Artificial intelligence unmanned cashier system

Abstract

The invention discloses an artificial intelligence unmanned cashier system, and belongs to the technical field of cashier supervision. The method is used for solving the technical problems that in an existing scheme, the active acquisition management effect of unmanned cashier for member handling is poor, and the active service optimization management effect for member continuous use is poor. According to the method, periodic data analysis in different aspects is carried out on existing member registration acquisition data of the unmanned cashier, an existing member registration acquisition scheme is dynamically managed in a self-adaptive manner according to an analysis result, and settlement habits of existing registered members of the unmanned cashier are periodically supervised. Member use state data analysis in different aspects is carried out on settlement habit supervision data, and dynamic management is carried out on an existing member viscosity maintenance scheme in a self-adaptive manner according to member use analysis data in different aspects; the method achieves the periodic supervision analysis and dynamic management of the member viscosity maintenance effect of an existing member viscosity maintenance scheme.

Description

Technical Field

[0001] The present invention relates to the technical field of cashier supervision, and in particular to an artificial intelligence unmanned cashier system. Background Art

[0002] The unmanned cashier system is a new retail solution achieved by integrating multiple advanced technologies, allowing customers to complete the shopping and payment process without human intervention.

[0003] The existing unmanned checkout solutions, when implemented, still remain at a single settlement. They cannot implement targeted membership acquisition prompts and management for settlements of users who have not signed up for membership, nor can they implement targeted supervision and service optimization management for settlement services of already signed up members. As a result, users cannot actively apply for membership and increase the frequency of members' frequent shopping. The unmanned checkout's active acquisition management for member applications is not effective, as is the active service optimization management for members' continued use. Summary of the invention

[0004] The purpose of the present invention is to provide an artificial intelligence unmanned cashier system to solve the technical problems in existing solutions that unmanned cashier has poor active acquisition management effect for member processing and poor active service optimization management effect for members' continuous use.

[0005] The purpose of the present invention can be achieved through the following technical solutions: Artificial intelligence unmanned cashier system, including: The unmanned cashier supervision and statistical processing module is used to prompt and confirm the identities of different users when settling accounts, and adaptively provide users with matching settlement service plans and data statistics based on the user's determination; The unmanned cashier member registration supervision module is used to perform periodic data analysis on the existing member registration acquisition data of the unmanned cashier in different aspects, and dynamically manage the existing member registration acquisition scheme adaptively based on the analysis results; Among them, the existing member registration acquisition data of the unmanned cashier is processed in terms of growth, and the corresponding acquisition implementation value of the existing member registration acquisition is obtained, and the existing member registration acquisition data of the unmanned cashier is processed in terms of growth change, and the corresponding acquisition effect value of the existing member registration acquisition is obtained; Integrate and analyze the acquired acquisition implementation value and acquisition effect value to obtain the member acquisition status corresponding to the supervision cycle, and maintain the subsequent implementation of the existing member registration acquisition plan based on the member acquisition status obtained through analysis, or adjust the existing member registration acquisition plan; The unmanned cashier member utilization supervision module is used to periodically supervise the settlement habits of existing registered members of the unmanned cashier, and conduct member usage status data analysis in different aspects on the settlement habit supervision data, and adaptively and dynamically manage the existing member stickiness maintenance plan based on different aspects of member usage analysis data; including maintaining the subsequent implementation of the existing member stickiness maintenance plan, or adjusting the existing member stickiness maintenance plan.

[0006] Preferably, when the user settles the account, a prompt is given as to whether the user is a member. If the user confirms that he is not a member, a prompt is given to register as a member. If the user chooses not to register as a member for settlement, the user is redirected to the ordinary user settlement page, and the total number of failed membership acquisitions is increased by one. If the user chooses to register as a member for settlement, the page will jump to the member registration page. After the user fills in the information to complete the member registration, the page will jump to the member settlement page, and the total number of successful membership acquisitions will be increased by one.

