WO2021129342A1

WO2021129342A1 - Data processing method, apparatus and device, storage medium, and computer program

Info

Publication number: WO2021129342A1
Application number: PCT/CN2020/133651
Authority: WO
Inventors: 周雪琪
Original assignee: 北京市商汤科技开发有限公司
Priority date: 2019-12-27
Filing date: 2020-12-03
Publication date: 2021-07-01
Also published as: JP2023507043A; CN111160967A

Abstract

A data processing method, apparatus and device, a storage medium, and a computer program. The data processing method comprises: acquiring guest data of a target guest (S11); determining the guest level of the target guest on the basis of the guest data (S12); and determining data to be pushed that corresponds to the guest level, and according to a means of data pushing corresponding to the guest level, pushing the data to be pushed to the target guest (S13).

Description

Data processing method, device, equipment, storage medium and computer program

Cross-reference statement

This application claims the priority of the Chinese patent application with the application number 201911379987.1 filed with the Chinese Patent Office on December 27, 2019, the entire content of which is incorporated into this application by reference.

Technical field

This application relates to a data processing method, device, equipment, storage medium and computer program.

Background technique

In actual use, sales staff will provide differentiated reception to visitors based on their characteristics, so as to increase the conversion rate of visitors and obtain greater benefits. At present, the work of data sorting and business follow-up is usually carried out manually to provide services for visitors based on the results of data sorting. However, artificial data collation often results in data omissions, and the results obtained by different sales personnel are uneven, which affects the business follow-up effect. Therefore, a data processing method is urgently needed.

Summary of the invention

In view of this, this application provides a data processing solution.

In the first aspect, an embodiment of the present application provides a data processing method, the method includes: obtaining visitor data of a target visitor; determining the visitor level of the target visitor based on the visitor data; determining that it corresponds to the visitor level The data to be pushed; and push the data to be pushed to the target visitor according to the data push mode corresponding to the visitor level.

In a possible implementation manner, the visitor data includes visit data and profile data; the visitor level includes a first visitor level determined based on the visit data, and/or, determined based on the profile data Second visitor level.

In a possible implementation manner, in a case where the visitor data includes the visit data and the visitor level includes the first visitor level, the determination of the target visitor's status based on the visitor data The visitor level includes: determining the number of visits and/or the average duration of a single visit of the target visitor within a preset time period according to the visit data; in response to the number of visits being higher than a first threshold, And/or, the single average visit time is higher than a first time threshold, and it is determined that the first visitor level of the target visitor is a high-frequency customer.

In a possible implementation manner, the visitor data further includes an identity type, and the determining the visitor level of the target visitor based on the visitor data includes: determining that the target visitor lasts according to the visit data The time interval between the time of one visit and the current moment, and/or the single average visit time of the target visitor within the preset time period; in response to the time interval exceeding the second threshold, and/or , The single average visit time is lower than the second time threshold, and when the identity type of the target visitor is the first type, it is determined that the first visitor level of the target visitor is a churn customer, or, When the identity type of the target visitor is the second type, it is determined that the first visitor level of the target visitor is a sleeping customer.

In a possible implementation manner, the profile data includes the spending power data of the target visitor and the objects of interest, where the visitor data includes the profile data, and the visitor level includes the second visitor level. Next, the determining the visitor level of the target visitor based on the visitor data includes: determining the selling price of the target visitor according to the following target; and determining the target visitor corresponding to the target visitor according to the spending power data Consumption interval; in response to whether the selling price belongs to the consumption interval, determine the second visitor level of the target visitor.

In a possible implementation manner, in the case that the selling price does not belong to the consumption range, or the selling price belongs to the consumption range but the difference from the upper limit of the consumption range is less than a preset value, The determining the data to be pushed corresponding to the visitor level includes: searching for data of other objects of the same type as the following object based on the following object, and determining the data of the other object as the data to be pushed .

In a possible implementation manner, the data pushing manners corresponding to different visitor levels are at least partially different; the data pushing manner includes at least one of push time, time interval between two adjacent pushes, and push way.

In a possible implementation manner, after the determination of the visitor level of the target visitor, the method further includes: sending the visitor level of the target visitor to a terminal, so that the terminal compares the visitor level with Storage and/or display associated with the target visitor.

In a second aspect, an embodiment of the present application provides a data processing device, the device includes: an acquisition module for acquiring visitor data of a target visitor; a determination module for determining the target visitor’s data based on the visitor data Visitor level; a processing module, used to determine the data to be pushed corresponding to the visitor level, and push the data to be pushed to the target visitor according to the data push method corresponding to the visitor level.

In a possible implementation manner, in a case where the visitor data includes the visit data and the visitor level includes the first visitor level, the determining module is configured to: according to the visit data , Determine the number of visits and/or the average duration of a single visit of the target visitor within a preset time period; in response to the number of visits being higher than the first threshold, and/or, the single average visit When the duration is higher than the first duration threshold, it is determined that the first visitor level of the target visitor is a high-frequency customer.

In a possible implementation manner, the visitor data further includes an identity type, and the determining module is configured to determine the time interval between the time of the last visit of the target visitor and the current moment according to the visit data, And/or, the single average visit duration of the target visitor within the preset time period; in response to the time interval exceeding a second threshold, and/or, the single average visit duration is lower than the first A two-time threshold, when the identity type of the target visitor is the first type, the first visitor level of the target visitor is determined to be a churn customer, or the first visitor level of the target visitor is determined to be a sleeping customer .

In a possible implementation manner, the profile data includes the spending power data of the target visitor and the objects of interest, where the visitor data includes the profile data, and the visitor level includes the second visitor level. Next, the determining module is configured to: determine the selling price of the attention object according to the attention object; determine the consumption interval corresponding to the target visitor according to the spending power data; and respond to whether the selling price belongs to the price The consumption interval is used to determine the second visitor level of the target visitor.

In a possible implementation manner, the processing module is further configured to: when the selling price does not belong to the consumption interval, or the selling price belongs to the consumption interval but is different from the upper limit of the consumption interval If it is less than the preset value, based on the concerned object, search for data of other objects of the same type as the concerned object, and determine the data of the other object as the data to be pushed.

In a possible implementation manner, the processing module is further configured to: after the determining module determines the visitor level of the target visitor, send the visitor level of the target visitor to the terminal, so that the terminal Storage and/or display that associates the visitor level with the target visitor.

In a third aspect, an embodiment of the present application provides a data processing device, including: a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The processor implements the computer program when the computer program is executed. Apply for the steps of the data processing method described in the embodiment.

In a fourth aspect, an embodiment of the present application provides a storage medium storing a computer program, and when the computer program is executed by a processor, the processor executes the steps of the data processing method described in the embodiment of the present application.

