WO2020048240A1 - 业务推荐方法、装置、电子设备及可读存储介质 - Google Patents

业务推荐方法、装置、电子设备及可读存储介质 Download PDF

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Publication number
WO2020048240A1
WO2020048240A1 PCT/CN2019/096491 CN2019096491W WO2020048240A1 WO 2020048240 A1 WO2020048240 A1 WO 2020048240A1 CN 2019096491 W CN2019096491 W CN 2019096491W WO 2020048240 A1 WO2020048240 A1 WO 2020048240A1
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Prior art keywords
user
recommendation
preset
rule
payment
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PCT/CN2019/096491
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English (en)
French (fr)
Inventor
辛知
杨一鹏
李超
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阿里巴巴集团控股有限公司
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Application filed by 阿里巴巴集团控股有限公司 filed Critical 阿里巴巴集团控股有限公司
Priority to SG11202010708PA priority Critical patent/SG11202010708PA/en
Priority to EP19856696.0A priority patent/EP3779843A4/en
Publication of WO2020048240A1 publication Critical patent/WO2020048240A1/zh
Priority to US17/082,646 priority patent/US20210042720A1/en

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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
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/08—Payment architectures
    • G06Q20/085—Payment architectures involving remote charge determination or related payment systems
    • G06Q20/0855—Payment architectures involving remote charge determination or related payment systems involving a third party
    • 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
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/401—Transaction verification
    • G06Q20/4014—Identity check for transactions
    • G06Q20/40145—Biometric identity checks
    • 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
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations
    • 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
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/2866—Architectures; Arrangements
    • H04L67/30—Profiles
    • H04L67/306—User profiles
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/535—Tracking the activity of the user

Definitions

  • the embodiments of the present specification relate to the field of data processing technologies, and in particular, to a service recommendation method, device, electronic device, and readable storage medium.
  • the embodiments of the present specification provide a service recommendation method, device, electronic device, and readable storage medium.
  • an embodiment of the present specification provides a service recommendation method, including: receiving a recommendation request sent by a client, where the recommendation request is that the client detects that a user enters a preset scenario, and determines that the user satisfies Sent when presetting the opening conditions of the payment service; obtaining the characteristic information of the user based on the recommendation request; determining the recommended copy of the recommendation by matching the characteristic information with a preset rule associated with a recommendation copy in advance Sending the recommended copy to the client, so that the client displays a recommendation interface to the user according to the recommended copy, and the recommendation interface is used to recommend the preset payment service to the user .
  • an embodiment of the present specification provides a service recommendation method, including: when detecting that a user enters a preset scenario, determining whether the user meets a provisioning condition of a preset payment service; when the provisioning condition is satisfied, Send a recommendation request to the server, so that the server obtains the characteristic information of the user based on the recommendation request, and determines the recommendation recommendation of this recommendation by matching the characteristic information with a preset rule associated with a recommendation copy in advance.
  • Copywriting receiving the recommended copy issued by the server, and displaying a recommendation interface to the user according to the recommended copy, the recommendation interface being used to recommend the preset payment service to the user.
  • an embodiment of the present specification provides a service recommendation method, which includes: when detecting that a user enters a preset scenario, determining whether the user meets a provisioning condition of a preset payment service, wherein the preset scenario is A password payment scenario, a supplementary scenario, or a secret finding scenario; when the activation conditions are met, a recommendation interface is displayed to the user, and the recommendation interface is used to recommend the preset payment service to the user.
  • an embodiment of the present specification provides a service recommendation device, which is applied to a server and includes a receiving module, an acquiring module, a determining module, and a copy sending module.
  • a receiving module is configured to receive a recommendation request sent by a client, where the recommendation request is sent by the client when it detects that a user enters a preset scenario and determines that the user meets a provisioning condition of a preset payment service.
  • An obtaining module configured to obtain characteristic information of the user based on the recommendation request.
  • a determining module configured to determine the recommended copy of the recommendation by matching the feature information with a preset rule associated with the recommended copy in advance.
  • a copy sending module is configured to send the recommended copy to the client, so that the client displays a recommendation interface to the user according to the recommended copy, and the recommendation interface is used to recommend the user to the user.
  • the default payment service is described.
  • an embodiment of the present specification provides a service recommendation device, which is applied to a client and includes a judgment module, a request sending module, and a display module.
  • a judging module is configured to judge whether the user meets a provisioning condition of a preset payment service when detecting that the user enters a preset scenario.
  • a request sending module is configured to: when the provisioning condition is met, the client sends a recommendation request to a server, so that the server obtains characteristic information of the user based on the recommendation request, and combines the characteristic information with the characteristic information.
  • a preset rule associated with the recommended copy is matched in advance to determine the recommended copy of the recommendation.
  • a display module is configured to receive the recommendation copy issued by the server, and display a recommendation interface to the user according to the recommendation copy, and the recommendation interface is used to recommend the preset payment service to the user.
  • an embodiment of the present specification provides a service recommendation device, including: a detection module, configured to determine whether the user meets a provisioning condition of a preset payment service when detecting that the user enters a preset scenario, where The preset scenario is a password payment scenario, a supplementary scenario, or a secret finding scenario; a recommendation module is configured to display a recommendation interface to the user when the activation condition is satisfied, and the recommendation interface is used to recommend the user to the user.
  • the default payment service is described.
  • an embodiment of the present specification provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor.
  • the processor implements the first aspect when the program is executed. , The second aspect, or the steps of the business recommendation method provided by the third aspect.
  • an embodiment of the present specification provides a computer-readable storage medium having stored thereon a computer program that, when executed by a processor, implements the business recommendation method provided in the first aspect, the second aspect or the third aspect above A step of.
  • a client first sends a recommendation request to a server when it detects that a user enters a preset scenario and determines that the user meets the provisioning conditions of the preset payment service, and then the server based on the recommendation request
  • the characteristic information of the user is obtained, and by matching the characteristic information with a preset rule pre-associated with the recommended copy, the recommended copy of the recommendation is determined, and the recommended copy is delivered to the client, and the client according to the recommendation Copywriting shows users a recommendation interface.
  • FIG. 1 is a schematic diagram of an application scenario according to an embodiment of the present specification
  • FIG. 2 is a flowchart of a service recommendation method provided by the first aspect of the embodiment of the present specification
  • FIG. 3 is a flowchart of a service recommendation method provided by a second aspect of the embodiment of the present specification.
  • FIG. 4 is a flowchart of a service recommendation method provided by a third aspect of the embodiment of the present specification.
  • FIG. 5 is a schematic structural diagram of a service recommendation apparatus according to a fourth aspect of the embodiment of the present specification.
  • FIG. 6 is a schematic structural diagram of a service recommendation device according to a fifth aspect of the embodiment of the present specification.
  • FIG. 7 is a schematic structural diagram of a service recommendation apparatus according to a sixth aspect of the embodiment of the present specification.
  • FIG. 8 is a schematic structural diagram of an electronic device according to a seventh aspect of the embodiment of the present specification.
  • the IFAA protocol is a security verification protocol, which is mainly used to support various services such as fingerprint payment, face payment, and SE certificate.
  • the password payment scenario refers to the scenario where the user just completed the verification using the password payment.
  • the secret finding scenario refers to the scenario where the user forgets the payment password and completes the password recovery by performing some specified operations such as answering questions.
  • the supplementary scenario refers to a scenario where the user has not set a payment password, and the system requires the payment password to be completed before completing the payment password setting.
  • FIG. 1 is a schematic diagram of an operating environment applicable to the embodiment of the present specification.
  • one or more user terminals 100 may be connected to one or more servers 300 (only one is shown in FIG. 1) through a network 200 for data communication or interaction.
  • the user terminal 100 may be a smart device with a network function, such as a personal computer (PC), a notebook computer, a tablet computer, a smart phone, an e-reader, an in-vehicle device, a network television, or a wearable device.
  • PC personal computer
  • notebook computer such as a notebook computer, a tablet computer, a smart phone, an e-reader, an in-vehicle device, a network television, or a wearable device.
  • a client terminal is installed in the user terminal 100, and the client terminal may be a third-party application software or a browser, which corresponds to a server (Server) side, and provides services for users, such as payment services. To pay for transactions.
  • server server
  • an embodiment of the present specification provides a service recommendation method.
  • This embodiment is a service recommendation method performed by a server. Referring to FIG. 2, the method includes steps S201 to S204.
  • Step S201 Receive a recommendation request sent by a client, where the recommendation request is sent by the client when it detects that a user enters a preset scenario and determines that the user meets the prerequisites for opening a preset payment service.
  • the preset payment service may be a payment service using biometric information, such as a fingerprint payment service and a face payment service.
  • biometric information such as a fingerprint payment service and a face payment service.
  • fingerprint verification and face recognition have a higher success rate, so increasing the user's use of fingerprint payment or face payment will help improve the overall payment success rate. Therefore, in order to expand the coverage of fingerprint payment or fingerprint payment users, business recommendations need to be made to users.
  • the preset payment service may also be another payment service that needs to be recommended to the user.
  • the client screens the user's scene and the users to be recommended.
  • a recommendation request is sent to the server.
  • the preset scenes can be set according to actual applications. In these scenes, it is more in line with the user's mind to give the user an alternative payment method to choose from.
  • the preset scene may be any scene in a specified scene set.
  • the specified scene set may include, but is not limited to, a password payment scene, an encryption scene, and a secret finding scene. It is understandable that when the user has just completed the password payment, it is a good time to recommend it to the user. The password payment itself requires the user to remember the password and enter it for a long time. When the user has just completed such a process, make a recommendation and recommend it to the user.
  • the opening conditions can be set according to the actual payment service requirements.
  • the provisioning conditions include one or more of the following three conditions: the user terminal used by the user supports a preset security protocol; the user used by the user The biometric information of the user is pre-entered in the terminal; and the preset payment service of the user is in an un-enabled state.
  • the process of the client determining whether the user meets the provisioning conditions of the preset payment service may include: determining whether the preset payment service of the user is in an activated state, and if so, ending the recommendation. If not, determine whether the user terminal used by the user supports the preset security protocol. If not, end this recommendation. If yes, determine whether the user terminal used by the user has previously entered the user's biometric information. If not, , Then end the recommendation, and if so, determine that the user satisfies the provisioning conditions of the preset payment service.
  • the above-mentioned determining steps of the opening state, the determining steps of the security protocol, and the determining steps of inputting biological characteristics information may not be performed in the above order.
  • the determination of the security protocol may be performed first, and then the opening states and biological characteristics Judgment of information entry.
  • the preset security protocol may be an IFAA protocol or a similar security protocol.
  • the IFAA agreement or similar security protocol is the basic condition for supporting fingerprint or face payments.
  • the isSupported interface can be called to determine whether the phone supports the IFAA protocol through the status bit built into the framework by the phone manufacturer.
  • the biometric information such as fingerprint information or face information
  • pre-entered in the user terminal by the user is stored in a specific location of the user terminal.
  • the user can determine whether the user's biometric information is stored in a specific location in the user terminal through an interface provided by the system.
  • the stored biometric information should correspond to the preset payment service.
  • the preset payment service is a fingerprint payment service
  • the biometric information is fingerprint information
  • the preset payment service is a face payment service
  • the biometric information Face information when the preset payment service is a face payment service.
  • Step S202 Acquire characteristic information of the user based on the recommendation request.
  • the recommendation request includes the user's identity information, for example, the user's account information or other identity information, so that the server can find the characteristic information of the user according to the user's identity information.
  • the characteristic information of the user may include, but is not limited to, the device of the user terminal used by the user, whether there is a previous record of activation, and the frequency of use.
  • the characteristic information of the user may also include the age of the user and the city where the user is located.
  • Step S203 Determine the recommended copy of the current recommendation by matching the feature information with a preset rule associated with the recommended copy in advance.
  • the preset rule may include one rule or multiple rules pre-configured with a priority order, which are specifically set according to actual needs.
  • Each rule is associated with a pre-configured recommendation copy.
  • the recommended copy can be specifically configured according to different rules, which is conducive to displaying suitable recommended copy for the user according to the characteristic information of the user, so that the displayed recommended copy is more in line with the user's mind, thereby improving the recommended Success rate.
  • the preset rule includes a rule
  • the characteristic information of the user is matched with the rule, and when the match is successful, the recommended copy associated with the rule is used as the recommended copy for this recommendation.
  • the matching fails, no subsequent recommendation is made for the user.
  • the server may feed back to the client information indicating the end of the recommendation, so that the client ends the recommendation when receiving the information.
  • the match fails, it means that the user does not have personalized features, and the preset default copy is used as the recommended copy for this recommendation.
  • the user's feature information and preset rules can be set as needed, and the feature information corresponds to a specific preset rule.
  • the embodiments of this specification mainly introduce the following four rules for introduction. Of course, in the specific implementation process, the following four rules are not limited.
