WO2021129342A1 - 数据处理方法、装置、设备、存储介质及计算机程序 - Google Patents

数据处理方法、装置、设备、存储介质及计算机程序 Download PDF

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Publication number
WO2021129342A1
WO2021129342A1 PCT/CN2020/133651 CN2020133651W WO2021129342A1 WO 2021129342 A1 WO2021129342 A1 WO 2021129342A1 CN 2020133651 W CN2020133651 W CN 2020133651W WO 2021129342 A1 WO2021129342 A1 WO 2021129342A1
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Prior art keywords
visitor
data
level
target
visit
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PCT/CN2020/133651
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English (en)
French (fr)
Inventor
周雪琪
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Beijing Sensetime Technology Development Co Ltd
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Beijing Sensetime Technology Development Co Ltd
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Priority to JP2022538817A priority Critical patent/JP2023507043A/ja
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0202—Market predictions or forecasting for commercial activities
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Recommending goods or services

Definitions

  • This application relates to a data processing method, device, equipment, storage medium and computer program.
  • this application provides a data processing solution.
  • 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.
  • 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.
  • the determination of the target visitor's status based on the visitor data 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.
  • the visitor data further includes an identity type
  • 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.
  • 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.
  • 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.
  • 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 .
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the visitor data further includes an identity type
  • 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 .
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • FIG. 1 is a schematic flowchart of a data processing method provided by an embodiment of this application
  • FIG. 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.
  • the embodiments of the present disclosure can be applied to various electronic devices, including but not limited to fixed devices and/or mobile devices.
  • the fixed device includes but is not limited to: a personal computer (PC), or a server, etc.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the visit data includes the number of visits of the target visitor within a preset time period.
  • the visit data includes the single visit time of the target visitor.
  • the visit data includes a single average visit time of the target visitor within a preset time period.
  • 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.
  • the termination time is the time before the current time (may include the current time).
  • the visitor data may include profile data, and the profile data includes spending power data of the target visitor and objects of interest.
  • 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.
  • 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.
  • the first visitor level may reflect the visitor status of the visitor
  • the second visitor level may reflect the purchase intention of the visitor.
  • the visitor level for reflecting other attributes may also be included.
  • the categories included in the visitor level and the parallel items included in each category are not limited.
  • 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.
  • the ranges of purchase possibilities corresponding to different second visitor levels are different.
  • the data to be pushed is data corresponding to the visitor level that is ready to be pushed to the target visitor.
  • the data to be pushed includes vehicle type content.
  • 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. .
  • 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.
  • the push channels include emails, short messages, phone calls, WeChat, Moments, official accounts, and so on.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • a third type such as a blacklist, can also be included.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the high-frequency customers, the lost customers, and the sleeping customers can be set or adjusted according to user needs.
  • the profile data includes the spending power data of the target visitor and the objects of interest.
  • 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.
  • the concerned object may include the car of interest, and the selling price thereof is determined accordingly.
  • 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.
  • the second visitor level is divided into S level, A level, B level, C level, and D level as an example.
  • 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.
  • 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.
  • 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.
  • 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).
  • 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.
  • 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).
  • 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.
  • 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.
  • 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).
  • 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 ,
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the difference between the selling price and the upper limit of the consumption range will affect the second visitor level.
  • 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.
  • the method 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.
  • 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.
  • 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.
  • 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.
  • 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 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.
  • 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.
  • 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 may be displayed in the form of tags in the visitor list and/or visitor page.
  • 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.
  • the sales staff responsible for follow-up of the visitor in the store to perform efficient data management.
  • step S11 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.
  • the historical visit information includes at least visit time.
  • the historical visit information may be all visit information of the target visitor before this visit.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the evaluation criteria corresponding to different evaluation items may be the same or different.
  • 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.
  • 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.
  • 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.
  • the terminal stores and/or displays the relationship between the visitor level and the target visitor.
  • 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.
  • the method further includes: receiving an analysis result of visitor level information corresponding to the target visitor; and displaying the analysis result.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Figure 3(b) shows a schematic diagram of visitor information of a certain terminal user displayed on the terminal side.
  • FIG. 3(b) 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.
  • the terminal user 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.
  • 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.
  • 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.
  • 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.
  • customers are lost customers.
  • 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.
  • 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.
  • 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.
  • 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.
  • FIG. 5(c) shows a schematic diagram of a visitor list displayed on the terminal side and automatically recognized by the server side.
  • 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.
  • 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.
  • FIG. 6 shows a schematic diagram of a visitor tag editing interface in a specific application scenario, and the terminal user can edit the interface.
  • 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.
  • the terminal 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.
  • the terminal interface displays tag information of multiple visitors.
  • the visitor's label is in an editable state.
  • the terminal performs an editing operation on the visitor's tag based on the editing information input by the user.
  • the terminal 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.
  • 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.
  • the identity type of the visitor is changed from a customer to a member based on the operation.
  • 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.
  • the profile data may include evaluation information
  • 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.
  • 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.
  • 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.
  • the first visitor level can reflect the visitor's visit
  • the second visitor level can reflect the purchase intention of the visitor.
  • 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.
  • the visitor data further includes an identity type
  • 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.
  • the profile data includes the spending power data and the objects of interest of the target visitor.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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. .
  • 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.
  • the processor includes executable code
  • the executable code is stored in a storage medium
  • the processor may be connected to the storage medium through a communication interface such as a bus.
  • 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.
  • the visitor level includes a first visitor level and/or a second visitor level.
  • the display processing module 50 is configured to store and/or display the visitor level information associated with the target visitor.
  • 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.
  • the display processing module 50 is also used to store and/or display part of the visitor data associated with the target visitor.
  • 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.
  • 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.
  • 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. .
  • 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.
  • 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.
  • a communication interface such as a bus.
  • 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.
  • a 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.
  • the processor causes the processor to execute the steps of the data processing method described in the embodiment of the present application.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • 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.
  • 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.
  • 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.
  • the foregoing program can be stored in a computer readable storage medium.
  • 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.
  • 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.
  • 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.