The technical solution provided by the embodiment of this application obtains the visitor data of the target visitor; determines the visitor level of the target visitor based on the visitor data; determines the data to be pushed corresponding to the visitor level and corresponds to the visitor level The data push method is to push the data to be pushed to the target visitor. In this way, it is possible to save at least part of the time and effort caused by manual data sorting, thereby effectively improving the efficiency of data processing. In addition, based on the visitor data, the visitor level of the target visitor is determined, and the visitor data can be effectively used to divide the visitor level of each target visitor to distinguish or mark different target visitors; and according to the data corresponding to the visitor level The push method, pushing the data to be pushed, can provide more targeted data push for target visitors of different visitor levels, thereby further improving the visitor experience and visitor conversion rate.

Description of the drawings

FIG. 1 is a schematic flowchart of a data processing method provided by an embodiment of this application;

2 is a schematic flowchart of another data processing method provided by an embodiment of the application;

Figure 3(a) is a schematic diagram of the visitor information of the day displayed on the terminal side and automatically recognized on the server side according to an embodiment of this application;

FIG. 3(b) is a schematic diagram of visitor information of a certain terminal user displayed on the terminal side according to an embodiment of this application;

Figure 3(c) is a schematic diagram of a single visitor information displayed on the terminal side according to an embodiment of the application;

Figure 3(d) is a schematic diagram of a visitor editing interface displayed on the terminal side according to an embodiment of the application;

FIG. 4 is a schematic diagram of a flow of analyzing visitor levels based on visiting frequency provided by an embodiment of the application;

Figure 5 (a) is a schematic diagram of a terminal provided by an embodiment of the application receiving a push of a visit message;

Figure 5(b) is a schematic diagram showing the previous visit messages of a certain visitor provided by this embodiment of the application;

FIG. 5(c) is a schematic diagram of a visitor list displayed on the terminal side and automatically recognized by the server side according to an embodiment of this application;

Figure 5(d) is a schematic diagram of analysis based on visitor data in a certain period of time provided by an embodiment of this application;

Fig. 6 is a schematic diagram of a visitor tag editing interface provided by an embodiment of the application;

FIG. 7 is a schematic diagram of the composition structure of a data processing device provided by an embodiment of the application;

FIG. 8 is a schematic diagram of the composition structure of another data processing device provided by an embodiment of the application.

Detailed ways

In order to enable those skilled in the art to better understand the solutions of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only These are a part of the embodiments of this application, but not all of the embodiments.

The terms "first", "second", and "third" in the specification embodiments and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or Priority. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion, for example, including a series of steps or units. The method, system, product, or device need not be limited to those clearly listed steps or units, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products, or devices.

The embodiments of the present disclosure can be applied to various electronic devices, including but not limited to fixed devices and/or mobile devices. For example, the fixed device includes but is not limited to: a personal computer (PC), or a server, etc., and the server may be a cloud server or a common server. The mobile device includes but is not limited to one or more of a mobile phone, a tablet computer, or a wearable device.

The embodiment of the present application provides a data processing method, which can be applied to the above-mentioned electronic device. As shown in Figure 1, the method mainly includes the following steps:

Step S11: Obtain visitor data of the target visitor;

Step S12: Determine the visitor level of the target visitor based on the visitor data;

Step S13: Determine the data to be pushed corresponding to the visitor level, and push the data to be pushed to the target visitor according to the data push mode corresponding to the visitor level.

In the embodiment of the present disclosure, the target visitor generally refers to a visitor being served, for example, a customer, a visitor who is highly likely to become a customer, and so on. The target visitor can refer to one or more of the above-mentioned served visitors. In an implementation manner, the target visitor may be any person except for the whitelist among all the people who go to the target place. It is understandable that the target visitors do not include people who are listed as whitelists.

Wherein, the white list includes at least one of the following: employees at the target site, cleaning personnel, maintenance masters, courier personnel, and takeaway personnel. It should be noted that the white list can be set or adjusted according to user requirements. In the embodiments of the present disclosure, the target place may refer to a place where goods can be exhibited or sold, including but not limited to 4S stores, shops, shopping malls, supermarkets, etc.

In the embodiment of the present disclosure, the visitor data may include visitation data, which is obtained by collecting a face image and/or a human body image of a target visitor in a target place through a camera. For example, the visit data includes the number of visits of the target visitor within a preset time period. For another example, the visit data includes the single visit time of the target visitor. For another example, the visit data includes a single average visit time of the target visitor within a preset time period. Wherein, the preset time period may include a period of time starting from the start time and ending with the end time, such as one day, one week, one month, one quarter, six months, one year, etc. The preset time period may be determined based on actual needs, and the embodiment of the present disclosure does not limit the setting method, specific value, etc. of the preset time period. It should be noted that the termination time is the time before the current time (may include the current time).

In the embodiment of the present disclosure, the visitor data may include profile data, and the profile data includes spending power data of the target visitor and objects of interest. In an application scenario of the present disclosure, the consumption power data can be parameters reflecting the economic level of the visitor, such as occupation, monthly income, annual income, residence, etc.; the concerned object can be used to reflect the product that the visitor prefers, for example, Preferred car type.

In the embodiment of the present disclosure, the visitor level may include at least one of a first visitor level determined based on visit data and a second visitor level determined based on profile data. In an application scenario, for example, the first visitor level may reflect the visitor status of the visitor, and the second visitor level may reflect the purchase intention of the visitor. In the embodiment of the present disclosure, the visitor level for reflecting other attributes may also be included. In the embodiment of the present application, the categories included in the visitor level and the parallel items included in each category are not limited.

In an implementation manner, the first visitor level includes high-frequency customers, churn customers, sleeping customers, etc., and different first visitor levels correspond to different visit frequencies. The second visitor level includes grade S, grade A, grade B, grade C, and grade D; or, the second visitor grade includes grade A, grade B, grade C, grade D, and grade E; or, The second visitor level includes H level, A level, B level, C level, and D level. In an application scenario of the present disclosure, the ranges of purchase possibilities corresponding to different second visitor levels are different.

In the embodiment of the present disclosure, the data to be pushed is data corresponding to the visitor level that is ready to be pushed to the target visitor. In an application scenario of the present disclosure, the data to be pushed includes vehicle type content. Exemplarily, for target visitors with high purchasing intentions, the content of the car models preferred by the target visitors can be directly and targeted; for target visitors with low purchasing intentions, the content of similar and/or contrasting car models of the target visitors' preferred car models can be posted. .

In the embodiment of the present disclosure, the data pushing manners corresponding to different visitor levels are at least partially different. The data push method includes at least one of the push time, the time interval between two adjacent pushes, and the push path. For example, the push channels include emails, short messages, phone calls, WeChat, Moments, official accounts, and so on.

In order to determine the visitor level of the target visitor based on the visitor data, in some implementations, when the visitor data includes visit data and the visitor level includes the first visitor level, the target visitor’s level is determined based on the visitor data. The visitor level includes: determining the number of visits and/or the average duration of a single visit of the target visitor within a preset time period according to the visit data; in response to the number of visits being higher than a first threshold, And/or, the single average visit time is higher than a first time threshold, and it is determined that the first visitor level of the target visitor is a high-frequency customer.