  • the preset rules may include scene rules.
  • a scene rule is a rule set according to a specific scene.
  • the feature information may include information of a scene in which a user is currently located.
  • determining the recommended recommended copy of the current recommendation includes matching the feature information with a scene rule.
  • Matching feature information with scene rules specifically includes: determining whether the scene information of the user currently belongs to the specified scene, and if the user's current scene information belongs to the specified scene, determining that the feature information matches the scene rule Succeeded, the recommended copy that is associated with the scene rule in advance is used as the recommended copy for this recommendation. If the current scene information of the user does not belong to the specified scene, it is determined that the feature information fails to match the scene rule.
  • the specified scenario corresponding to the scene rule may include a supplementary scenario and a confidentiality scenario.
  • the preset payment service is a service that uses biometric information for payment, because there is no problem of forgetting the fingerprint or face image, it is especially suitable for easy-to-forget users.
  • the recommended copy corresponding to the scene rule you can start with “easy mind” Cut in, for example, for fingerprint payment services, the recommended copy corresponding to the scenario rule can be set to "don't be afraid to forget, my fingerprint is my password".
  • the preset rule may include a provisioning record rule, which is a rule set for a user who changes phones.
  • the user who changes the phone refers to a user who is different from the user terminal currently using the preset payment service.
  • the characteristic information may include identification information, and the identification information is used to indicate whether the user has a historical opening record of a preset payment service.
  • determining the recommended recommended copy of the current recommendation includes matching the feature information with a provisioning record rule.
  • Matching the characteristic information with the provisioning record rule specifically includes: judging whether the user has a historical provisioning record of the preset payment service according to the identification information, and if yes, determining that the characteristic information matches the provisioning record rule successfully , Taking the recommended copy associated with the provisioning record rule in advance as the recommended copy for this recommendation.
  • the server may find out whether the user has a history of opening records corresponding to the preset payment service based on the identity information of the user in the recommendation request, and set the identification information to represent the search result.
  • the search result indicates that the user has a history of pre-established payment services, it indicates that the user is a replacement user. It is determined that the feature information matches the activation record rules successfully.
  • the search result is that the user does not have a history of pre-established payment services.
  • It is determined that the feature information fails to match the provisioning record rule.
  • the recommended copy corresponding to the opening record rule can be set to remind the user to open a preset payment service.
  • the corresponding recommended copy can be set to "enable fingerprint payment to make payment more secure and convenient.”
  • the preset rule may include a payment frequency rule, and the payment frequency rule is used to screen users with a higher payment frequency.
  • the characteristic information may include how often the user uses the client to make a payment.
  • the frequency at which the user uses the client to make a payment may be the frequency at which the user uses the client to perform a payment operation within a specified time period before the current time. For example, the frequency of payments in the previous month, quarter, or year.
  • determining the recommended recommended copy of this time includes matching the characteristic information with a payment frequency rule.
  • Matching the feature information with the payment frequency rule specifically includes: judging whether the frequency of the user's payment using the client exceeds a preset threshold, and if so, determining that the feature information matches the payment frequency rule successfully, and pre-matches the payment with the payment
  • the recommended copy associated with the frequency rule is used as the recommended copy for this recommendation. If not, it is determined that the feature information fails to match the payment frequency rule.
  • the preset threshold can be set according to the payment frequency distribution of each user in the actual application. According to the payment frequency rules, high-frequency payment users can be screened.
  • the preset payment service is a payment service using biometric information
  • biometric information such as fingerprints or faces
  • passwords because the verification process of biometric information such as fingerprints or faces is faster than passwords, it is particularly suitable for high-frequency users who often grab promotions, so configure the payment frequency
  • the recommended copy corresponding to the payment frequency rule can be configured as "enable fingerprint payment, and pay one step faster”.
  • the preset rules may include user attribute rules.
  • the user attribute rules are used to filter user types.
  • the characteristic information may include a model of a user terminal used by the user.
  • determining the recommended recommended copy of this time includes matching the characteristic information with a user attribute rule.
  • Matching feature information with user attribute rules specifically includes: determining whether the user belongs to a preset user according to the model of the user terminal used by the user, and if the user belongs to the preset user, determining the feature information and the The user attribute rule is successfully matched, and the recommended copy associated with the user attribute rule is used as the recommended copy of the current recommendation. If the user does not belong to a preset user, it is determined that the feature information matches the user attribute rule. failure.
  • the server can determine whether the user is a preset user by integrating the type of the user terminal used by the user and other characteristics of the user such as the age of the user, the city where the user is located, and the user's ability to pay.
  • the user's ability to pay can be the transaction amount of the user within a specified time period before the current time. For example, when other characteristics of the user include the age of the user, the city where the user is located, and the user's ability to pay, the models of the user terminal used by the user belong to the preset model set, the age of the user is within the preset age range, When the user's city is a first-tier city and the user's ability to pay exceeds a preset amount, it is determined that the user belongs to the preset user.
  • the preset age range and the preset amount can be set according to actual conditions. Because the prices of different models of user terminals of different brands are different, it is possible to obtain in advance models for user terminals of each brand whose prices exceed a preset price threshold, and build a set of preset models.
  • the server may also determine whether the user belongs to the preset user by determining whether the model of the user terminal used by the user belongs to a preset model set. If the model of the user terminal used by the user belongs to The preset model set determines that the user belongs to the preset user. If the model of the user terminal used by the user does not belong to the preset model set, it determines that the user does not belong to the preset user.
  • the recommended copy corresponding to the user attribute rule can be configured as "60% of XX mobile phone users are using the fingerprint to pay, and even if they enter the password, they are out! Among them, "XX" can be the brand of the mobile phone.
  • each rule is associated with a corresponding recommended copy.
  • the above-mentioned matching of the feature information with a preset rule pre-associated with the recommended copy to determine the recommended copy of the recommendation includes: sequentially comparing the feature information with the multiple rules according to the priority order. Matching is performed; when the feature information is successfully matched with any one of the rules, the recommended copy corresponding to the successfully matched rule is taken as the recommended copy of the current recommendation. It should be noted that the priority order of multiple rules included in the pre-rule can be set and adjusted according to the actual test result of the recommendation success rate under each rule.
  • rule A is associated with a preset recommendation copy P1
  • rule B is associated with a preset recommendation copy P2
  • rule C is associated with a preset recommendation copy P3 .
  • the pre-configured priority order is: rule A> rule B> rule C
  • the user's characteristic information is first matched with rule A.
  • the recommended copy P1 is used as the recommended copy of the current recommendation, and it stops.
  • Match when the match fails, continue to match the user's characteristic information with rule B; when the match is successful, the recommended copy P2 is used as the recommended copy of the current recommendation to stop matching; when the match fails, continue to match the user
  • the matching feature information matches rule C.
  • the recommendation copy P3 is used as the recommended copy for this recommendation, and the matching is stopped.
  • the matching fails, that is, the user's feature information does not match the preset rule, it is not correct.
  • the user makes subsequent recommendations.
  • the server can feed back information to the client to indicate the end of the recommendation, so that the client ends the recommendation when receiving the information.
  • a preset default copy can be used as the recommended copy for this recommendation.
  • the preset rules may include two or more of the above-mentioned scene rules, provisioning record rules, payment frequency rules, and user attribute rules.
  • the preset rules may also include other rules, which may be specifically set as required.
  • the preset rules include any of the above-mentioned scenario rules, provisioning record rules, payment frequency rules, and user attribute rules
  • these two rules correspond to a priority order, and feature information is first compared with the priority among them The higher rule is used to match.
  • the match is successful, the recommended copy corresponding to the rule is used as the recommended copy of the recommendation, and the matching is ended.
  • the match fails, the feature information is compared with another one with a relatively lower priority. Rules to match.
  • the preset rules include any of the above three rules of the scene rule, the opening record rule, the payment frequency rule, and the user attribute rule
  • the three types of rules correspond to the priority order, and the priority order is from high to low. Match the feature information with these three rules.
  • the preset rules include the above-mentioned scene rules, opening record rules, payment frequency rules, and user attribute rules
  • these four rules correspond to a priority order
  • the feature information is sequentially related to the four in order of priority. Rules to match.
  • the priority order of the above scenario rules, provisioning record rules, payment frequency rules, and user attribute rules may be: scenario rules> provisioning record rules> payment frequency rules> User attribute rules.
  • the recommended copy corresponding to the open record rule is used as the recommended copy of the current recommendation to end the match.
  • the feature information is matched with the payment frequency rule.
  • the recommended copy corresponding to the payment frequency rule is used as the recommended copy of this recommendation, and the matching is ended.
  • the feature information is matched with the user attribute rule.
  • the recommended copy corresponding to the user attribute rule is used. As the recommended copy of the recommendation, end the matching; when the match fails, end the recommendation or use the preset default copy as the recommended copy.
  • Step S204 Send the recommended copy to the client, so that the client displays a recommendation interface to the user according to the recommended copy, and the recommendation interface is used to recommend the preset to the user. Payment business.
  • the server After determining the recommended copy of the recommendation through step S203, the server sends the recommended copy to the client, and the client displays a recommendation interface based on the recommended copy.
  • the recommendation interface can display the recommended copy and an activation button for activating a preset payment service.
  • the user can browse the recommended copy in the recommendation interface. If the user wants to activate the preset payment protocol, he can trigger the activation button to activate the preset payment service. At this time, the recommendation is successful. If the user does not want to activate the preset, For the payment protocol, you can choose to exit the recommendation interface or directly close the client. At this time, the recommendation fails.
  • the method further includes a strategy adjustment step.
  • the strategy adjustment step specifically includes: the user receiving the client feedback based on the recommendation interface Adjusting behavior data based on the behavior data; and adjusting the preset rule based on the behavior data.
  • the behavior data of the user based on the recommendation interface may include data such as whether the user clicked the activation button displayed on the recommendation interface, whether the user exited the recommendation interface, whether the user directly exited the client, and the user's time on the recommendation interface. .
  • a specific strategy for the server to adjust the preset rule based on the behavior data may be set according to an actual application. For example, when the preset rule includes multiple rules, when recommending to users who meet one of the rules, the success rate is lower than the preset first threshold, or the proportion of users who choose to quit the client directly after displaying the recommendation interface Above the preset second critical value, it indicates that the rule is not applicable, delete the rule or modify the rule.
  • the preset rule includes a scene rule, a provisioning record rule, a payment frequency rule, and a user attribute rule
  • the priority order is: scenario rule> provisioning record rule> payment frequency rule> user attribute rule
  • the priority order of the preset rules is adjusted as: scenario rules> payment frequency rules> opening record rules> user attribute rules.
  • the server may further send an inquiry instruction to the client corresponding to the user, so that the client pops up an inquiry window in the recommendation interface for inquiring that the user has encountered a problem, and the user may enter the encountered problem in the inquiry window , And feedback to the server, so that after receiving the problem feedback, the server can help interested users solve the problem and complete the opening of the preset payment service.
  • the service recommendation method provided in the embodiments of the present specification, by using appropriate scenarios, to screen users for the feature information and preset rules for users who have the provisioning conditions, it is helpful to synchronize while not significantly increasing the interruption rate. Increase the success rate of recommendations.
  • an embodiment of the present specification provides a service recommendation method.
  • This embodiment is a service recommendation method performed by a client. Referring to FIG. 3, the method includes the following steps S301 to S303.
  • step S301 when it is detected that the user enters a preset scene, it is determined whether the user meets the provisioning conditions of the preset payment service.
  • the preset payment service may be a payment service using biometric information, such as a fingerprint payment service and a face payment service.
  • biometric information such as a fingerprint payment service and a face payment service.
  • fingerprint verification and face recognition have a higher success rate, so increasing the user's use of fingerprint payment or face payment will help improve the overall payment success rate. Therefore, in order to expand the coverage of fingerprint payment or fingerprint payment users, business recommendations need to be made to users.
  • the preset payment service may also be another payment service that needs to be recommended to the user.
  • the client screens the user's scene and the users to be recommended.
  • a recommendation request is sent to the server.
  • the preset scenes can be set according to actual applications. In these scenes, it is more in line with the user's mind to give the user an alternative payment method to choose from.
  • the preset scene may be any scene in a specified scene set.
  • the specified scene set may include, but is not limited to, a password payment scene, an encryption scene, and a secret finding scene.
  • the user's related operation is the password payment operation, that is, the user completes the payment operation after the password verification is passed by entering the password
  • the user's related operation is the password replacement operation That is, when the user is required to complete the payment password by the system, the operation of completing the password is performed according to the instructions of the system.
  • the user's related operation is the operation of recovering the password. The operation of retrieving the password.
  • the step of detecting whether a user enters a password payment scenario includes: when detecting that a user triggers a password payment operation, determining whether the password payment operation is in a completed state, and if so, determining whether The user enters the password payment scenario.
