Gas station major supervision risk early warning platform

Abstract

The invention discloses a gas station major supervision risk early warning platform, and relates to the field. Which comprises a retail management center part, a non-oil product center part and a commercial customer center part and is used for non-oil product management, specifically comprises coupon abnormity management and centralized entry abnormity management, and comprises over-high / low-sales-volume customer early warning management and low-sales-price customer early warning management. According to the invention, multiple functions of retail management, non-oil product management and commercial customer management can be realized, and user consumption abnormity white list management of an IC card and a petrochemical wallet can be realized under each function; carrying out early warning management on point preferential customers and barreling customers; performing single-batch recharging consumption management; performing abnormal feedback management; employee abnormal consumption behavior management; and strategic + provincial customer archives, large customer consumption gliding management, coupon abnormity management, centralized entry abnormity management, early warning management of customers with too high sales volume / low sales volume, early warning management of customers with low sales price and the like, so that all-around early warning management of the gas station is realized.

Description

Technical Field

[0001] The present invention relates to a field, and in particular to a gas station large-scale supervision risk early warning platform. Background Art

[0002] The existing gas station management system has problems such as card duplication risk, excessive network traffic, untimely video surveillance and inability to achieve comprehensive management of gas stations.

[0003] In order to solve the above problems, after searching, the Chinese patent publication number CN112714115B discloses a gas station safety management system, including: a business risk warning module, an information security warning module, a video monitoring module and a comprehensive management module, the comprehensive management module is respectively connected to the business risk warning module, the information security warning module and the video monitoring module, the comprehensive management module is used to start the video monitoring module to retrieve the monitoring video of various parts of the gas station when the business risk warning module and the information security warning module issue a warning; the business risk warning module includes a card set data acquisition unit, a cash-out data acquisition unit, a sales lag data acquisition unit and a business risk warning unit, the card set data acquisition unit is used to obtain the card set data of the gas station, and the cash-out data acquisition unit is used to obtain the cash-out data.

[0004] The above patent has the following deficiencies: its business risk warning module can only carry out early warning monitoring of card set data, etc., and its warning dimension is relatively single and has certain limitations.

[0005] To this end, the present invention proposes a gas station large-scale supervision risk early warning platform. Summary of the invention

[0006] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a gas station large-scale supervision risk early warning platform.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A gas station supervision risk early warning platform, comprising:

[0009] The Retail Management Center is used for retail management, including whitelist management of IC card and petrochemical wallet users’ consumption anomalies; early warning management of points-based preferential customers and bucket-filling customers; management of one-order-one-batch recharge consumption; abnormal feedback management; management of abnormal consumption behavior of employees; strategic + provincial customer files, and management of consumption decline of major customers;

[0010] The non-oil product center is used for non-oil product management, including coupon exception management and centralized entry exception management;

[0011] Commercial Customer Center Department, which includes early warning management for customers with excessively high / low sales volume and early warning management for customers selling at low prices.

[0012] Preferably: the IC card and petrochemical wallet user consumption abnormal whitelist management logic is:

[0013] A1: The designated retail personnel of the local branch enter the customer type, whitelist, and customer name. Customer types include gas card accounts and mobile phone numbers.

[0014] A2: The gas card account is controlled by the city where the account is opened, and the mobile phone number is controlled by the city where the account is first created;

[0015] A3: The system supports viewing records of whitelist creation and deletion reasons, creation and deletion time, and operator records.

[0016] Preferably: the early warning management of the points preferential customers and the bucket filling customers includes:

[0017] B1: Customer information. The platform captures the OA approval order information of points discount, wallet discount customers, and bucket customers in the OA system to generate a customer detail report. Customer data that cannot be extracted by the platform can be edited and viewed by organization authority.

[0018] B2: Pre-expiry warning: the system captures customers with points discounts and petrochemical wallet customers and warns them several days in advance, pushes information about customers who are about to expire via SMS on a monthly basis, and pushes information about customers who are about to expire to the retail department manager and customer maintenance management post of the local branch company. It supports querying the customer's sales volume and discount amount during the discount period, and can analyze by oil product and card type;

[0019] B3: Warning of abnormal consumption of points discount. Based on the detailed list of points discount customers, the account opening and discount application places are added. If the consumption in the discount application place accounts for less than 60%, a warning will be issued. The warning report needs to show the consumption in the discount application city and other cities and the corresponding proportion. You can choose to query on a monthly or cumulative basis.