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Abstract

一种数据处理方法、装置、设备、存储介质及计算机程序。其中，所述数据处理方法包括：获取目标访客的访客数据（S11）；基于所述访客数据，确定所述目标访客的访客等级（S12）；确定与所述访客等级对应的待推送数据，并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据（S13）。

Description

数据处理方法、装置、设备、存储介质及计算机程序
交叉引用声明
本申请要求于2019年12月27日提交中国专利局的申请号为201911379987.1的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及一种数据处理方法、装置、设备、存储介质及计算机程序。
背景技术
实际使用中，销售人员会根据访客的特点，对其进行差异化接待，以提高访客转化率，获得更大的利益。目前，数据整理、业务跟进的工作通常人为进行，以根据数据整理结果为访客提供服务。然而，人为整理数据，往往会出现数据纰漏，而且不同销售人员整理得到的结果参差不齐，从而影响业务跟进效果。因此，亟需一种数据处理方法。
发明内容
有鉴于此，本申请提供一种数据处理方案。
第一方面，本申请实施例提供了一种数据处理方法，所述方法包括：获取目标访客的访客数据；基于所述访客数据，确定所述目标访客的访客等级；确定与所述访客等级对应的待推送数据；并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。
在一种可能的实现方式中，所述访客数据包括到访数据和资料数据；所述访客等级包括基于所述到访数据确定的第一访客等级，和/或，基于所述资料数据确定的第二访客等级。
在一种可能的实现方式中，在所述访客数据包括所述到访数据，所述访客等级包括所述第一访客等级的情况下，所述基于所述访客数据，确定所述目标访客的访客等级，包括：根据所述到访数据，确定在预设时间段内所述目标访客的到访次数和/或单次平均到访时长；响应于所述到访次数高于第一阈值，和/或，所述单次平均到访时长高于第一时长阈值，确定所述目标访客的第一访客等级为高频客户。
在一种可能的实现方式中，所述访客数据还包括身份类型，所述基于所述访客数据，确定所述目标访客的访客等级，包括：根据所述到访数据，确定所述目标访客最后一次到访的时间距离当前时刻的时间间隔，和/或，在所述预设时间段内所述目标访客的单次平均到访时长；响应于所述时间间隔超过第二阈值，和/或，所述单次平均到访时长低于第二时长阈值，在所述目标访客的所述身份类型为第一类型时，确定所述目标访客的第一访客等级为流失客户，或是，在所述目标访客的所述身份类型为第二类型时，确定所述目标访客的第一访客等级为沉睡客户。
在一种可能的实现方式中，所述资料数据包括所述目标访客的消费力数据以及关注对象，在所述访客数据包括所述资料数据，所述访客等级包括所述第二访客等级的情况下，所述基于所述访客数据，确定所述目标访客的访客等级，包括：根据所述关注对象，确定所述关注对象的售价；根据所述消费力数据，确定所述目标访客对应的消费区间；响应于所述售价是否属于所述消费区间，确定所述目标访客的第二访客等级。
在一种可能的实现方式中，在所述售价不属于所述消费区间，或者所述售价属于所述消费区间但与所述消费区间上限值之差小于预设值的情况下，所述确定与所述访客等 级对应的待推送数据包括：基于所述关注对象，查找与所述关注对象属于同一类型的其他对象的数据，将所述其他对象的数据确定为所述待推送数据。
在一种可能的实现方式中，不同所述访客等级对应的数据推送方式至少部分不同；所述数据推送方式至少包括推送时间、相邻两次推送的时间间隔、推送途径中的一项。
在一种可能的实现方式中，在所述确定所述目标访客的访客等级之后，所述方法还包括：向终端发送所述目标访客的访客等级，以使所述终端将所述访客等级与所述目标访客相关联的存储和/或展示。
第二方面，本申请实施例提供了一种数据处理装置，所述装置包括：获取模块，用于获取目标访客的访客数据；确定模块，用于基于所述访客数据，确定所述目标访客的访客等级；处理模块，用于确定与所述访客等级对应的待推送数据，并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。
在一种可能的实现方式中，所述访客数据包括到访数据和资料数据；所述访客等级包括基于所述到访数据确定的第一访客等级，和/或，基于所述资料数据确定的第二访客等级。
在一种可能的实现方式中，在所述访客数据包括所述到访数据，所述访客等级包括所述第一访客等级的情况下，所述确定模块，用于：根据所述到访数据，确定在预设时间段内所述目标访客的到访次数和/或单次平均到访时长；响应于所述到访次数高于第一阈值，和/或，所述单次平均到访时长高于第一时长阈值，确定所述目标访客的第一访客等级为高频客户。
在一种可能的实现方式中，所述访客数据还包括身份类型，所述确定模块用于：根据所述到访数据，确定所述目标访客最后一次到访的时间距离当前时刻的时间间隔，和/或，在所述预设时间段内所述目标访客的单次平均到访时长；响应于所述时间间隔超过第二阈值，和/或，所述单次平均到访时长低于第二时长阈值，在所述目标访客的所述身份类型为第一类型时，确定所述目标访客的第一访客等级为流失客户，或是，确定所述目标访客的第一访客等级为沉睡客户。
在一种可能的实现方式中，所述资料数据包括所述目标访客的消费力数据以及关注对象，在所述访客数据包括所述资料数据，所述访客等级包括所述第二访客等级的情况下，所述确定模块用于：根据所述关注对象，确定所述关注对象的售价；根据所述消费力数据，确定所述目标访客对应的消费区间；响应于所述售价是否属于所述消费区间，确定所述目标访客的第二访客等级。
在一种可能的实现方式中，所述处理模块还用于：在所述售价不属于所述消费区间，或者所述售价属于所述消费区间但与所述消费区间上限值之差小于预设值的情况下，基于所述关注对象，查找与所述关注对象属于同一类型的其他对象的数据，将所述其他对象的数据确定为所述待推送数据。
在一种可能的实现方式中，不同所述访客等级对应的数据推送方式至少部分不同；所述数据推送方式至少包括推送时间、相邻两次推送的时间间隔、推送途径中的一项。
在一种可能的实现方式中，所述处理模块，还用于：在所述确定模块确定出所述目标访客的访客等级之后，向终端发送所述目标访客的访客等级，以使所述终端将所述访客等级与所述目标访客相关联的存储和/或展示。
第三方面，本申请实施例提供了一种数据处理设备，包括：存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现本申请实施例所述的数据处理方法的步骤。
第四方面，本申请实施例提供了一种存储介质，存储有计算机程序，所述计算机程序被处理器执行时，使得所述处理器执行本申请实施例所述的数据处理方法的步骤。
本申请实施例提供的技术方案，获取目标访客的访客数据；基于所述访客数据，确定所述目标访客的访客等级；确定与所述访客等级对应的待推送数据，并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。如此，能够至少部分节省人为进行数据整理而造成的耗时耗力，从而有效提高数据处理的效率。并且，基于访客数据，确定目标访客的访客等级，能够有效利用访客数据对各目标访客的访客等级进行划分，以起到区分或是标记不同目标访客的作用；而按照所述访客等级对应的数据推送方式，推送所述待推送数据，能为不同访客等级的目标访客提供更有针对性的数据推送，从而进一步提高访客体验和访客转化率。