It should be noted that the first threshold and the first duration threshold are both preset thresholds. The first threshold and the first duration threshold may be set in advance according to the investment time, cost, etc., and/or demand, and the setting method and the like are not limited here.

In this way, the first visitor level of the target visitor is determined according to the number of visits of the target visitor within the preset time period or the average visit time of a single visit.

Exemplarily, when the number of visits in the preset time period is higher than the first threshold, the first visitor level of the target visitor is determined as a high-frequency customer; the average visit time of a single visit in the preset time period If it is higher than the first time threshold, the first visitor level of the target visitor is determined as a high-frequency customer; or, the number of visits within the preset time period is higher than the first threshold, and the visitor level within the preset time period In the case where the average duration of a single visit is higher than the first duration threshold, the first visitor level of the target visitor is determined as a high-frequency customer.

Considering that the identity types of target visitors may be different, for example, some target visitors are judged as ordinary visitors, and some target visitors are judged as important visitors, and target visitors with different identity types can have different visitor levels. Therefore, in a possible implementation, the visitor data also includes the identity type. The identity type may include a first type such as ordinary visitors, and a second type such as important visitors. In addition, a third type, such as a blacklist, can also be included.

Correspondingly, the determining the visitor level of the target visitor based on the visitor data includes: determining the time interval between the time of the last visit of the target visitor and the current moment according to the visit data, and/or, The single average visit duration of the target visitor within the preset time period; in response to the time interval exceeding a second threshold, and/or the single average visit duration is lower than the second duration threshold, it is determined The first visitor level of the target visitors of the first type is a churn customer, or it is determined that the first visitor level of the target visitors of the second type is a sleeping customer.

It should be noted that the second threshold and the second duration threshold are both preset thresholds. The second threshold and the second duration threshold may be set in advance according to the time invested, cost, etc., and/or demand, and the setting method and the like are not limited here.

In an application scenario of the present disclosure, the criterion for distinguishing the first type and the second type may be whether the target visitor is a member; if it is a member, the identity type is determined to be the second type; if it is not a member , The identity type is determined to be the first type.

Exemplarily, if the identity type of the target visitor is the first type, and the time interval between the time of the last visit and the current moment exceeds the second threshold, the first visitor level of the target visitor is determined to be a lost customer; If the identity type is the first type, and the single average visit time of the target visitor is lower than the second duration threshold, the first visitor level of the target visitor is determined to be a lost customer; or, if the identity type of the target visitor is the first type , The time interval between the time of the last visit and the current moment exceeds the second threshold, and the single average visit time of the target visitor is lower than the second time threshold, it is determined that the first visitor level of the target visitor is a lost customer.

Exemplarily, if the identity type of the target visitor is the second type, and the time interval between the time of the last visit and the current moment exceeds the second threshold, the first visitor level of the target visitor is determined to be a sleeping customer; If the identity type is the second type, and the single average visit time of the target visitor is lower than the second duration threshold, the first visitor level of the target visitor is determined to be a sleeping customer; or, if the identity type of the target visitor is the second type , The time interval between the last visit time and the current moment exceeds the second threshold, and the average single visit time is lower than the second time threshold, then the first visitor level of the target visitor is determined to be a sleeping customer.

It should be noted that the high-frequency customers, the lost customers, and the sleeping customers can be set or adjusted according to user needs.

In order to determine the visitor level of the target visitor based on the visitor data, in some implementation manners, the profile data includes the spending power data of the target visitor and the objects of interest. In the case where the visitor data includes profile data and the visitor level includes the second visitor level, the determining the visitor level of the target visitor based on the visitor data includes: determining according to the attention object The selling price of the concerned object; determining the consumption interval corresponding to the target visitor according to the consumption power data; and determining the second visitor level of the target visitor in response to whether the selling price belongs to the consumption interval.

In an application scenario of the present disclosure, the concerned object may include the car of interest, and the selling price thereof is determined accordingly. In this application scenario, the second visitor level is evaluated by analyzing the car type and consumption power data of the target visitor. The second visitor level represents the purchase ability of the target visitor, and facilitates differentiated reception according to the determined second visitor level. In turn, more visitor reception energy and visitor relationship maintenance energy can be selectively put into high-value visitors, which is conducive to improving the visitor conversion rate.

In the following, only the second visitor level is divided into S level, A level, B level, C level, and D level as an example. Among them, the purchase intentions of the target visitors indicated by the above-mentioned second visitor levels are successively decreased, which means that the purchase intention of the visitors indicated by the S level is the highest, and the purchase intention of the visitors indicated by the D level is the lowest. It should be noted that in the actual application process, the second visitor level can also be arranged as S level, A level, B level, C level, and D level according to the purchase intention from low to high. In the embodiment of the present application, the correspondence between each item in the second visitor level (for example, S level, A level, B level, C level, D level) and the level of the indicated purchase intention is not limited, and The number of items included in the second visitor level is not limited, and can be defined and/or adjusted according to user needs.

In an implementation manner, when the consumption interval is [Y1, Y2] and the selling price of the car of interest is greater than Y5, the second visitor level of the target visitor is the D level. That is, when the visitor's consumption interval (where the visitor's consumption interval can often reflect the economic situation of the visitor) is much lower than the price of the visitor's car model, it can be regarded as the visitor's purchase intention is extremely low (here refers to the visitor Usually do not have the ability to buy the car of interest, or the possibility of purchase is low).

When the consumption interval is (Y2, Y3) and the price of the car concerned is (Y4, Y5), the second visitor level of the target visitor is grade C, that is, the consumption interval of the visitor and the price of the car concerned by the visitor exist If there is a certain gap, and the visitor's consumption range is lower than the price of the car of interest, it can be regarded as the visitor's purchase intention is low.

When the consumption interval is (Y3, Y4) and the price of the car concerned (Y3, Y4), the second visitor level of the target visitor is level B, that is, the consumption interval of the visitor belongs to the same interval as the price of the car concerned If it is within the range, it can be considered that the purchase intention of the visitor is moderate (this means that the visitor has the ability to purchase the car of interest, and the price of the car of interest is within the expected price range of the visitor).

When the consumption interval is (Y4, Y5) and the price of the car concerned (Y2, Y3), the second visitor level of the target visitor is A grade, that is, the consumption interval of the visitor and the price of the car concerned by the visitor exist If there is a certain gap, and the consumption range of the visitor is higher than the price of the car of interest, it can be regarded as the visitor's purchase intention is higher.

