Digital integral circulation system based on block chain technology

Abstract

The invention discloses a digital point circulation system based on a block chain technology, relates to the field of business, and solves the problem that the digital point circulation system is poor in security, and the digital point circulation system comprises a consumption data module which is used for obtaining first to b-th point merchant and customer in-store consumption data, the merchant data module is used for respectively acquiring sales quantity quantification coefficients corresponding to a first point merchant to a bth point merchant according to the regional consumption basic data to obtain a first sales quantity quantification coefficient to a bth sales quantity quantification coefficient; and the point circulation module is used for carrying out point circulation management according to the regional consumption basic data and the merchant basic sales data, and the digital point circulation security can be effectively improved.

Description

Technical Field

[0001] The present invention belongs to the commercial field and relates to blockchain technology, specifically a digital points circulation system based on blockchain technology. Background Art

[0002] The existing digital points circulation system has the following defects when circulating digital points:

[0003] 1. Many points systems are independently maintained by different merchants or platforms, lacking connection and sharing, resulting in data silos;

[0004] 2. Existing points systems often have security risks and are vulnerable to hacker attacks or fraud, which can easily infringe on customers' rights and interests;

[0005] To this end, we propose a digital points circulation system based on blockchain technology. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a digital points circulation system based on blockchain technology. The present invention is based on obtaining the first points merchant to the bth points merchant respectively, and obtaining the customer consumption coefficient set of each points merchant within the user consumption monitoring period to obtain customer in-store consumption data. The first points merchant to the bth points merchant and the customer in-store consumption data are defined as regional consumption basic data. According to the regional consumption basic data, the sales quantification coefficients corresponding to the first points merchant to the bth points merchant are obtained respectively to obtain the first sales quantification coefficient to the bth sales quantification coefficient, and the first sales quantification coefficient to the bth sales quantification coefficient are defined as merchant basic sales data. Points circulation management is performed according to the regional consumption basic data and the merchant basic sales data respectively.

[0007] In order to achieve the above objectives, the present invention adopts the following technical solutions: The specific working process of each module of a digital points circulation system based on blockchain technology is as follows:

[0008] Consumption data module: used to obtain the first to b-th points merchants, and obtain the customer consumption coefficient set of each points merchant within the user consumption monitoring period, to obtain customer in-store consumption data. The first to b-th points merchants and customer in-store consumption data are defined as regional consumption basic data;

[0009] Merchant data module: used to obtain the sales quantification coefficients corresponding to the first to b-th points merchants based on the regional consumption basic data, obtain the first to b-th sales quantification coefficients, and define the first to b-th sales quantification coefficients as the merchant basic sales data;

[0010] Points circulation module: used to manage points circulation based on regional consumption basic data and merchant basic sales data.

[0011] Furthermore, the consumption data module obtains regional consumption basic data as follows:

[0012] Obtain the constituent merchants of the target points program, and mark the constituent merchants as the first points merchant to the bth points merchant respectively;

[0013] Conduct consumption analysis on customers visiting the first points merchant to obtain a set of first customer consumption coefficients;

[0014] Repeat the process of obtaining the customer consumption coefficient set corresponding to the first points merchant, and obtain the customer consumption coefficient sets corresponding to the second points merchant to the b-th points merchant respectively, to obtain the second customer consumption coefficient set to the b-th customer consumption set;

[0015] The first customer consumption coefficient set to the bth customer consumption set is defined as customer in-store consumption data;

[0016] The data of in-store consumption of customers from the first to the bth points merchant is defined as regional consumption basic data.

[0017] Furthermore, the consumption data module obtains the first customer consumption coefficient set as follows:

[0018] Mark the time value corresponding to the current moment as the first reference time point, mark the time point corresponding to a characteristic period before the reference time point as the second reference time point, and mark the time range between the first reference time point and the second reference time point as the user consumption monitoring period;

[0019] Randomly select one customer from the in-store customers during the user consumption monitoring period as a sample consumer;

[0020] Monitor the consumption of sample consumer customers during the user consumption monitoring period and obtain the corresponding customer consumption value coefficient of the sample consumer customers;

[0021] Repeat the process of obtaining the customer consumption value coefficient corresponding to the sample consumer customers, obtain the customer consumption value coefficient corresponding to each in-store consumer customer, obtain the customer consumption coefficient set corresponding to the first points merchant, and name it the first customer consumption coefficient set.