  • the specific process of the password payment operation may include the client obtaining the payment password entered by the user and sending the payment password to the server for verification.
  • the verification is passed, the current payment transaction is completed, and when the verification feedback received by the server passes
  • the payment is completed, that is, the password payment operation is in the completed state.
  • the step of detecting whether the user enters the password-encrypting scene includes: the detecting step of the preset scenario includes: when detecting that the user triggers the password-adding operation, determining whether the password-adding operation is in a completed state If yes, it is determined that the user enters the backfill scenario.
  • the system will send an instruction to the user, asking the user to complete the payment password.
  • the user can trigger the password replacement operation to set the payment password according to the system prompt.
  • the payment password is set successfully Indicates that the password reset operation is completed.
  • the step of detecting whether the user enters the secret finding scene includes: when detecting that the user triggers the password retrieval operation, determining whether the secret finding operation is in a completed state, and if so, determining that the user enters The finding scene.
  • the opening conditions can be set according to the actual payment service requirements.
  • the provisioning conditions include one or more of the following three conditions: the user terminal used by the user supports a preset security protocol; the user used by the user The biometric information of the user is pre-entered in the terminal; and the preset payment service of the user is in an un-enabled state.
  • the process of the client determining whether the user meets the provisioning conditions of the preset payment service may include: determining whether the preset payment service of the user is in an activated state, and if so, ending the recommendation. If not, determine whether the user terminal used by the user supports the preset security protocol. If not, end this recommendation. If yes, determine whether the user terminal used by the user has previously entered the user's biometric information. If not, , Then end the recommendation, and if so, determine that the user satisfies the provisioning conditions of the preset payment service.
  • the above-mentioned determining steps of the opening state, the determining steps of the security protocol, and the determining steps of inputting biological characteristics information may not be performed in the above order.
  • the determination of the security protocol may be performed first, and then the opening states and biological characteristics Judgment of information entry.
  • the preset security protocol may be an IFAA protocol or a similar security protocol.
  • the IFAA agreement or similar security protocol is the basic condition for supporting fingerprint or face payments.
  • the isSupported interface can be called to determine whether the phone supports the IFAA protocol through the status bit built into the framework by the phone manufacturer.
  • the biometric information such as fingerprint information or face information
  • pre-entered in the user terminal by the user is stored in a specific location of the user terminal.
  • the user can determine whether the user's biometric information is stored in a specific location in the user terminal through an interface provided by the system.
  • the stored biometric information should correspond to the preset payment service.
  • the preset payment service is a fingerprint payment service
  • the biometric information is fingerprint information
  • the preset payment service is a face payment service
  • the biometric information Face information when the preset payment service is a face payment service.
  • Step S302 When the provisioning condition is satisfied, send a recommendation request to the server, so that the server obtains the characteristic information of the user based on the recommendation request, and associates the characteristic information with a pre-associated recommendation copy in advance. Set rules to match to determine the recommended copy of this recommendation.
  • the recommendation request includes the user's identity information, for example, the user's account information or other identity information, so that the server can find the characteristic information of the user according to the user's identity information.
  • the characteristic information of the user may include, but is not limited to, the device of the user terminal used by the user, whether there is a previous record of activation, and the frequency of use.
  • the characteristic information of the user may also include the age of the user and the city where the user is located.
  • the server determines the implementation manner of the recommended recommendation text by matching the characteristic information with a preset rule associated with the recommendation text in advance, and may refer to the specific implementation manner of step S203 in the business recommendation method provided in the first aspect above. , Will not repeat them here.
  • Step S303 Receive the recommendation copy issued by the server, and display a recommendation interface to the user according to the recommendation copy, where the recommendation interface is used to recommend the preset payment service to the user.
  • the recommendation interface can display the recommended copy and an activation button for activating a preset payment service.
  • the user can browse the recommended copy in the recommendation interface. If the user wants to activate the preset payment protocol, he can trigger the activation button to activate the preset payment service. At this time, the recommendation is successful. If the user does not want to activate the preset, For the payment protocol, you can choose to exit the recommendation interface or directly close the client. At this time, the recommendation fails.
  • the method may further include: obtaining the user based on the recommendation Interface behavior data, and feedback the behavior data to the server, so that the server adjusts the preset rule based on the behavior data.
  • the behavior data of the user based on the recommendation interface may include data such as whether the user clicked the activation button displayed on the recommendation interface, whether the user exited the recommendation interface, whether the user directly exited the client, and the user's time on the recommendation interface .
  • a specific strategy for the server to adjust the preset rule based on the behavior data may be set according to an actual application.
  • a preset recommended fatigue strategy in order to control the interruption rate within a reasonable range, a preset recommended fatigue strategy may be followed.
  • the service recommendation method when determining that a user meets the provisioning conditions of a preset payment service, before the client sends a recommendation request to the server, the service recommendation method further includes: acquiring a history corresponding to the user. The recommendation record determines whether the historical recommendation record satisfies a preset condition. If so, the step of sending a recommendation request to the server is performed. If not, the current recommendation is stopped.
  • the historical recommendation record may include: the first number of recommendations and / or the second number of recommendations.
  • the first recommendation number is the number of preset payment service recommendations for the user in the first target time period
  • the second recommendation number is the number of preset payment service recommendations for the user in the second target time period.
  • the time length of one target time period is shorter than the time length of the second target time period, and it is set as required.
  • the first target time period may be within seven days before the current time
  • the second target time period may be within one year before the current time.
  • determining whether the historical recommendation record satisfies a preset condition may specifically include: determining whether the first recommendation number is less than or equal to a preset first number threshold. If it is less than or equal to the preset first number of times threshold, it is determined whether the second recommendation number is less than or equal to the preset second number of times threshold; if it is less than or equal to the preset second number of thresholds, it is determined that the historical recommendation record meets the preset Condition; if the first recommendation number is greater than a preset first number threshold or the second recommendation number is greater than a preset second number threshold, it is determined that the historical recommendation record does not satisfy the preset condition.
  • the first number of times threshold and the second number of times threshold can be set according to actual needs.
  • the threshold for the first number of times can be set to zero, and the threshold for the second number of times can be set to 5, so as to ensure that the user is not repeatedly recommended in the first target time period, and the number of recommended times is not exceeded in the second target time period. 5 times in order to control the interruption rate within a reasonable range.
  • the service recommendation method may further include: detecting whether there is any Set the history of the target function to be closed within a period of time. If it is, execute the step of sending a recommendation request to the server. If not, stop this recommendation.
  • the preset time period can be set according to actual needs, for example, it can be set to 60 days before the current time.
  • the target function corresponds to the preset payment service.
  • the target function is the fingerprint recognition function of the user terminal.
  • the target function can be TouchID; when the preset payment service is In the face payment service, the target function is the face recognition function of the user terminal.
  • the target function can be FaceID.
  • the service recommendation method provided in the embodiments of the present specification, by using appropriate scenarios, to screen users for the feature information and preset rules for users who have the provisioning conditions, it is helpful to synchronize while not significantly increasing the interruption rate. Increase the success rate of recommendations.
  • an embodiment of the present specification provides a service recommendation method.
  • This embodiment is a service recommendation method performed by a client. Referring to FIG. 4, the method includes the following steps S401 to S402.
  • step S401 when it is detected that a user enters a preset scenario, it is determined whether the user meets a provisioning condition of a preset payment service, wherein the preset scenario is a password payment scenario, a supplementary scenario or a secret finding scenario.
  • the preset scenario is a password payment scenario, a supplementary scenario or a secret finding scenario.
  • the preset scene may be any scene in a specified scene set.
  • the specified scene set may include a password payment scene, a supplementary scene, and a secret finding scene.
  • the user's related operation is the password payment operation, that is, the user completes the payment operation after the password verification is passed by entering the password
  • the user's related operation is the password replacement operation That is, when the user is required to complete the payment password by the system, the operation to complete the password is performed according to the instructions of the system.
  • the user's related operation is the password recovery operation, that is, after the user clicks the forgot password button, the system performs the instructions. The operation of retrieving the password.
  • the step of detecting whether the user enters the password payment scenario includes: when detecting that the user triggers the password payment operation, determining whether the password payment operation is in a completed state, and if so, determining whether the password payment operation is in a completed state. The user enters the password payment scenario.
  • the specific process of the password payment operation may include the client obtaining the payment password entered by the user and sending the payment password to the server for verification.
  • the verification is passed, the current payment transaction is completed, and when the verification feedback received by the server passes
  • the payment is completed, that is, the password payment operation is in the completed state.
  • the step of detecting whether the user enters the password-encrypting scene includes: the detecting step of the preset scenario includes: when detecting that the user triggers the password-adding operation, determining whether the password-adding operation is in a completed state If yes, it is determined that the user enters the backfill scenario.
  • the system will send an instruction to the user, asking the user to complete the payment password.
  • the user can trigger the password replacement operation to set the payment password according to the system prompt.
  • the payment password is set successfully Indicates that the password reset operation is completed.
  • the step of detecting whether the user enters the secret finding scene includes: when detecting that the user triggers the password retrieval operation, determining whether the secret finding operation is in a completed state, and if so, determining that the user enters The finding scene.
  • the password recovery operation can be triggered to retrieve or reset the password.
  • the specific process can be based on the relevant system Instructs to perform corresponding operations, for example, answering pre-set questions, etc.
  • the password retrieval is successful, it indicates that the password retrieval operation is completed.
  • the opening conditions can be set according to the actual payment service requirements.
  • the provisioning conditions include one or more combinations of the following three conditions: the user terminal used by the user supports a preset security protocol; the user used by the user The biometric information of the user is pre-entered in the terminal; and the preset payment service of the user is in an un-enabled state.
  • the user terminal used by the user supports a preset security protocol
  • the user used by the user The biometric information of the user is pre-entered in the terminal
  • the preset payment service of the user is in an un-enabled state.
  • Step S402 When the provisioning conditions are met, a recommendation interface is displayed to the user, and the recommendation interface is used to recommend the preset payment service to the user.
  • a user when a user enters a preset scenario and satisfies an activation condition of a preset payment service, it indicates that the user is a target user suitable for recommendation of a preset payment service, and then performs a recommendation of a preset payment service to the user.
  • the client may display the preset recommendation interface to the user.
  • the recommendation interface displays preset related descriptions of the preset payment service and an activation button for activating the preset payment service.
  • the client may send a recommendation request to the server.
  • the recommendation request includes the user's identity information, for example, it may be the user's account information or other identity information.
  • the server is based on the received recommendation request. To obtain the characteristic information of the user, and by matching the characteristic information with a preset rule associated with the recommended copy in advance, the recommended recommended copy is determined, and the recommended copy is fed back to the client, and the client sends the recommended copy to the user Display the recommendation interface.
  • the specific process may refer to the corresponding description in the service recommendation method provided in the first aspect, and is not repeated here.
  • a preset recommended fatigue strategy in order to control the interruption rate within a reasonable range, a preset recommended fatigue strategy may be followed.
  • the service recommendation method when determining that a user meets the provisioning conditions of a preset payment service, before displaying a recommendation interface to the user, the service recommendation method further includes: acquiring a history corresponding to the user. The recommendation record determines whether the historical recommendation record satisfies a preset condition. If so, the step of displaying a recommendation interface to the user is performed. If not, the current recommendation is stopped.
  • the specific process of obtaining the historical recommendation record corresponding to the user and judging whether the historical recommendation record meets a preset condition may refer to the related description in the service recommendation method provided by the second aspect, which is not repeated here.
  • the service recommendation method provided in the embodiments of this specification recommends a preset payment service to users who have the provisioning conditions in an appropriate scenario, which is helpful to improve the success rate of recommendation.
  • an embodiment of the present specification also provides a service recommendation device, and the device provided in this embodiment may run on a server.
  • the service recommendation device 50 may include:
  • the receiving module 51 is configured to receive a recommendation request sent by a client, where the recommendation request is sent by the client when it detects that a user enters a preset scenario and determines that the user meets a provisioning condition of a preset payment service;
  • An obtaining module 52 configured to obtain characteristic information of the user based on the recommendation request
  • a determining module 53 is configured to determine the recommended copy of the recommendation by matching the feature information with a preset rule associated with the recommended copy in advance;
  • a copy sending module 54 is configured to send the recommended copy to the client, so that the client displays a recommendation interface to the user according to the recommended copy, and the recommendation interface is used to recommend to the user The preset payment service.
  • the preset rule includes multiple rules pre-configured with priorities, and each rule corresponds to a recommended copy.
  • the determining module 53 is specifically configured to: The feature information is sequentially matched with the multiple rules; when the feature information is successfully matched with any one of the rules, the recommended copy corresponding to the successfully matched rule is used as the recommended copy of the current recommendation.
  • the feature information includes scene information where the user is currently located
  • the preset rule includes a scene rule
  • the determining module 53 includes a first matching sub-module 531 for determining Whether the current scene information of the user belongs to a specified scene, and if so, it is determined that the feature information matches the scene rule successfully, and the recommended copy associated with the scene rule in advance is used as the recommended copy of the current recommendation.