[0007] Preferably, when processing the growth data of the existing member registration data of the unmanned cashier, the total number of newly added registered members in the unmanned cashier process during the supervision period is counted, and the total number of newly added registered members in the unmanned cashier process is calculated by the formula Calculate and obtain the corresponding acquisition implementation value CS for existing member registrations; where NZ is the total number of newly registered members in the unmanned checkout process during the supervision period; NJ is the total number of settlements in the unmanned checkout process during the supervision period; NH is the total number of members settled in the unmanned checkout process during the supervision period; A is the acquisition implementation design value corresponding to the supervision period.

[0008] Preferably, when processing the growth change of the existing member registration acquisition data of the unmanned cashier, the calculated acquisition implementation value is calculated by the formula Calculate and obtain the acquisition effect value XC corresponding to the existing member registration acquisition; where CS' is the acquisition implementation value calculated and obtained corresponding to the previous monitoring cycle; B is the acquisition effect design value.

[0009] Preferably, when data analysis is performed on the member acquisition status corresponding to the unmanned cashier within the supervision period, the acquisition implementation value and the acquisition effect value processed and acquired within the supervision period are analyzed through the member acquisition status recognition model, and the member acquisition status identifier ZH corresponding to the supervision period is output; Among them, the expression of the member acquisition status recognition model is: .

[0010] Preferably, according to the member acquisition status identifier with a value of 0, the existing member registration acquisition scheme is associated with a member acquisition status normal tag in the current supervision cycle; And, according to CS<1 or XC<1, the existing member registration acquisition plan is associated with a member acquisition status slightly abnormal label in the current supervision cycle; According to CS<1 and XC<1, the existing member registration acquisition plan is associated with the member acquisition status severe abnormality label in the current supervision cycle; Maintain the subsequent implementation of the existing member registration and acquisition plan based on the normal member acquisition status label, and adjust the existing member registration and acquisition plan based on the severe abnormal member acquisition status label.

[0011] Preferably, the subsequent implementation effect of the existing member registration acquisition scheme is observed and processed according to the member acquisition status slightly abnormal label, and the member acquisition status labels corresponding to the subsequent N supervision cycles are processed and counted, and the formula is used to calculate the member acquisition status labels corresponding to the subsequent N supervision cycles. Calculate the observed value SG of the implementation effect; where N1 and N2 are the total number of mildly abnormal labels of member acquisition status and the total number of severely abnormal labels of member acquisition status, respectively; α is the error correction factor, and is a real number greater than 1; is the floor rounding function; If the observed value of the implementation effect is 0, the subsequent implementation of the existing member registration acquisition plan will be maintained; If the observed value of the implementation effect is not 0, the existing member registration acquisition plan will be adjusted.

[0012] Preferably, when the settlement habits of all settlement members within the supervision period are supervised, the clearable points corresponding to the settlement members are obtained, and whether the points redemption conditions are met according to the clearable points. If the clearable points meet the points redemption conditions and the member clicks on the points during the settlement process, the total number of members using the benefits is increased by one; If the settleable points meet the points redemption conditions and the member does not click to use the points during the settlement process, the total number of members whose benefits have not been used will be increased by one.

[0013] Preferably, the total number of members using the member benefits and the total number of members not using the member benefits are calculated by the formula Calculate and obtain the local maintenance value WJ corresponding to the existing member stickiness maintenance plan; where NS and NW are the total number of members who use and the total number of members who do not use their rights during the supervision period, respectively; C and D are the design values ​​used in the first period and the second period, respectively; max() means obtaining the maximum value among several real numbers.

[0014] Preferably, if the local maintenance value is greater than or equal to 1, it is determined that the local maintenance state corresponding to the existing member stickiness maintenance plan is normal, and the subsequent implementation of the existing member stickiness maintenance plan is maintained; Otherwise, it is determined that the local maintenance state corresponding to the existing member stickiness maintenance plan is abnormal, and the existing member stickiness maintenance plan is adjusted.