[0022] Furthermore, the consumption data module obtains the customer consumption value coefficient corresponding to the sample consumer customer, as follows:

[0023] Obtain the cumulative number of in-store purchases by the sample consumer during the user consumption monitoring period, and mark the cumulative number of in-store purchases as the first to the cth in-store purchases according to the time corresponding to the in-store purchases;

[0024] Obtain the single consumption amounts corresponding to the first to the cth in-store consumption of the sample consumer customers, and obtain the first to cth single consumption amounts;

[0025] Sum the first single consumption amount to the cth single consumption amount to get the total consumption of the customer period;

[0026] Calculate the average of the first to cth single consumption amounts to get the average consumption amount of the customer period;

[0027] Obtain the stability coefficient of customer consumption amount;

[0028] Obtain the time length corresponding to the user consumption monitoring cycle to obtain the monitoring cycle duration, calculate the ratio of c to the monitoring cycle duration, and obtain the customer's periodic consumption frequency;

[0029] The customer consumption value coefficient corresponding to the sample consumer customers is obtained by calculating the customer consumption amount stability coefficient, the customer cycle average consumption amount and the customer cycle consumption frequency;

[0030] Calculate the customer consumption value coefficient corresponding to the sample consumer customers.

[0031] Furthermore, the consumption data module obtains the stability coefficient of the customer's consumption amount, as follows:

[0032] The stability coefficient of customer consumption amount is obtained by calculating the first single consumption amount to the cth single consumption amount;

[0033] Calculate the stability coefficient of customer consumption amount.

[0034] Furthermore, the merchant data module obtains the merchant's basic sales data as follows:

[0035] Obtain regional consumption basic data, obtain data for the selected first to b-th points merchants based on the regional consumption basic data, and randomly select one merchant from the first to b-th points merchants as a sample monitoring merchant;

[0036] Mark the time value corresponding to the current moment as the first merchant monitoring time point, mark the time point corresponding to the merchant monitoring characteristic period before the first merchant monitoring time point as the second merchant monitoring time point, and mark the time range between the first merchant monitoring time point and the second merchant monitoring time point as the merchant sales monitoring cycle;

[0037] Conduct sales analysis on sample monitored merchants to obtain the corresponding sales quantitative coefficients of sample monitored merchants;

[0038] Repeat the process of obtaining the sales quantification coefficients corresponding to the sample monitored merchants, and obtain the sales quantification coefficients corresponding to the first to b-th points merchants respectively, to obtain the first to b-th sales quantification coefficients;

[0039] The first sales quantification coefficient to the bth sales quantification coefficient are defined as the merchant's basic sales data.

[0040] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0041] 1. This invention uses blockchain technology to achieve decentralization, eliminating the reliance of digital points on a single central institution and ensuring that customers' digital points cannot be tampered with.

[0042] 2. The present invention ensures the objectivity of the digital points acquisition process by respectively obtaining the sales quantification coefficient and the customer consumption coefficient for digital recharge. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0044] Figure 1 is a block diagram of the overall system of the present invention;

[0045] Figure 2 It is a diagram of the implementation steps of the present invention;

[0046] Figure 3 This is the core architecture diagram of Ethereum in this invention. DETAILED DESCRIPTION

[0047] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] Example 1

[0049] See also Figure 1The present invention provides a technical solution: a digital points circulation system based on blockchain technology, comprising a consumption data module, a merchant data module, a points circulation module and a server, wherein the consumption data module, the merchant data module and the points circulation module are respectively connected to the server, and the server controls the consumption data module, the merchant data module and the points circulation module respectively;

[0050] The consumption data module obtains the first to b-th points merchants respectively, and obtains the customer consumption coefficient set of each points merchant during the user consumption monitoring period to obtain customer in-store consumption data. The first to b-th points merchants and customer in-store consumption data are defined as regional consumption basic data;

[0051] Obtain the constituent merchants of the target points program, and mark the constituent merchants as the first points merchant to the bth points merchant respectively;

[0052] It should be noted here that:

[0053] The b involved here is the number value corresponding to the point merchant in the target point project, and b is an integer greater than 0;

[0054] Conduct consumption analysis on customers visiting the first points merchant to obtain a set of first customer consumption coefficients;

[0055] The details are as follows:

[0056] Mark the time value corresponding to the current moment as the first reference time point, mark the time point corresponding to a characteristic period before the reference time point as the second reference time point, and mark the time range between the first reference time point and the second reference time point as the user consumption monitoring period;

[0057] It should be noted here that:

[0058] The user consumption monitoring cycle involved here is dynamically updated as the time value corresponding to the current moment changes;

[0059] Randomly select one customer from the in-store customers during the user consumption monitoring period as a sample consumer;

[0060] Monitor the consumption of sample consumer customers during the user consumption monitoring period and obtain the corresponding customer consumption value coefficient of the sample consumer customers;

[0061] The details are as follows:

[0062] Obtain the cumulative number of in-store purchases by the sample consumer during the user consumption monitoring period, and mark the cumulative number of in-store purchases as the first to the cth in-store purchases according to the time corresponding to the in-store purchases;

[0063] It should be noted here that:

[0064] In this application, c is the cumulative number of visits to the store by the sample consumer during the user consumption monitoring period, and c is an integer greater than 0;

[0065] Obtain the single consumption amounts corresponding to the first to the cth in-store consumption of the sample consumer customers, and obtain the first to cth single consumption amounts;

[0066] Sum the first single consumption amount to the cth single consumption amount to get the total consumption of the customer period;

[0067] Calculate the average of the first to cth single consumption amounts to get the average consumption amount of the customer period;

