WO2021027143A1 - Procédé, appareil et dispositif de poussée d'informations et support d'informations lisible par ordinateur - Google Patents

Procédé, appareil et dispositif de poussée d'informations et support d'informations lisible par ordinateur Download PDF

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Publication number
WO2021027143A1
WO2021027143A1 PCT/CN2019/117565 CN2019117565W WO2021027143A1 WO 2021027143 A1 WO2021027143 A1 WO 2021027143A1 CN 2019117565 W CN2019117565 W CN 2019117565W WO 2021027143 A1 WO2021027143 A1 WO 2021027143A1
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Prior art keywords
user
target
screening
preset
users
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PCT/CN2019/117565
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English (en)
Chinese (zh)
Inventor
张越
张桂添
范骏超
李阳
徐国熙
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平安科技（深圳）有限公司
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Publication of WO2021027143A1 publication Critical patent/WO2021027143A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
    • G06Q30/0239—Online discounts or incentives
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q30/0241—Advertisements
    • G06Q30/0277—Online advertisement

Definitions

  • This application relates to the field of data processing, and in particular to an information push method, device, equipment, and computer-readable storage medium.
  • Internet marketing also known as online marketing or electronic marketing, refers to a type of marketing that uses the Internet.
  • the Internet has brought many unique conveniences to marketing.
  • marketing activities are generally general investment, extensive and cost-insensitive marketing activities, which are not targeted, not only low accuracy, but also waste of marketing costs.
  • the main purpose of this application is to provide an information push method, device, equipment, and computer-readable storage medium, aiming to solve the technical problem of low accuracy of existing activity information push methods.
  • this application provides an information push method, wherein the information push method includes the following steps:
  • a target user that meets the preset screening condition is determined among the users to be screened, and the preset activity information is pushed to the target user;
  • the corresponding activity reward is issued to the user to be monitored according to the preset activity information.
  • the method before the step of obtaining the user screening condition in the user screening instruction when the user screening instruction is received, and determining the corresponding user screening model according to the user screening condition, the method further includes:
  • a training set is generated according to the historical user tags, historical performance data, and corresponding qualified performance data, and a corresponding user screening model is generated according to the training set training.
  • the step of generating a training set according to the historical user tags, historical performance data, and corresponding qualified performance data, and generating a corresponding user screening model according to the training set training includes:
  • a user screening model is generated according to the corresponding relationship and related user tags, wherein the user screening model is used to screen out specific users that meet corresponding screening conditions.
  • the step of determining, among the users to be screened based on the user screening model and the user tag, target users that meet the preset screening conditions, and pushing preset activity information to the target users Specifically:
  • the target user exists among the users to be screened, the target user is classified according to the user tag corresponding to the target user and the relevant user tag corresponding to the qualified performance data;
  • the corresponding preset activity information is pushed to target users of various levels.
  • the method further includes:
  • a reminder message that there is no target user among the users to be screened is generated, and the relevant user tag corresponding to the qualified performance data is displayed, so that the planner can follow the relevant user tag Adjust the preset activity information.
  • the step of obtaining user data of the user to be screened, and generating a user label corresponding to the user to be screened according to a preset label unit and the user data includes:
  • the user basic information, user behavior data, and user transaction data are compared with preset label units, and user labels corresponding to the users to be screened are generated.
  • this application also provides an information pushing device, the information pushing device includes:
  • the model determining module is configured to obtain the user screening conditions in the user screening instructions when the user screening instructions are received, and determine the corresponding user screening model according to the user screening conditions;
  • a label generation module configured to obtain user data of users to be screened, and generate user labels corresponding to the users to be screened according to a preset label unit and the user data;
  • An information push module configured to determine, among the users to be screened, target users that meet the preset screening conditions according to the user screening model and the user tags, and push preset activity information to the target users;
  • the information pushing device also includes an activity monitoring module, and the activity monitoring module is used to:
  • the corresponding activity reward is issued to the user to be monitored according to the preset activity information.