附图说明
图1为本申请实施例提供的一种数据处理方法的流程示意图；
图2为本申请实施例提供的另一种数据处理方法的流程示意图；
图3(a)为本申请实施例提供的终端侧显示的、服务器侧自动识别的当天访客信息的示意图；
图3(b)为本申请实施例提供的终端侧显示的、某一终端用户的访客信息的示意图；
图3(c)为本申请实施例提供的终端侧显示的单个访客信息的示意图；
图3(d)为本申请实施例提供的终端侧显示的访客编辑界面示意图；
图4为本申请实施例提供的基于到访频次分析访客等级的流程示意图；
图5(a)为本申请实施例提供的终端接收到访消息推送的示意图；
图5(b)为本申请实施例提供的展示某访客历次到访消息的示意图；
图5(c)为本申请实施例提供的终端侧显示的、服务器侧自动识别的访客列表的示意图；
图5(d)为本申请实施例提供的基于某一时间段内访客数据的分析示意图；
图6为本申请实施例提供的访客标签编辑界面示意图；
图7为本申请实施例提供的一种数据处理装置的组成结构示意图；
图8为本申请实施例提供的另一种数据处理装置的组成结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本申请实施例方案，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚地描述，显然，所描述的实施例仅仅是本申请一部分的实施例，而不是全部的实施例。
本申请的说明书实施例和权利要求书及上述附图中的术语“第一”、“第二”、和“第三”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。此外，术语“包括”和“具有”以及其任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元。方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
本公开实施例可以应用于各种电子设备中，该电子设备包括但不限于固定设备和/或移动设备。例如，所述固定设备包括但不限于：个人电脑(Personal Computer，PC)、或者服务器等，所述服务器可以是云服务器或普通服务器。所述移动设备包括但不限于：手机、平板电脑或可穿戴式设备中的一项或是多项。
本申请实施例提供一种数据处理方法，可以应用于上述电子设备中。如图1所示，所述方法主要包括以下步骤：
步骤S11、获取目标访客的访客数据；
步骤S12、基于所述访客数据，确定所述目标访客的访客等级；
步骤S13、确定与所述访客等级对应的待推送数据，并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。
在本公开实施例中，所述目标访客通常指的是被服务的访客，比如，客户、极有可能成为客户的访客等。目标访客指的可以是上述被服务的访客中的一位或是多位。在一种实现方式中，目标访客可以是到目标场所的所有人中除白名单以外的任意一个人。可以理解，所述目标访客不包括被列为白名单的人。
其中，所述白名单包括下述至少之一：目标场所的员工，保洁人员，维修师傅，快递人员，外卖人员。需要说明的是，所述白名单可根据用户需求进行设定或调整。在本公开实施例中，所述目标场所可以指的是能够展览或销售商品的地方，包括但不限于4S店、商铺、商场、超级市场等。
在本公开实施例中，所述访客数据可包括到访数据，所述到访数据是通过摄像机采集目标场所中目标访客的人脸图像和/或人体图像获得的。比如，所述到访数据包括预设时间段内目标访客的到访次数。又比如，所述到访数据包括目标访客的单次到访时间。再比如，所述到访数据包括预设时间段内目标访客的单次平均到访时长。其中，所述预设时间段可以包括以起始时间为开始、以终止时间为截至的一段时间，例如一天、一周、一月、一季度、半年、一年等。该预设时间段可以基于实际需求确定，本公开实施例对预设时间段的设置方式、具体取值等不做限定。需要说明的是，所述终止时间为当前时刻之前(可以包括当前时刻)的时间。
在本公开实施例中，所述访客数据可包括资料数据，所述资料数据包括目标访客的消费力数据以及关注对象。在本公开的一个应用场景中，该消费力数据可以是反映访客经济水平的参数，比如，职业、月收入、年收入、居住地等；该关注对象可以用于反映访客喜好的产品，比如，偏好车型。
在本公开实施例中，所述访客等级可以包括基于到访数据确定的第一访客等级，以及基于资料数据确定的第二访客等级中的至少一项。在一个应用场景中，例如，第一访客等级可反映访客到访情况，第二访客等级可反映访客购买意向。在本公开实施例中，还可以包括用于反映其他属性的访客等级。在本申请实施例中，对于访客等级所包括的种类，以及每个种类下所包括的并列项等，不予限定。
在一种实现方式中，所述第一访客等级包括高频客户、流失客户、沉睡客户等，不同的第一访客等级对应的到访频次不同。所述第二访客等级包括S等级、A等级、B等级、C等级、D等级；或者，所述第二访客等级包括A等级、B等级、C等级、D等级、E等级；或者，所述第二访客等级包括H等级、A等级、B等级、C等级、D等级。在 本公开的一个应用场景中，不同第二访客等级对应的购买可能性的范围不同。
在本公开实施例中，所述待推送数据，是准备向目标访客推送的、与访客等级对应的数据。在本公开的一个应用场景中，所述待推送数据包括车型内容。示例性地，对于购买意向高的目标访客，可以直接针对性的推送目标访客偏好的车型内容；对于购买意向低的目标访客，可以推送目标访客偏好车型的同类和/或反差较大的车型内容。
在本公开实施例中，不同所述访客等级对应的数据推送方式至少部分不同。所述数据推送方式至少包括推送时间、相邻两次推送的时间间隔、推送途径中的一项。比如，所述推送途径包括邮件、短信、电话、微信、朋友圈、公众号等。
本申请实施例提供的技术方案，获取目标访客的访客数据；基于所述访客数据，确定所述目标访客的访客等级；确定与所述访客等级对应的待推送数据，并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。如此，能够至少部分节省人为进行数据整理而造成的耗时耗力，从而有效提高数据处理效率。并且，基于访客数据，确定目标访客的访客等级，能够有效利用访客数据对各目标访客的访客等级进行划分，以起到区分或是标记不同目标访客的作用；而按照所述访客等级对应的数据推送方式，推送所述待推送数据，能为不同访客等级的目标访客提供更有针对性的数据推送，从而进一步提高访客体验和访客转化率。
为了基于访客数据确定目标访客的访客等级，在一些实现方式中，在访客数据包括到访数据，访客等级包括第一访客等级的情况下，所述基于所述访客数据，确定所述目标访客的访客等级，包括：根据所述到访数据，确定在预设时间段内所述目标访客的到访次数和/或单次平均到访时长；响应于所述到访次数高于第一阈值，和/或，所述单次平均到访时长高于第一时长阈值，确定所述目标访客的第一访客等级为高频客户。
需要说明的是，所述第一阈值和所述第一时长阈值，都是预先设置的阈值。所述第一阈值和所述第一时长阈值，可以根据投入的时间、成本等，和/或需求，预先进行设置，在此对于设置方式等不予限定。
如此，根据目标访客在预设时间段内的到访次数或单次平均到访时长，确定目标访客的第一访客等级。