[0020] B4: Guantong customer rebate warning, capture Guantong customer monthly consumption and compare it with the customer consumption site and customer discount range in the OA approval form. The system automatically calculates the rebate amount. The system takes the latest date of the customer discount approval time. The customer is uniquely identified by the customer code. The local branch company designates the rebate outlets and the rebate time for rebate. Capture the outlet rebate records and the rebate calculated by the system. If there is a discrepancy, warn and form an early warning report.

[0021] Preferably: the single batch recharge consumption management includes:

[0022] C1: Enable online customer refueling record function, including station, card number, customer recharge amount, discount range, and rebate amount;

[0023] C2: Supports permission maintenance and management. The provincial company or municipal company assigns input permissions to designated users. Only users who have activated the input permissions have permission to maintain.

[0024] C3: Compare the customer discount information extracted from the station-level records with the actual system data, including recharge records, refueling records, and card balances;

[0025] C4: Management requires data entry before business operations. System warnings are required for business situations where operations are performed before recording.

[0026] Preferably: in the abnormal feedback, the provincial company issues the number of abnormal checks within the specified time - the station manager checks - the county and district review - the city spot check - and forms an analysis table, which specifically includes:

[0027] D1: The warning information of the big supervision system is reversed to BW and compared by card number. The warning information that is the same as BW is verified and pushed in both directions. Other warning information is reported according to the verification situation;

[0028] D2: Stationmaster verification - county and district review - city and prefecture random inspection - form analysis table.

[0029] Preferably: the management of abnormal consumption behavior of employees includes:

[0030] E1: Determine whether the customer is an employee based on the phone number in the abnormal consumption report, and add an employee flag to the warning report;

[0031] E2: No interface is involved, but an employee information import function is added to manually import employee information into the system on a monthly basis.

[0032] Preferably: the strategy + provincial customer files, major customer consumption decline management, which includes:

[0033] F1: Set keywords to form a customer or industry file name, import in batches by customer code or by entering keywords to search and import, and form the required customer file according to this operation, and generate a consumption table for the customers in the file by city, county, and district; secondly, for each customer file, generate a data analysis table, including the city, county, and district where the card was opened, the discount range of the gas card, the number of secondary cards, the proportion of gasoline and diesel, and the proportion of consumption in a certain period in the place where the card was opened and the place where the card was not opened;

[0034] F2: For customers whose monthly consumption is fixed and can be increased, manually selectable consumption segments are added. The required consumption date segment is selected, and reports are generated for the same-month and month-on-month sales by city, county, and district. The corresponding customer details can be exported, and warnings can be issued for customers whose monthly sales decline by 30% month-on-month, and customer sales details can be displayed.

[0035] Preferably: it includes:

[0036] G1: If a single mobile phone number uses n coupons on the same day, the warning is issued, and the current warning of m consecutive coupons is retained. The two warning conditions are in an OR relationship, where n and m are preset values ​​and support dynamic configuration adjustment;

[0037] G2: Personnel tags are added to the abnormal non-oil coupons. The serial number corresponds to the information of the consumed goods, the sales amount, the sales quantity, and the payment method. The abnormal non-oil coupons include continuous coupon use, the same coupon amount and a high proportion, the high proportion of coupon amount, and the high coupon amount. The personnel tags include the mobile phone number corresponding to the coupon and whether the person is an employee.

[0038] G3: Add the name and number of the coupon usage rules.

[0039] Preferably: the centralized entry of exceptions includes:

[0040] H1: Add the exclusion of business data such as store-in-store sales, advertising, and car wash, and add sales serial numbers corresponding to product sales information, sales quantity, and payment methods;

[0041] H2: Add custom filter items for serial number and group purchase order number labels;

[0042] The above-mentioned high / low sales volume customer warning includes the following logic:

[0043] L1: Set an adjustable upper threshold of 1 to issue an early warning to customers whose oil purchase volume last week was greater than threshold 1 and whose oil purchase volume this week exceeded 100% of the previous week's oil purchase volume on a month-on-month basis;

[0044] L2: Set an adjustable lower threshold value 2 to issue an early warning to customers whose oil purchase volume last month was greater than threshold 2 and whose oil purchase volume this month is less than 50% of the previous month's oil purchase volume.

[0045] Preferably: the logic of the early warning management of low-price sales customers is: to issue early warnings to customers whose single sales price is lower than the average sales price of the branch on that day every day, input the start and end time periods in the system every day, and compare the data of the two time periods.