  • the label generation module is further used for:
  • the user basic information, user behavior data, and user transaction data are compared with preset label units, and user labels corresponding to the users to be screened are generated.
  • this application also provides an information pushing device, which includes a processor, a memory, and computer readable instructions stored on the memory and executable by the processor, wherein When the computer-readable instructions are executed by the processor, the steps of the above-mentioned information pushing method are realized.
  • the present application also provides a computer-readable storage medium having computer-readable instructions stored on the computer-readable storage medium, and when the computer-readable instructions are executed by a processor, the implementation is as described above The steps of the information push method.
  • This application provides an information push method, that is, when a user screening instruction is received, the user screening condition in the user screening instruction is obtained, and the corresponding user screening model is determined according to the user screening condition; and the users of the users to be screened are obtained Data, a user label corresponding to the user to be screened is generated according to a preset label unit and the user data; according to the user screening model and the user label, it is determined that the user to be screened meets the preset screening condition And push preset event information to the target user.
  • this application generates corresponding user tags based on user data, and then generates a user screening model based on user tags and corresponding business data, so that all users who meet the marketing conditions can be screened out according to the user screening model.
  • Targeting marketing costs to effective users not only achieves targeted marketing and saves marketing costs, but also improves the accuracy of push, enhances the user's sense of participation, and solves the technical problem of low accuracy of existing event information push methods.
  • FIG. 1 is a schematic diagram of the hardware structure of the information push device involved in the solution of the embodiment of the application;
  • FIG. 3 is a schematic flowchart of a second embodiment of the information pushing method of this application.
  • FIG. 4 is a schematic flowchart of a third embodiment of the information pushing method of this application.
  • Fig. 5 is a schematic diagram of functional modules of the first embodiment of the information pushing device of this application.
  • the information pushing methods involved in the embodiments of the present application are mainly applied to information pushing devices, and the information pushing devices may be devices with display and processing functions such as PCs, portable computers, and mobile terminals.
  • FIG. 1 is a schematic diagram of the hardware structure of the information pushing device involved in the solution of the embodiment of the application.
  • the information pushing device may include a processor 1001 (for example, a CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005.
  • the communication bus 1002 is used to realize the connection and communication between these components;
  • the user interface 1003 may include a display (Display), an input unit such as a keyboard (Keyboard);
  • the network interface 1004 may optionally include a standard wired interface, a wireless interface (Such as WI-FI interface);
  • the memory 1005 can be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory.
  • the memory 1005 may optionally be a storage device independent of the aforementioned processor 1001.
  • FIG. 1 does not constitute a limitation on the information push device, and may include more or less components than those shown in the figure, or combine certain components, or different component arrangements.
  • the memory 1005 as a computer-readable storage medium in FIG. 1 may include an operating system, a network communication module, and computer-readable instructions.
  • the network communication module is mainly used to connect to the server and perform data communication with the server; and the processor 1001 can call the computer-readable instructions stored in the memory 1005 and execute the information pushing method provided in the embodiment of the present application.
  • the embodiment of the present application provides an information push method.
  • FIG. 2 is a schematic flowchart of the first embodiment of the information pushing method of this application.
  • the information pushing method includes the following steps:
  • Step S10 When a user screening instruction is received, the user screening condition in the user screening instruction is obtained, and a corresponding user screening model is determined according to the user screening condition;
  • an information push method which generates corresponding user tags based on user data, and then generates a user screening model based on the user tags and corresponding business data Therefore, the target users who meet the marketing conditions can be selected according to the user screening model, and marketing costs can be accurately placed to effective users. This not only achieves targeted marketing, saves marketing costs, and improves the accuracy of push.
  • This application can be applied to push marketing activities information of online salespersons in the insurance marketing platform.
  • the information pushing method is applied to an information pushing system, and the information pushing system includes a terminal and a server.
  • the server When the server receives the user screening instruction sent by the terminal, it obtains the user screening conditions for screening users in the user screening instruction, and determines the corresponding user screening model in the preset model library according to the user screening conditions. For example, according to the user screening conditions of "select users with qualified performance", a user screening model for user screening based on user performance data is obtained.