示例性地，在预设时间段内的到访次数高于第一阈值的情况下，将目标访客的第一访客等级确定为高频客户；在预设时间段内的单次平均到访时长高于第一时长阈值的情况下，将目标访客的第一访客等级确定为高频客户；或者，在预设时间段内的到访次数高于第一阈值，且在预设时间段内的单次平均到访时长高于第一时长阈值的情况下，将目标访客的第一访客等级确定为高频客户。
考虑目标访客的身份类型可能不同，例如有的目标访客被判定为普通访客，有的目标访客被判定为重要访客，不同身份类型的目标访客对应的访客等级可以不同。因此，在一种可能的实现方式中，访客数据还包括身份类型。身份类型可以包括第一类型例如普通访客，第二类型例如重要访客。此外，还可以包括第三类型，例如黑名单等。
相应的，所述基于所述访客数据，确定所述目标访客的访客等级，包括：根据到访数据，确定所述目标访客最后一次到访的时间距离当前时刻的时间间隔，和/或，在所述预设时间段内所述目标访客的单次平均到访时长；响应于所述时间间隔超过第二阈值，和/或，所述单次平均到访时长低于第二时长阈值，确定第一类型的所述目标访客的第一 访客等级为流失客户，或是，确定第二类型的所述目标访客的第一访客等级为沉睡客户。
需要说明的是，所述第二阈值和所述第二时长阈值，都是预先设置的阈值。所述第二阈值和所述第二时长阈值，可以根据投入的时间、成本等，和/或需求，预先进行设置，在此对于设置方式等不予限定。
在本公开的一个应用场景中，所述第一类型和所述第二类型的区分标准可以是所述目标访客是否为会员；若为会员，则判定其身份类型为第二类型；若不是会员，则判定其身份类型为第一类型。
如此，根据目标访客在预设时间段内的到访次数或单次平均到访时长，确定目标访客的第一访客等级。
示例性地，若目标访客的身份类型为第一类型，且最后一次到访的时间距离当前时刻的时间间隔超过第二阈值，则确定目标访客的第一访客等级为流失客户；若目标访客的身份类型为第一类型，且该目标访客的单次平均到访时长低于第二时长阈值，则确定目标访客的第一访客等级为流失客户；或者，若目标访客的身份类型为第一类型，最后一次到访的时间距离当前时刻的时间间隔超过第二阈值，且该目标访客的单次平均到访时长低于第二时长阈值，则确定目标访客的第一访客等级为流失客户。
示例性地，若目标访客的身份类型为第二类型，且最后一次到访的时间距离当前时刻的时间间隔超过第二阈值，则确定目标访客的第一访客等级为沉睡客户；若目标访客的身份类型为第二类型，且该目标访客的单次平均到访时长低于第二时长阈值，则确定目标访客的第一访客等级为沉睡客户；或者，若目标访客的身份类型为第二类型，最后一次到访的时间距离当前时刻的时间间隔超过第二阈值，且单次平均到访时长低于第二时长阈值，则确定目标访客的第一访客等级为沉睡客户。
需要说明的是，所述高频客户、所述流失客户和所述沉睡客户等可以根据用户需求进行设定或调整。
为了基于访客数据确定目标访客的访客等级，在一些实现方式中，所述资料数据包括所述目标访客的消费力数据以及关注对象。在所述访客数据包括资料数据，所述访客等级包括所述第二访客等级的情况下，所述基于所述访客数据，确定所述目标访客的访客等级，包括：根据所述关注对象，确定所述关注对象的售价；根据所述消费力数据，确定所述目标访客对应的消费区间；响应于所述售价是否属于所述消费区间，确定所述目标访客的第二访客等级。
在本公开的一个应用场景中，关注对象可以包括关注车型，并相应确定其售价。在该应用场景中，通过分析目标访客的关注车型和消费力数据来评估第二访客等级，该第二访客等级表征目标访客购买能力，便于根据确定出的第二访客等级进行差异化的接待，进而将更多的访客接待精力和访客关系维护精力有选择的付诸于高价值访客，从而有利于提高访客转化率。
下面，仅以第二访客等级分为S等级、A等级、B等级、C等级、D等级为例说明。其中，上述各第二访客等级所指示的目标访客的购买意向依次降低，也就意味着，S等级指示的访客的购买意向最高，D等级指示的访客的购买意向最低。需要说明的是，在实际应用过程中，第二访客等级还可以按照购买意向从低到高排列为S等级、A等级、B等级、C等级、D等级。在本申请实施例中，对于第二访客等级中每项(比如，S等 级、A等级、B等级、C等级、D等级)与指示的购买意向的高低之间的对应关系不予限定，且对于第二访客等级包括多少项不予限定，可以根据用户需求定义和/或调整。
在一种实现方式中，当消费区间为[Y1,Y2]、关注车型的售价大于Y5的情况下，目标访客的第二访客等级为D等级。即在访客的消费区间(其中，访客的消费区间往往可以反映访客经济情况)远远低于访客的关注车型的售价的情况下，可以视为访客的购买意向极低(这里指的是访客通常不具备购买关注车型的能力，或是购买可能性较低)。
当消费区间为(Y2,Y3]、关注车型的售价(Y4,Y5]的情况下，目标访客的第二访客等级为C等级，即在访客的消费区间与访客的关注车型的售价存在一定差距，且访客的消费区间低于关注车型的售价的情况下，可以视为访客的购买意向较低。
当消费区间为(Y3,Y4]、关注车型的售价(Y3,Y4]的情况下，目标访客的第二访客等级为B等级，即在访客的消费区间与关注车型的售价属于同一区间范围内的情况下，可以视为访客的购买意向适中(这里指的是访客具备购买关注车型的能力，且关注车型的售价在访客预期的售价范围内)。
当消费区间为(Y4,Y5]、关注车型的售价(Y2,Y3]的情况下，目标访客的第二访客等级为A等级，即在访客的消费区间与访客的关注车型的售价存在一定差距，且访客的消费区间高于关注车型的售价的情况下，可以视为访客的购买意向较高。
当消费区间为(Y5,∞)、关注车型的售价(Y1,Y2]的情况下，目标访客的第二访客等级为S等级，即在访客的消费区间远远高于访客的关注车型的售价的情况下，可以视为访客的购买意向极高(这里指的是访客不仅具备购买关注车型的能力，且访客的经济情况对于支付关注车型的售价而言，绰绰有余)。
其中，0≤Y1＜Y2＜Y3＜Y4＜Y5。
可以理解，上述所示的第二访客等级的划分以及消费区间和售价的划分，仅仅是示意性地，本申请对此不做限定。
示例性地，如果目标访客的消费区间是30万-50万，若其关注车型的售价是100万，那可以认为第二访客等级表征访客的购买意向非常低，如D等级；若其关注车型的售价是60万，那可以认为第二访客等级表征访客的购买意向比较低，如C等级；若其关注车型的售价小于或等于50万，则可以认为第二访客等级表征访客具备较高的购买意向，只是在等级划分时，由于价位接近消费区间上限，所以可能购买意向也会较低，如B等级；若其关注车型的售价小于或等于40万，那完全在消费区间范围内，那可以认为第二访客等级表征访客的购买意向较高，如A等级；若其关注车型的售价小于或等于30万，那完全在消费区间范围内，或是低于内心最低价，那可以认为第二访客等级表征访客的购买意向非常高，如S等级。
其中，D等级表征目标访客的购买可能性小于或等于P1；
C等级表征目标访客的购买可能性大于P1，且小于等于P2；
B等级表征目标访客的购买可能性大于P2，且小于或等于P3；
A等级表征目标访客的购买可能性大于P3，且小于或等于P4；
S等级表征目标访客的购买可能性大于P4；其中，0≤P1＜P2＜P3＜P4＜P5。
可见，等级越高，表明目标访客短期内的购买可能性越大；等级越低，表明目标访客长期内购买可能性都较低。
在上述应用场景中，响应于所述售价是否属于所述消费区间，确定所述目标访客的第二访客等级，包括：如果所述售价不属于所述消费区间，确定所述访客难以购买所期望的车型，确定所述目标访客的第二访客等级为表征无购买意向或是购买意向最低的级别；所述售价属于所述消费区间，确定所述目标访客有购买意向，确定所述目标访客的第二访客等级为高于所述售价不属于所述消费区间的级别，如有购买意向或是有购买意向时按照购买意向大小进一步划分的级别。