When the consumption range is (Y5, ∞) and the price of the car concerned (Y1, Y2), the second visitor level of the target visitor is S grade, that is, the consumption range of the visitor is much higher than that of the car concerned. In the case of the price, it can be regarded as the visitor's purchase intention is extremely high (this means that the visitor not only has the ability to buy the car of interest, but the economic situation of the visitor is more than enough to pay the price of the car of interest).

Among them, 0≤Y1<Y2<Y3<Y4<Y5.

It can be understood that the division of the second visitor level and the division of the consumption interval and the selling price shown above are merely illustrative, and this application does not limit this.

For example, if the consumption range of the target visitor is 300,000 to 500,000, and if the price of the car concerned is 1 million, then it can be considered that the second visitor level indicates that the purchase intention of the visitor is very low, such as D level; If the price of the model is 600,000, it can be considered that the second visitor level indicates that the visitor’s purchase intention is relatively low, such as the C level; if the price of the car concerned is less than or equal to 500,000, then the second visitor level can be considered to indicate that the visitor has A higher purchase intention is only in the grade division, because the price is close to the upper limit of the consumption range, so the purchase intention may also be lower, such as B grade; if the price of the car concerned is less than or equal to 400,000, it is completely in the consumption range Within the range, it can be considered that the second visitor level represents a higher purchase intention of the visitor, such as A level; if the price of the car concerned is less than or equal to 300,000, it is completely within the range of consumption, or lower than the lowest price , It can be considered that the second visitor level indicates that the purchase intention of the visitor is very high, such as the S level.

Among them, the D level indicates that the purchase probability of the target visitor is less than or equal to P1;

Grade C indicates that the purchase probability of the target visitor is greater than P1 and less than or equal to P2;

Level B indicates that the purchase probability of the target visitor is greater than P2 and less than or equal to P3;

Level A indicates that the purchase probability of the target visitor is greater than P3 and less than or equal to P4;

The S grade indicates that the purchase probability of the target visitor is greater than P4; among them, 0≤P1<P2<P3<P4<P5.

It can be seen that the higher the level, the greater the purchase possibility of the target visitor in the short term; the lower the level, the lower the purchase possibility of the target visitor in the long term.

In the above application scenario, in response to whether the selling price belongs to the consumption range, determining the second visitor level of the target visitor includes: if the selling price does not belong to the consumption range, determining that it is difficult for the visitor to purchase For the desired car model, determine that the second visitor level of the target visitor is the level that indicates no purchase intention or the lowest purchase intention; the selling price belongs to the consumption range, it is determined that the target visitor has purchase intention, and the The second visitor level of the target visitor is a level higher than the price that does not belong to the consumption range, and the level is further divided according to the size of the purchase intention if there is a purchase intention or when there is a purchase intention.

Here, the selling price does not belong to the consumption range, and it can be understood that the selling price is not within the consumption range. The selling price is not within the consumption range, and includes not only the selling price above the upper limit of the consumption range, but also includes the selling price below the lower limit of the consumption range. Exemplarily, the consumption range is 300,000-500,000. If the price of the model concerned by the target visitor is 600,000, it indicates that the price is not within the consumption range; if the price of the model concerned by the target visitor is 200,000, it also indicates the price Not within the consumption range. In practical applications, the selling price does not belong to the consumption range, and can only be understood as the selling price above the upper limit of the consumption range; alternatively, it can be understood as the selling price above the upper limit of the consumption range and the selling price below the lower limit of the consumption range.

In the above application scenario, when the selling price falls within the consumption range, the difference between the selling price and the upper limit of the consumption range will affect the second visitor level. The larger the difference is, the higher the purchase possibility of the target visitor is, and the corresponding second visitor level means that the target visitor is most likely to buy the car of this model.

In some embodiments, in the case that the second visitor level of the target visitor is determined according to the data data such as the object of interest and spending power data, and the second visitor level includes multiple levels, the determining is based on the visitor data The visitor level of the target visitor may further include: the interval to which the disposable income reflected in response to the spending power data belongs is the first disposable interval, and/or the interval to which the pre-disposable income reflected by the attention object belongs is the first A pre-dominant interval determines that the second visitor level of the target visitor is one of the multiple levels. Wherein, before determining that the second visitor level of the target visitor is one of the multiple levels, the method further includes: dividing the disposable income reflected by the consumption power data into multiple disposable ranges; and /Or, divide the pre-dominant income reflected by the concerned object into multiple pre-dominance intervals. In this way, the second visitor level of the target visitor is determined by comparing the controllable interval and the pre-dominant interval. Among them, dividing the second visitor level into multiple levels can make the determined second visitor level more accurate.

In order to save computing resources, in an implementation manner, the second visitor level of the target visitor is determined only when the first visitor level of the target visitor is a high-frequency customer. That is, in the case where the first visitor level of the target visitor is a lost customer or a sleeping customer, the second visitor level of the target visitor will not be determined.

In a possible implementation manner, in the case that the selling price does not belong to the consumption range, or the selling price belongs to the consumption range but the difference from the upper limit of the consumption range is less than a preset value, The determining the data to be pushed corresponding to the visitor level includes: searching for data of other objects of the same type as the object of interest based on the object of interest; and determining the data of other objects as the data to be pushed.

In an application scenario, in the case that the selling price does not belong to the consumption range, data of other car models of the same type as the car model concerned can be searched for and determined as the data to be pushed. In this way, it is helpful to push the target visitors to the models that are in line with their economic capabilities, thereby helping to increase the visitor conversion rate.

In another application scenario, in the case that the selling price belongs to the consumption range but the selling price is closer to the upper limit of the consumption range, data of other vehicle models of the same type as the concerned vehicle type can be searched for and determined as the data to be pushed .

In this way, it is helpful to push to the visitor terminal the car model that matches the visitor's purchase intention, thereby helping to provide the visitor with multiple choices of the same type of car model, and also helping to increase the visitor conversion rate.

In some embodiments, after determining the visitor level of the target visitor, the method further includes: sending the visitor level of the target visitor to a terminal, so that the terminal compares the visitor level with the target visitor level. Storage and/or display associated with visitors. Wherein, the terminal includes, but is not limited to, a personal computer, a mobile phone, a tablet computer, a wearable device, and the like. The display associating the visitor level with the target visitor may include: a display associating the visitor level with the target visitor in the form of a tag. And, the display that associates the visitor level with the target visitor may include: a display that associates the visitor level with the target visitor in a visitor list and/or a visitor page.

In some embodiments, the method further includes: sending part of the visitor data of the target visitor, such as identity type, visit data, etc., to the terminal, so that the terminal can correlate the part of the visitor data with the target visitor The storage and/or display of links. Similarly, the part of the visitor data associated with the target visitor may be displayed in the form of tags in the visitor list and/or visitor page.

In an application scenario, the visitor level of the visitor is displayed through the terminal, which is convenient for the sales staff responsible for follow-up of the visitor in the store to perform efficient data management. For example, it is convenient for end users such as sales staff to intuitively understand the visits and/or purchase intentions of target visitors, and assist the store to detect high-value visitors; it is also convenient for end users such as sales staff to perform differentiated reception according to the determined visitor level, and then More visitor reception energy and visitor relationship maintenance energy will be selectively put into high-value visitors, which will help increase the visitor conversion rate.