[0068] The stability coefficient of customer consumption amount is obtained by calculating the first single consumption amount to the cth single consumption amount;

[0069] Calculate the stability coefficient of customer consumption amount. The specific formula is as follows:

[0070] ;

[0071] Among them, Xfw is the stability coefficient of the customer's consumption amount, Je1 to Jep are the first to cth single consumption amounts respectively, and Jep is the average consumption amount of the customer during the period;

[0072] Obtain the time length corresponding to the user consumption monitoring cycle to obtain the monitoring cycle duration, calculate the ratio of c to the monitoring cycle duration, and obtain the customer's periodic consumption frequency;

[0073] The customer consumption value coefficient corresponding to the sample consumer customers is obtained by calculating the customer consumption amount stability coefficient, the customer cycle average consumption amount and the customer cycle consumption frequency;

[0074] Calculate the customer consumption value coefficient corresponding to the sample consumer customers. The specific formula configuration is as follows:

[0075] ;

[0076] Among them, Jxx is the customer consumption value coefficient corresponding to the sample consumer customer, Xfz is the average consumption amount of the customer period, Xfw is the customer consumption amount stability coefficient, and Xpl is the customer period consumption frequency;

[0077] Repeat the process of obtaining the customer consumption value coefficient corresponding to the sample consumer customers, and obtain the customer consumption value coefficient corresponding to each in-store consumer customer respectively, to obtain the customer consumption coefficient set corresponding to the first points merchant, and name it the first customer consumption coefficient set;

[0078] Repeat the process of obtaining the customer consumption coefficient set corresponding to the first points merchant, and obtain the customer consumption coefficient sets corresponding to the second points merchant to the b-th points merchant respectively, to obtain the second customer consumption coefficient set to the b-th customer consumption set;

[0079] The first customer consumption coefficient set to the bth customer consumption set is defined as customer in-store consumption data;

[0080] The first point merchant to the b-th point merchant and customer in-store consumption data are defined as regional consumption basic data;

[0081] The merchant data module obtains the sales quantification coefficients corresponding to the first point merchant to the bth point merchant based on the regional consumption basic data, obtains the first sales quantification coefficient to the bth sales quantification coefficient, and defines the first sales quantification coefficient to the bth sales quantification coefficient as the merchant basic sales data;

[0082] Obtain regional consumption basic data, obtain data for the selected first to b-th points merchants based on the regional consumption basic data, and randomly select one merchant from the first to b-th points merchants as a sample monitoring merchant;

[0083] Mark the time value corresponding to the current moment as the first merchant monitoring time point, mark the time point corresponding to the merchant monitoring characteristic period before the first merchant monitoring time point as the second merchant monitoring time point, and mark the time range between the first merchant monitoring time point and the second merchant monitoring time point as the merchant sales monitoring cycle;

[0084] It should be noted here that:

[0085] The merchant sales monitoring cycle involved here is dynamically updated as the time value corresponding to the current moment changes;

[0086] Conduct sales analysis on sample monitored merchants to obtain the corresponding sales quantitative coefficients of sample monitored merchants;

[0087] Divide the merchant sales monitoring cycle into m sales monitoring sub-cycles, and name the m sales monitoring sub-cycles as the first sales monitoring sub-cycle to the mth sales monitoring sub-cycle;

[0088] It should be noted here that:

[0089] In this application, m is the quantity value corresponding to the sales monitoring sub-period, and m is an integer greater than 0;

[0090] Obtain samples from big data to monitor the average daily turnover of merchants in the area where the merchants are located;

[0091] Obtain the number of customers visiting the sample monitored merchant from the first sales monitoring sub-period to the mth sales monitoring sub-period, and obtain the value of the number of customers in the first sub-period and the number of customers visiting the store in the mth sub-period;

[0092] Calculate the average number of customers visiting the store in the mth sub-period by the number of customers in the first sub-period to get the average number of customers visiting the store in the period;

[0093] The merchant customer flow stability coefficient is calculated by taking the number of customers in the first sub-period, the number of customers visiting the store in the mth sub-period, and the average number of customers visiting the store during the period;

[0094] Calculate the merchant customer flow stability coefficient. The specific formula is as follows:

[0095] ;

[0096] Among them, Klw is the merchant customer flow stability coefficient, Gk1 to Gkm are the number of customers in the first sub-period and the number of customers visiting the store in the mth sub-period respectively, and Gkp is the average number of customers visiting the store during the period;

[0097] Obtain the store sales of the sample monitored merchants from the first sales monitoring sub-period to the mth sales monitoring sub-period, and obtain the sales from the first period to the mth period;

[0098] The sales from the first cycle to the mth cycle are summed to obtain the total sales of the cycle. The ratio of the total sales of the cycle to the average daily turnover of the merchant is calculated to obtain the cycle turnover ratio.