  • the characteristic information includes identification information
  • the identification information is used to indicate whether the user has a history of opening the preset payment service
  • the determining module 53 includes: a second match A sub-module 532, configured to determine whether the user has a history of opening a preset payment service according to the identification information, and if yes, determine that the feature information and the opening record rule are successfully matched, and will be pre-connected with the The recommendation copy associated with the record rule is used as the recommendation copy for this recommendation.
  • the characteristic information includes a frequency of payment by the user using the client
  • the preset rule includes a payment frequency rule
  • the determining module 53 includes a third matching sub-module 533 For determining whether the frequency exceeds a preset threshold, and if yes, determining that the feature information matches the payment frequency rule successfully, and using the recommended copy associated with the payment frequency rule in advance as the recommended copy for the current recommendation.
  • the characteristic information includes a model of a user terminal used by the user
  • the preset rule includes a user attribute rule
  • the determining module 53 includes a fourth matching sub-module 534 for Determining whether the user belongs to a preset user according to the model of the user terminal used by the user, and if so, determining that the characteristic information matches the user attribute rule successfully, and recommending to associate the user with the user attribute rule in advance Copywriting as the recommended copy for this recommendation.
  • the apparatus further includes: an adjustment module 55, configured to receive behavior data of the user based on the recommendation interface received by the client, and adjust the preset based on the behavior data. Rules are adjusted.
  • an embodiment of the present specification also provides a service recommendation device, and the device provided in this embodiment may run on a client.
  • the service recommendation device 60 may include:
  • a judging module 61 configured to judge whether the user satisfies the opening condition of a preset payment service when detecting that the user enters a preset scenario
  • a request sending module 62 is configured to: when the provisioning condition is met, the client sends a recommendation request to a server, so that the server obtains characteristic information of the user based on the recommendation request, and sends the characteristic information by using the characteristic information. Match the preset rules with the recommended copy in advance to determine the recommended copy for this recommendation;
  • a display module 63 is configured to receive the recommendation copy issued by the server, and display a recommendation interface to the user according to the recommendation copy, where the recommendation interface is used to recommend the preset payment service to the user.
  • the preset payment service is a service using biometric information for payment
  • the provisioning conditions include one or more of the following conditions: the user terminal used by the user supports pre-payment The security protocol provided; the biometric information of the user is pre-registered in the user terminal used by the user; and the preset payment service of the user is in an un-enabled state.
  • the apparatus further includes: a feedback module, configured to obtain behavior data of the user based on the recommendation interface, and feed back the behavior data to the server, so that the server is based on The behavior data adjusts the preset rule.
  • a feedback module configured to obtain behavior data of the user based on the recommendation interface, and feed back the behavior data to the server, so that the server is based on The behavior data adjusts the preset rule.
  • the device further includes: a first filtering module, configured to obtain a history recommendation record corresponding to the user, determine whether the history recommendation record meets a preset condition, and if yes, execute a request to a server. Step of sending a recommendation request. If not, stop the recommendation.
  • a first filtering module configured to obtain a history recommendation record corresponding to the user, determine whether the history recommendation record meets a preset condition, and if yes, execute a request to a server. Step of sending a recommendation request. If not, stop the recommendation.
  • the device further includes: a second filtering module, configured to detect whether there is a history record of the target terminal being turned off within a preset period of time in the user terminal, and if yes, execute sending to the server Step of recommendation request, if not, stop this recommendation.
  • a second filtering module configured to detect whether there is a history record of the target terminal being turned off within a preset period of time in the user terminal, and if yes, execute sending to the server Step of recommendation request, if not, stop this recommendation.
  • the preset scenario is a password payment scenario, an encryption scenario, or a security finding scenario.
  • an embodiment of the present specification further provides a service recommendation device, and the device provided in this embodiment may run on a client.
  • the service recommendation device 70 may include:
  • a detection module 71 is configured to determine whether the user meets a provisioning condition of a preset payment service when detecting that the user enters a preset scenario, wherein the preset scenario is a password payment scenario, a supplementary scenario, or a secret finding scenario;
  • the recommendation module 72 is configured to display a recommendation interface to the user when the provisioning condition is satisfied, and the recommendation interface is used to recommend the preset payment service to the user.
  • the detection module 71 is specifically configured to: when detecting that a user triggers a password payment operation, determine whether the password payment operation is in a completed state If yes, it is determined that the user enters the password payment scenario.
  • the detection module 71 is specifically configured to: when detecting that a user triggers a password reset operation, determine whether the password reset operation is in the Completion status, if yes, it is determined that the user enters the backfill scenario.
  • the detection module 71 is specifically configured to: when detecting that a user triggers a password retrieval operation, determine whether the secret finding operation is in a completed state State, if yes, it is determined that the user enters the secret finding scene.
  • the present invention also provides an electronic device.
  • the electronic device includes a memory 804, one or more processors 802, and a memory stored on the memory 804 and operable on the processor 802. Computer program.
  • the processor 802 executes the program to implement the steps of the service recommendation method in the embodiment provided by the first aspect of the foregoing.