  • the preset model library selects the corresponding training set according to the screening requirements in advance to train and generate each screening model of the corresponding function.
  • Step S20 Obtain user data of the user to be screened, and generate a user tag corresponding to the user to be screened according to a preset label unit and the user data;
  • the user-related label units are extracted in advance based on historical user data in the database and used as the preset label units.
  • the preset label unit includes gender, age range, hometown, number of online, business area, etc.
  • the user basic information is the user's name, age, gender, family members, etc.
  • the user behavior data is the business area where the user promotes the business, the upper limit number of times the user logs into the insurance marketing platform, the number of times the user calls the customer, and the duration, etc.
  • the user transaction data is the number of orders that the user has successfully signed, the order amount, and the order time.
  • the corresponding user label is added to each user, that is, a user portrait is generated for each user to be screened, such as gender female, professional white-collar worker, business area Shenzhen Baoan District, 55 online times ( Within a month) etc.
  • Step S30 According to the user screening model and the user tag, a target user meeting the preset screening condition is determined among the users to be screened, and preset activity information is pushed to the target user.
  • the user tag of each user to be screened is input to the user screening model, and the user screening model compares the user tag with the target user tag corresponding to the preset screening condition, so that each user is Determine a target user matching the target user label, that is, the user label corresponding to the target user matches the target user label, or the user label value corresponding to the target user is greater than the target user label value.
  • effective target users are screened out of all users to be screened through the user screening model, and a preset marketing strategy is sent to the target users.
  • the user ID corresponding to the target user is added to the user list executed by the preset marketing strategy, and the users to be counted in the user list are obtained in the target time zone corresponding to the preset marketing strategy Whether to complete the task target corresponding to the preset marketing strategy, and when the users to be counted complete the corresponding task target, the corresponding reward is issued according to the preset marketing strategy. Or, when the user to be counted fails to complete the corresponding task goal, the corresponding punishment measure is executed according to the preset marketing strategy.
  • Step S40 adding the user identifier corresponding to the target user to the corresponding user list, and obtaining the target time period and task target corresponding to the preset activity information;
  • Step S50 Obtain task data of the user to be monitored in the target time period in the user list, and determine whether the user to be monitored has completed the corresponding task goal according to the task data;
  • step S60 if the user to be monitored completes the corresponding task goal, a corresponding activity reward is issued to the user to be monitored according to the preset activity information.
  • the user identification corresponding to the target user such as the user name or user ID, etc.
  • the user in the user list that is, the user to be monitored, is monitored for tasks. That is, the task data completed by each user to be monitored within the target time period corresponding to the activity is obtained, and it is determined whether the task data completed by each user to be monitored reaches the corresponding task goal. If the goal is completed, the reward information corresponding to the activity is sent to the user to be monitored, or a corresponding task completion reminder message is generated to the user to be monitored or the event administrator, etc. If it is not completed, the penalty message corresponding to the activity is sent to the user to be monitored or the activity administrator, or a reminder message that the activity is not completed is generated and sent to the user to be monitored, etc.
  • This embodiment provides an information push method, that is, when a user screening instruction is received, the user screening condition in the user screening instruction is obtained, and the corresponding user screening model is determined according to the user screening condition; For user data, a user tag corresponding to the user to be screened is generated according to a preset label unit and the user data; according to the user screening model and the user tag, it is determined that the user to be screened meets the preset screening Conditional target users, and push preset activity information to the target users.
  • this application generates corresponding user tags based on user data, and then generates a user screening model based on user tags and corresponding business data, so that all users who meet the marketing conditions can be screened out according to the user screening model.
  • Targeting marketing costs to effective users not only achieves targeted marketing and saves marketing costs, but also improves the accuracy of push, enhances the user's sense of participation, and solves the technical problem of low accuracy of existing event information push methods.
  • FIG. 3 is a schematic flowchart of a second embodiment of an information pushing method according to this application.