[0099] Calculate the average sales from the first period to the mth period to get the average sales of the period;

[0100] The cycle sales stability coefficient is obtained by calculating the sales from the first cycle to the mth cycle and the average sales of the cycle;

[0101] The cycle sales stability coefficient is calculated using the following formula:

[0102] ;

[0103] Among them, Sew is the cycle sales stability coefficient, Se1 to Sem are the sales from the first cycle to the mth cycle respectively, and Sep is the average sales of the cycle;

[0104] The sales quantification coefficient corresponding to the sample monitored merchants is obtained by calculating the period sales stability coefficient, period turnover ratio and merchant customer flow stability coefficient;

[0105] Calculate the sales quantification coefficient corresponding to the sample monitored merchants. The specific formula configuration is as follows:

[0106] ;

[0107] Among them, Xll is the sales quantitative coefficient corresponding to the sample monitored merchants, Zyb is the cycle turnover ratio, Sew is the cycle sales stability coefficient, and Klw is the merchant customer flow stability coefficient;

[0108] Repeat the process of obtaining the sales quantification coefficients corresponding to the sample monitored merchants, and obtain the sales quantification coefficients corresponding to the first to b-th points merchants respectively, to obtain the first to b-th sales quantification coefficients;

[0109] The first sales quantification coefficient to the bth sales quantification coefficient are defined as the merchant's basic sales data;

[0110] The merchant data module obtains the merchant's basic sales data and transmits it to the points circulation module;

[0111] The points circulation module manages points circulation based on regional consumption basic data and merchant basic sales data;

[0112] Obtain regional consumption basic data, and obtain the first to b-th points merchants and customer in-store consumption data based on the regional consumption data;

[0113] Conduct digital points circulation management for first-class points merchants based on customer in-store consumption data;

[0114] The details are as follows:

[0115] Obtain customer in-store consumption data, and obtain a first customer consumption coefficient set based on the customer in-store consumption data;

[0116] Create a points blockchain corresponding to the first points merchant through the Ethereum platform to obtain the first merchant points blockchain. Use the Ethereum platform to treat each customer who visits the store during the user consumption monitoring cycle as a block. When the customer visits the store to consume, synchronize the reward digital points earned by the current customer to the corresponding block.

[0117] It is necessary to add here:

[0118] In the specific implementation, the specific steps for the circulation of customer reward digital points are as follows:

[0119] Step 1: Define the CustomerBlock structure to record the customer address, spending amount, reward points, and timestamp, and use the dynamic array customerBlocks to store all customer block data. At the same time, map the customer address to the points balance through mapping. The contract constructor initializes the merchant address. The merchant calls the contract through the recordCustomerVisit function. After verifying the caller's identity, it calculates the reward points based on the spending amount and the preset points ratio, generates a new block, and updates the customer's points balance. At the same time, it triggers the RewardIssued event so that the merchant system can monitor and synchronize data.

[0120] Step 2: After the customer arrives at the store, the merchant system identifies the customer's wallet address and records the purchase amount, calling the recordCustomerVisit function of the smart contract through Web3.js. The contract first verifies whether the caller is an authorized merchant. If the verification is successful, the reward points are calculated based on the purchase amount and the points ratio (e.g., 1 yuan = 1 point). The customer information, purchase amount, points value, and timestamp are encapsulated into a new block and stored in an on-chain array. The customer points balance mapping table is also updated. After the transaction is executed, the contract triggers an event log. The merchant system monitors the event and updates the local database to ensure the consistency of on-chain and off-chain data.

[0121] Step 3: The merchant system stores the complete consumption record in IPFS or a private database, and only submits the data hash value to the smart contract. The contract verifies the hash value to ensure that the data has not been tampered with. Alternatively, the merchant system uses a Merkle tree structure to aggregate multiple consumption records into a Merkle root and then upload it to the chain. Customers can prove the authenticity of their consumption records by submitting the transaction path, while reducing on-chain storage overhead.

[0122] Step 4: The merchant system signs the transaction using the merchant wallet private key and calls the smart contract function. The system must implement permission control logic to ensure that only authorized merchants can call the points issuance interface. To optimize gas efficiency, the system can process customer records in batches (e.g., daily aggregation and single upload to the chain), or compress transaction data and submit it to the main chain through Layer 2 expansion solutions (e.g., Optimistic Rollup) to reduce the cost of each transaction.

[0123] Step 5: Customers can check their points balance and spending history through a blockchain browser or the merchant app. The merchant system provides a front-end interface that calls the getCustomerPoints function of the smart contract to obtain real-time points data. If customers need to verify their historical spending records, they can use the Merkle proof or IPFS hash link provided by the merchant system to compare the hash value stored on the chain with the original data to ensure that the data has not been tampered with.