  • the processor 802 executes the program, the steps of implementing the service recommendation method in the embodiment provided in the second aspect above, or implementing the service recommendation method in the embodiment provided by the third aspect above step.
  • the bus architecture (represented by the bus 800).
  • the bus 800 may include any number of interconnected buses and bridges.
  • the bus 800 will include one or more processors represented by the processor 802 and memory 804.
  • the various circuits of the memory are linked together.
  • the bus 800 can also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art, and therefore, they are not described further herein.
  • the bus interface 805 provides an interface between the bus 800 and the receiver 801 and the transmitter 803.
  • the receiver 801 and the transmitter 803 may be the same element, that is, a transceiver, providing a unit for communicating with various other devices on a transmission medium.
  • the processor 802 is responsible for managing the bus 800 and general processing, and the memory 804 may be used to store data used by the processor 802 when performing operations.
  • FIG. 8 is only schematic, and the above electronic device may further include more or fewer components than those shown in FIG. 8, or have a different configuration from that shown in FIG. 8.
  • Each component shown in FIG. 8 may be implemented by hardware, software, or a combination thereof.
  • the present invention also provides a computer-readable storage medium on which a computer program is stored, which is implemented when the program is executed by a processor. Steps of the service recommendation method in the embodiment provided in the first aspect of the foregoing.
  • the present invention also provides a computer-readable storage medium on which a computer program is stored, which is implemented when the program is executed by a processor. Steps of the service recommendation method in the embodiment provided in the second aspect of the foregoing.
  • the present invention also provides a computer-readable storage medium on which a computer program is stored, which is implemented when the program is executed by a processor. Steps of the service recommendation method in the embodiment provided in the third aspect above.
  • These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to work in a particular manner such that the instructions stored in the computer-readable memory produce a manufactured article including the instruction device, the instructions
  • the device implements the functions specified in one or more flowcharts and / or one or more blocks of the block diagram.
  • These computer program instructions can also be loaded on a computer or other programmable data processing device, so that a series of steps can be performed on the computer or other programmable device to produce a computer-implemented process, which can be executed on the computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more flowcharts and / or one or more blocks of the block diagrams.

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Abstract

本说明书实施例提供了一种业务推荐方法，通过在预设场景下，对满足预设支付业务的开通条件的用户，基于用户的特征信息与预先关联有推荐文案的预设规则，来筛选出本次推荐的推荐文案，进而基于该推荐文案向用户展示推荐界面，有利于在保证不显著提高打扰率的同时，同步提高推荐的成功率。

Description

业务推荐方法、装置、电子设备及可读存储介质 技术领域
本说明书实施例涉及数据处理技术领域，尤其涉及一种业务推荐方法、装置、电子设备及可读存储介质。
背景技术
随着互联网技术的发展，为业务推广带来了很大的便利。为了扩大新增支付业务的用户覆盖率，需要向用户进行业务推荐。因此，需要一种能够有效提高成功率的推荐方法。
发明内容
本说明书实施例提供了一种业务推荐方法、装置、电子设备及可读存储介质。
第一方面，本说明书实施例提供了一种业务推荐方法，包括：接收客户端发送的推荐请求，所述推荐请求是所述客户端在检测到用户进入预设场景，并判定所述用户满足预设支付业务的开通条件时发送的；基于所述推荐请求获取所述用户的特征信息；通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；将所述推荐文案下发给所述客户端，以使所述客户端根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
第二方面，本说明书实施例提供了一种业务推荐方法，包括：当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件；当满足所述开通条件时，向服务器发送推荐请求，以使得所述服务器基于所述推荐请求，获取所述用户的特征信息，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；接收所述服务器下发的所述推荐文案，并根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
第三方面，本说明书实施例提供了一种业务推荐方法，包括：当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件，其中，所述预设场景为密码支付场景、补密场景或找密场景；当满足所述开通条件时，向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
第四方面，本说明书实施例提供了一种业务推荐装置，应用于服务器，包括：接收模块、获取模块、确定模块以及文案发送模块。接收模块，用于接收客户端发送的推荐请求，所述推荐请求是所述客户端在检测到用户进入预设场景，并判定所述用户满足预设支付业务的开通条件时发送的。获取模块，用于基于所述推荐请求获取所述用户的特征信息。确定模块，用于通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案。文案发送模块，用于将所述推荐文案下发给所述客户端，以使所述客户端根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
第五方面，本说明书实施例提供了一种业务推荐装置，应用于客户端，包括：判断模块、请求发送模块以及展示模块。判断模块，用于当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件。请求发送模块，用于当满足所述开通条件时，所述客户端向服务器发送推荐请求，以使得所述服务器基于所述推荐请求，获取所述用户的特征信息，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案。展示模块，用于接收所述服务器下发的所述推荐文案，并根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
第六方面，本说明书实施例提供了一种业务推荐装置，包括：检测模块，用于当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件，其中，所述预设场景为密码支付场景、补密场景或找密场景；推荐模块，用于当满足所述开通条件时，向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
第七方面，本说明书实施例提供了一种电子设备，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上述第一方面、第二方面或第三方面提供的业务推荐方法的步骤。
第八方面，本说明书实施例提供了一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现上述第一方面、第二方面或第三方面提供的业务推荐方法的步骤。
本说明书实施例有益效果如下：
本说明书实施例提供的业务推荐方法，先由客户端在检测到用户进入预设场景，且判定该用户满足预设支付业务的开通条件时，向服务器发送推荐请求，然后由服务器基 于该推荐请求获取该用户的特征信息，通过将该特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案，并将该推荐文案下发给客户端，由客户端根据该推荐文案向用户展示推荐界面。通过在合适的场景下，对具备开通条件的用户，针对用户的特征信息以及预设规则筛选推荐文案，有利于在保证不显著提高打扰率的同时，同步提高推荐的成功率。
附图说明
图1为本说明书实施例的一种应用场景示意图；
图2为本说明书实施例第一方面提供的业务推荐方法的流程图；
图3为本说明书实施例第二方面提供的业务推荐方法的流程图；
图4为本说明书实施例第三方面提供的业务推荐方法的流程图；
图5为本说明书实施例第四方面提供的业务推荐装置的结构示意图；
图6为本说明书实施例第五方面提供的业务推荐装置的结构示意图；
图7为本说明书实施例第六方面提供的业务推荐装置的结构示意图；
图8为本说明书实施例第七方面提供的电子设备结构示意图。
具体实施方式
为了更好的理解上述技术方案，下面通过附图以及具体实施例对本说明书实施例的技术方案做详细的说明，应当理解本说明书实施例以及实施例中的具体特征是对本说明书实施例技术方案的详细的说明，而不是对本说明书技术方案的限定，在不冲突的情况下，本说明书实施例以及实施例中的技术特征可以相互组合。
本说明书实施例中，IFAA协议是一种安全校验协议，主要用于支持指纹支付、面容支付、SE证书等多种业务。密码支付场景是指用户在刚使用密码支付完成校验的场景。找密场景是指用户忘记了支付密码，通过执行一些指定操作如答复问题完成密码找回的场景。补密场景是指用户尚未设置过支付密码，被系统要求补齐支付密码后，完成支付密码设置的场景。
请参见图1，为适用于本说明书实施例的一种运行环境示意图。如图1所示，一个或多个用户终端100(图1中仅示出一个)可通过网络200与一个或多个服务器300(图 1中仅示出一个)相连，以进行数据通信或交互。其中，用户终端100可以是个人电脑(personal computer，PC)、笔记本电脑、平板电脑、智能手机、电子阅读器、车载设备、网络电视、可穿戴设备等具有网络功能的智能设备。
于本说明书实施例中，用户终端100中安装有客户端，该客户端可以是第三方应用软件也可以是浏览器，与服务器(Server)端相对应，为用户提供服务，例如支付服务，用于对交易进行支付。
第一方面，本说明书实施例提供了一种业务推荐方法，本实施例为服务器所执行的业务推荐方法。请参见图2，该方法包括步骤S201-步骤S204。
步骤S201，接收客户端发送的推荐请求，所述推荐请求是所述客户端在检测到用户进入预设场景，并判定所述用户满足预设支付业务的开通条件时发送的。
本说明书实施例中，预设支付业务可以是利用生物特征信息进行支付的业务，如指纹支付业务、面容支付业务等。指纹校验和人脸识别相比较密码有较高的成功率，所以提高用户的指纹支付使用比例或面容支付使用比例有助于提高整体的支付成功率。因此，为了扩大指纹支付或指纹支付用户的覆盖率，需要向用户进行业务推荐。当然，在本说明书的其他实施例中，预设支付业务也可以是其他需要向用户推荐的支付业务。
为了增加推荐的成功率，客户端会对用户所处的场景以及所要推荐用户进行筛选。当检测到用户进入预设场景，并判定用户满足预设支付业务的开通条件时，再向服务器发送推荐请求。
本说明书实施例中，预设场景可以根据实际应用设置，在这些场景下给用户一种另外的支付方式供选择会更符合用户心智。具体来讲，预设场景可以为指定场景集合中的任意一种场景。本说明书实施例中，指定场景集合可以包括但不限于密码支付场景、补密场景和找密场景。可以理解的是，用户刚刚完成密码支付时，是给用户进行推荐的好时机，密码支付本身需要用户牢记密码，并且输入时间较长，在用户刚刚完成这样一个流程时做推荐，给用户推荐一种更省时省力的选择，更符合用户心智；同理，在补密场景或找密场景中，用户刚刚经历过因为忘记密码而带来的多余操作的麻烦，此时正好是给用户提供了一个不需要记忆的方案的好时机。因此，在合适的场景下对用户进行新的支付业务推荐，用户更容易接受，有利于提高推荐的成功率。
当预设支付业务为利用生物特征信息进行支付的业务时，开通条件可以根据实际支付业务需要设置。作为一种可选的实施方式，上述步骤S201中，开通条件包括以下三 种条件中的一种或多种组合：所述用户使用的用户终端支持预设的安全协议；所述用户使用的用户终端中预先录入有所述用户的生物特征信息；以及所述用户的预设支付业务处于未开通状态。
具体来讲，于本说明书的一实施例中，客户端判断用户是否满足预设支付业务的开通条件的过程可以包括：判断用户的预设支付业务是否处于开通状态，若是，则结束本次推荐，若否，则判断用户使用的用户终端是否支持预设的安全协议，若否，则结束本次推荐，若是，则判断用户使用的用户终端中是否预先录入有用户的生物特征信息，若否，则结束本次推荐，若是，则判定用户满足预设支付业务的开通条件。需要说明的是，上述的开通状态判断步骤、安全协议判断步骤和生物特性信息录入判断步骤也可以不按照上述顺序执行，例如，也可以先执行安全协议的判断，然后再执行开通状态和生物特性信息录入的判断。