[0015] Compared with the existing solutions, the present invention achieves the following beneficial effects: The present invention performs periodic data analysis on different aspects of the existing member registration acquisition data of unmanned checkout, and adaptively and dynamically manages the existing member registration acquisition scheme according to the analysis results, thereby realizing periodic supervision analysis and dynamic management of the member registration acquisition effect of the existing member registration acquisition scheme, and improving the active acquisition supervision analysis effect and active optimization management effect of the unmanned checkout for member processing.

[0016] The present invention performs periodic supervision on the settlement habits of existing registered members of the unmanned cashier, and performs member usage status data analysis of different aspects on the settlement habit supervision data, and adaptively performs dynamic management on the existing member stickiness maintenance plan according to the member usage analysis data of different aspects, thereby realizing periodic supervision analysis and dynamic management of the member stickiness maintenance effect of the existing member stickiness maintenance plan, and improving the proactive service optimization management effect of the unmanned cashier for continuous use of members. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with the accompanying drawings.

[0018] Figure 1 This is a module block diagram of the artificial intelligence unmanned cashier system of the present invention.

[0019] Figure 2 This is a flowchart of the steps of operating the artificial intelligence unmanned cashier system of the present invention.

[0020] Figure 3 This is a flowchart of the data analysis of member acquisition status identification in the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] like Figure 1 to Figure 2 As shown, the present invention is an artificial intelligence unmanned cashier system, including an unmanned cashier supervision and statistical processing module, an unmanned cashier member registration supervision module and an unmanned cashier member utilization supervision module; The unmanned cashier supervision and statistical processing module is used to prompt and confirm the identities of different users during settlement, and adaptively provide users with matching settlement service plans and data statistics based on the user's determination; including: When the user settles the bill, the user is prompted whether he is a member. If the user confirms that he is not a member, he will be prompted to register as a member. If the user chooses not to register as a member for settlement, he will be redirected to the ordinary user settlement page and the total number of failed membership acquisitions will be increased by one. Among them, when the user settles the bill, he can use the self-service settlement machine to perform self-service settlement; If the user chooses to register for membership settlement, the page will jump to the membership registration page. After the user fills in the information to complete the membership registration, the page will jump to the membership settlement page, and the total number of successful membership acquisitions will increase by one; In the embodiment of the present invention, by prompting and confirming the identities of different users during settlement, and supervising and collecting data on whether users choose to register as members, reliable individual user settlement supervision data support can be provided for subsequent supervision analysis of existing member registration and acquisition schemes.

