting preset conditions of preset business events;

and acquiring behavior data of the sample user in a specified time period from a preset database to obtain a sample data set.

The preset condition is a condition related to a business target of the preset business event, and if the business target is to improve the financial and purchase rate of a new account opening user, the corresponding preset condition can be the new account opening user of the bank.

The target determination module 102 is configured to determine a target event of interest according to a preset event category and a service target.

The business target is a specific business target related to an actual business, the target attention event is a specific event corresponding to the business target and belonging to the preset event category, namely a specific action implemented by the user, and if the business target is to improve the first financial rate of the user, the target attention event is a data record of any financial product which can be used for the user to purchase the non-current bank deposit for the first time.

In detail, the goal determination module 102 is specifically configured to:

acquiring a service target based on a preset service event requirement;

and searching a category corresponding to the service target in preset event categories, and determining a target attention event from the sample data set according to the category.

The influence event determining module 103 is configured to select, according to the preset event category, data that has a forward correlation with the target attention event from the sample data set, so as to obtain an influence event.

In detail, the impact event determining module 103 is specifically configured to:

dividing the sample data set according to the preset event category and the event occurrence time to obtain a single event set;

and calculating the related possibility of each event in the single event set and the target attention event, and selecting the event corresponding to the related possibility greater than a preset threshold value to obtain an influence event.

Further, the calculating of the related possibility of each event in the single event set and the target attention event is a correlation coefficient calculated by a preset correlation formula, and the correlation coefficient is used as the related possibility of the corresponding event.

In the embodiment of the present invention, the correlation formula is:

where r (X, Y) is a correlation coefficient, X is one event in the single event set and is the target event of interest, Cov (X, Y) is a covariance of data X and data Y, σ_XIs the standard deviation, σ, of the data X_YIs the standard deviation of the data Y.

The attribution analysis module 104 is configured to perform attribution analysis on the impact events to obtain an analysis result.

In detail, the attribution analysis module 104 is specifically configured to:

calculating attribution scores of each event in the influence events to the target attention events through a preset probability formula to obtain attribution scores of single events;

determining the optimal operation time of each event in the influence events based on a preset box separation analysis method to obtain the optimal operation time point of a single event;

determining a combined event behavior path based on the attribution score of the single event and the frequency of the single event;

and collecting the attribution score of the single event, the optimal operation time point of the single event and the combined event behavior path to obtain an analysis result.

Further, the calculating, by a preset probability formula, the attribution score of each event in the influence events to the target attention event to obtain the attribution score of a single event includes:

calculating the occurrence probability of the target attention event when each event in the influence events occurs based on the conditional probability to obtain the influence probability;

calculating the occurrence probability of the target attention event when each event does not occur in the influence events based on the conditional probability to obtain the non-influence probability;

and calculating the attribution score of each event in the influence events by using a preset probability formula according to the influence probability and the non-influence probability to obtain the attribution score of a single event.

Wherein the preset probability formula is as follows:

wherein score (A) is a ascribed score for a single one of the impact events A, P (B | A) is a probability of the target event of interest B occurring at the time of the single one of the impact events A,is the probability that the target event of interest B occurred when a single event a of the impact events did not occur.

Further, the determining the optimal operation time of each event in the influence events based on a preset binning analysis method to obtain the optimal operation time point of a single event includes:

acquiring the number of days between each event in the influence events and the target attention event;

the number of days at intervals is subjected to box separation to obtain an optimal operation interval;

and determining the optimal operation time of the single event based on the optimal operation interval to obtain the optimal operation time point of the single event.

Further, the determining a combined event behavior path based on the attribution score of the single event and the frequency of the single event comprises:

acquiring the event with the attribution score larger than a preset threshold value to obtain an attribution event;

obtaining events with the frequency greater than a preset threshold value in the influence events to obtain high-frequency events;

and combining and sequencing the attribution events and the high-frequency events according to the sequence of the occurrence time of the events to obtain a combined event behavior path.

The policy optimization module 105 is configured to determine an optimized operation policy for the business objective based on the analysis result.

In detail, the embodiment of the present invention determines an optimized business strategy of the business objective based on the attribution score of a single event in the analysis result, combining events of high frequency, and combining event behavior paths, and ensures the achievement of the final business objective.

Fig. 3 is a schematic structural diagram of an electronic device implementing an attribution analysis method for a business event according to an embodiment of the present invention.

The electronic device 1 may comprise a processor 10, a memory 11 and a bus, and may further comprise a computer program, such as an attribution analysis program 12 of a business event, stored in the memory 11 and executable on the processor 10.

The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only to store application software installed in the electronic device 1 and various types of data, such as codes of the attribution analysis program 12 of a business event, etc., but also to temporarily store data that has been output or is to be output.

The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the whole electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules (e.g., attribution analysis programs of business events, etc.) stored in the memory 11 and calling data stored in the memory 11.

The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.

Fig. 3 shows only an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than those shown, or some components may be combined, or a different arrangement of components.

For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.

Further, the electronic device 1 may further include a network interface, and optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a bluetooth interface, etc.), which are generally used for establishing a communication connection between the electronic device 1 and other electronic devices.

Optionally, the electronic device 1 may further comprise a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visualized user interface, among other things.

It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.

The attribution analysis program 12 of the business events stored in the memory 11 in the electronic device 1 is a combination of instructions that, when executed in the processor 10, can implement:

acquiring behavior data of a sample user of a preset service event to obtain a sample data set;

determining a target attention event according to a preset event category and a service target;

selecting data which is in forward correlation with the target attention event from the sample data set according to the preset event category to obtain an influence event;

carrying out attribution analysis on the influence events to obtain an analysis result;

and determining an optimized operation strategy for the business objective based on the analysis result.

Specifically, the specific implementation method of the processor 10 for the instruction may refer to the description of the relevant steps in the embodiments corresponding to fig. 1 to fig. 3, which is not repeated herein.

Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).

The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:

acquiring behavior data of a sample user of a preset service event to obtain a sample data set;

determining a target attention event according to a preset event category and a service target;

selecting data which is in forward correlation with the target attention event from the sample data set according to the preset event category to obtain an influence event;

carrying out attribution analysis on the influence events to obtain an analysis result;

and determining an optimized operation strategy for the business objective based on the analysis result.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.

The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.

The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.

Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.