  • the method further includes:
  • Step S01 Acquire historical performance data corresponding to historical users and corresponding historical user tags, add historical performance data that exceeds a preset performance threshold with a performance qualified flag, so as to determine the corresponding performance in the historical performance data according to the performance qualified flag. Qualified performance data;
  • general user performance data is associated with the user data of the user.
  • the user performance data is directly proportional, inversely proportional, or exponentially increasing with one or several types of user data.
  • the historical performance data and historical user data corresponding to the online salesperson are acquired in the insurance marketing platform, and the historical user tags corresponding to the online salesperson are generated according to the historical user data.
  • the historical performance data exceeds the preset threshold, that is, the historical performance data whose performance meets the standard is added with a performance qualified mark, so that the system can identify the historical performance data whose performance is qualified.
  • Step S02 Generate a training set according to the historical user tags, historical performance data, and corresponding qualified performance data, and train and generate a corresponding user screening model according to the training set.
  • a training set is generated based on the historical user tags, historical performance data, and corresponding qualified performance data, that is, based on a deep learning algorithm, the corresponding relationship between the performance data in the training set and the user tags is extracted, and the qualified performance is determined Relevant user tags corresponding to the data; generate a user screening model, wherein the user screening model is used to screen out specific users that meet the corresponding screening conditions.
  • the corresponding relationship between each historical performance data and historical user tags is extracted, and then the qualified historical performance data is determined according to the qualified performance identifier, and the qualified historical performance is determined according to the corresponding relationship
  • the relevant user tags corresponding to the data are used as the screening rules of the user screening model.
  • the business area is Nanshan District, Shenzhen
  • the user performance data corresponding to user tags with more than 600 calls can generally meet the standard, and will be launched soon
  • the business area is Nanshan District, Shenzhen
  • the number of calls to customers exceeds 600 (within one month) as the target user label.
  • Those exceeding the above value are the target user labels.
  • FIG. 4 is a schematic flowchart of a third embodiment of an information pushing method according to this application.
  • the step S30 specifically includes:
  • Step S31 Determine, according to the user screening model and the user tag, whether there are target users meeting the preset screening conditions among the users to be screened;
  • the user tag corresponding to the user to be screened is input to the user screening model, and the user screening model determines that the user tag matches the tag corresponding to the target user to be screened. That is, the to-be-screened users with tags corresponding to the target users are filtered out through the user screening model, as the target users.
  • Step S32 if the target user exists among the users to be screened, the target user is classified according to the user tag corresponding to the target user and the related user tag corresponding to the qualified performance data;
  • the target users can be further classified according to their user tags and performance-related user tags. Such as high-performance and long-term stable user categories, high-performance but unstable user categories, and business-qualified and stable categories.
  • Step S33 Push the corresponding preset activity information to target users of various levels according to the preset activity information push list.
  • different incentive marketing activities can be set up according to user categories with high performance and long-term stability, user categories with high performance but unstable, and categories with qualified and stable business, that is, different activities are pushed for target users of different levels. information.
  • the preset activity information push list is that the server receives the marketing activity table uploaded by the planner, and parses out the marketing user object and marketing strategy information in the marketing activity table, and stores the user object and the activity push information as a pre-determined association Set up event information push list.
  • step S31 it further includes:
  • a reminder message that there is no target user among the users to be screened is generated, and the relevant user tag corresponding to the qualified performance data is displayed, so that the planner can follow the relevant user tag Adjust the preset activity information.
  • a corresponding reminder message is generated, and a reminder message that there is no target user among the users to be screened is displayed so that the user can
  • the user's filter conditions are set incorrectly, resulting in the screening of eligible target users.
  • relevant user tags corresponding to the qualified performance data are displayed, so that planners can set corresponding marketing strategies according to the relevant user tags, thereby pushing different activity push information for target users of different levels.
  • the embodiment of the present application also provides an information push device.
  • Fig. 5 is a schematic diagram of the functional modules of the first embodiment of the information pushing device of this application.