[0124] Step 6: Use the onlyMerchant modifier to restrict point issuance permissions to prevent malicious calls; use event logging to record key operations (such as point issuance and block generation) for easy audit tracking; for high-concurrency scenarios, the system can be deployed on Layer 2 networks such as Optimism or Arbitrum, using compressed transactions and state root submission technology to increase throughput to thousands of transactions per second while maintaining security compatibility with the Ethereum main chain;

[0125] Obtain the reward digital points corresponding to the current customer, as follows:

[0126] Obtaining the customer consumption reward coefficient corresponding to the current customer through the first customer consumption coefficient set, obtaining the initial digital points, and calculating the product of the customer consumption reward coefficient and the initial digital points to obtain the reward digital points;

[0127] It should be noted here that:

[0128] The initial digital points involved here are set by the first points merchant;

[0129] Repeat the process of digital points circulation management for the first points merchant, and perform digital points circulation management for the corresponding in-store customers of the first points merchant to the bth points merchant respectively;

[0130] Conduct point circulation management for the first point merchant to the bth point merchant based on the merchant's basic sales data;

[0131] The details are as follows:

[0132] Obtain the first to bth sales quantification coefficients respectively based on the first to bth points merchants;

[0133] See also Figure 3 , establish a points merchant blockchain through the Ethereum platform, create b blocks in the points merchant blockchain, and b blocks correspond to the first points merchant to the bth points merchant, and use the reward digital points corresponding to each points merchant to reward the corresponding blocks within each merchant sales monitoring cycle;

[0134] It should be added here that the specific steps for the blockchain circulation of reward digital points corresponding to point merchants are as follows:

[0135] Step 1: Deploy a dedicated blockchain network for reward points merchants on the Ethereum platform (you can choose a private chain, consortium chain, or directly use the main chain) and write the smart contract MerchantRewardChain;

[0136] Step 2: Each merchant registers by calling the registerMerchant function of the contract, submitting the merchant ID and wallet address. After the contract verifies that the ID is not occupied, it stores the address in the merchantRegistry and initializes the corresponding MerchantBlock block (rewardPool is initially 0, totalRewardsIssued is initially 0);

[0137] Step 3: At the beginning of each sales monitoring cycle (e.g., 00:00 every Monday), the contract automatically resets the rewardPool of all merchants to 0 and records the cycle start timestamp. The merchant system (e.g., POS terminal) submits transaction data, including merchant ID, sales amount, and customer address, by calling the contract's recordSale function for each sale. The contract calculates the points to be issued based on sales amount and allocation rules (e.g., sales amount * 1%), accumulates the points value to the corresponding merchant's rewardPool, and updates the lastUpdateTimestamp;

[0138] Step 4: At the end of the sales cycle (e.g., every Sunday at 24:00), the merchant can call the contract's issueRewards function, specifying the customer address and the points value to be issued;

[0139] Step 5: The contract automatically triggers the finalizeCycle function at the end of the cycle, transfers the remaining points in rewardPool (if any) to the merchant's reserved account (such as a marketing fund), and resets rewardPool to 0.

[0140] It should be noted here that:

[0141] The block corresponding to each points merchant involved here also includes the corresponding merchant's operating data, which includes but is not limited to sales, business hours, and in-store customer consumption records;

[0142] Obtain the reward digital points corresponding to the first points merchant, as follows:

[0143] Obtain the first sales quantification coefficient and the initial points value corresponding to the first points merchant;

[0144] It should be noted here that:

[0145] The initial points value involved here is set by the management platform corresponding to the target points project;

[0146] The initial points value and the first sales quantification coefficient are calculated to obtain the reward digital points corresponding to the first points merchant;

[0147] The reward digital points corresponding to the first points merchant are calculated as follows:

[0148] ;

[0149] Among them, Jif is the reward digital points corresponding to the first points merchant, Csj is the reward digital points, and Xll1 is the first sales quantification coefficient;

[0150] In this application, if a corresponding calculation formula appears, the above calculation formula is dimensionless and its numerical calculation is performed. The weight coefficient, proportional coefficient and other coefficients in the formula are set to a result value obtained by quantifying each parameter. Regarding the size of the weight coefficient and the proportional coefficient, as long as it does not affect the proportional relationship between the parameter and the result value, it is acceptable.

[0151] Example 2

[0152] See also Figure 2 Based on another concept of the same invention, a digital points circulation method based on blockchain technology is proposed, which is applicable to a digital points circulation system based on blockchain technology. The digital points circulation method includes the following steps:

[0153] Step S1: Obtain the first to b-th points merchants respectively, obtain the customer consumption coefficient set of each points merchant during the user consumption monitoring period, obtain customer in-store consumption data, and define the first to b-th points merchants and customer in-store consumption data as regional consumption basic data;

[0154] Step S11: Obtain the constituent merchants of the target points program, and mark the constituent merchants as the first points merchant to the bth points merchant respectively;

[0155] Step S12: performing consumption analysis on customers visiting the first points merchant to obtain a customer consumption reward coefficient;

[0156] The details are as follows:

[0157] Step S121: Mark the time value corresponding to the current moment as the first reference time point, mark the time point corresponding to a characteristic period before the reference time point as the second reference time point, and mark the time range between the first reference time point and the second reference time point as the user consumption monitoring period;

[0158] Step S122: Randomly select a customer from the in-store customers during the user consumption monitoring period as a sample customer;