[0046] The beneficial effects of the present invention are:

[0047] 1. The present invention can realize multiple functions including retail management, non-oil product management and commercial customer management, and under each function, it can respectively manage the whitelist of consumption abnormalities of IC card and petrochemical wallet users; early warning management of customers with points discount and barrel filling customers; management of recharge consumption on a single-batch basis; abnormal feedback management; management of abnormal consumption behavior of employees; strategic + provincial customer files, management of consumption decline of major customers, management of abnormal coupons and centralized abnormal entry, early warning management of customers with excessively high / low sales volume and early warning management of customers selling at low prices, etc., thereby realizing all-round early warning management of gas stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is an architecture diagram of a gas station large-scale supervision risk warning platform proposed by the present invention. DETAILED DESCRIPTION

[0049] The technical solution of the present invention is further described in detail below in conjunction with specific implementation methods.

[0050] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "set" should be understood in a broad sense, for example, they can be fixedly connected or set, or detachably connected or set, or integrally connected or set. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0051] Embodiment 1:

[0052] A gas station large-scale supervision risk early warning platform, comprising:

[0053] The Retail Management Center is used for retail management, including whitelist management of IC card and petrochemical wallet users’ consumption anomalies; early warning management of points-based preferential customers and bucket-filling customers; management of one-order-one-batch recharge consumption; abnormal feedback management; management of abnormal consumption behavior of employees; strategic + provincial customer files, and management of consumption decline of major customers;

[0054] The non-oil product center is used for non-oil product management, including coupon exception management and centralized entry exception management;

[0055] Commercial Customer Center Department, which includes early warning management for customers with excessively high / low sales volume and early warning management for customers selling at low prices.

[0056] The management logic of the whitelist of abnormal consumption of IC card and petrochemical wallet users is as follows:

[0057] A1: The designated retail personnel of the local branch enter the customer type, whitelist, and customer name. Customer type includes gas card account and mobile phone number;

[0058] A2: The gas card account is controlled by the city where the account is opened, and the mobile phone number is controlled by the city where the account is first created;

[0059] A3: The system supports viewing records of whitelist creation and deletion reasons, creation and deletion time, and operator records.

[0060] The early warning management of customers with points discount and customers with bucket filling includes:

[0061] B1: Customer information. The platform captures the OA approval order information of points discount, wallet discount customers, and bucket customers in the OA system to generate a customer detail report. Customer data that cannot be extracted by the platform can be edited and viewed by organization authority.

[0062] B2: Pre-expiry warning: the system captures customers with points discounts and petrochemical wallet customers and warns them several days in advance, pushes information about customers who are about to expire via SMS on a monthly basis, and pushes information about customers who are about to expire to the retail department manager and customer maintenance management post of the local branch company. It supports querying the customer's sales volume and discount amount during the discount period, and can analyze by oil product and card type;

[0063] B3: Warning of abnormal consumption of points discount. Based on the detailed list of points discount customers, the account opening and discount application places are added. If the consumption in the discount application place accounts for less than 60%, a warning will be issued. The warning report needs to show the consumption in the discount application city and other cities and the corresponding proportion. You can choose to query on a monthly or cumulative basis.

[0064] B4: Guantong customer rebate warning, capture Guantong customer monthly consumption and compare it with the customer consumption site and customer discount range in the OA approval form. The system automatically calculates the rebate amount. The system takes the latest date of the customer discount approval time. The customer is uniquely identified by the customer code. The local branch company designates the rebate outlets and the rebate time for rebate. Capture the outlet rebate records and the rebate calculated by the system. If there is a discrepancy, warn and form an early warning report.

[0065] The single batch recharge consumption management includes:

[0066] C1: Enable online customer refueling record function, including station, card number, customer recharge amount, discount range, and rebate amount;

[0067] C2: Supports permission maintenance and management. The provincial company or municipal company assigns input permissions to designated users. Only users who have activated the input permissions have permission to maintain.

[0068] C3: Compare the customer discount information extracted from the station-level records with the actual system data, including recharge records, refueling records, and card balances;

[0069] C4: Management requires data entry before business operations. System warnings are required for business situations where operations are performed before recording.

[0070] In the abnormal feedback, the provincial company issues the number of abnormal checks within the specified time - the station manager checks - the county and district review - the city spot check - and forms an analysis table, which specifically includes:

[0071] D1: The warning information of the big supervision system is reversed to BW and compared by card number. The warning information that is the same as BW is verified and pushed in both directions. Other warning information is reported according to the verification situation;

[0072] D2: Stationmaster verification - county and district review - city and prefecture random inspection - form analysis table.

[0073] The management of abnormal consumption behavior of employees includes:

[0074] E1: Determine whether the customer is an employee based on the phone number in the abnormal consumption report, and add an employee flag to the warning report;

[0075] E2: No interface is involved, but an employee information import function is added to manually import employee information into the system on a monthly basis.

