Internet-based group purchase package intelligent settlement system

Abstract

The invention relates to the technical field of intelligent settlement, and particularly discloses an internet-based intelligent settlement system for a group purchase package, and the system comprises an information obtaining module which obtains the price of an original package and the number of commodities in the group purchase package, and calculates the unit price of the commodities; the information processing module is used for obtaining consumption records of the users, obtaining verification time, prices and the number of commodities, and calculating time intervals, average verification time and average group purchase prices; the information calculation module is used for calculating a purchase capability coefficient and a quantity fluctuation value and setting a first recommendation package; and the information output module is used for calculating unit prices of different recommended packages according to a price function, calculating prices of the recommended packages and screening out the recommended packages. According to the group purchase package recommendation method provided by the invention, the user has more opportunities of selection through group purchase package recommendation, and the group purchase demand of the user is better met.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent settlement, and in particular to an Internet-based group purchase package intelligent settlement system. Background Art

[0002] With the rapid development of some group buying platforms, group buying has also become an emerging shopping model. Most merchants will put some very favorable group buying packages on the group buying platforms to attract customers to buy at lower prices.

[0003] When a group purchase package is added to the user's shopping cart, the system will provide the user with some new group purchase packages. The user can choose whether to change the package according to his or her own needs. The group purchase packages provided by the system to the user come from the merchant's group purchase package database. The merchant's group purchase package database contains a large amount of group purchase package information. The group purchase package database can meet the user's needs for group purchase packages.

[0004] In the prior art, the group purchase packages on the group purchase platform are set by the merchants, and users choose from the group purchase packages set by the merchants. Users who have purchased group purchase packages on the group purchase platform need to go to offline stores to verify the group purchase packages, and the staff will add the corresponding group purchase packages to the user's shopping cart by entering the verification code. However, the content of the group purchase packages on the group purchase platform is relatively fixed, and it is difficult for users to choose a group purchase package that suits them. When users go to offline stores for verification, the system will recommend packages to users. Therefore, there is an urgent need for a method to screen out group purchase packages that are suitable for users, so as to achieve the purpose of accurate recommendation, so that users can choose group purchase packages that better meet their needs. Summary of the invention

[0005] The purpose of the present invention is to provide an Internet-based group purchase package intelligent settlement system to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An Internet-based group purchase package intelligent settlement system, comprising:

[0008] Information acquisition module: Mark the group purchase package purchased by the user as the original package and obtain the price S of the original package ori and the number of items in the group purchase package N ori , and calculate the unit price P of the product ori =S ori / N ori ;

[0009] Information processing module: The merchant obtains the consumption record of the user who purchased the group purchase package in this store and obtains the verification time T of the i-th group purchase package i , the price of group purchase packagei and the number of items in the group purchase package N i , where i is a positive integer;

[0010] Calculate the purchase time interval ΔT i =T i -T i-1 , where ΔT i Represents the time interval between the verification of the i-th group purchase package and the i-1-th group purchase package, and calculates the average verification time The average group purchase price of group purchase packages purchased by users Where I represents the total number of times group purchase packages are purchased;

[0011] Information calculation module: Calculate the user's purchasing power coefficient X according to the average verification time and the average group purchase price. The calculation formula of the purchasing power coefficient X is as follows:

[0012]

[0013] Wherein, γ represents a preset first adjustment coefficient;

[0014] Calculate the product quantity fluctuation value Among them, N ave Represents the average number of items in the group purchase package purchased by the user, and sets 2J first recommended packages according to the fluctuation value of the number of items, where J is the preset first recommended package quantity threshold, and the number of items in the jth first recommended package is NT j =N ori +ρ·(jJ)·f, where ρ is the preset change value of the commodity quantity;

[0015] Information output module: according to the price function Calculate the unit price P(NT j ), where μ represents the preset price change coefficient;

[0016] Calculate the recommended price ST of the jth first recommended package j =P(NT j )*NT j , the number of items in the first recommended package is NT j ;

[0017] Obtain the merchant's package database, and filter out the group purchase packages in the package database that are close to the recommended price and quantity of goods as the recommended packages.