In some embodiments, when the visitor data includes visit data, step S11 includes: acquiring historical visit information of the target visitor; and determining the visit of the target visitor according to the historical visit information data.

Here, the historical visit information includes at least visit time.

It should be noted that the historical visit information may be all visit information of the target visitor before this visit. Of course, the historical visit information may also be visit information within a certain period of time from the current visit, and the certain period of time can be set or adjusted according to design or requirements.

In an application scenario, the historical visit information may also include at least one of the following: visit location information or visit store, checkout purchase information, stay time, consultation time, purchase intention, etc. The length of stay mentioned here refers to the period of time between the target visitor’s entering the store and leaving the store, as collected by the camera.

It should be noted that this application does not limit the degree of refinement of historical visit information. The more detailed the historical visit information, the more conducive to the subsequent discovery of target visitors.

In this way, the visit data of the target visitor is determined by analyzing the historical visit information, and the first visitor level is determined for the target visitor based on the visit data, which facilitates differentiated data processing according to the determined first visitor level, and then can More visitor reception energy and visitor relationship maintenance energy will be selectively put into high-value visitors, which will help increase the visitor conversion rate.

In some embodiments, in the case that the visitor data includes profile data, step S11 includes: collecting consumption power data and objects of interest of the target visitor; and determining the target visitor’s spending power data and objects of interest based on the consumption power data and the objects of interest. Information data.

In an application scenario, when a visitor visits, a questionnaire can be provided for the visitor. The questionnaire includes multiple options such as expected product purchase, ideal price, age, education, position, work unit, etc. Each option may correspond to multiple answers, and the visitor selects from the multiple answers.

In this way, it is convenient to determine the profile data of the visitor based on the questionnaire data, which in turn helps to analyze the high-value visitors based on the profile data.

In another application scenario, after the target visitor visits, the terminal user can provide evaluation data based on the visit record of the target visitor. The evaluation data includes at least one of purchasing ability data and purchasing intention data.

Here, the terminal user can be understood as a person who can provide evaluation data based on the visit record of the target visitor, such as a salesperson.

Exemplarily, in the process of receiving target visitors, the sales staff judges the purchase ability and purchase intention of the target visitors based on their own experience, and scores the target visitors on the terminal for one or more evaluation items according to known evaluation criteria Or rating. For example, the evaluation items include purchasing ability evaluation items and purchase intention evaluation items, and the evaluation data includes scoring or rating results; the server or other device determines the purchase possibility of the target visitor based on the evaluation data. It should be noted that the evaluation criteria corresponding to different evaluation items may be the same or different.

In this way, in the process of receiving target visitors, the sales staff judges the purchase ability and purchase intention of the target visitors based on their own experience, and enters the evaluation data of the target visitors on the terminal as the data data, so that the server or other devices can base the evaluation on the evaluation data. The data determines the visitor level of the target visitor. For sales personnel, the operation is convenient and fast, and it is also convenient for servers or other devices to provide evaluation information for different target visitors according to uniform standards.

Based on the foregoing data processing method, an embodiment of the present application also provides a data processing method applied to a terminal. As shown in Figure 2, the method includes the following steps.

Step S21: Receive visitor level information of the target visitor.

Step S22: Display the visitor level information of the target visitor. Wherein, the terminal stores and/or displays the relationship between the visitor level and the target visitor. Specifically, the visitor level information and the target visitor may be displayed in the form of a tag in a visitor list and/or a visitor page.

In this way, it is convenient for the terminal user to quickly identify whether the target visitor is a new visitor based on the visitor level information. In addition, it can realize the rapid distribution of processing tasks according to the visitor level of the target visitor. On the one hand, it is helpful for sales staff to perform targeted work and services and improve work efficiency; on the other hand, it is also convenient for differentiated reception according to the determined visitor level. In turn, more visitor reception energy and visitor relationship maintenance energy can be selectively put into high-value visitors, which is conducive to improving the visitor conversion rate.

In some embodiments, the method further includes: receiving an analysis result of visitor level information corresponding to the target visitor; and displaying the analysis result.

In this way, it is convenient for the end user to know the analysis result of the visitor level information of the target visitor in time, which in turn facilitates the user to perform targeted processing based on the analysis result, thereby improving visitor experience and visitor conversion rate.

Exemplarily, the salesperson may combine the two types of tags of the first visitor level and the second visitor level to adopt different marketing strategies for the visitors. For example, when the second visitor level indicates a higher level but the first visitor level is a lost customer, based on the above label, the salesperson needs to use a richer and more effective follow-up and marketing strategy to bring back visitors.

Exemplarily, when the second visitor level indicates that the level is low but the first visitor level is a high-frequency customer, based on the above label, the salesperson can re-evaluate the visitor’s real purchase intention, grasp the key visitors, and reflect on their presence in the visitor. Whether the method of determining high-value visitors in the follow-up process is wrong.

In some embodiments, the method further includes: receiving partial visitor data, such as identity type, visit data, etc., and storing and/or displaying it in association with the target visitor. Specifically, the part of the visitor data associated with the target visitor may be displayed in the form of a tag in the visitor list and/or the visitor page.

Figure 3 (a)-Figure 3 (d) show the display of visitor information on the terminal side in a specific application scenario. Fig. 3(a) shows a schematic diagram of the visitor information of the day displayed on the terminal side and automatically recognized by the server side. As can be seen from Figure 3(a), the interface displays the information of all visitors who visited that day, specifically including whether each visitor is the first visit, the number of visits, the visit time, and whether to follow up and other information. Provides detailed data support for the end user, which is convenient for the end user to understand the visitor's information based on the data displayed on the interface and decide whether to follow up with the visitor. Figure 3(b) shows a schematic diagram of visitor information of a certain terminal user displayed on the terminal side. It can be seen from Figure 3(b) that the terminal user’s visitor information is displayed on the interface, which specifically includes whether each visitor is the first visit, the number of visits, and the visit time. FIG. 3(c) shows a schematic diagram of the information of a single visitor displayed on the terminal side, which specifically includes information such as the cumulative number of visits, the time of the most recent visit, and the accompanying persons who visit each time. Figure 3(d) shows a schematic diagram of a visitor editing interface displayed on the terminal side. As shown in Figure 3(d), a potential customer level item is displayed on the interface, and the potential customer level represents the second visitor level. The user can edit the visitor's potential level, that is, the user can select the specific level in the second visitor level, for example, according to the communication with the visitor this time, decide whether to change the level evaluated last time. In this way, it is convenient for the terminal user to learn about the information of the store visitor, and to provide differentiated reception for the visitor's visitor level information; it is also convenient for the end user to rank the store visitor based on experience.