[0159] Step S123: monitoring the consumption of sample consuming customers during the user consumption monitoring period to obtain the customer consumption value coefficient corresponding to the sample consuming customers;

[0160] The details are as follows:

[0161] Step S1231: Obtain the cumulative number of in-store purchases by the sample consumer during the user consumption monitoring period, and mark the cumulative number of in-store purchases as the first in-store purchase to the cth in-store purchase in order of the time corresponding to the in-store purchase;

[0162] Step S1232: Obtain the single consumption amounts corresponding to the first to c-th in-store consumption of the sample consumer customer, and obtain the first to c-th single consumption amounts;

[0163] Step S1233: Sum the first single consumption amount to the cth single consumption amount to obtain the customer's total period consumption;

[0164] Step S1234: Calculate the average of the first single consumption amount to the cth single consumption amount to obtain the customer's average consumption amount during the period;

[0165] Step S1235: Obtaining the customer's consumption amount stability coefficient;

[0166] The specific steps are as follows:

[0167] The stability coefficient of customer consumption amount is obtained by calculating the first single consumption amount to the cth single consumption amount;

[0168] Calculate the stability coefficient of customer consumption amount. The specific formula is as follows:

[0169] ;

[0170] Among them, Xfw is the stability coefficient of the customer's consumption amount, Je1 to Jep are the first to cth single consumption amounts respectively, and Jep is the average consumption amount of the customer during the period;

[0171] Step S1236: Obtain the time length corresponding to the user consumption monitoring period to obtain the monitoring period duration, calculate the ratio of c to the monitoring period duration, and obtain the customer's periodic consumption frequency;

[0172] Step S1237: Calculate the customer consumption value coefficient corresponding to the sample consumer by using the customer consumption amount stability coefficient, the customer cycle average consumption amount, and the customer cycle consumption frequency;

[0173] Calculate the customer consumption value coefficient corresponding to the sample consumer customers. The specific formula configuration is as follows:

[0174] ;

[0175] Among them, Jxx is the customer consumption value coefficient corresponding to the sample consumer customer, Xfz is the average consumption amount of the customer period, Xfw is the customer consumption amount stability coefficient, and Xpl is the customer period consumption frequency;

[0176] Step S124: Repeat the process of obtaining the customer consumption value coefficients corresponding to the sample consumer customers, respectively obtain the customer consumption value coefficients corresponding to each in-store consumer customer, obtain the customer consumption coefficient set corresponding to the first points merchant, and name it the first customer consumption coefficient set;

[0177] Step S13: Repeat the process of acquiring the customer consumption coefficient set corresponding to the first points merchant, and respectively acquire the customer consumption coefficient sets corresponding to the second points merchant to the bth points merchant, to obtain the second customer consumption coefficient set to the bth customer consumption coefficient set;

[0178] Step S14: defining the first customer consumption coefficient set to the bth customer consumption set as customer in-store consumption data;

[0179] Step S15: defining the in-store consumption data of customers from the first to the bth points merchant as regional consumption basic data;

[0180] Step S2: Obtain sales quantification coefficients corresponding to the first to b-th points merchants respectively based on the regional consumption basic data, obtain the first to b-th sales quantification coefficients, and define the first to b-th sales quantification coefficients as merchant basic sales data;

[0181] Step S21: Acquire regional consumption basic data, acquire data from the first to b-th selected points merchants based on the regional consumption basic data, and randomly select one merchant from the first to b-th points merchants as a sample monitoring merchant;

[0182] Step S22: Mark the time value corresponding to the current moment as the first merchant monitoring time point, mark the time point corresponding to the merchant monitoring characteristic period before the first merchant monitoring time point as the second merchant monitoring time point, and mark the time range between the first merchant monitoring time point and the second merchant monitoring time point as the merchant sales monitoring period;

[0183] Step S23: Analyze the sales of sample monitored merchants to obtain the sales quantitative coefficient corresponding to the sample monitored merchants;

[0184] The details are as follows:

[0185] Step S231: Divide the merchant sales monitoring cycle into m sales monitoring sub-cycles, and name the m sales monitoring sub-cycles as the first sales monitoring sub-cycle to the mth sales monitoring sub-cycle respectively;

[0186] Step S232: Obtain the average daily turnover of merchants in the area where the sample monitoring merchants are located through big data;

[0187] Step S233: Obtain the number of customers visiting the sample monitored merchant during the first sales monitoring sub-period to the mth sales monitoring sub-period, and obtain the value of the number of customers in the first sub-period and the number of customers visiting the store in the mth sub-period;

[0188] Step S234: Obtaining the merchant customer flow stability coefficient;

[0189] The details are as follows:

[0190] Step S2341: Calculate the average of the number of customers in the first sub-period and the number of customers visiting the store in the mth sub-period to obtain the average number of customers visiting the store during the period;

[0191] Step S2342: Calculate the merchant customer flow stability coefficient by combining the number of customers in the first sub-period, the number of customers visiting the store in the mth sub-period, and the average number of customers visiting the store during the period;