[0018] As a further solution of the present invention: a method for selecting a group purchase package with a similar price and quantity of goods to the recommended package in a group purchase package database as a recommended package specifically includes:

[0019] The price fluctuation range of the jth first recommended package [ST j -A,ST j +A] and commodity quantity fluctuation range [NT j -B,NT j +B], where A is the preset price fluctuation coefficient and B is the preset commodity quantity fluctuation coefficient;

[0020] The group purchase packages in the group purchase package database are screened and the group purchase package prices are within the price fluctuation range [ST j -A,ST j +A] and the quantity of the product is within the fluctuation range of the quantity of the product [NT j -B,NT j +B] is marked as a candidate package, and the comprehensive value K of the i-th candidate package is calculated. i =|ST j -S i_pre |+|NT j -N i_pre |, select the candidate package with the smallest comprehensive value as the recommended package, where S i_pre represents the price of the i-th selected package, N j_pre Represents the number of items in the i-th package to be selected.

[0021] As a further solution of the present invention: if the comprehensive values ​​of the to-be-selected packages are equal, the to-be-selected package with a lower price is preferentially selected as the recommended package.

[0022] As a further solution of the present invention: if the purchase time interval ΔT i ≤η, the i-th group purchase package and the i-1-th group purchase package are regarded as one group purchase package, and the price and quantity of goods of the i-th group purchase package and the i-1-th group purchase package are added respectively, where η represents the preset minimum time interval.

[0023] As a further solution of the present invention: Calculate the average group purchase price S ave When the group purchase package purchased by the user does not participate in the average group purchase price S ave Calculation.

[0024] As a further solution of the present invention: when the commodity quantity fluctuation value f=0, if the commodity quantity N ori =N ave , then stop the subsequent steps and do not recommend the recommended package;

[0025] If the number of products N ori ≠N ave , then execute the subsequent steps normally.

[0026] As a further solution of the present invention: Get the number of products NT of the jth recommended package j The number of items in the group purchase package launched by the merchant N x , calculate the difference in the number of goods NC = NT j -N x If the difference in the number of goods NC is less than the preset minimum number of goods N min , at this time, select the lower-priced package as the recommended package.

[0027] As a further solution of the present invention: when setting the recommended set meal quantity threshold J, ensure that the j-th item quantity NT is calculated in the subsequent steps j >0 and unit price P(NT j )>0.

[0028] An Internet-based group purchase package intelligent settlement system also includes:

[0029] Coupon module: obtains the coupon information in the user account, the coupon information includes the usage requirements of the coupon and the total number of coupons YH;

[0030] According to the coupon usage requirements, the packages that meet the coupon usage requirements are screened out from the merchant's package database and marked as the second category recommended packages, and the second category recommended package with the lowest price is selected as the recommended package;

[0031] Each coupon corresponds to a recommended package, YH recommended packages are screened out, and all recommended packages are displayed to customers.

[0032] Beneficial effects of the present invention: The present invention automatically generates recommended packages by obtaining the group purchase package information of the user. First, the group purchase package information purchased by the user is obtained, the package is marked as the original package, and the corresponding price and quantity of goods are obtained. The purpose is to understand the user's desire to play this time, so as to make appropriate adjustments. If the price of the group purchase package purchased this time is high, it means that the user has a high desire to play this time, so when setting the recommended package, reasonable adjustments should be made to achieve the purpose of accurate recommendation.

[0033] Get the user's purchase history and calculate the user's average redemption time. The average redemption time can show the user's preference for the product. The shorter the average redemption time, the more frequently the user purchases the group purchase package. The average group purchase price S is calculated. ave The purpose is to understand the user's consumption capacity, so as to take the user's consumption capacity into consideration when recommending group purchase packages, and make recommendations when the user's consumption situation permits, thereby increasing the success rate of the recommendation.