Figure 4 shows a schematic flow chart of analyzing visitor levels based on visiting frequency in a specific application scenario. As shown in Figure 4, the camera is responsible for collecting face images and/or human body images in the environment; the original images collected are transferred to the subsequent processing link on the server side through a unified access service. On the server side, feature extraction and indexing of facial images and/or human images through image processing and forwarding services; transfer the obtained data to the Kafka message queue through the data standardization service; call the retrieval service to retrieve the data in the Kafka message queue Perform decontamination and deduplication processing; use the face and/or human body feature data obtained after decontamination and deduplication as the retrieval object to retrieve the visitor's data in the existing database to determine this collection Whether the arriving visitor is a new visitor; if it is determined to be a new visitor, give it the first type of label such as customer; if it is determined to be an old visitor, the second type of matching is performed again according to the database, such as identifying whether it is a member, and then This determines the first visitor level. For example, according to an example, customers who have appeared more than or equal to 3 times in the last 15 days are marked as high-frequency customers, members who have been in the store for more than 30 days in the last time are marked as sleeping members, and have been in the store for more than 30 days in the last time. Of customers are lost customers. Specifically, if it is determined that the visitor is a member, the last visit time will be queried, and it will be judged whether it has been more than 30 days since the last visit. When it is determined that it has exceeded 30 days, the visitor will be marked as a sleeping member, otherwise, it will not proceed. mark. If the visitor is a non-member, that is, it is a customer, query the number of visits by the customer within 15 days, and add 1 to the number of visits, and then determine whether the number of visits within 15 days is greater than or equal to 3. If it is greater than or equal to 3, then mark the customer as a high-frequency customer; if the number of visits within 15 days is less than 3, query the last visit time to determine whether the last visit time exceeds 30 days. When it is determined that it exceeds 30 days, mark it as a lost customer.

It should be noted that it can be understood that the process shown in Figure 4 can be set or adjusted according to user requirements or design requirements.

Figures 5(a)-5(d) show schematic diagrams of the push, display, classification and analysis of visited messages in a specific application scenario. Figure 5(a) shows a schematic diagram of a terminal receiving a push of a visit message. End users, such as sales staff, can query the visitor's identity type and visitor level by receiving visitor arrival messages in real time, and provide high-quality visitor reception at the first time. In addition, end users, such as security personnel, can determine the blacklisted personnel and their locations in the first time by receiving the blacklist warning message push in real time, which helps to efficiently eliminate risks. Figure 5(b) shows a schematic diagram showing the previous visit messages of a certain visitor. By displaying the historical visit record of a visitor on the terminal side, it is greatly convenient for the terminal user to distinguish and trace the key information in the previous reception process, and can assist in judging the purchase intention and value of the visitor by integrating the previous visits. In this way, the end user's grasp of visitor information is improved, which in turn helps increase the visitor conversion rate. Figure 5(c) shows a schematic diagram of a visitor list displayed on the terminal side and automatically recognized by the server side. Among them, the server side can support visitor classification based on tags, and managers and sales staff, as end users, can perform targeted customer marketing and customer operations for visitors under a certain tag. Figure 5(d) shows a schematic diagram of analysis based on visitor data in a certain period of time. Through this schematic diagram, you can grasp the visitor group analysis data and the passenger flow trend data, such as the comparison chart of the total passenger flow and the number of member visits, and the comparison chart of new and old visitors. If combined with transaction data, it can help managers analyze and locate current business and operational issues, and then proceed with the next stage of business job promotion and marketing campaign design based on the basis.

Figure 6 shows a schematic diagram of a visitor tag editing interface in a specific application scenario, and the terminal user can edit the interface. As shown in Figure 6, this interface allows end users to manage visitors. Taking the visitor's identity type as a member as an example, each member's avatar, personnel ID, name, label, operation and other items are displayed on the interface. The user can edit each member by clicking the edit button corresponding to the operation item. For example, select the label that it thinks is suitable for the member from the optional label library, or customize the label for a certain member, etc. You can also delete members that they think have gone through the withdrawal procedures or have low value through the delete button corresponding to the operation item.

In this application scenario, by way of example, when an operation of searching for a designated visitor input by the user is received, the terminal displays a brief introduction interface of the designated visitor, and the label of the designated visitor is displayed on the interface. Upon receiving the operation of entering the visitor details page input by the user, the terminal displays the detailed introduction interface of the designated visitor, including the historical visit record of the designated visitor. When receiving the operation of editing the custom label of the visitor input by the user, the terminal receives and displays the custom label of the designated visitor edited by the user.

In this application scenario, for example, the terminal interface displays tag information of multiple visitors. When receiving a user's sliding left or right operation on a visitor in the interface, the visitor's label is in an editable state. When receiving the editing information input by the user, the terminal performs an editing operation on the visitor's tag based on the editing information input by the user.

In this application scenario, for example, upon receiving an operation of pulling up the scroll bar on the interface input by the user, the terminal updates the visitor list displayed on the current interface. When a user finds a visitor to a specified store on a specified date from the current interface, he clicks to enter the visitor details page. When receiving the operation of converting the visitor from a customer to a member input by the user, the identity type of the visitor is changed from a customer to a member based on the operation.

It should be noted that it can be understood that the above-mentioned process is only illustrative, and in actual applications, differentiated setting operations can be provided for users to realize different above-mentioned functions.

According to the embodiment of the present disclosure, the camera is responsible for collecting images, and transmitting the collected images to the server, so that the server can recognize the images and obtain the face and/or human body characteristics of the target visitor contained in the images. The visitor data of the target visitor in the image, such as identity type, visit data and profile data, are obtained based on the human face and/or human body characteristics. Among them, the profile data may include evaluation information, and the visit data may include historical visit information. Determine the visitor level information of the visitor according to the identity type, visit data and profile data. The server transmits the tag information of the target visitor to the user terminal installed with the APP for display by the user terminal, which is convenient for the end user to perform differentiated processing according to the determined target visitor label, and thus can more energy for the reception of the visitor and the relationship between the visitor The maintenance energy is selectively put into high-value visitors, which is conducive to improving the visitor conversion rate.

An embodiment of the present application also provides a data processing device. As shown in FIG. 7, the device includes an acquiring module 10, a determining module 20, and a processing module 30. The acquiring module 10 is used to acquire the visitors of the target visitor. Data; the determining module 20 is used to determine the visitor level of the target visitor based on the visitor data; the processing module 30 is used to determine the data to be pushed corresponding to the visitor level, and according to the visitor The data push method corresponding to the level pushes the data to be pushed to the target visitor.

In some embodiments, the visitor data includes visit data and profile data. The visitor level includes a first visitor level determined based on the visit data, and/or a second visitor level determined based on the profile data. In an application scenario, the first visitor level can reflect the visitor's visit, and the second visitor level can reflect the purchase intention of the visitor.