  • the information pushing device includes:
  • the model determining module 10 is configured to, when a user screening instruction is received, obtain user screening conditions in the user screening instruction, and determine a corresponding user screening model according to the user screening conditions;
  • the label generating module 20 is configured to obtain user data of the user to be screened, and generate a user label corresponding to the user to be screened according to a preset label unit and the user data;
  • the information push module 30 is configured to determine, among the users to be screened, target users that meet the preset screening conditions according to the user screening model and the user tags, and push preset activity information to the target users.
  • the information pushing device further includes an activity monitoring module 40, and the activity monitoring module 40 is configured to:
  • the corresponding activity reward is issued to the user to be monitored according to the preset activity information.
  • the label generating module 20 is also used for:
  • the user basic information, user behavior data, and user transaction data are compared with preset label units, and user labels corresponding to the users to be screened are generated.
  • the information pushing device further includes:
  • the historical data acquisition module is used to acquire historical performance data corresponding to historical users and corresponding historical user tags, and add historical performance data that exceeds a preset performance threshold with a performance qualified indicator, so that the historical performance data is listed in the historical performance data according to the performance qualified indicator. Determine the corresponding qualified performance data in the
  • the screening model training module is used to generate a training set according to the historical user tags, historical performance data, and corresponding qualified performance data, and to train and generate a corresponding user screening model according to the training set.
  • screening model training module is also used for:
  • a user screening model is generated, wherein the user screening model is used to screen out specific users that meet corresponding screening conditions.
  • the information pushing module 30 further includes:
  • a user judging unit configured to judge whether there is a target user that meets the preset screening condition among the users to be screened according to the user screening model and the user tag;
  • a rating unit configured to classify the target user according to the user tag corresponding to the target user and the relevant user tag corresponding to the qualified performance data if the target user exists among the users to be screened;
  • the information push unit is configured to push the list according to the preset activity information, and push the corresponding preset activity information to target users of various levels.
  • information pushing module 30 is also used for:
  • a reminder message that there is no target user among the users to be screened is generated, and the relevant user tag corresponding to the qualified performance data is displayed, so that the planner can follow the relevant user tag Adjust the preset activity information.
  • each module in the above-mentioned information pushing device corresponds to each step in the above-mentioned information pushing method embodiment, and its functions and implementation processes will not be repeated here.
  • the embodiments of the present application also provide a computer-readable storage medium, and the computer-readable storage medium may be a non-volatile readable storage medium.
  • the computer-readable storage medium of the present application stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the above-mentioned information pushing method are realized.

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Abstract

L'invention concerne un procédé, un appareil et un dispositif de poussée d'informations, et un support d'informations lisible par ordinateur, le procédé consistant à : acquérir un état de criblage d'utilisateur et déterminer un modèle de criblage d'utilisateur correspondant en fonction de l'état de criblage d'utilisateur (S10) ; acquérir des données d'utilisateur d'un utilisateur à cribler, et selon une unité d'étiquette prédéfinie et les données d'utilisateur, générer une étiquette d'utilisateur correspondant à l'utilisateur à cribler (S20) ; en fonction du modèle de criblage d'utilisateur et de l'étiquette d'utilisateur, déterminer un utilisateur cible et pousser des informations d'activité prédéfinies vers l'utilisateur cible (S30). Une étiquette d'utilisateur correspondante est générée sur la base de données d'utilisateur, et ensuite un service correspondant génère un modèle de criblage d'utilisateur sur la base de l'étiquette d'utilisateur et des données. Ainsi, un utilisateur cible qui satisfait un état de commercialisation peut être criblé parmi tous les utilisateurs selon le modèle de criblage d'utilisateur, et les coûts de commercialisation peuvent être fournis avec précision à des utilisateurs effectifs, ce qui permet d'obtenir une commercialisation ciblée, tout en réduisant également les coûts de commercialisation ; de plus, la précision de poussée est améliorée et le sens de participation entre utilisateurs est amélioré.
PCT/CN2019/117565 2019-08-14 2019-11-12 Procédé, appareil et dispositif de poussée d'informations et support d'informations lisible par ordinateur WO2021027143A1 (fr)

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