[0034] The user's favorite coefficient is calculated by the formula. It can be seen from the formula that when the average group purchase price remains unchanged, the smaller the average redemption time, the larger the value of the favorite coefficient, and the average group purchase price S ave The increase will also lead to an increase in the liking coefficient X. It is understandable that for a product, the user is willing to spend a lot of time and money, which means that the user is interested in this product. Therefore, this formula can be used to express the user's liking for the product in the form of data, so as to specifically express the user's liking for the product. At the same time, it is also convenient for the subsequent setting of the number of products and the unit price of the recommended package.

[0035] The price function is used to calculate the unit price of the recommended package. The formula shows that the price function is a piecewise function. The number of items in the recommended package will fluctuate. According to common sense, the more items there are, the lower the price of the item. Conversely, the fewer items there are, the higher the price of the item. In the formula, the unit price P of the item in the original package is used. ori As a benchmark, the unit price of the goods is increased or decreased on this basis. After the unit price is calculated, the price of the recommended package is calculated according to the quantity and unit price of the goods, and a recommendation is made. If the user thinks that all the recommended packages are not suitable, the original package is selected. If there is a more preferred recommended package, when the user selects it, the corresponding recommended package is added to the shopping cart and settled. At this time, the coupons in the user account are obtained. If there are coupons that meet the usage conditions, the coupon with the largest discount amount is selected for use.

[0036] In summary, the present invention provides a group purchase package recommendation method, which enables users to have more choices through group purchase package recommendation, thereby better meeting the group purchase needs of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] Figure 1 The present invention is a structural schematic diagram of an Internet-based group purchase package intelligent settlement system. DETAILED DESCRIPTION

[0039] 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.

[0040] See also Figure 1 As shown, the present invention is an Internet-based group purchase package intelligent settlement system, comprising:

[0041] Information acquisition module: Mark the group purchase package purchased by the user as the original package and obtain the price S of the original package ori and the number of items in the group purchase package N ori , and calculate the unit price P of the product ori =S ori / N ori ;

[0042] Information processing module: The merchant obtains the consumption record of the user who purchased the group purchase package in this store and obtains the verification time T of the i-th group purchase package i , the price of group purchase package i and the number of items in the group purchase package N i , where i is a positive integer;

[0043] Calculate the purchase time interval ΔT i =T i -T i-1 , where ΔT i Represents the time interval between the verification of the i-th group purchase package and the i-1-th group purchase package, and calculates the average verification time The average group purchase price of group purchase packages purchased by users Where I represents the total number of times group purchase packages are purchased;

[0044] Information calculation module: Calculate the user's purchasing power coefficient X according to the average verification time and the average group purchase price. The calculation formula of the purchasing power coefficient X is as follows:

[0045]

[0046] Wherein, γ represents a preset first adjustment coefficient;

[0047] Calculate the product quantity fluctuation value Among them, N ave Represents the average number of items in the group purchase package purchased by the user, and sets 2J first recommended packages according to the fluctuation value of the number of items, where J is the preset first recommended package quantity threshold, and the number of items in the jth first recommended package is NT j =N ori +ρ·(jJ)·f, where ρ is the preset change value of the commodity quantity;

[0048] Information output module: according to the price function Calculate the unit price P(NT j ), where μ represents the preset price change coefficient;

[0049] Calculate the recommended price ST of the jth first recommended package j =P(NT j )*NTj , the number of items in the first recommended package is NT j ;

[0050] Obtain the merchant's package database, and filter out the group purchase packages in the package database that are close to the recommended price and quantity of goods as the recommended packages.

[0051] It should be noted that in order to automatically generate recommended packages by obtaining the user's group purchase package information, we first obtain the group purchase package information purchased by the user, mark this package as the original package, and obtain the corresponding price and quantity of goods. The purpose is to understand the user's desire to play this time, so as to make appropriate adjustments. If the price of the group purchase package purchased this time is high, it means that the user has a high desire to play this time, so when setting the recommended package, reasonable adjustments should be made to achieve the purpose of accurate recommendation.