这里，所述售价不属于所述消费区间，可以理解为售价不在所述消费区间内。所述售价不在消费区间内，既包括售价在消费区间的上限之上，也包括售价在消费区间的下限之下。示例性地，消费区间为30万-50万，若目标访客关注车型的售价为60万，表明售价不在消费区间内；若目标访客关注的车型的售价为20万，也表明售价不在消费区间内。实际应用中，售价不属于消费区间，可以仅理解为售价在消费区间的上限之上；或者，理解为售价在消费区间的上限之上，以及售价在消费区间的下限之下。
在上述应用场景中，在售价属于消费区间的情况下，售价与消费区间的上限之间的差值，会影响第二访客等级。差值越大，表明目标访客的购买可能性越高，相应的第二访客等级所表示的含义为目标访客极有可能购买这个车型的车。
在一些实施例中，在根据关注对象和消费力数据等资料数据来确定目标访客的第二访客等级且所述第二访客等级包括多个级别的情况下，所述基于所述访客数据，确定所述目标访客的访客等级，还可以包括：响应于所述消费力数据反映的可支配收入所属区间为第一可支配区间，和/或，所述关注对象反映的预支配收入所属区间为第一预支配区间，确定所述目标访客的第二访客等级为所述多个级别中的一种级别。其中，在确定所述目标访客的第二访客等级为所述多个级别中的一种级别之前，所述方法还包括：将消费力数据反映的可支配收入划分成多个可支配区间；和/或，将关注对象反映的预支配收入划分成多个预支配区间。如此，通过比较可支配区间和预支配区间，确定目标访客的第二访客等级。其中，将第二访客等级划分为多个级别，能够使确定出的第二访客等级更精确。
为了节省计算资源，在一种实现方式中，在目标访客的第一访客等级为高频客户的情况下，才会确定目标访客的第二访客等级。也即，在目标访客的第一访客等级为流失客户或沉睡客户的情况下，将不确定目标访客的第二访客等级。
在一种可能的实现方式中，在所述售价不属于所述消费区间，或者所述售价属于所述消费区间但与所述消费区间上限值之差小于预设值的情况下，所述确定所述访客等级对应的待推送数据包括：基于所述关注对象，查找与所述关注对象属于同一类型的其他对象的数据；将其他对象的数据确定为待推送数据。
在一个应用场景中，在所述售价不属于所述消费区间的情况下，可以查找与关注车型类型相同的其他车型的数据，确定为所述待推送数据。如此，有助于向目标访客推送与其经济能力相符的车型，从而有助于提高访客转化率。
为在另一个应用场景中，在所述售价属于所述消费区间但售价更靠近消费区间上限的情况下，可以查找与所述关注车型类型相同的其他车型的数据，确定为待推送数据。
如此，有助于向访客终端推送与访客购买意向相符的车型，从而有助于为访客提供多种同类型车型的选择，更有助于提高访客转化率。
在一些实施例中，在所述确定所述目标访客的访客等级之后，所述方法还包括：向终端发送所述目标访客的访客等级，以使所述终端将所述访客等级与所述目标访客相关联的存储和/或展示。其中，所述终端包括但不限于个人电脑、手机、平板电脑、可穿戴设备等。所述将所述访客等级与所述目标访客相关联的展示可以包括：以标签的形式将所述访客等级与所述目标访客相关联的展示。以及，所述将所述访客等级与所述目标访客相关联的展示可以包括：在访客列表和/或访客页面中将所述访客等级与所述目标访客相关联的展示。
在一些实施例中，所述方法还包括：向终端发送所述目标访客的部分访客数据，例如身份类型，到访数据等，以使所述终端将所述部分访客数据与所述目标访客相关联的存储和/或展示。类似的，可以以标签的形式在访客列表和/或访客页面中将所述部分访客数据与所述目标访客相关联的展示。
在一个应用场景中，通过终端展示访客的访客等级，便于门店内的负责访客跟进的销售人员进行高效的数据管理。例如，能够方便终端用户如销售人员直观了解目标访客到访情况和/或购买意向，辅助门店探查到高价值访客；也便于终端用户如销售人员根据确定出的访客等级进行差异化的接待，进而将更多的访客接待精力和访客关系维护精力有选择的付诸于高价值访客，从而有利于提高访客转化率。
在一些实施例中，在所述访客数据包括到访数据的情况下,步骤S11包括：获取所述目标访客的历史到访信息；根据所述历史到访信息，确定所述目标访客的到访数据。
这里，所述历史到访信息至少包括到访时间。
需要说明的是，所述历史到访信息可以是目标访客在本次到访之前的所有到访信息。当然，所述历史到访信息还可以是距离本次到访一定时间段内的到访信息，该一定时间段可根据设计或需求进行设定或调整。
在一个应用场景中，所述历史到访信息还可包括下列中的至少一种：到访地点信息或到访店面、结账购买信息、停留时长、咨询时长、购买意向等。这里所述的停留时长是指摄像机采集到的、目标访客从进入门店到离开门店之间的时间段。
需要说明的是，本申请并不对历史到访信息的细化程度进行限定。历史到访信息越详细，越有利于后续对目标访客的发掘。
如此，通过对历史到访信息进行分析来确定目标访客的到访数据，根据到访数据为目标访客确定第一访客等级，便于根据确定出的第一访客等级进行差异化的数据处理，进而能够将更多的访客接待精力和访客关系维护精力有选择的付诸于高价值访客，从而有利于提高访客转化率。
在一些实施例中，在所述访客数据包括资料数据的情况下,步骤S11包括：采集所述目标访客的消费力数据和关注对象；基于所述消费力数据和关注对象确定所述目标访客的资料数据。
在一个应用场景中，在访客到访时，可为访客提供调查问卷。该调查问卷中包括期望购买产品、理想价位、年龄、学历、职位、工作单位等多个选项，每个选项可对应有多个答案，由该访客从所述多个答案中勾选。
如此，便于根据调查问卷数据确定访客的资料数据，进而有助于根据该资料数据分析出高价值访客。
在另一个应用场景中，在目标访客到访后，终端用户可以基于所述目标访客的到访记录给出评价数据。所述评价数据至少包括购买能力数据和购买意愿数据中的一种。
这里，所述的终端用户可以理解为能够基于目标访客的到访记录给出评价数据的人员，如销售人员。
示例性地，销售人员在接待目标访客的过程中，根据自己的经验判断目标访客的购买能力和购买意愿，并根据已知评价标准为一个或多个评价项在终端上为该目标访客进行打分或者评级。例如，所述评价项包括购买能力评价项和购买意愿评价项，而评价数据包括打分或者评级结果；服务器或其他设备基于该评价数据确定该目标访客的购买可能性。需要说明的是，不同评价项对应的评价标准可能相同或不同。
如此，销售人员在接待目标访客的过程中，根据自己的经验判断目标访客的购买能力和购买意愿，在终端上输入对该目标访客的评价数据作为资料数据，以便于服务器或其他设备基于该评价数据确定该目标访客的访客等级。对于销售人员而言，操作方便、快捷，也便于服务器或其他设备对不同目标访客根据统一标准给出评估信息。
基于上述数据处理方法，本申请实施例还提供了一种应用于终端的数据处理方法。如图2所示，所述方法包括以下步骤。
步骤S21：接收目标访客的访客等级信息。
步骤S22：显示所述目标访客的访客等级信息。其中，所述终端将所述访客等级与所述目标访客相关联的存储和/或展示。具体的，可以以标签的形式在访客列表和/或访客页面中将所述访客等级信息与所述目标访客相关联的展示。
如此，便于终端用户根据该访客等级信息快速识别出目标访客是否为新访客。另外，能够根据目标访客的访客等级实现处理任务的快速分配，一方面有利于销售人员进行针对性工作和服务，提高工作效率；另一方面也便于根据确定出的访客等级进行差异化的接待，进而将更多的访客接待精力和访客关系维护精力有选择的付诸于高价值访客，从而有利于提高访客转化率。