具体地，当预设支付业务具体为指纹支付业务或面容支付业务时，预设安全协议可以是IFAA协议或类似安全协议。IFAA协议或类似安全协议是支持指纹支付或面容支付的基本条件。例如，当用户终端为智能手机时，可以调用isSupported接口通过手机厂商在Framework内置的状态位来判断该手机是否支持IFAA协议。
具体地，用户在用户终端中预先录入的生物特征信息如指纹信息或人脸信息会存储在用户终端的特定位置。用户可以通过系统提供的接口来判断用户终端中的特定位置是否存储有用户的生物特征信息。当然，所存储的生物特征信息应与预设支付业务对应，例如，当预设支付业务为指纹支付业务时，生物特征信息为指纹信息，当预设支付业务为面容支付业务时，生物特征信息为人脸信息。
步骤S202，基于所述推荐请求获取所述用户的特征信息。
可以理解的是，推荐请求中包括用户的身份信息，例如可以是用户的账号信息或其他的身份信息，以便于服务器可以根据用户的身份信息查找该用户的特征信息。本说明书实施例中，用户的特征信息可以包括但不限于用户所用用户终端的设备、之前是否有开通记录、使用频率。例如，用户的特征信息还可以包括用户的年龄以及所在城市等。
步骤S203，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案。
本说明书实施例中，预设规则可以包括一条规则或预先配置有优先级顺序的多条规则，具体根据实际需要设置。每条规则均关联有预先配置的推荐文案。需要说明的是， 推荐文案可以根据不同的规则具体配置，这样有利于根据用户的特征信息针对性地为用户展示适合的推荐文案，使得所展示的推荐文案更能够符合用户心智，从而提高推荐的成功率。
当预设规则包括一条规则时，则将用户的特征信息与该规则匹配，当匹配成功时，则将该规则关联的推荐文案作为本次推荐的推荐文案。当匹配失败时，则不对该用户进行后续推荐，此时，服务器可以向客户端反馈用于表示结束本次推荐的信息，使得客户端在接收到该信息时结束本次推荐。或者，当匹配失败时，则表示用户不具有个性化特征，将预先设置的默认文案，作为本次推荐的推荐文案。
具体来讲，用户的特征信息和预设规则可以根据需要设置，特征信息与具体的预设规则对应。本说明书实施例主要列举以下四种规则进行介绍，当然，在具体实施过程中，不限于以下四种规则。
第一种，预设规则可以包括场景规则。场景规则为根据特定场景设置的规则，此时，特征信息可以包括用户当前所处的场景信息。相应地，此时，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括将特征信息与场景规则进行匹配。将特征信息与场景规则进行匹配具体包括：判断所述用户当前所处的场景信息是否属于指定场景，若用户当前所处的场景信息属于指定场景，则判定所述特征信息与所述场景规则匹配成功，将预先与所述场景规则关联的推荐文案作为本次推荐的推荐文案，若用户当前所处的场景信息不属于指定场景，则判定特征信息与场景规则匹配失败。
在一种具体的应用场景中，场景规则对应的指定场景可以包括补密场景和找密场景。当预设支付业务为利用生物特征信息进行支付的业务时，因为指纹或人脸图像不存在忘记的问题，特别适合易忘的用户，配置场景规则对应的推荐文案时，可以从“省心”切入，例如，对于指纹支付业务，场景规则对应的推荐文案可以设置为“不怕忘，我的指纹就是我的密码”。
第二种，预设规则可以包括开通记录规则，开通记录规则是针对换机的用户设置的规则。换机的用户是指不同于当前使用的用户终端上开通过预设支付业务的用户。此时，特征信息可以包括标识信息，该标识信息用于表示用户是否具有预设支付业务的历史开通记录。相应地，此时，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括将特征信息与开通记录规则进行匹配。将特征信息与开通记录规则进行匹配具体包括：根据所述标识信息判断所述用户是否具有所述预设支 付业务的历史开通记录，若是，则判定所述特征信息与所述开通记录规则匹配成功，将预先与所述开通记录规则关联的推荐文案作为本次推荐的推荐文案。
例如，在一种具体应用场景中，服务器可以基于推荐请求中用户的身份信息查找该用户是否有对应于预设支付业务的历史开通记录，并通过设置标识信息来表征查找结果。当查找结果为用户具有预设支付业务的历史开通记录时，则表示该用户为换机用户，判定特征信息与开通记录规则匹配成功，当查找结果为用户没有预设支付业务的历史开通记录时，则判定特征信息与开通记录规则匹配失败。
对于换机用户来讲，对预设支付业务的使用已经非常熟悉，只需要提醒其开通即可。因此，开通记录规则对应的推荐文案，可以设置用于提醒用户开通预设支付业务的文案，例如，对于指纹支付业务，相应推荐文案可以设置为“开通指纹支付，让付款更安全便捷”。
第三种，预设规则可以包括支付频率规则，支付频率规则用于对支付频率较高的用户进行筛选。此时，特征信息可以包括用户使用客户端进行支付的频率。具体地，用户使用客户端进行支付的频率可以为当前时间之前的指定时间段内，用户使用该客户端进行支付操作的频率。例如，前一个月、前一个季度或前一年的支付频率。相应地，此时，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括将特征信息与支付频率规则进行匹配。将特征信息与支付频率规则进行匹配具体包括：判断用户使用客户端进行支付的频率是否超过预设阈值，若是，则判定所述特征信息与所述支付频率规则匹配成功，将预先与所述支付频率规则关联的推荐文案作为本次推荐的推荐文案，若否，则判定所述特征信息与所述支付频率规则匹配失败。
其中，预设阈值可以根据实际应用中各用户的支付频率分布设置。根据支付频率规则可以筛选出高频支付用户。当预设支付业务为利用生物特征信息进行支付的业务时，由于因为生物特征信息如指纹或人脸的验证过程比密码要快，特别适合那些经常抢促销的高频用户，因此，配置支付频率规则对应的推荐文案时，可以从“快速”切入。例如，对于指纹支付业务，支付频率规则对应的推荐文案可以配置为“开通指纹支付，支付快人一步”。
第四种，预设规则可以包括用户属性规则，用户属性规则用于对用户类型进行筛选。此时，特征信息可以包括用户使用的用户终端的机型。相应地，此时，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括将特征信息与用户属性规则进行匹配。将特征信息与用户属性规则进行匹配具体包括：根据所 述用户使用的用户终端的机型判断所述用户是否属于预设用户，若所述用户属于预设用户，则判定所述特征信息与所述用户属性规则匹配成功，将预先与所述用户属性规则关联的推荐文案作为本次推荐的推荐文案，若所述用户不属于预设用户，则判定所述特征信息与所述用户属性规则匹配失败。
具体来讲，服务器可以综合用户使用的用户终端的机型以及用户的其他特征如用户的年龄、用户所在的城市、用户的支付能力等来判断该用户是否为预设用户。用户的支付能力可以为用户在当前时间之前的指定时间段内的交易金额。例如，当用户的其他特征包括用户的年龄、用户所在的城市、用户的支付能力时，可以在用户使用的用户终端的机型属于预设机型集合、用户的年龄在预设年龄范围内、用户所在的城市为一线城市且用户的支付能力超过预设金额时，判定该用户属于预设用户。其中，预设年龄范围以及预设金额可以根据实际情况设置。由于不同品牌的用户终端的不同机型的价格不同，可以预先针对每种品牌的用户终端获取价格超过预设价格阈值的机型，构建预设机型集合。
或者，在本说明书的其他实施例中，服务器也可以通过判断用户使用的用户终端的机型是否属于预设机型集合来判断用户是否属于预设用户，若用户使用的用户终端的机型属于预设机型集合，则判定该用户属于预设用户，若用户使用的用户终端的机型不属于预设机型集合，则判定该用户不属于预设用户。
在一种具体的应用场景中，对于与用户属性规则匹配的用户，可以从这类用户中使用更普遍的角度来推荐。因此，配置用户属性规则对应的推荐文案时，可以从“从众”切入。例如，对于指纹支付业务，且用户使用的用户终端为智能手机时，用户属性规则对应的推荐文案可以配置为“60％的XX手机用户都在用指纹支付，还输密码就out了！”。其中，“XX”可以为手机的品牌。
另外，当预设规则包括预先配置有优先级顺序的多条规则时，每条规则均关联有相应的推荐文案。此时，上述通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括：按照所述优先级顺序将所述特征信息依次与所述多条规则进行匹配；当所述特征信息与其中任意一条规则匹配成功时，则将匹配成功的规则对应的推荐文案作为本次推荐的推荐文案。需要说明的是，预先规则所包括的多条规则的优先级顺序可以根据实际对各规则下的推荐成功率的测试结果设置和调整。
例如，假设预设规则包括规则A、规则B和规则C，其中，规则A与预先设置的推荐文案P1关联，规则B与预先设置的推荐文案P2关联，规则C与预先设置的推荐文 案P3关联。若预先配置的优先级顺序为：规则A＞规则B＞规则C，则先将用户的特征信息与规则A进行匹配，当匹配成功时，则将推荐文案P1作为本次推荐的推荐文案，停止匹配；当匹配失败时，则继续将用户的特征信息与规则B进行匹配，当匹配成功时，则将推荐文案P2作为本次推荐的推荐文案，停止匹配；当匹配失败时，则继续将用户的特征信息与规则C进行匹配，当匹配成功时，则将推荐文案P3作为本次推荐的推荐文案，停止匹配，当匹配失败时即用户的特征信息与预设规则均不匹配时，则不对该用户进行后续推荐，此时，服务器可以向客户端反馈用于表示结束本次推荐的信息，使得客户端在接收到该信息时结束本次推荐。或者，当用户的特征信息与预设规则均不匹配时，可以将预先设置的默认文案，作为本次推荐的推荐文案。
于本说明书一实施例中，预设规则可以包括上述的场景规则、开通记录规则、支付频率规则以及用户属性规则中的两种以上。当然，在本说明书的其他实施例中，除了这几种规则以外，预设规则还可以包括其他规则，具体可以根据需要设置。
例如，当预设规则包括上述的场景规则、开通记录规则、支付频率规则以及用户属性规则中的任意两种规则时，这两种规则对应有优先级顺序，先将特征信息与其中优先级相对较高的规则进行匹配，当匹配成功时，则将该规则对应的推荐文案作为本次推荐的推荐文案，结束匹配，当匹配失败时，则将特征信息与其中优先级相对较低的另一规则进行匹配。
当预设规则包括上述的场景规则、开通记录规则、支付频率规则以及用户属性规则中的任意三种规则时，这三种规则对应有优先级顺序，则按照优先级由高到低的顺序依次将特征信息与这三种规则进行匹配。
当预设规则包括上述的场景规则、开通记录规则、支付频率规则以及用户属性规则时，这四种规则对应有优先级顺序，则按照优先级由高到低的顺序依次将特征信息与这四种规则进行匹配。按照实际测试结果的推荐成功率，作为一种可选的方式，上述场景规则、开通记录规则、支付频率规则以及用户属性规则的优先级顺序可以为：场景规则＞开通记录规则＞支付频率规则＞用户属性规则。此时，则先将特征信息与场景规则进行匹配，当匹配成功时，则将场景规则对应的推荐文案作为本次推荐的推荐文案，结束匹配；当匹配失败时，则将特征信息与开通记录规则进行匹配，当匹配成功时，则将开通记录规则对应的推荐文案作为本次推荐的推荐文案，结束匹配；当匹配失败时，则将特征信息与支付频率规则进行匹配，当匹配成功时，则将支付频率规则对应的推荐文案作为本次推荐的推荐文案，结束匹配；当匹配失败时，则将特征信息与用户属性规则进 行匹配，当匹配成功时，则将用户属性规则对应的推荐文案作为本次推荐的推荐文案，结束匹配；当匹配失败时，则结束本次推荐或是将预先设置的默认文案作为本次推荐的文案。
步骤S204，将所述推荐文案下发给所述客户端，以使所述客户端根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
通过上述步骤S203确定本次推荐的推荐文案后，服务器将推荐文案下发到客户端中，客户端基于该推荐文案展示推荐界面。推荐界面中可以显示该推荐文案以及用于开通预设支付业务的开通按钮。用户可以在推荐界面中浏览到推荐文案，若用户想要开通预设支付协议，可以通过执行触发该开通按钮的操作，开通预设支付业务，此时则表示推荐成功，若用户不想开通预设支付协议，可以选择退出推荐界面或者直接关闭客户端，此时则表示推荐失败。
于本说明书一实施例中，为了进一步完善推荐策略，提高业务推荐的成功率，本方法还包括策略调整步骤，策略调整步骤具体包括：接收所述客户端反馈的所述用户基于所述推荐界面的行为数据；基于所述行为数据对所述预设规则进行调整。
具体来讲，用户基于所述推荐界面的行为数据可以包括：用户是否点击推荐界面上显示的开通按钮、用户是否退出推荐界面、用户是否直接退出了客户端以及用户在推荐界面的停留时间等数据。
服务器基于所述行为数据对所述预设规则进行调整的具体策略可以根据实际应用设置。例如，当预设规则包括多种规则时，当给满足其中一种规则的用户进行推荐时，成功率低于预设的第一临界值，或在展示推荐界面后选择直接退出客户端的用户比例高于预设的第二临界值，则表明该规则不适用，删除该规则或对该规则进行修改。又例如，当预设规则包括场景规则、开通记录规则、支付频率规则以及用户属性规则，且优先级顺序为：场景规则＞开通记录规则＞支付频率规则＞用户属性规则，假设通过收集预设数量的用户反馈的行为数据后，表明给符合支付频率规则的用户进行推荐的成功率高于给满足开通记录规则的用户进行推荐的成功率，可以调整开通记录规则和支付频率规则的优先级顺序，即将预设规则的优先级顺序调整为：场景规则＞支付频率规则＞开通记录规则＞用户属性规则。
再例如，当用户在推荐界面的停留时间超过预设的停留时间阈值时，表明用户可能有意向开通所推荐的预设支付业务，但是可能遇到一些问题而没有完成业务的开通。此 时，服务器可以进一步发送询问指令至该用户对应的客户端，使得客户端在推荐界面中弹出一询问窗口，用于询问该用户是都遇到问题，用户可以在询问窗口输入遇到的问题，并反馈给服务器，以便于服务器在接收到问题反馈后可以帮助有意向的用户解决问题并完成预设支付业务的开通。
本说明书实施例提供的业务推荐方法，通过在合适的场景下，对具备开通条件的用户，针对用户的特征信息以及预设规则筛选推荐文案，有利于在保证不显著提高打扰率的同时，同步提高推荐的成功率。
第二方面，本说明书实施例提供了一种业务推荐方法，本实施例为客户端所执行的业务推荐方法。请参见图3，该方法包括以下步骤S301-步骤S303。
步骤S301，当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件。
本说明书实施例中，预设支付业务可以是利用生物特征信息进行支付的业务，如指纹支付业务、面容支付业务等。指纹校验和人脸识别相比较密码有较高的成功率，所以提高用户的指纹支付使用比例或面容支付使用比例有助于提高整体的支付成功率。因此，为了扩大指纹支付或指纹支付用户的覆盖率，需要向用户进行业务推荐。当然，在本说明书的其他实施例中，预设支付业务也可以是其他需要向用户推荐的支付业务。
为了增加推荐的成功率，客户端会对用户所处的场景以及所要推荐用户进行筛选。当检测到用户进入预设场景，并判定用户满足预设支付业务的开通条件时，再向服务器发送推荐请求。
本说明书实施例中，预设场景可以根据实际应用设置，在这些场景下给用户一种另外的支付方式供选择会更符合用户心智。具体来讲，预设场景可以为指定场景集合中的任意一种场景。本说明书实施例中，指定场景集合可以包括但不限于密码支付场景、补密场景和找密场景。
为了检测用户是否进入预设场景，需要对用户的相关操作进行监控。可以理解的是，对于密码支付场景，用户的相关操作为密码支付操作，即用户通过输入密码，在密码校验通过后完成支付的操作；对于补密场景，用户的相关操作为密码补设操作，即用户被系统要求补齐支付密码时，按照系统指示执行的补齐密码的操作；对于找密场景，用户的相关操作为密码找回操作，即用户点击忘记密码按钮后，按照系统指示执行的重新找回密码的操作。
具体来讲，作为一种可选的实施方式，检测用户是否进入密码支付场景的步骤包括：当检测到用户触发密码支付操作时，判断所述密码支付操作是否处于完成状态，若是，则判定所述用户进入所述密码支付场景。
需要说明的是，密码支付操作的具体过程可以包括客户端获取用户输入的支付密码，并将该支付密码发送给服务器验证，当验证通过时，完成当前支付交易，当接收到服务器反馈的验证通过指示时，表示完成支付，即密码支付操作处于完成状态。
作为一种可选的实施方式，检测用户是否进入补密场景的步骤包括：预设场景的检测步骤包括：当检测到用户触发密码补设操作时，判断所述密码补设操作是否处于完成状态，若是，则判定所述用户进入所述补密场景。
需要说明的是，对于没有设置支付密码的用户，系统会发出指示给该用户，要求该用户补齐支付密码，用户可以根据系统的提示触发密码补设操作以设置支付密码，当支付密码设置成功时，表示密码补设操作处于完成状态。
作为一种可选的实施方式，检测用户是否进入找密场景的步骤包括：当检测到用户触发密码找回操作时，判断所述找密操作是否处于完成状态，若是，则判定所述用户进入所述找密场景。
可以理解的是，用户刚刚完成密码支付时，是给用户进行推荐的好时机，密码支付本身需要用户牢记密码，并且输入时间较长，在用户刚刚完成这样一个流程时做推荐，给用户推荐一种更省时省力的选择，更符合用户心智；同理，在补密场景或找密场景中，用户刚刚经历过因为忘记密码而带来的多余操作的麻烦，此时正好是给用户提供了一个不需要记忆的方案的好时机。因此，在合适的场景下对用户进行新的支付业务推荐，用户更容易接受，有利于提高推荐的成功率。