[0192] Calculate the merchant customer flow stability coefficient. The specific formula is as follows:

[0193] ;

[0194] Among them, Klw is the merchant customer flow stability coefficient, Gk1 to Gkm are the number of customers in the first sub-period and the number of customers visiting the store in the mth sub-period respectively, and Gkp is the average number of customers visiting the store during the period;

[0195] Step S2343: Obtain the store sales of the sample monitored merchant from the first sales monitoring sub-period to the mth sales monitoring sub-period, and obtain the sales from the first period to the mth period;

[0196] Step S2344: Sum the sales from the first period to the mth period to obtain the total sales for the period, and calculate the ratio of the total sales for the period to the average daily sales of the merchant to obtain the period turnover ratio;

[0197] Step S2345: Calculate the average of the sales from the first period to the mth period to obtain the average sales of the period;

[0198] Step S2346: Calculate the sales from the first period to the mth period and the average sales of the period to obtain the period sales stability coefficient;

[0199] The cycle sales stability coefficient is calculated using the following formula:

[0200] ;

[0201] Among them, Sew is the cycle sales stability coefficient, Se1 to Sem are the sales from the first cycle to the mth cycle respectively, and Sep is the average sales of the cycle;

[0202] Step S2347: Calculate the sales quantification coefficient corresponding to the sample monitored merchant by using the period sales stability coefficient, the period turnover ratio, and the merchant customer flow stability coefficient;

[0203] Calculate the sales quantification coefficient corresponding to the sample monitored merchants. The specific formula configuration is as follows:

[0204] ;

[0205] Among them, Xll is the sales quantitative coefficient corresponding to the sample monitored merchants, Zyb is the cycle turnover ratio, Sew is the cycle sales stability coefficient, and Klw is the merchant customer flow stability coefficient;

[0206] Step S235: Repeat the process of obtaining the sales quantification coefficients corresponding to the sample monitored merchants, and obtain the sales quantification coefficients corresponding to the first to b-th points merchants, respectively, to obtain the first to b-th sales quantification coefficients;

[0207] Step S24: defining the first sales quantification coefficient to the bth sales quantification coefficient as the merchant basic sales data;

[0208] Step S3: performing point circulation management based on regional consumption basic data and merchant basic sales data;

[0209] Step S31: Obtain regional consumption basic data, and obtain the first to b-th points merchants and customer in-store consumption data based on the regional consumption data;

[0210] Step S32: performing digital points circulation management for the first points merchant based on the customer's in-store consumption data;

[0211] The details are as follows:

[0212] Step S321: Acquire customer in-store consumption data, and acquire a first customer consumption coefficient set based on the customer in-store consumption data;

[0213] Step S322: Create a points blockchain corresponding to the first points merchant through the Ethereum platform to obtain the first merchant points blockchain. Use the Ethereum platform to treat each customer who visits the first points merchant during the user consumption monitoring cycle as a block. When the customer visits the store to consume, synchronize the reward digital points earned by the current customer to the corresponding block.

[0214] Step S323: Obtain the reward digital points corresponding to the current customer;

[0215] The details are as follows:

[0216] Step S3231: Obtain the customer consumption reward coefficient corresponding to the current customer through the first customer consumption coefficient set, obtain initial digital points, calculate the product of the customer consumption reward coefficient and the initial digital points, and obtain reward digital points;

[0217] Step S324: Repeat the process of digital points circulation management for the first points merchant, and perform digital points circulation management for the corresponding in-store customers of the first points merchant to the bth points merchant respectively;

[0218] Step S33: performing point circulation management for the first point merchant to the bth point merchant based on the merchant basic sales data;

[0219] The details are as follows:

[0220] Step S331: Obtaining first to b-th sales quantification coefficients from the first to b-th points merchants respectively;

[0221] Step S332: Establish a points merchant blockchain through the Ethereum platform, create b blocks in the points merchant blockchain, and b blocks correspond to the first points merchant to the bth points merchant. During each merchant sales monitoring cycle, use the reward digital points corresponding to each points merchant to reward the corresponding blocks;

[0222] Step S333: Obtaining the reward digital points corresponding to the first points merchant;

[0223] Step S3331: Obtain the first sales quantification coefficient and the initial points value corresponding to the first points merchant;

[0224] Step S3332: Calculate the initial points value and the first sales quantification coefficient to obtain the reward digital points corresponding to the first points merchant;

[0225] The reward digital points corresponding to the first points merchant are calculated as follows:

[0226] ;

[0227] Among them, Jif is the reward digital points corresponding to the first points merchant, Csj is the reward digital points, and Xll1 is the first sales quantification coefficient;

[0228] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A digital points circulation system based on blockchain technology, characterized by: include: Consumption data module: used to obtain the first to b-th points merchants, and obtain the customer consumption coefficient set of each points merchant within the user consumption monitoring period, to obtain customer in-store consumption data. The first to b-th points merchants and customer in-store consumption data are defined as regional consumption basic data; Merchant data module: used to obtain the sales quantification coefficients corresponding to the first to b-th points merchants based on the regional consumption basic data, obtain the first to b-th sales quantification coefficients, and define the first to b-th sales quantification coefficients as the merchant basic sales data; Points circulation module: used to manage points circulation based on regional consumption basic data and merchant basic sales data.