在一些实施例中，所述方法还包括：接收所述目标访客对应的访客等级信息的分析结果；显示所述分析结果。
如此，便于终端用户及时知晓关于目标访客的访客等级信息的分析结果，进而有利于用户根据该分析结果进行针对性处理，从而提高访客体验和访客转化率。
示例性地，销售人员可以结合第一访客等级和第二访客等级这两类标签对访客采取不同的营销策略。比如，当第二访客等级指示等级较高但第一访客等级为流失客户时，基于上述标签，销售人员需使用更丰富有效的跟进和营销策略，拉回访客。
示例性地，当第二访客等级指示等级较低但第一访客等级为高频客户时，基于上述标签，销售人员可重新评估此访客的真实购买意图，把握住重点访客，以及反思自己在访客跟进过程中判定高价值访客的方法是否有误。
在一些实施例中，所述方法还包括：接收部分访客数据，例如身份类型，到访数据等，并将其与所述目标访客相关联的存储和/或展示。具体的，可以以标签的形式在访客列表和/或访客页面中将所述部分访客数据与所述目标访客相关联的展示。
图3(a)-图3(d)示出了一个具体的应用场景中，访客信息在终端侧的显示。图3(a)示出了终端侧显示的、服务器侧自动识别的当天访客信息的示意图。从图3(a) 可以看出，该界面上显示有当天到访的所有访客的信息，具体包括每一访客是否为初次到访、到访次数、到访时间、以及是否跟进等信息，为终端用户提供了详细的数据支撑，便于终端用户根据该界面所显示数据了解访客的信息，以及决定是否要对访客进行跟进。图3(b)示出了终端侧显示的、某一终端用户的访客信息的示意图。从图3(b)可以看出，该界面上显示该终端用户的访客信息，具体包括每一访客是否为初次到访、到访次数、到访时间。图3(c)示出了终端侧显示的单个访客信息的示意图，具体包括累计到访次数、最近到访时间、每次到访的同行人员等信息。图3(d)示出了终端侧显示的访客编辑界面示意图。如图3(d)所示，该界面上显示有潜客等级项，该潜客等级表示第二访客等级。用户可编辑访客的潜客等级，即用户可选择第二访客等级中的具体级别，如具体根据本次与访客的沟通情况决定是否对上次所评的级别进行更改。如此，便于终端用户了解到店访客的信息，根据到店访客的访客等级信息，对其进行差异化接待；也便于终端用户根据经验对到店访客进行评级。
图4示出了一个具体的应用场景中，基于到访频次分析访客等级的流程示意图。如图4所示，摄像机负责采集环境中人脸图像和/或人体图像；将采集到的原始图像通过统一接入服务传入服务器侧的后续处理环节。在服务器侧，通过图片处理与转发服务对人脸图像和/或人体图像进行特征提取和索引；将所得数据通过数据标准化服务传入Kafka消息队列中；通过调用检索服务对Kafka消息队列中的数据进行去脏和去重处理；将经过去脏和去重处理后所得的人脸和/或人体特征数据作为检索对象，以检索现有数据库中是否已有此访客的数据，来判断本次采集到的访客是否为新访客；如果判定为新访客，对其赋予第一类型例如客户的标签；如果判定为老访客，则再次根据数据库进行第二类型的匹配，例如识别是否为会员，并由此进行第一访客等级的判定。比如，根据一个示例，在最近15天内出现次数大于或等于3次的客户标记为高频客户，最近一次到店时间已超过30天的会员标记为沉睡会员，最近一次到店时间已超过30天的客户为流失客户。具体地，若判定该访客为会员，则查询上次到访时间，判断距离上次到访时间是否已经超过30天，当确定已经超过30天时，将该访客标记为沉睡会员，否则，不进行标记。如果该访客为非会员，即为客户，则查询该客户15天内到访次数，并将到访次数加1，然后判断15天内到访次数是否大于或等于3。如果大于或等于3，则将该客户标记为高频客户；如果15天内到访次数小于3，则查询上次到访时间，判断上次到访时间是否超过30天。当确定超过30天时，将其标记为流失客户。
需要说明的是，可以理解，图4中所示流程，可根据用户需求或设计需求进行设定或调整。
图5(a)-5(d)示出了一个具体的应用场景中，到访消息的推送、展示、分类和分析的示意图。图5(a)示出了终端接收到访消息推送的示意图。终端用户，例如销售人员，通过实时接收访客到访消息推送，可查询该访客的身份类型和访客等级，第一时间进行高品质的访客接待。并且，终端用户，例如安保人员，通过实时接收到黑名单告警消息推送，第一时间确定黑名单人员与其位置，有助于高效排除风险。图5(b)示出了展示某访客历次到访消息的示意图。通过在终端侧显示某访客的历史到访记录，大大方便终端用户区分并追溯历次接待过程中的重点信息，并可通过综合历次到访情况来辅助判断访客购买意愿与价值大小。如此，提高了终端用户对访客信息的掌握，进而有 助于提高访客转化率。图5(c)示出了终端侧显示的、服务器侧自动识别的访客列表的示意图。其中，服务器侧可支持基于标签进行访客分类，管理者与销售人员作为终端用户，均可针对某标签下的访客进行针对性客户营销和客户运营。图5(d)示出了基于某一时间段内访客数据的分析示意图。通过该示意图，可掌握访客群分析数据与客流趋势数据，如总客流量与会员到访量的对比图以及新老访客对比图。若结合成交数据，能帮助管理者分析和定位当前业务与运营问题，进而有根据的进行下一阶段的业务岗位提升和营销活动设计。
图6示出了一个具体的应用场景中，访客标签编辑界面示意图，终端用户可对该界面进行编辑。如图6所示，该界面可供终端用户对访客进行管理。以访客的身份类型为会员为例，界面上显示每个会员的头像、人员ID、姓名、标签、操作等项，用户可通过点击操作项对应的编辑按钮，对每个会员进行编辑操作。比如，从可选标签库中选择其认为与该会员相适应的标签，或者为某个会员自定义标签等。还可以通过操作项对应的删除按钮，删除其认为已办理退会手续或低价值的会员。
在该应用场景中，示例性地，在接收到用户输入的搜索指定访客的操作时，终端显示该指定访客的简要介绍界面，该界面上显示有该指定访客的标签。在接收到用户输入的进入此访客详情页面的操作时，终端显示该指定访客的详细介绍界面，包括该指定访客的历史到访记录。在接收到用户输入的编辑此访客的自定义标签的操作时，终端接收并显示用户编辑的、该指定访客的自定义标签。
在该应用场景中，示例性地，该终端界面上显示有多个访客的标签信息。接收到用户针对界面中一个访客的向左或向右滑动的操作时，该访客的标签处于可编辑状态。在接收到用户输入的编辑信息时，终端基于用户输入的编辑信息执行对该访客的标签的编辑操作。
在该应用场景中，示例性地，在接收到用户输入的上拉该界面上滚动条的操作时，终端更新当前界面上所显示的访客名单。用户从当前界面上找到指定日期下的指定门店访客时，通过点击操作进入此访客详情页面。接收到用户输入的将该访客从客户转化为会员的操作时，基于该操作将该访客的身份类型由客户变更为会员。
需要说明的是，可以理解，上述流程仅仅是示意性地，实际应用中，可为用户实现不同上述功能提供差异化的设置操作。
根据本公开的实施例，摄像机负责采集图像，将采集到的图像传输至服务器，以由服务器对图像进行识别，获得图像中包含的目标访客的人脸和/或人体特征。基于人脸和/或人体特征得到所述图像中目标访客的访客数据，如身份类型、到访数据和资料数据。其中，资料数据可包括评估信息，到访数据可包括历史到访信息。根据所述身份类型、到访数据和资料数据，确定所述访客的访客等级信息。服务器将目标访客的标签信息传输至安装有APP的用户终端，以由用户终端显示，便于终端用户根据确定出的目标访客标签进行差异化的处理，进而能够将更多的访客接待精力和访客关系维护精力有选择的付诸于高价值访客，从而有利于提高访客转化率。