当预设支付业务为利用生物特征信息进行支付的业务时，开通条件可以根据实际支付业务需要设置。作为一种可选的实施方式，上述步骤S301中，开通条件包括以下三种条件中的一种或多种组合：所述用户使用的用户终端支持预设的安全协议；所述用户使用的用户终端中预先录入有所述用户的生物特征信息；以及所述用户的预设支付业务处于未开通状态。
具体来讲，于本说明书的一实施例中，客户端判断用户是否满足预设支付业务的开通条件的过程可以包括：判断用户的预设支付业务是否处于开通状态，若是，则结束本次推荐，若否，则判断用户使用的用户终端是否支持预设的安全协议，若否，则结束本 次推荐，若是，则判断用户使用的用户终端中是否预先录入有用户的生物特征信息，若否，则结束本次推荐，若是，则判定用户满足预设支付业务的开通条件。需要说明的是，上述的开通状态判断步骤、安全协议判断步骤和生物特性信息录入判断步骤也可以不按照上述顺序执行，例如，也可以先执行安全协议的判断，然后再执行开通状态和生物特性信息录入的判断。
具体地，当预设支付业务具体为指纹支付业务或面容支付业务时，预设安全协议可以是IFAA协议或类似安全协议。IFAA协议或类似安全协议是支持指纹支付或面容支付的基本条件。例如，当用户终端为智能手机时，可以调用isSupported接口通过手机厂商在Framework内置的状态位来判断该手机是否支持IFAA协议。
具体地，用户在用户终端中预先录入的生物特征信息如指纹信息或人脸信息会存储在用户终端的特定位置。用户可以通过系统提供的接口来判断用户终端中的特定位置是否存储有用户的生物特征信息。当然，所存储的生物特征信息应与预设支付业务对应，例如，当预设支付业务为指纹支付业务时，生物特征信息为指纹信息，当预设支付业务为面容支付业务时，生物特征信息为人脸信息。
步骤S302，当满足所述开通条件时，向服务器发送推荐请求，以使得所述服务器基于所述推荐请求，获取所述用户的特征信息，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案。
可以理解的是，推荐请求中包括用户的身份信息，例如可以是用户的账号信息或其他的身份信息，以便于服务器可以根据用户的身份信息查找该用户的特征信息。本说明书实施例中，用户的特征信息可以包括但不限于用户所用用户终端的设备、之前是否有开通记录、使用频率。例如，用户的特征信息还可以包括用户的年龄以及所在城市等。
具体来讲，服务器通过将特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案的实施方式可以参考上述第一方面提供的业务推荐方法中步骤S203的具体实施方式，此处不再赘述。
步骤S303，接收所述服务器下发的所述推荐文案，并根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
推荐界面中可以显示该推荐文案以及用于开通预设支付业务的开通按钮。用户可以在推荐界面中浏览到推荐文案，若用户想要开通预设支付协议，可以通过执行触发该开通按钮的操作，开通预设支付业务，此时则表示推荐成功，若用户不想开通预设支付协 议，可以选择退出推荐界面或者直接关闭客户端，此时则表示推荐失败。
于本说明书一实施例中，为了进一步完善推荐策略，提高业务推荐的成功率，在根据所述推荐文案向所述用户展示推荐界面之后，本方法还可以包括：获取所述用户基于所述推荐界面的行为数据，将所述行为数据反馈给所述服务器，以使得所述服务器基于所述行为数据对所述预设规则进行调整。
具体来讲，用户基于所述推荐界面的行为数据可以包括：用户是否点击推荐界面上显示的开通按钮、用户是否退出推荐界面、用户是否直接退出了客户端以及用户在推荐界面的停留时间等数据。服务器基于所述行为数据对所述预设规则进行调整的具体策略可以根据实际应用设置。
于本说明书一实施例中，为了控制打扰率在合理的范围，可以遵循预设的推荐疲劳策略。具体来讲，作为一种可选的实施方式，在判定用户满足预设支付业务的开通条件时，在客户端向服务器发送推荐请求之前，本业务推荐方法还包括：获取所述用户对应的历史推荐记录，判断所述历史推荐记录是否满足预设条件，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
具体地，历史推荐记录可以包括：第一推荐次数和/或第二推荐次数。其中，第一推荐次数为第一目标时间段内对该用户进行预设支付业务推荐的次数，第二推荐次数为第二目标时间段内对该用户进行预设支付业务推荐的次数，且第一目标时间段的时间长度小于第二目标时间段的时间长度，具体根据需要设置。例如，第一目标时间段可以是当前时间之前的七天内，第二目标时间段可以是当前时间之前的一年内。
当历史推荐记录包括第一推荐次数和第二推荐次数时，判断所述历史推荐记录是否满足预设条件可以具体包括：判断第一推荐次数是否小于或等于预设的第一次数阈值，若小于或等于预设的第一次数阈值，则判断第二推荐次数是否小于或等于预设的第二次数阈值，若小于或等于预设的第二次数阈值，则判定历史推荐记录满足预设条件；若第一推荐次数大于预设的第一次数阈值或第二推荐次数大于预设的第二次数阈值，则判定历史推荐记录不满足预设条件。
其中，第一次数阈值和第二次数阈值可以根据实际需要设置。例如，第一次数阈值可以设置为零，第二次数阈值可以设置为5，这样就可以保证用户在第一目标时间段内不被重复推荐，在第二目标时间段内被推荐次数不超过5次，以便于将打扰率控制在合理的范围。
作为一种可选的实施方式，在判定用户满足预设支付业务的开通条件时，在客户端向服务器发送推荐请求之前，本业务推荐方法还可以包括：检测所在的用户终端中是否有在预设时间段内关闭目标功能的历史记录，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
其中，预设时间段可以根据实际需要设置，例如可以设置为当前时间之前的60天内。目标功能与预设支付业务对应，例如，当预设支付业务为指纹支付业务时，目标功能为用户终端的指纹识别功能，以iOS系统为例，目标功能可以为TouchID；当预设支付业务为面容支付业务时，目标功能为用户终端的人脸识别功能，以iOS系统为例，目标功能可以为FaceID。
可以理解的是，用户主动关闭目标功能表明了用户的一种意愿，出于某种原因用户不愿意再使用目标功能，因此，为了避免影响用户体验，需要停止对该用户进行预设支付业务推荐。
本说明书实施例提供的业务推荐方法，通过在合适的场景下，对具备开通条件的用户，针对用户的特征信息以及预设规则筛选推荐文案，有利于在保证不显著提高打扰率的同时，同步提高推荐的成功率。
第三方面，本说明书实施例提供了一种业务推荐方法，本实施例为客户端所执行的业务推荐方法。请参见图4，该方法包括以下步骤S401-步骤S402。
步骤S401，当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件，其中，所述预设场景为密码支付场景、补密场景或找密场景。
其中，预设场景可以为指定场景集合中的任意一种场景。本说明书实施例中，指定场景集合可以包括密码支付场景、补密场景和找密场景。
为了检测用户是否进入预设场景，需要对用户的相关操作进行监控。可以理解的是，对于密码支付场景，用户的相关操作为密码支付操作，即用户通过输入密码，在密码校验通过后完成支付的操作；对于补密场景，用户的相关操作为密码补设操作，即用户被系统要求补齐支付密码时，按照系统指示执行的补齐密码的操作；对于找密场景，用户的相关操作为密码找回操作，即用户点击忘记密码按钮后，按照系统指示执行的重新找回密码的操作。
具体来讲，作为一种可选的实施方式，检测用户是否进入密码支付场景的步骤包括：当检测到用户触发密码支付操作时，判断所述密码支付操作是否处于完成状态， 若是，则判定所述用户进入所述密码支付场景。
需要说明的是，密码支付操作的具体过程可以包括客户端获取用户输入的支付密码，并将该支付密码发送给服务器验证，当验证通过时，完成当前支付交易，当接收到服务器反馈的验证通过指示时，表示完成支付，即密码支付操作处于完成状态。
作为一种可选的实施方式，检测用户是否进入补密场景的步骤包括：预设场景的检测步骤包括：当检测到用户触发密码补设操作时，判断所述密码补设操作是否处于完成状态，若是，则判定所述用户进入所述补密场景。
需要说明的是，对于没有设置支付密码的用户，系统会发出指示给该用户，要求该用户补齐支付密码，用户可以根据系统的提示触发密码补设操作以设置支付密码，当支付密码设置成功时，表示密码补设操作处于完成状态。
作为一种可选的实施方式，检测用户是否进入找密场景的步骤包括：当检测到用户触发密码找回操作时，判断所述找密操作是否处于完成状态，若是，则判定所述用户进入所述找密场景。
需要说明的是，当用户通过密码支付的方式进行支付时，需要用户输入支付密码，若用户忘记支付密码，可以通过触发密码找回操作来找回或重置密码，具体过程可以按照系统的相关指示执行相应操作，例如，答复预先设置的问题等，当密码找回成功时，表示密码找回操作处于完成状态。
可以理解的是，用户刚刚完成密码支付时，是给用户进行推荐的好时机，密码支付本身需要用户牢记密码，并且输入时间较长，在用户刚刚完成这样一个流程时做推荐，给用户推荐一种更省时省力的选择，更符合用户心智；同理，在补密场景或找密场景中，用户刚刚经历过因为忘记密码而带来的多余操作的麻烦，此时正好是给用户提供了一个不需要记忆的方案的好时机。因此，在合适的场景下对用户进行新的支付业务推荐，用户更容易接受，有利于提高推荐的成功率。
当预设支付业务为利用生物特征信息进行支付的业务时，开通条件可以根据实际支付业务需要设置。作为一种可选的实施方式，上述步骤S401中，开通条件包括以下三种条件中的一种或多种组合：所述用户使用的用户终端支持预设的安全协议；所述用户使用的用户终端中预先录入有所述用户的生物特征信息；以及所述用户的预设支付业务处于未开通状态。具体来讲，判断用户是否满足预设支付业务的开通条件的实施方式可以参照上述第一方面中的相关描述，此处不再赘述。
步骤S402，当满足所述开通条件时，向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
本说明书实施例中，当用户进入预设场景且满足预设支付业务的开通条件时，则表示该用户为适合进行预设支付业务推荐的目标用户，进而向该用户进行预设支付业务推荐。
具体来讲，向目标用户进行预设支付业务推荐的方式可以有多种。作为一种可选的实施方式，客户端可以向该用户展示预先设置的推荐界面。推荐界面中展示有预先设置的关于预设支付业务的相关描述以及用于开通预设支付业务的开通按钮。
作为另一种可选的实施方式，客户端可以向服务器发送推荐请求，该推荐请求中包含有用户的身份信息，例如可以是用户的账号信息或其他的身份信息，服务器基于接收到的推荐请求，获取用户的特征信息，通过将特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案，并将该推荐文案反馈给客户端，客户端根据该推荐文案向用户展示推荐界面。具体过程可以参照上述第一方面提供的业务推荐方法中的相应描述，此处不再赘述。
于本说明书一实施例中，为了控制打扰率在合理的范围，可以遵循预设的推荐疲劳策略。具体来讲，作为一种可选的实施方式，在判定用户满足预设支付业务的开通条件时，在向所述用户展示推荐界面之前，本业务推荐方法还包括：获取所述用户对应的历史推荐记录，判断所述历史推荐记录是否满足预设条件，若是，则执行向所述用户展示推荐界面的步骤，若否，则停止本次推荐。其中，获取所述用户对应的历史推荐记录，判断所述历史推荐记录是否满足预设条件的具体过程可以参照上述第二方面提供的业务推荐方法中的相关描述，此处不再赘述。
本说明书实施例提供的业务推荐方法，通过在合适的场景下，对具备开通条件的用户推荐预设支付业务，有利于提高推荐的成功率。
第四方面，基于与前述第一方面提供的实施例中业务推荐方法同样的发明构思，本说明书实施例还提供了一种业务推荐装置，本实施例提供的装置可运行于服务器。请参考图5，该业务推荐装置50可以包括：
接收模块51，用于接收客户端发送的推荐请求，所述推荐请求是所述客户端在检测到用户进入预设场景，并判定所述用户满足预设支付业务的开通条件时发送的；
获取模块52，用于基于所述推荐请求获取所述用户的特征信息；
确定模块53，用于通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；
文案发送模块54，用于将所述推荐文案下发给所述客户端，以使所述客户端根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
作为一种可选的实施方式，所述预设规则包括预先配置有优先级的多条规则，每条规则均对应有推荐文案，所述确定模块53具体用于：按照所述优先级顺序将所述特征信息依次与所述多条规则进行匹配；当所述特征信息与其中任意一条规则匹配成功时，则将匹配成功的规则对应的推荐文案作为本次推荐的推荐文案。
作为一种可选的实施方式，所述特征信息包括所述用户当前所处的场景信息，所述预设规则包括场景规则，所述确定模块53包括：第一匹配子模块531，用于判断所述用户当前所处的场景信息是否属于指定场景，若是，则判定所述特征信息与所述场景规则匹配成功，将预先与所述场景规则关联的推荐文案作为本次推荐的推荐文案。
作为一种可选的实施方式，所述特征信息包括标识信息，所述标识信息用于表示所述用户是否具有所述预设支付业务的历史开通记录，所述确定模块53包括：第二匹配子模块532，用于根据所述标识信息判断所述用户是否具有所述预设支付业务的历史开通记录，若是，则判定所述特征信息与所述开通记录规则匹配成功，将预先与所述开通记录规则关联的推荐文案作为本次推荐的推荐文案。
作为一种可选的实施方式，所述特征信息包括所述用户使用所述客户端进行支付的频率，所述预设规则包括支付频率规则，所述确定模块53包括：第三匹配子模块533，用于判断所述频率是否超过预设阈值，若是，则判定所述特征信息与所述支付频率规则匹配成功，将预先与所述支付频率规则关联的推荐文案作为本次推荐的推荐文案。
作为一种可选的实施方式，所述特征信息包括所述用户使用的用户终端的机型，所述预设规则包括用户属性规则，所述确定模块53包括：第四匹配子模块534，用于根据所述用户使用的用户终端的机型判断所述用户是否属于预设用户，若是，则判定所述特征信息与所述用户属性规则匹配成功，将预先与所述用户属性规则关联的推荐文案作为本次推荐的推荐文案。
作为一种可选的实施方式，所述装置还包括：调整模块55，用于接收所述客户端反馈的所述用户基于所述推荐界面的行为数据；基于所述行为数据对所述预设规则进 行调整。
需要说明的是，本说明书实施例所提供的业务推荐装置50，其中各个单元执行操作的具体方式已经在上述第一方面提供的方法实施例中进行了详细描述，此处将不做详细阐述说明。
第五方面，基于与前述第二方面提供的实施例中业务推荐方法同样的发明构思，本说明书实施例还提供了一种业务推荐装置，本实施例提供的装置可运行于客户端。请参考图6，该业务推荐装置60可以包括：
判断模块61，用于当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件；
请求发送模块62，用于当满足所述开通条件时，所述客户端向服务器发送推荐请求，以使得所述服务器基于所述推荐请求，获取所述用户的特征信息，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；
展示模块63，用于接收所述服务器下发的所述推荐文案，并根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
作为一种可选的实施方式，所述预设支付业务为利用生物特征信息进行支付的业务，所述开通条件包括以下条件中的一种或多种组合：所述用户使用的用户终端支持预设的安全协议；所述用户使用的用户终端中预先录入有所述用户的生物特征信息；以及所述用户的预设支付业务处于未开通状态。
作为一种可选的实施方式，所述装置还包括：反馈模块，用于获取所述用户基于所述推荐界面的行为数据，将所述行为数据反馈给所述服务器，以使得所述服务器基于所述行为数据对所述预设规则进行调整。
作为一种可选的实施方式，所述装置还包括：第一过滤模块，用于获取所述用户对应的历史推荐记录，判断所述历史推荐记录是否满足预设条件，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
作为一种可选的实施方式，所述装置还包括：第二过滤模块，用于检测所在的用户终端中是否有在预设时间段内关闭目标功能的历史记录，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
作为一种可选的实施方式，所述预设场景为密码支付场景、补密场景或找密场 景。
需要说明的是，本说明书实施例所提供的业务推荐装置60，其中各个单元执行操作的具体方式已经在上述第二方面提供的方法实施例中进行了详细描述，此处将不做详细阐述说明。