[0023] The unmanned cashier member registration supervision module is used to perform periodic data analysis on the existing member registration acquisition data of the unmanned cashier in different aspects, and dynamically manage the existing member registration acquisition scheme adaptively based on the analysis results; including: When processing the growth data of the existing member registration data of unmanned cashier, the total number of newly registered members in the unmanned cashier process during the supervision period is counted. The unit of the supervision period is month, which can be one month, and the formula Calculate and obtain the corresponding acquisition implementation value CS of the existing member registration acquisition; where NZ is the total number of newly registered members in the unmanned cashier process during the supervision period; NJ is the total number of settlements in the unmanned cashier process during the supervision period; NH is the total number of members settled in the unmanned cashier process during the supervision period; A is the acquisition implementation design value corresponding to the supervision period, which can be determined based on the preliminary test data of the unmanned cashier operation, or based on the design requirement data of the unmanned cashier operation; The acquisition implementation value is used to calculate all new registered member data of the existing member registration acquisition scheme within the supervision cycle to digitally represent the implementation status of new member acquisition within the supervision cycle; When processing the growth and change of the existing member registration data of unmanned cashier, the calculated acquisition implementation value is calculated by the formula Calculate and obtain the acquisition effect value XC corresponding to the existing member registration acquisition; where CS´ is the acquisition implementation value calculated and obtained in the previous monitoring cycle; B is the acquisition effect design value, which can be determined based on the preliminary test data of the unmanned cashier operation, or based on the design requirement data of the unmanned cashier operation; The acquisition effect value is used to calculate all new member registration data of the existing member registration acquisition scheme in the current regulatory cycle and all new member registration data in the previous regulatory cycle, so as to digitally represent the implementation status of new member acquisition in the current regulatory cycle; When performing data analysis on the member acquisition status corresponding to unmanned cashier within the supervision period, the acquisition implementation value and acquisition effect value processed and acquired within the supervision period are analyzed through the member acquisition status recognition model, and the member acquisition status identifier ZH corresponding to the supervision period is output; Among them, the expression of the member acquisition status recognition model is: ; The member acquisition status flag contains a value of 0 or 1; The member acquisition status identifier is used to integrate and calculate the new member registration supervision processing data from different aspects in the early stage, so as to digitally represent the member acquisition status corresponding to the existing member registration acquisition plan within the supervision cycle; like Figure 3 As shown, according to the member acquisition status identifier with a value of 0, the existing member registration acquisition plan is associated with the member acquisition status normal label in the current supervision cycle; And, according to CS<1 or XC<1, the existing member registration acquisition plan is associated with a member acquisition status slightly abnormal label in the current supervision cycle; According to CS<1 and XC<1, the existing member registration acquisition plan is associated with the member acquisition status severe abnormality label in the current supervision cycle; Maintain the subsequent implementation of the existing member registration acquisition plan based on the normal member acquisition status label, and adjust the existing member registration acquisition plan based on the severe abnormal member acquisition status label; It should be noted that when the existing member registration acquisition plan is associated with the member acquisition status mild abnormality label in the current supervision cycle, due to the certain errors in the single member acquisition status mild abnormality processing analysis, further data processing and analysis is required to determine the persistence and negative impact of the mild abnormality of the member acquisition status, so as to implement reliable plan management; According to the mildly abnormal member acquisition status label, the subsequent implementation effect of the existing member registration acquisition plan is observed and processed, and the member acquisition status labels corresponding to the subsequent N supervision cycles are processed and counted, where N is a positive integer, and the specific value can be 5, and the formula Calculate the observed value SG of the implementation effect; where N1 and N2 are the total number of mildly abnormal labels of member acquisition status and the total number of severely abnormal labels of member acquisition status, respectively; α is the error correction factor, and is a real number greater than 1, and the specific value can be 1.75; is the floor rounding function; Among them, the implementation effect observation value is used to integrate and calculate all member acquisition status label data obtained in the subsequent supervision and processing of the member acquisition status mild abnormality label, so as to digitally represent the stable negative impact of the existing member registration acquisition scheme corresponding to the member acquisition status mild abnormality; If the observed value of the implementation effect is 0, the subsequent implementation of the existing member registration acquisition plan will be maintained; If the observed implementation effect value is not 0, the existing member registration acquisition plan is adjusted. Specifically, the marketing content of the existing member registration prompt page can be adjusted; In the embodiment of the present invention, by performing periodic data analysis of different aspects of the existing member registration acquisition data of the unmanned checkout, and adaptively performing dynamic management of the existing member registration acquisition plan based on the analysis results, periodic supervision analysis and dynamic management of the member registration acquisition effect of the existing member registration acquisition plan are achieved, thereby improving the active acquisition supervision analysis effect and active optimization management effect of the unmanned checkout for member processing.