本申请实施例还提供了一种数据处理装置，如图7所示，所述装置包括获取模块10、确定模块20和处理模块30，其中：所述获取模块10，用于获取目标访客的访客数据；所述确定模块20，用于基于所述访客数据，确定所述目标访客的访客等级；所述 处理模块30，用于确定与所述访客等级对应的待推送数据，并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。
在一些实施例中，所述访客数据包括到访数据和资料数据。所述访客等级包括基于所述到访数据确定的第一访客等级，和/或，基于所述资料数据确定的第二访客等级。在一个应用场景中，第一访客等级可反映访客到访情况，第二访客等级可反映访客购买意向。
在一些实施例中，在所述访客数据包括到访数据，所述访客等级包括所述第一访客等级的情况下，所述确定模块20用于：根据所述到访数据，确定在预设时间段内所述目标访客的到访次数和/或单次平均到访时长；响应于所述到访次数高于第一阈值，和/或，所述单次平均到访时长高于第一时长阈值，确定所述目标访客的第一访客等级为高频客户。
在一些实施例中，所述访客数据还包括身份类型，所述确定模块20用于：根据所述到访数据，确定所述目标访客最后一次到访的时间距离当前时刻的时间间隔，和/或，在所述预设时间段内所述目标访客的单次平均到访时长；响应于所述时间间隔超过第二阈值，和/或，所述单次平均到访时长低于第二时长阈值，在所述目标访客的所述身份类型为第一类型时，确定所述目标访客的第一访客等级为流失客户，或是，在所述目标访客的所述身份类型为第二类型时，确定所述目标访客的第一访客等级为沉睡客户。
在一些实施例中，所述资料数据包括所述目标访客的消费力数据以及关注对象，在所述访客数据包括资料数据，所述访客等级包括所述第二访客等级的情况下，所述确定模块20用于：根据所述关注对象，确定所述关注对象的售价；根据所述消费力数据，确定所述目标访客对应的消费区间；响应于所述售价是否属于所述消费区间，确定所述目标访客的第二访客等级。
在一些实施例中，所述处理模块30还用于：在所述售价不属于所述消费区间，或者所述售价属于所述消费区间但与所述消费区间上限值之差小于预设值的情况下，基于所述关注对象，查找与所述关注对象属于同一类型的其他对象的数据，并将所述其他对象的数据确定为所述待推送数据。
在一些实施例中，不同所述访客等级对应的数据推送方式至少部分不同；所述数据推送方式至少包括推送时间、相邻两次推送的时间间隔、推送途径中的一项。
在一些实施例中，所述处理模块30还用于：在所述确定模块20确定所述目标访客的访客等级之后，向终端发送所述目标访客的访客等级，以使所述终端将所述访客等级与所述目标访客相关联的存储和/或展示。其中，可以以标签的形式在访客列表和/或访客页面中将所述访客等级与所述目标访客相关联的展示。
在一些实施例中，处理模块30还用于：向终端发送所述目标访客的部分访客数据，例如身份类型，到访数据等，以使所述终端将所述部分访客数据与所述目标访客相关联的存储和/或展示。类似的，可以以标签的形式在访客列表和/或访客页面中将所述部分访客数据与所述目标访客相关联的展示。
本领域技术人员应当理解，在一些可选实施例中，图7中所示的数据处理装置中的各处理模块的实现功能可参照前述数据处理方法的相关描述而理解。
本领域技术人员应当理解，在一些可选实施例中，图7所示的数据处理装置中 各处理单元的功能可通过运行于处理器上的程序而实现，也可通过具体的逻辑电路而实现。
实际应用中，上述的获取模块10、确定模块20和处理模块30的具体结构均可对应于处理器。所述处理器具体的结构可以为中央处理器(CPU，Central Processing Unit)、微处理器(MCU，Micro Controller Unit)、数字信号处理器(DSP，Digital Signal Processing)或可编程逻辑器件(PLC，Programmable Logic Controller)等具有处理功能的电子元器件或电子元器件的集合。其中，所述处理器包括可执行代码，所述可执行代码存储在存储介质中，所述处理器可以通过总线等通信接口与所述存储介质中相连，在执行具体的各单元的对应功能时，从所述存储介质中读取并运行所述可执行代码。所述存储介质用于存储所述可执行代码的部分优选为非瞬间存储介质。
本申请实施例提供的数据处理装置，能够有效利用访客数据对各目标访客的访客等级进行划分，以起到区分或是标记不同目标访客的作用；而按照所述访客等级对应的数据推送方式，推送所述待推送数据，能为不同访客等级的目标访客提供更有针对性的数据推送，从而进一步提高访客体验和访客转化率。
本申请实施例还提供了一种数据处理装置，应用于终端，如图8所示，所述装置包括：
通信模块40，用于接收目标访客的访客等级信息；
显示处理模块50，用于显示所述目标访客的访客等级信息。
其中，所述访客等级包括第一访客等级和/或第二访客等级。
在一种可能的实现方式中，所述显示处理模块50用于将所述访客等级信息与所述目标访客相关联的存储和/或展示。其中，可以以标签的形式在访客列表和/或访客页面中将所述访客等级信息与所述目标访客相关联的展示。
在一种可能的实现方式中，所述显示处理模块50还用于将部分访客数据与所述目标访客相关联的存储和/或展示。类似的，可以以标签的形式在访客列表和/或访客页面中将所述部分访客数据与所述目标访客相关联的展示。
本领域技术人员应当理解，在一些可选实施例中，图8中所示的数据处理装置中的各处理模块的实现功能可参照前述数据处理方法的相关描述而理解。
本领域技术人员应当理解，在一些可选实施例中，图8所示的数据处理装置中各处理单元的功能可通过运行于处理器上的程序而实现，也可通过具体的逻辑电路而实现。
实际应用中，上述的通信模块40和显示处理模块50的具体结构均可对应于处理器。所述处理器具体的结构可以为CPU、MCU、DSP或PLC等具有处理功能的电子元器件或电子元器件的集合。其中，所述处理器包括可执行代码，所述可执行代码存储在存储介质中，所述处理器可以通过总线等通信接口与所述存储介质中相连，在执行具体的各单元的对应功能时，从所述存储介质中读取并运行所述可执行代码。所述存储介质用于存储所述可执行代码的部分优选为非瞬间存储介质。
本申请实施例所述数据处理装置，便于终端用户及时知晓当前目标访客的访客等级，便于根据确定出的访客等级标签进行差异化的处理，进而能够将更多的访客接待精力和访客关系维护精力有选择的付诸于高价值访客，从而有利于提高访客转化率。
本申请实施例提供了一种数据处理设备，包括：存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现本申请实施例所述的数据处理方法的步骤。
本申请实施例提供了一种存储介质，存储有计算机程序，所述计算机程序被处理器执行时，使得所述处理器执行本申请实施例所述的数据处理方法的步骤。
本领域技术人员应当理解，本实施例的计算机存储介质中各程序的功能，可参照前述各实施例所述的数据处理方法的相关描述而理解。
还应理解，本文中列举的各个可选实施例仅仅是示例性的，用于帮助本领域技术人员更好地理解本申请实施例的技术方案，而不应理解成对本申请实施例的限定，本领域普通技术人员可以在本文所记载的各个可选实施例的基础上进行各种改变和替换，也应理解为本申请实施例的一部分。