第六方面，基于与前述第三方面提供的实施例中业务推荐方法同样的发明构思，本说明书实施例还提供了一种业务推荐装置，本实施例提供的装置可运行于客户端。请参考图7，该业务推荐装置70可以包括：
检测模块71，用于当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件，其中，所述预设场景为密码支付场景、补密场景或找密场景；
推荐模块72，用于当满足所述开通条件时，向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
作为一种可选的实施方式，当所述预设场景为密码支付场景时，所述检测模块71具体用于：当检测到用户触发密码支付操作时，判断所述密码支付操作是否处于完成状态，若是，则判定所述用户进入所述密码支付场景。
作为一种可选的实施方式，当所述预设场景为补密场景时，所述检测模块71具体用于：当检测到用户触发密码补设操作时，判断所述密码补设操作是否处于完成状态，若是，则判定所述用户进入所述补密场景。
作为一种可选的实施方式，当所述预设场景为找密场景时，所述检测模块71具体用于：当检测到用户触发密码找回操作时，判断所述找密操作是否处于完成状态，若是，则判定所述用户进入所述找密场景。
需要说明的是，本说明书实施例所提供的业务推荐装置70，其中各个单元执行操作的具体方式已经在上述第二方面提供的方法实施例中进行了详细描述，此处将不做详细阐述说明。
第七方面，基于同一发明构思，本发明还提供一种电子设备，如图8所示，包括存储器804、一个或多个处理器802及存储在存储器804上并可在处理器802上运行的计算机程序。当该电子设备作为服务器时，所述处理器802执行所述程序时实现前文第一方面提供的实施例中业务推荐方法的步骤。当该电子设备作为用户终端时，所述处理器802执行所述程序时实现前文第二方面提供的实施例中业务推荐方法的步骤，或者实现前文第三方面提供的实施例中业务推荐方法的步骤。
其中，在图8中，总线架构(用总线800来代表)，总线800可以包括任意数量的互联的总线和桥，总线800将包括由处理器802代表的一个或多个处理器和存储器804代表的存储器的各种电路链接在一起。总线800还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路链接在一起，这些都是本领域所公知的，因此，本文不再对其进行进一步描述。总线接口805在总线800和接收器801和发送器803之间提供接口。接收器801和发送器803可以是同一个元件，即收发机，提供用于在传输介质上与各种其他装置通信的单元。处理器802负责管理总线800和通常的处理，而存储器804可以被用于存储处理器802在执行操作时所使用的数据。
可以理解的是，图8所示的结构仅为示意，上述电子设备还可包括比图8中所示更多或者更少的组件，或者具有与图8所示不同的配置。图8中所示的各组件可以采用硬件、软件或其组合实现。
第八方面，基于与前述第一方面提供的实施例中业务推荐方法同样的发明构思，本发明还提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现前文第一方面提供的实施例中业务推荐方法的步骤。
第九方面，基于与前述第二方面提供的实施例中业务推荐方法同样的发明构思，本发明还提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现前文第二方面提供的实施例中业务推荐方法的步骤。
第十方面，基于与前述第二方面提供的实施例中业务推荐方法同样的发明构思，本发明还提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现前文第三方面提供的实施例中业务推荐方法的步骤。
本说明书是参照根据本说明书实施例的方法、设备、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的设备。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括 指令设备的制造品，该指令设备实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本说明书的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本说明书范围的所有变更和修改。
显然，本领域的技术人员可以对本说明书进行各种改动和变型而不脱离本说明书的精神和范围。这样，倘若本说明书的这些修改和变型属于本说明书权利要求及其等同技术的范围之内，则本说明书也意图包含这些改动和变型在内。

Claims (36)

  1. 一种业务推荐方法，包括：
    接收客户端发送的推荐请求，所述推荐请求是所述客户端在检测到用户进入预设场景，并判定所述用户满足预设支付业务的开通条件时发送的；
    基于所述推荐请求获取所述用户的特征信息；
    通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；
    将所述推荐文案下发给所述客户端，以使所述客户端根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
  2. 根据权利要求1所述的方法，所述预设规则包括预先配置有优先级的多条规则，每条规则均对应有推荐文案，所述通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括：
    按照所述优先级顺序将所述特征信息依次与所述多条规则进行匹配；
    当所述特征信息与其中任意一条规则匹配成功时，则将匹配成功的规则对应的推荐文案作为本次推荐的推荐文案。
  3. 根据权利要求1所述的方法，所述特征信息包括所述用户当前所处的场景信息，所述预设规则包括场景规则，所述通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括：
    判断所述用户当前所处的场景信息是否属于指定场景，若是，则判定所述特征信息与所述场景规则匹配成功，将预先与所述场景规则关联的推荐文案作为本次推荐的推荐文案。
  4. 根据权利要求1所述的方法，所述特征信息包括标识信息，所述标识信息用于表示所述用户是否具有所述预设支付业务的历史开通记录，所述预设规则包括开通记录规则，所述通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括：
    根据所述标识信息判断所述用户是否具有所述预设支付业务的历史开通记录，若是，则判定所述特征信息与所述开通记录规则匹配成功，将预先与所述开通记录规则关联的推荐文案作为本次推荐的推荐文案。
  5. 根据权利要求1所述的方法，所述特征信息包括所述用户使用所述客户端进行支付的频率，所述预设规则包括支付频率规则，所述通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括：
    判断所述频率是否超过预设阈值，若是，则判定所述特征信息与所述支付频率规则匹配成功，将预先与所述支付频率规则关联的推荐文案作为本次推荐的推荐文案。
  6. 根据权利要求1所述的方法，所述特征信息包括所述用户使用的用户终端的机型，所述预设规则包括用户属性规则，所述通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案包括：
    根据所述用户使用的用户终端的机型判断所述用户是否属于预设用户，若是，则判定所述特征信息与所述用户属性规则匹配成功，将预先与所述用户属性规则关联的推荐文案作为本次推荐的推荐文案。
  7. 根据权利要求1所述的方法，还包括：
    接收所述客户端反馈的所述用户基于所述推荐界面的行为数据；
    基于所述行为数据对所述预设规则进行调整。
  8. 一种业务推荐方法，包括：
    当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件；
    当满足所述开通条件时，向服务器发送推荐请求，以使得所述服务器基于所述推荐请求，获取所述用户的特征信息，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；
    接收所述服务器下发的所述推荐文案，并根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
  9. 根据权利要求8所述的方法，所述预设支付业务为利用生物特征信息进行支付的业务，所述开通条件包括以下条件中的一种或多种组合：
    所述用户使用的用户终端支持预设的安全协议；
    所述用户使用的用户终端中预先录入有所述用户的生物特征信息；以及
    所述用户的预设支付业务处于未开通状态。
  10. 根据权利要求8所述的方法，所述根据所述推荐文案向所述用户展示推荐界面之后，还包括：
    获取所述用户基于所述推荐界面的行为数据，将所述行为数据反馈给所述服务器，以使得所述服务器基于所述行为数据对所述预设规则进行调整。
  11. 根据权利要求8所述的方法，所述向服务器发送推荐请求之前，还包括：
    获取所述用户对应的历史推荐记录，判断所述历史推荐记录是否满足预设条件，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
  12. 根据权利要求8所述的方法，所述向服务器发送推荐请求之前，还包括：
    检测所在的用户终端中是否有在预设时间段内关闭目标功能的历史记录，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
  13. 根据权利要求8所述的方法，所述预设场景为密码支付场景、补密场景或找密场景。
  14. 一种业务推荐方法，包括：
    当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件，其中，所述预设场景为密码支付场景、补密场景或找密场景；
    当满足所述开通条件时，向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
  15. 根据权利要求14所述的方法，当所述预设场景为密码支付场景时，所述预设场景的检测步骤包括：
    当检测到用户触发密码支付操作时，判断所述密码支付操作是否处于完成状态，若是，则判定所述用户进入所述密码支付场景。
  16. 根据权利要求14所述的方法，当所述预设场景为补密场景时，所述预设场景的检测步骤包括：
    当检测到用户触发密码补设操作时，判断所述密码补设操作是否处于完成状态，若是，则判定所述用户进入所述补密场景。
  17. 根据权利要求14所述的方法，当所述预设场景为找密场景时，所述预设场景的检测步骤包括：
    当检测到用户触发密码找回操作时，判断所述找密操作是否处于完成状态，若是，则判定所述用户进入所述找密场景。
  18. 一种业务推荐装置，应用于服务器，包括：
    接收模块，用于接收客户端发送的推荐请求，所述推荐请求是所述客户端在检测到用户进入预设场景，并判定所述用户满足预设支付业务的开通条件时发送的；
    获取模块，用于基于所述推荐请求获取所述用户的特征信息；
    确定模块，用于通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；
    文案发送模块，用于将所述推荐文案下发给所述客户端，以使所述客户端根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
  19. 根据权利要求18所述的装置，所述预设规则包括预先配置有优先级的多条规 则，每条规则均对应有推荐文案，所述确定模块具体用于：
    按照所述优先级顺序将所述特征信息依次与所述多条规则进行匹配；
    当所述特征信息与其中任意一条规则匹配成功时，则将匹配成功的规则对应的推荐文案作为本次推荐的推荐文案。
  20. 根据权利要求18所述的装置，所述特征信息包括所述用户当前所处的场景信息，所述预设规则包括场景规则，所述确定模块包括：
    第一匹配子模块，用于判断所述用户当前所处的场景信息是否属于指定场景，若是，则判定所述特征信息与所述场景规则匹配成功，将预先与所述场景规则关联的推荐文案作为本次推荐的推荐文案。
  21. 根据权利要求18所述的装置，所述特征信息包括标识信息，所述标识信息用于表示所述用户是否具有所述预设支付业务的历史开通记录，所述确定模块包括：
    第二匹配子模块，用于根据所述标识信息判断所述用户是否具有所述预设支付业务的历史开通记录，若是，则判定所述特征信息与所述开通记录规则匹配成功，将预先与所述开通记录规则关联的推荐文案作为本次推荐的推荐文案。
  22. 根据权利要求18所述的装置，所述特征信息包括所述用户使用所述客户端进行支付的频率，所述预设规则包括支付频率规则，所述确定模块包括：
    第三匹配子模块，用于判断所述频率是否超过预设阈值，若是，则判定所述特征信息与所述支付频率规则匹配成功，将预先与所述支付频率规则关联的推荐文案作为本次推荐的推荐文案。
  23. 根据权利要求18所述的装置，所述特征信息包括所述用户使用的用户终端的机型，所述预设规则包括用户属性规则，所述确定模块包括：
    第四匹配子模块，用于根据所述用户使用的用户终端的机型判断所述用户是否属于预设用户，若是，则判定所述特征信息与所述用户属性规则匹配成功，将预先与所述用户属性规则关联的推荐文案作为本次推荐的推荐文案。
  24. 根据权利要求18所述的装置，还包括：
    调整模块，用于接收所述客户端反馈的所述用户基于所述推荐界面的行为数据；基于所述行为数据对所述预设规则进行调整。
  25. 一种业务推荐装置，应用于客户端，包括：
    判断模块，用于当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件；
    请求发送模块，用于当满足所述开通条件时，所述客户端向服务器发送推荐请求， 以使得所述服务器基于所述推荐请求，获取所述用户的特征信息，通过将所述特征信息与预先关联有推荐文案的预设规则进行匹配，确定本次推荐的推荐文案；
    展示模块，用于接收所述服务器下发的所述推荐文案，并根据所述推荐文案向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
  26. 根据权利要求25所述的装置，所述预设支付业务为利用生物特征信息进行支付的业务，所述开通条件包括以下条件中的一种或多种组合：
    所述用户使用的用户终端支持预设的安全协议；
    所述用户使用的用户终端中预先录入有所述用户的生物特征信息；以及
    所述用户的预设支付业务处于未开通状态。
  27. 根据权利要求25所述的装置，还包括：
    反馈模块，用于获取所述用户基于所述推荐界面的行为数据，将所述行为数据反馈给所述服务器，以使得所述服务器基于所述行为数据对所述预设规则进行调整。
  28. 根据权利要求25所述的装置，还包括：
    第一过滤模块，用于获取所述用户对应的历史推荐记录，判断所述历史推荐记录是否满足预设条件，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
  29. 根据权利要求25所述的装置，还包括：
    第二过滤模块，用于检测所在的用户终端中是否有在预设时间段内关闭目标功能的历史记录，若是，则执行向服务器发送推荐请求的步骤，若否，则停止本次推荐。
  30. 根据权利要求25所述的装置，所述预设场景为密码支付场景、补密场景或找密场景。
  31. 一种业务推荐装置，包括：
    检测模块，用于当检测到用户进入预设场景时，判断所述用户是否满足预设支付业务的开通条件，其中，所述预设场景为密码支付场景、补密场景或找密场景；
    推荐模块，用于当满足所述开通条件时，向所述用户展示推荐界面，所述推荐界面用于向所述用户推荐所述预设支付业务。
  32. 根据权利要求31所述的装置，当所述预设场景为密码支付场景时，所述检测模块具体用于：
    当检测到用户触发密码支付操作时，判断所述密码支付操作是否处于完成状态，若是，则判定所述用户进入所述密码支付场景。
  33. 根据权利要求31所述的装置，当所述预设场景为补密场景时，所述检测模块具体用于：
    当检测到用户触发密码补设操作时，判断所述密码补设操作是否处于完成状态，若是，则判定所述用户进入所述补密场景。
  34. 根据权利要求31所述的装置，当所述预设场景为找密场景时，所述检测模块具体用于：
    当检测到用户触发密码找回操作时，判断所述找密操作是否处于完成状态，若是，则判定所述用户进入所述找密场景。
  35. 一种电子设备，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权利要求1-17中任一项所述方法的步骤。
  36. 一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现权利要求1-17中任一项所述方法的步骤。
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