[0024] The unmanned cashier member utilization supervision module is used to periodically supervise the settlement habits of existing registered members of the unmanned cashier, and analyze the member usage status data in different aspects of the settlement habit supervision data, and adaptively manage the existing member stickiness maintenance plan dynamically based on the member usage analysis data in different aspects; including: When supervising the settlement habits of all settlement members within the supervision period, obtain the corresponding clearing points of the settlement members, and determine whether the points redemption conditions are met based on the clearing points. If the clearing points meet the points redemption conditions and the member clicks on the points during the settlement process, the total number of members using the benefits will be increased by one; If the settleable points meet the points redemption conditions and the member does not click to use the points during the settlement process, the total number of members who have not used their benefits will be increased by one; The total number of people using membership benefits and the total number of people not using membership benefits are calculated by the formula Calculate and obtain the local maintenance value WJ corresponding to the existing member stickiness maintenance plan; where NS and NW are the total number of members who use the member rights and interests during the supervision period and the total number of members who do not use the member rights and interests, respectively; C and D are the design values ​​for the first cycle and the second cycle, respectively, which can be determined based on the preliminary test data of the unmanned cashier operation or the design requirement data of the unmanned cashier operation; max() means obtaining the maximum value among several real numbers; If the local maintenance value is greater than or equal to 1, the local maintenance status corresponding to the existing member stickiness maintenance plan is determined to be normal, and the subsequent implementation of the existing member stickiness maintenance plan is maintained; Otherwise, it is determined that the local maintenance state corresponding to the existing member stickiness maintenance plan is abnormal, and the existing member stickiness maintenance plan is adjusted; Among them, the existing member stickiness maintenance plan will be adjusted, specifically adding new member points usage scenarios and active reminders for member points usage; In the embodiment of the present invention, the settlement habits of existing registered members of the unmanned checkout are periodically supervised, and different aspects of member usage status data analysis are performed on the settlement habit supervision data. The existing member stickiness maintenance plan is adaptively and dynamically managed based on the different aspects of member usage analysis data, thereby achieving periodic supervision, analysis and dynamic management of the member stickiness maintenance effect of the existing member stickiness maintenance plan, and improving the proactive service optimization management effect of the unmanned checkout for continuous use by members.

[0025] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0026] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0027] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0028] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0029] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. Artificial intelligence unmanned cashier system, characterized by: include: The unmanned cashier supervision and statistical processing module is used to prompt and confirm the identities of different users when settling accounts, and adaptively provide users with matching settlement service plans and data statistics based on the user's determination; The unmanned cashier member registration supervision module is used to perform periodic data analysis on the existing member registration acquisition data of the unmanned cashier in different aspects, and dynamically manage the existing member registration acquisition scheme adaptively based on the analysis results; Among them, the existing member registration acquisition data of the unmanned cashier is processed in terms of growth, and the corresponding acquisition implementation value of the existing member registration acquisition is obtained, and the existing member registration acquisition data of the unmanned cashier is processed in terms of growth change, and the corresponding acquisition effect value of the existing member registration acquisition is obtained; Integrate and analyze the acquired acquisition implementation value and acquisition effect value to obtain the member acquisition status corresponding to the supervision cycle, and maintain the subsequent implementation of the existing member registration acquisition plan based on the member acquisition status obtained through analysis, or adjust the existing member registration acquisition plan; The unmanned cashier member utilization supervision module is used to periodically supervise the settlement habits of existing registered members of the unmanned cashier, and conduct member usage status data analysis in different aspects on the settlement habit supervision data, and adaptively and dynamically manage the existing member stickiness maintenance plan based on different aspects of member usage analysis data; including maintaining the subsequent implementation of the existing member stickiness maintenance plan, or adjusting the existing member stickiness maintenance plan.

2. The artificial intelligence unmanned cashier system according to claim 1, characterized in that: When the user checks out, they will be prompted whether they are members. If the user confirms that they are not a member, they will be prompted to register as a member. If the user chooses not to register as a member, they will be redirected to the ordinary user settlement page, and the total number of failed membership acquisitions will be increased by one; If the user chooses to register as a member for settlement, the page will jump to the member registration page. After the user fills in the information to complete the member registration, the page will jump to the member settlement page, and the total number of successful membership acquisitions will be increased by one.

3. The artificial intelligence unmanned cashier system according to claim 2, characterized in that: When processing the growth data of existing member registrations for unmanned cashiers, the total number of newly added registered members during the unmanned cashier process during the supervision period is counted, and the total number of newly added registered members during the unmanned cashier process is calculated using the formula Calculate and obtain the corresponding acquisition implementation value CS for existing member registrations; where NZ is the total number of newly registered members in the unmanned checkout process during the supervision period; NJ is the total number of settlements in the unmanned checkout process during the supervision period; NH is the total number of members settled in the unmanned checkout process during the supervision period; A is the acquisition implementation design value corresponding to the supervision period.