[0076] The strategy + provincial customer files and major customer consumption decline management includes:

[0077] F1: Set keywords to form a customer or industry file name, import in batches by customer code or by entering keywords to search and import, and form the required customer file according to this operation, and generate a consumption table for the customers in the file by city, county, and district; secondly, for each customer file, generate a data analysis table, including the city, county, and district where the card was opened, the discount range of the gas card, the number of secondary cards, the proportion of gasoline and diesel, and the proportion of consumption in a certain period in the place where the card was opened and the place where the card was not opened;

[0078] F2: For customers whose monthly consumption is fixed and can be increased, manually selectable consumption segments are added. The required consumption date segment is selected, and reports are generated for the same-month and month-on-month sales by city, county, and district. The corresponding customer details can be exported, and warnings can be issued for customers whose monthly sales decline by 30% month-on-month, and customer sales details can be displayed.

[0079] The coupon abnormality management includes:

[0080] G1: If a single mobile phone number uses n coupons on the same day, the warning is issued, and the current warning of m consecutive coupons is retained. The two warning conditions are in an OR relationship, where n and m are preset values ​​and support dynamic configuration adjustment;

[0081] G2: Personnel tags are added to the abnormal non-oil coupons. The serial number corresponds to the information of the consumed goods, the sales amount, the sales quantity, and the payment method. The abnormal non-oil coupons include continuous coupon use, the same coupon amount and a high proportion, the high proportion of coupon amount, and the high coupon amount. The personnel tags include the mobile phone number corresponding to the coupon and whether the person is an employee.

[0082] G3: Add the name and number of the coupon usage rules.

[0083] The centralized entry exceptions include:

[0084] H1: Add the exclusion of business data such as store-in-store sales, advertising, and car wash, and add sales serial numbers corresponding to product sales information, sales quantity, and payment methods;

[0085] H2: Add custom filtering items for serial number and group purchase order number labels.

[0086] The above-mentioned high / low sales volume customer warning includes the following logic:

[0087] L1: Set an adjustable upper threshold of 1 to issue an early warning to customers whose oil purchase volume last week was greater than threshold 1 and whose oil purchase volume this week exceeded 100% of the previous week's oil purchase volume on a month-on-month basis;

[0088] L2: Set an adjustable lower threshold value 2 to issue an early warning to customers whose oil purchase volume last month was greater than threshold 2 and whose oil purchase volume this month is less than 50% of the previous month's oil purchase volume.

[0089] The logic of the early warning management for low-price sales customers is as follows: every day, early warnings are issued to customers whose single sales price is lower than the average sales price of the branch on that day. The start and end time periods are entered in the system every day and on that day, and the data of the two time periods are compared.

[0090] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A gas station large-scale supervision risk early warning platform, characterized in that: include: The Retail Management Center is used for retail management, including the management of whitelists of abnormal consumption by users of IC cards and petrochemical wallets; Early warning management of customers with points discount and customers with bucket filling; management of recharge consumption in batches and orders; management of abnormal feedback; management of abnormal consumption behavior of employees; management of strategic + provincial customer files and consumption decline of major customers; The non-oil product center is used for non-oil product management, including coupon exception management and centralized entry exception management; Commercial Customer Center Department, which includes early warning management for customers with excessively high / low sales volume and early warning management for customers selling at low prices.

2. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: The management logic of the whitelist of abnormal consumption of IC card and petrochemical wallet users is as follows: A1: The designated retail personnel of the local branch enter the customer type, whitelist, and customer name. Customer type includes gas card account and mobile phone number; A2: The gas card account is controlled by the city where the account is opened, and the mobile phone number is controlled by the city where the account is first created; A3: The system supports viewing records of whitelist creation and deletion reasons, creation and deletion time, and operator records.

3. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: The early warning management of customers with points discount and customers with bucket filling includes: B1: Customer information. The platform captures the OA approval order information of points discount, wallet discount customers, and bucket customers in the OA system to generate a customer detail report. Customer data that cannot be extracted by the platform can be edited and viewed by organization authority. B2: Pre-expiry warning: the system captures customers with points discounts and petrochemical wallet customers and warns them several days in advance, pushes information about customers who are about to expire via SMS on a monthly basis, and pushes information about customers who are about to expire to the retail department manager and customer maintenance management post of the local branch company. It supports querying the customer's sales volume and discount amount during the discount period, and can analyze by oil product and card type; B3: Warning of abnormal consumption of points discount. Based on the detailed list of points discount customers, the account opening and discount application places are added. If the consumption in the discount application place accounts for less than 60%, a warning will be issued. The warning report needs to show the consumption in the discount application city and other cities and the corresponding proportion. You can choose to query on a monthly or cumulative basis. B4: Guantong customer rebate warning, capture Guantong customer monthly consumption and compare it with the customer consumption site and customer discount range in the OA approval form. The system automatically calculates the rebate amount. The system takes the latest date of the customer discount approval time. The customer is uniquely identified by the customer code. The local branch company designates the rebate outlets and the rebate time for rebate. Capture the outlet rebate records and the rebate calculated by the system. If there is a discrepancy, warn and form an early warning report.

4. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: The single batch recharge consumption management includes: C1: Enable online customer refueling record function, including station, card number, customer recharge amount, discount range, and rebate amount; C2: Supports permission maintenance and management. The provincial company or municipal company assigns input permissions to designated users. Only users who have activated input permissions have permission to maintain. C3: Compare the customer discount information extracted from the station-level records with the actual system data, including recharge records, refueling records, and card balances; C4: Management requires data entry before business operations. System warnings are required for business situations where operations are performed before recording.

5. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: In the abnormal feedback, the provincial company issues the number of abnormal checks within the specified time - the station manager checks - the county and district review - the city spot check - and forms an analysis table, which specifically includes: D1: The warning information of the big supervision system is reversed to BW and compared by card number. The warning information that is the same as BW is verified and pushed in both directions. Other warning information is reported according to the verification situation; D2: Stationmaster verification - county and district review - city and prefecture random inspection - form analysis table.

6. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: The management of abnormal consumption behavior of employees includes: E1: Determine whether the customer is an employee based on the phone number in the abnormal consumption report, and add an employee flag to the warning report; E2: No interface is involved, but an employee information import function is added to manually import employee information into the system on a monthly basis.

7. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: The strategy + provincial customer files and major customer consumption decline management includes: F1: Set keywords to form a customer or industry file name, import in batches by customer code or by entering keywords to search and import, and form the required customer file according to this operation, and generate a consumption table for the customers in the file by city, county, and district; secondly, for each customer file, generate a data analysis table, including the city, county, and district where the card was opened, the discount range of the gas card, the number of secondary cards, the proportion of gasoline and diesel, and the proportion of consumption in a certain period in the place where the card was opened and the place where the card was not opened; F2: For customers whose monthly consumption is fixed and can be increased, manually selectable consumption segments are added. The required consumption date segment is selected, and reports are generated for the same-month and month-on-month sales by city, county, and district. The corresponding customer details can be exported, and warnings can be issued for customers whose monthly sales decline by 30% month-on-month, and customer sales details can be displayed.

8. The gas station large-scale supervision risk early warning platform according to claim 1 is characterized in that: The coupon abnormality management includes: G1: If a single mobile phone number uses n coupons on the same day, the warning is issued, and the current warning of m consecutive coupons is retained. The two warning conditions are in an OR relationship, where n and m are preset values ​​and support dynamic configuration adjustment; G2: Personnel tags are added to the abnormal non-oil coupons. The serial number corresponds to the information of the consumed goods, the sales amount, the sales quantity, and the payment method. The abnormal non-oil coupons include continuous coupon use, the same coupon amount and a high proportion, the high proportion of coupon amount, and the high coupon amount. The personnel tags include the mobile phone number corresponding to the coupon and whether the person is an employee. G3: Add the name and number of the coupon usage rules.

9. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: The centralized entry exceptions include: H1: Remove business data such as store-in-store sales, advertising, and car washes, and add sales serial numbers corresponding to product sales information, sales quantity, and payment methods; H2: Add custom filter items for serial number and group purchase order number labels; The above-mentioned high / low sales volume customer warning includes the following logic: L1: Set an adjustable upper threshold of 1 to issue an early warning to customers whose oil purchase volume last week was greater than threshold 1 and whose oil purchase volume this week exceeded 100% of the previous week's oil purchase volume on a month-on-month basis; L2: Set an adjustable lower threshold value 2 to issue an early warning to customers whose oil purchase volume last month was greater than threshold 2 and whose oil purchase volume this month is less than 50% of the previous month's oil purchase volume.

10. A gas station large-scale supervision risk early warning platform according to claim 1, characterized in that: The logic of the early warning management for low-price sales customers is as follows: every day, early warnings are issued to customers whose single sales price is lower than the average sales price of the branch on that day. The start and end time periods are entered in the system every day and on that day, and the data of the two time periods are compared.

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