此外，本文对技术方案的描述着重于强调各个实施例的不同之处，其相同或相似之处可以相互参考，为了简洁，不再一一赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元；既可以位于一个地方，也可以分布到多个网络单元上；可以根据实际需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本申请各实施例中各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本申请上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本申请各个实施例所述方法的全部或部分。而前述的存储介质包括：移动存储设备、ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。

Claims (19)

  1. 一种数据处理方法，包括：
    获取目标访客的访客数据；
    基于所述访客数据，确定所述目标访客的访客等级；
    确定与所述访客等级对应的待推送数据；并
    按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。
  2. 根据权利要求1所述的方法，其特征在于，所述访客数据包括到访数据和资料数据；所述访客等级包括基于所述到访数据确定的第一访客等级，和/或，基于所述资料数据确定的第二访客等级。
  3. 根据权利要求2所述的方法，其特征在于，在所述访客数据包括所述到访数据，所述访客等级包括所述第一访客等级的情况下，所述基于所述访客数据，确定所述目标访客的访客等级，包括：
    根据所述到访数据，确定在预设时间段内所述目标访客的到访次数和/或单次平均到访时长；
    响应于所述到访次数高于第一阈值，和/或，所述单次平均到访时长高于第一时长阈值，确定所述目标访客的第一访客等级为高频客户。
  4. 根据权利要求3所述的方法，其特征在于，所述访客数据还包括身份类型，所述基于所述访客数据，确定所述目标访客的访客等级，包括：
    根据所述到访数据，确定所述目标访客最后一次到访的时间距离当前时刻的时间间隔，和/或，在所述预设时间段内所述目标访客的单次平均到访时长；
    响应于所述时间间隔超过第二阈值，和/或，所述单次平均到访时长低于第二时长阈值，
    在所述目标访客的所述身份类型为第一类型时，确定所述目标访客的第一访客等级为流失客户，或是，
    在所述目标访客的所述身份类型为第二类型时，确定所述目标访客的第一访客等级为沉睡客户。
  5. 根据权利要求2所述的方法，其特征在于，所述资料数据包括所述目标访客的消费力数据以及关注对象，在所述访客数据包括所述资料数据，所述访客等级包括所述第二访客等级的情况下，所述基于所述访客数据，确定所述目标访客的访客等级，包括：
    根据所述关注对象，确定所述关注对象的售价；
    根据所述消费力数据，确定所述目标访客对应的消费区间；
    响应于所述售价是否属于所述消费区间，确定所述目标访客的第二访客等级。
  6. 根据权利要求5所述的方法，其特征在于，在所述售价不属于所述消费区间，或者所述售价属于所述消费区间但与所述消费区间上限值之差小于预设值的情况下，所述确定与所述访客等级对应的待推送数据包括：
    基于所述关注对象，查找与所述关注对象属于同一类型的其他对象的数据，
    将所述其他对象的数据确定为所述待推送数据。
  7. 根据权利要求1至6任一项所述的方法，其特征在于，不同所述访客等级对应的数据推送方式至少部分不同；所述数据推送方式至少包括推送时间、相邻两次推送的时间间隔、推送途径中的一项。
  8. 根据权利要求1至7中任一项所述的方法，其特征在于，在所述确定所述目标访客的访客等级之后，所述方法还包括：
    向终端发送所述目标访客的访客等级，以使所述终端将所述访客等级与所述目标访客相关联的存储和/或展示。
  9. 一种数据处理装置，包括：
    获取模块，用于获取目标访客的访客数据；
    确定模块，用于基于所述访客数据，确定所述目标访客的访客等级；
    处理模块，用于确定与所述访客等级对应的待推送数据，并按照所述访客等级对应的数据推送方式，向所述目标访客推送所述待推送数据。
  10. 根据权利要求9所述的装置，其特征在于，所述访客数据包括到访数据和资料数据；所述访客等级包括基于所述到访数据确定的第一访客等级，和/或，基于所述资料数据确定的第二访客等级。
  11. 根据权利要求10所述的装置，其特征在于，在所述访客数据包括所述到访数据，所述访客等级包括所述第一访客等级的情况下，所述确定模块用于：
    根据所述到访数据，确定在预设时间段内所述目标访客的到访次数和/或单次平均到访时长；
    响应于所述到访次数高于第一阈值，和/或，所述单次平均到访时长高于第一时长阈值，确定所述目标访客的第一访客等级为高频客户。
  12. 根据权利要求11所述的装置，其特征在于，所述访客数据还包括身份类型，所述确定模块用于：
    根据所述到访数据，确定所述目标访客最后一次到访的时间距离当前时刻的时间间隔，和/或，在所述预设时间段内所述目标访客的单次平均到访时长；
    响应于所述时间间隔超过第二阈值，和/或，所述单次平均到访时长低于第二时长阈值，
    在所述目标访客的所述身份类型为第一类型时，确定所述目标访客的第一访客等级为流失客户，或是，
    在所述目标访客的所述身份类型为第二类型时，确定所述目标访客的第一访客等级为沉睡客户。
  13. 根据权利要求10所述的装置，其特征在于，所述资料数据包括所述目标访客的消费力数据以及关注对象，在所述访客数据包括所述资料数据，所述访客等级包括所述第二访客等级的情况下，所述确定模块用于：
    根据所述关注对象，确定所述关注对象的售价；
    根据所述消费力数据，确定所述目标访客对应的消费区间；
    响应于所述售价是否属于所述消费区间，确定所述目标访客的第二访客等级。
  14. 根据权利要求13所述的装置，其特征在于，所述处理模块，还用于：
    在所述售价不属于所述消费区间，或者所述售价属于所述消费区间但与所述消费区间上限值之差小于预设值的情况下，基于所述关注对象，查找与所述关注对象属于同一类型的其他对象的数据，将所述其他对象的数据确定为所述待推送数据。
  15. 根据权利要求9至14任一项所述的装置，其特征在于，不同所述访客等级对应的数据推送方式至少部分不同；所述数据推送方式至少包括推送时间、相邻两次推送的时间间隔、推送途径中的一项。
  16. 根据权利要求9至15中任一项所述的装置，其特征在于，所述处理模块还用于：
    在所述确定模块确定所述目标访客的访客等级之后，向终端发送所述目标访客的访客等级，以使所述终端将所述访客等级与所述目标访客相关联的存储和/或展示。
  17. 一种数据处理设备，包括：存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现权利要求1至8任一项所述的数据处理方法。
  18. 一种存储介质，存储有计算机程序，所述计算机程序被处理器执行时，使得所述处理器执行权利要求1至8任一项所述的数据处理方法。
  19. 一种计算机程序，包括计算机可执行代码，当所述计算机可执行代码在设备上运行时，使得所述设备中的处理器执行权利要求1-8任一项所述的数据处理方法。
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