4. The artificial intelligence unmanned cashier system according to claim 3 is characterized in that: When processing the growth and change of the existing member registration data of unmanned cashier, the calculated acquisition implementation value is calculated by the formula Calculate and obtain the acquisition effect value XC corresponding to the existing member registration acquisition; where CS' is the acquisition implementation value calculated and obtained corresponding to the previous monitoring cycle; B is the acquisition effect design value.

5. The artificial intelligence unmanned cashier system according to claim 4, characterized in that: When performing data analysis on the member acquisition status corresponding to unmanned cashier within the supervision period, the acquisition implementation value and acquisition effect value processed and acquired within the supervision period are analyzed through the member acquisition status recognition model, and the member acquisition status identifier ZH corresponding to the supervision period is output; Among them, the expression of the member acquisition status recognition model is: .

6. The artificial intelligence unmanned cashier system according to claim 5, characterized in that: According to the member acquisition status identifier with a value of 0, the existing member registration acquisition plan is associated with the member acquisition status normal label in the current supervision cycle; And, according to CS<1 or XC<1, the existing member registration acquisition plan is associated with a member acquisition status slightly abnormal label in the current supervision cycle; According to CS<1 and XC<1, the existing member registration acquisition plan is associated with the member acquisition status severe abnormality label in the current supervision cycle; Maintain the subsequent implementation of the existing member registration and acquisition plan based on the normal member acquisition status label, and adjust the existing member registration and acquisition plan based on the severely abnormal member acquisition status label.

7. The artificial intelligence unmanned cashier system according to claim 6, characterized in that: According to the mildly abnormal member acquisition status label, the subsequent implementation effect of the existing member registration acquisition plan is observed and processed, and the member acquisition status labels corresponding to the subsequent N supervision cycles are processed and counted, and the formula is used to calculate the member acquisition status labels corresponding to the subsequent N supervision cycles. Calculate the observed value SG of the implementation effect; where N1 and N2 are the total number of mildly abnormal labels of member acquisition status and the total number of severely abnormal labels of member acquisition status, respectively; α is the error correction factor, and is a real number greater than 1; is the floor rounding function; If the observed value of the implementation effect is 0, the subsequent implementation of the existing member registration acquisition plan will be maintained; If the observed value of the implementation effect is not 0, the existing member registration acquisition plan will be adjusted.

8. The artificial intelligence unmanned cashier system according to claim 2, characterized in that: When supervising the settlement habits of all settlement members within the supervision period, obtain the corresponding clearing points of the settlement members, and determine whether the points redemption conditions are met based on the clearing points. If the clearing points meet the points redemption conditions and the member clicks on the points during the settlement process, the total number of members using the benefits will be increased by one; If the settleable points meet the points redemption conditions and the member does not click to use the points during the settlement process, the total number of members whose benefits have not been used will be increased by one.

9. The artificial intelligence unmanned cashier system according to claim 8, characterized in that: The total number of people using membership benefits and the total number of people not using membership benefits are calculated by the formula Calculate and obtain the local maintenance value WJ corresponding to the existing member stickiness maintenance plan; where NS and NW are the total number of members who use and the total number of members who do not use their rights during the supervision period, respectively; C and D are the design values ​​used in the first period and the second period, respectively; max() means obtaining the maximum value among several real numbers.

10. The artificial intelligence unmanned cashier system according to claim 9, characterized in that: If the local maintenance value is greater than or equal to 1, the local maintenance status corresponding to the existing member stickiness maintenance plan is determined to be normal, and the subsequent implementation of the existing member stickiness maintenance plan is maintained; Otherwise, it is determined that the local maintenance state corresponding to the existing member stickiness maintenance plan is abnormal, and the existing member stickiness maintenance plan is adjusted.

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