In some embodiments, in a case where the visitor data includes visit data and the visitor level includes the first visitor level, the determining module 20 is configured to: according to the visit data, determine that The number of visits and/or the average duration of a single visit of the target visitor within a time period; in response to the number of visits being higher than the first threshold, and/or the average duration of a single visit is higher than the first The duration threshold determines that the first visitor level of the target visitor is a high-frequency customer.

In some embodiments, the visitor data further includes an identity type, and the determining module 20 is configured to: determine the time interval between the time of the last visit of the target visitor and the current moment according to the visit data, and/ Or, the single average visit duration of the target visitor within the preset time period; in response to the time interval exceeding a second threshold, and/or, the single average visit duration is lower than the second duration Threshold, when the identity type of the target visitor is the first type, it is determined that the first visitor level of the target visitor is a churn customer, or, when the identity type of the target visitor is the second type , It is determined that the first visitor level of the target visitor is a sleeping client.

In some embodiments, the profile data includes the spending power data and the objects of interest of the target visitor. In the case where the visitor data includes profile data and the visitor level includes the second visitor level, the determination The module 20 is configured to: determine the selling price of the attention object according to the attention object; determine the consumption interval corresponding to the target visitor according to the consumption power data; and respond to whether the selling price belongs to the consumption interval, Determine the second visitor level of the target visitor.

In some embodiments, the processing module 30 is further configured to: when the selling price does not belong to the consumption range, or the selling price belongs to the consumption range but the difference with the upper limit of the consumption range is less than a predetermined value. In the case of setting a value, based on the concerned object, data of other objects of the same type as the concerned object are searched, and the data of the other object is determined as the data to be pushed.

In some embodiments, the data push methods corresponding to different visitor levels are at least partially different; the data push methods include at least one of the push time, the time interval between two adjacent pushes, and the push path.

In some embodiments, the processing module 30 is further configured to: after the determining module 20 determines the visitor level of the target visitor, send the visitor level of the target visitor to the terminal, so that the terminal will The visitor level is stored and/or displayed in association with the target visitor. Wherein, a display in which the visitor level is associated with the target visitor may be displayed in a visitor list and/or visitor page in the form of a tag.

In some embodiments, the processing module 30 is further configured to: send part of the visitor data of the target visitor, such as identity type, visit data, etc., to the terminal, so that the terminal will associate the part of the visitor data with the target visitor. Associated storage and/or display. Similarly, the part of the visitor data associated with the target visitor may be displayed in the form of tags in the visitor list and/or visitor page.

Those skilled in the art should understand that, in some optional embodiments, the implementation functions of each processing module in the data processing apparatus shown in FIG. 7 can be understood with reference to the relevant description of the foregoing data processing method.

Those skilled in the art should understand that, in some alternative embodiments, the functions of each processing unit in the data processing device shown in FIG. 7 can be implemented by a program running on a processor, or can be implemented by a specific logic circuit. .

In practical applications, the specific structures of the above-mentioned acquisition module 10, determination module 20, and processing module 30 can all correspond to a processor. The specific structure of the processor may be a central processing unit (CPU, Central Processing Unit), a microprocessor (MCU, Micro Controller Unit), a digital signal processor (DSP, Digital Signal Processing), or a programmable logic device (PLC, Programmable Logic Controller) and other electronic components or collections of electronic components with processing functions. Wherein, the processor includes executable code, the executable code is stored in a storage medium, and the processor may be connected to the storage medium through a communication interface such as a bus. When performing the corresponding functions of specific units, , Read and run the executable code from the storage medium. The part of the storage medium for storing the executable code is preferably a non-transitory storage medium.

The data processing device provided by the embodiment of the application can effectively use visitor data to classify the visitor level of each target visitor, so as to distinguish or mark different target visitors; and according to the data push method corresponding to the visitor level, Pushing the data to be pushed can provide more targeted data push for target visitors of different visitor levels, thereby further improving visitor experience and visitor conversion rate.

The embodiment of the present application also provides a data processing device, which is applied to a terminal. As shown in FIG. 8, the device includes:

The communication module 40 is used to receive visitor level information of the target visitor;

The display processing module 50 is used to display the visitor level information of the target visitor.

Wherein, the visitor level includes a first visitor level and/or a second visitor level.

In a possible implementation manner, the display processing module 50 is configured to store and/or display the visitor level information associated with the target visitor. Wherein, the visitor level information and the target visitor may be displayed in the form of a tag in a visitor list and/or a visitor page.

In a possible implementation manner, the display processing module 50 is also used to store and/or display part of the visitor data associated with the target visitor. Similarly, the part of the visitor data associated with the target visitor may be displayed in the form of tags in the visitor list and/or visitor page.

Those skilled in the art should understand that, in some optional embodiments, the implementation functions of each processing module in the data processing device shown in FIG. 8 can be understood with reference to the relevant description of the foregoing data processing method.

Those skilled in the art should understand that, in some alternative embodiments, the functions of each processing unit in the data processing device shown in FIG. 8 can be realized by a program running on a processor, or can be realized by a specific logic circuit. .

In practical applications, the specific structures of the communication module 40 and the display processing module 50 described above can all correspond to a processor. The specific structure of the processor may be an electronic component or a collection of electronic components with processing functions such as a CPU, MCU, DSP, or PLC. Wherein, the processor includes executable code, the executable code is stored in a storage medium, and the processor may be connected to the storage medium through a communication interface such as a bus. When performing the corresponding functions of specific units, , Read and run the executable code from the storage medium. The part of the storage medium for storing the executable code is preferably a non-transitory storage medium.

The data processing device described in the embodiment of the application facilitates the terminal user to know the visitor level of the current target visitor in time, facilitates differentiated processing according to the determined visitor level label, and can save more energy for visitor reception and visitor relationship maintenance Selectively put into high-value visitors, so as to help increase the visitor conversion rate.

An embodiment of the present application provides a data processing device, including: a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the program, the method described in the embodiment of the present application is implemented. The steps of the data processing method.

The embodiment of the present application provides a storage medium storing a computer program. When the computer program is executed by a processor, the processor causes the processor to execute the steps of the data processing method described in the embodiment of the present application.

Those skilled in the art should understand that the function of each program in the computer storage medium of this embodiment can be understood with reference to the relevant description of the data processing method described in each of the foregoing embodiments.

It should also be understood that the various optional embodiments listed in this document are only exemplary, and are used to help those skilled in the art to better understand the technical solutions of the embodiments of the present application, and should not be construed as limiting the embodiments of the present application. A person of ordinary skill in the art can make various changes and substitutions on the basis of the various optional embodiments described herein, and it should also be understood as a part of the embodiments of this application.

In addition, the description of the technical solutions in this article focuses on emphasizing the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, the details are not repeated one by one.