2. A digital points circulation system based on blockchain technology according to claim 1, characterized in that: The consumption data module obtains regional consumption basic data, as follows: Obtain the constituent merchants of the target points program, and mark the constituent merchants as the first points merchant to the bth points merchant respectively; Conduct consumption analysis on customers visiting the first points merchant to obtain a set of first customer consumption coefficients; The customer consumption coefficient sets corresponding to the second point merchant to the bth point merchant are respectively acquired to obtain the second customer consumption coefficient set to the bth customer consumption set.

3. A digital points circulation system based on blockchain technology according to claim 2, characterized in that: The consumption data module obtains regional consumption basic data, as follows: The first customer consumption coefficient set to the bth customer consumption set is defined as customer in-store consumption data; The data of in-store consumption of customers from the first to the bth points merchant is defined as regional consumption basic data.

4. A digital points circulation system based on blockchain technology according to claim 3, characterized in that: The consumption data module obtains the first customer consumption coefficient set as follows: Mark the time value corresponding to the current moment as the first reference time point, mark the time point corresponding to a characteristic period before the reference time point as the second reference time point, and mark the time range between the first reference time point and the second reference time point as the user consumption monitoring period; A customer is randomly selected from the in-store consumers during the user consumption monitoring period as a sample consumer.

5. According to claim 4, a digital points circulation system based on blockchain technology is characterized in that: The consumption data module obtains the first customer consumption coefficient set as follows: Monitor the consumption of sample consumer customers during the user consumption monitoring period and obtain the corresponding customer consumption value coefficient of the sample consumer customers; The customer consumption value coefficient corresponding to each in-store consumer is obtained respectively to obtain a customer consumption coefficient set corresponding to the first points merchant, and the set is named the first customer consumption coefficient set.

6. A digital points circulation system based on blockchain technology according to claim 5, characterized in that: The consumption data module obtains the customer consumption value coefficient corresponding to the sample consumer customer, as follows: Obtain the cumulative number of in-store purchases by the sample consumer during the user consumption monitoring period, and mark the cumulative number of in-store purchases as the first to the cth in-store purchases according to the time corresponding to the in-store purchases; Obtain the single consumption amounts corresponding to the sample consumer customers' first to c-th in-store consumption, and obtain the first to c-th single consumption amounts.

7. A digital points circulation system based on blockchain technology according to claim 6, characterized in that: The consumption data module obtains the customer consumption value coefficient corresponding to the sample consumer customer, as follows: Sum the first single consumption amount to the cth single consumption amount to get the total consumption of the customer period; Calculate the average of the first to cth single consumption amounts to get the average consumption amount of the customer period; Get the customer's spending stability coefficient.

8. A digital points circulation system based on blockchain technology according to claim 7, characterized in that: The consumption data module obtains the customer consumption value coefficient corresponding to the sample consumer customer, as follows: Obtain the time length corresponding to the user consumption monitoring cycle to obtain the monitoring cycle duration, calculate the ratio of c to the monitoring cycle duration, and obtain the customer's periodic consumption frequency; The customer consumption value coefficient corresponding to the sample consumer customers is obtained by calculating the customer consumption amount stability coefficient, the customer cycle average consumption amount and the customer cycle consumption frequency; Calculate the customer consumption value coefficient corresponding to the sample consumer customers.

9. A digital points circulation system based on blockchain technology according to claim 8, characterized in that: The consumption data module obtains the stability coefficient of the customer's consumption amount, as follows: The stability coefficient of customer consumption amount is obtained by calculating the first single consumption amount to the cth single consumption amount; Calculate the stability coefficient of customer consumption amount.

10. The digital points circulation system based on blockchain technology according to claim 1 is characterized in that: The merchant data module obtains the merchant's basic sales data, as follows: Obtain regional consumption basic data, obtain data for the selected first to b-th points merchants based on the regional consumption basic data, and randomly select one merchant from the first to b-th points merchants as a sample monitoring merchant; Mark the time value corresponding to the current moment as the first merchant monitoring time point, mark the time point corresponding to the merchant monitoring characteristic period before the first merchant monitoring time point as the second merchant monitoring time point, and mark the time range between the first merchant monitoring time point and the second merchant monitoring time point as the merchant sales monitoring cycle; Conduct sales analysis on sample monitored merchants to obtain the corresponding sales quantitative coefficients of sample monitored merchants; Obtain the sales quantification coefficients corresponding to the first point merchant to the b-th point merchant respectively, and obtain the first sales quantification coefficient to the b-th sales quantification coefficient; The first sales quantification coefficient to the bth sales quantification coefficient are defined as the merchant's basic sales data.

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