In the several embodiments provided in this application, it should be understood that the disclosed device and method may be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other divisions in actual implementation, such as: multiple units or components can be combined, or It can be integrated into another system, or some features can be ignored or not implemented. In addition, the coupling, or direct coupling, or communication connection between the components shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms. of.

The units described above as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.

In addition, in each embodiment of the present application, the functional units can all be integrated into one processing unit, or each unit can be individually used as a unit, or two or more units can be integrated into one unit; the above-mentioned integrated The unit can be implemented in the form of hardware, or in the form of hardware plus software functional units.

Those of ordinary skill in the art can understand that all or part of the steps in the above method embodiments can be implemented by a program instructing relevant hardware. The foregoing program can be stored in a computer readable storage medium. When the program is executed, the execution includes The steps of the foregoing method embodiment; and the foregoing storage medium includes: removable storage devices, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks, etc. The medium storing the program code.

Alternatively, if the aforementioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it may also be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application can be embodied in the form of a software product in essence or a part that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for A computer device (which may be a personal computer, a server, or a network device, etc.) is allowed to execute all or part of the methods described in the various embodiments of the present application. The aforementioned storage media include: removable storage devices, ROM, RAM, magnetic disks, or optical disks and other media that can store program codes.

Claims

A data processing method, including:

Obtain visitor data of target visitors;

Determine the visitor level of the target visitor based on the visitor data;

Determine the data to be pushed corresponding to the visitor level; and

Push the data to be pushed to the target visitor according to the data push mode corresponding to the visitor level.
The method according to claim 1, wherein the visitor data includes visit data and profile data; the visitor level includes a first visitor level determined based on the visit data, and/or, based on the The second visitor level determined by the profile data.
The method according to claim 2, characterized in that, in the case that the visitor data includes the visit data and the visitor level includes the first visitor level, the determining the visitor data is based on the visitor data. State the visitor level of the target visitor, including:

According to the visit data, determine the number of visits and/or the average duration of a single visit of the target visitor within a preset time period;

In response to the number of visits being higher than the first threshold, and/or the single average visit duration is higher than the first duration threshold, it is determined that the first visitor level of the target visitor is a high-frequency customer.
The method according to claim 3, wherein the visitor data further includes an identity type, and the determining the visitor level of the target visitor based on the visitor data includes:

According to the visit data, determine the time interval between the time of the last visit of the target visitor and the current moment, and/or the single average visit time of the target visitor within the preset time period;

In response to the time interval exceeding the second threshold, and/or the single average visit time is lower than the second time threshold,

When the identity type of the target visitor is the first type, it is determined that the first visitor level of the target visitor is a lost customer, or,

When the identity type of the target visitor is the second type, it is determined that the first visitor level of the target visitor is a sleeping customer.
The method according to claim 2, wherein the profile data includes the spending power data of the target visitor and the objects of interest, the visitor data includes the profile data, and the visitor level includes the second In the case of a visitor level, the determining the visitor level of the target visitor based on the visitor data includes:

Determine the selling price of the concerned object according to the concerned object;

Determine the consumption interval corresponding to the target visitor according to the consumption power data;

In response to whether the selling price belongs to the consumption range, the second visitor level of the target visitor is determined.
The method according to claim 5, characterized in that, when the selling price does not belong to the consumption range, or the selling price belongs to the consumption range but the difference from the upper limit of the consumption range is less than a preset value In the case of, the determining the data to be pushed corresponding to the visitor level includes:

Based on the object of interest, search for data of other objects of the same type as the object of interest,

The data of the other object is determined as the data to be pushed.
The method according to any one of claims 1 to 6, wherein the data push methods corresponding to different visitor levels are at least partially different; the data push methods include at least push time and the time interval between two adjacent pushes , One of the push channels.
The method according to any one of claims 1 to 7, characterized in that, after the determining the visitor level of the target visitor, the method further comprises:

The visitor level of the target visitor is sent to the terminal, so that the terminal stores and/or displays the visitor level in association with the target visitor.
A data processing device includes:

The acquisition module is used to acquire the visitor data of the target visitor;

A determining module, configured to determine the visitor level of the target visitor based on the visitor data;

The processing module is configured to determine the data to be pushed corresponding to the visitor level, and push the data to be pushed to the target visitor according to the data push mode corresponding to the visitor level.
The device according to claim 9, wherein the visitor data includes visit data and profile data; the visitor level includes a first visitor level determined based on the visit data, and/or, based on the The second visitor level determined by the profile data.
The apparatus according to claim 10, wherein, in a case where the visitor data includes the visit data and the visitor level includes the first visitor level, the determining module is configured to:

According to the visit data, determine the number of visits and/or the average duration of a single visit of the target visitor within a preset time period;

In response to the number of visits being higher than the first threshold, and/or the single average visit duration is higher than the first duration threshold, it is determined that the first visitor level of the target visitor is a high-frequency customer.
The device according to claim 11, wherein the visitor data further includes an identity type, and the determining module is configured to:

According to the visit data, determine the time interval between the time of the last visit of the target visitor and the current moment, and/or the single average visit time of the target visitor within the preset time period;

In response to the time interval exceeding the second threshold, and/or the single average visit time is lower than the second time threshold,

When the identity type of the target visitor is the first type, it is determined that the first visitor level of the target visitor is a lost customer, or,

When the identity type of the target visitor is the second type, it is determined that the first visitor level of the target visitor is a sleeping customer.
The device according to claim 10, wherein the profile data includes the spending power data and the objects of interest of the target visitor, the visitor data includes the profile data, and the visitor level includes the second In the case of visitor level, the determining module is used to:

Determine the selling price of the concerned object according to the concerned object;

Determine the consumption interval corresponding to the target visitor according to the consumption power data;

In response to whether the selling price belongs to the consumption range, the second visitor level of the target visitor is determined.
The device according to claim 13, wherein the processing module is further configured to:

In the case that the selling price does not belong to the consumption range, or the selling price belongs to the consumption range but the difference from the upper limit of the consumption range is less than a preset value, based on the concerned object, search for The object of interest belongs to data of other objects of the same type, and the data of the other object is determined as the data to be pushed.
The device according to any one of claims 9 to 14, wherein the data push methods corresponding to different visitor levels are at least partially different; the data push methods include at least the push time and the time interval between two adjacent pushes , One of the push channels.
The device according to any one of claims 9 to 15, wherein the processing module is further configured to:

After the determining module determines the visitor level of the target visitor, it sends the visitor level of the target visitor to the terminal, so that the terminal stores and/or displays the visitor level in association with the target visitor.
A data processing device comprising: a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the computer program described in any one of claims 1 to 8 is implemented Data processing method.
A storage medium storing a computer program, and when the computer program is executed by a processor, the processor executes the data processing method according to any one of claims 1 to 8.
A computer program comprising computer executable code, which when the computer executable code runs on a device, causes a processor in the device to execute the data processing method according to any one of claims 1-8.