[0052] Get the user's purchase history and calculate the user's average redemption time. The average redemption time can show the user's preference for the product. The shorter the average redemption time, the more frequently the user purchases the group purchase package. The average group purchase price S is calculated. ave The purpose is to understand the user's consumption capacity, so as to take the user's consumption capacity into consideration when recommending group purchase packages, and make recommendations when the user's consumption situation permits, thereby increasing the success rate of the recommendation.

[0053] The user's favorite coefficient is calculated by the formula. It can be seen from the formula that when the average group purchase price remains unchanged, the smaller the average redemption time, the larger the value of the favorite coefficient, and the average group purchase price S ave The increase will also lead to an increase in the liking coefficient X. It is understandable that for a product, the user is willing to spend a lot of time and money, which means that the user is interested in this product. Therefore, this formula can be used to express the user's liking for the product in the form of data, so as to specifically express the user's liking for the product. At the same time, it is also convenient for the subsequent setting of the number of products and the unit price of the recommended package.

[0054] The price function is used to calculate the unit price of the recommended package. The formula shows that the price function is a piecewise function. The number of items in the recommended package will fluctuate. According to common sense, the more items there are, the lower the price of the item. Conversely, the fewer items there are, the higher the price of the item. In the formula, the unit price P of the item in the original package is used. ori As a benchmark, the unit price of the goods is increased or decreased on this basis. After the unit price is calculated, the price of the recommended package is calculated according to the quantity and unit price of the goods, and a recommendation is made. If the user thinks that all the recommended packages are not suitable, the original package is selected. If there is a more preferred recommended package, when the user selects it, the corresponding recommended package is added to the shopping cart and the settlement is carried out.

[0055] In another preferred embodiment of the present invention, a method for selecting a group purchase package in a group purchase package database having a similar price and commodity quantity to the recommended package as a recommended package specifically includes:

[0056] The price fluctuation range of the jth first recommended package [ST j -A,ST j +A] and commodity quantity fluctuation range [NT j -B,NT j +B], where A is the preset price fluctuation coefficient and B is the preset commodity quantity fluctuation coefficient;

[0057] The group purchase packages in the group purchase package database are screened and the group purchase package prices are within the price fluctuation range [ST j -A,ST j +A] and the quantity of the product is within the fluctuation range of the quantity of the product [NT j -B,NT j +B] is marked as a candidate package, and the comprehensive value K of the i-th candidate package is calculated. i =|ST j -S i_pre |+|NT j -N i_pre |, select the candidate package with the smallest comprehensive value as the recommended package, where S i_pre represents the price of the i-th selected package, N j_pre Represents the number of items in the i-th package to be selected.

[0058] It is worth noting that the merchant's group purchase package database is obtained and the comprehensive value is calculated. The smaller the comprehensive value, the more the candidate package meets the requirements, so the candidate package with the lowest comprehensive value is selected as the recommended package.

[0059] In another preferred embodiment of the present invention, if the comprehensive values ​​of the to-be-selected packages are equal, the to-be-selected package with a lower price is preferentially selected as the recommended package.

[0060] It is worth noting that in actual situations, if the comprehensive values ​​of two candidate packages are equal and their corresponding comprehensive values ​​are both the smallest, in order to minimize the user's expenses, the candidate package with the lower price is selected as the recommended package.

[0061] In another preferred embodiment of the present invention, if the purchase time interval ΔT i ≤η, the i-th group purchase package and the i-1-th group purchase package are regarded as one group purchase package, and the price and quantity of the group purchase package are added together. The price and quantity of the i-th group purchase package and the i-1-th group purchase package are added together, respectively, where η represents the preset minimum time interval.

[0062] It is understandable that when users purchase goods, they find that there is a lack of group purchase packages that suit them, so they choose to purchase multiple group purchase packages in combination. Since the interval between two group purchase packages is very short, if they are processed separately, the average verification time will be shortened, resulting in a larger error in the final result, affecting the accuracy of the final result.

[0063] In another preferred embodiment of the present invention, the average group purchase price S is calculated. ave When the group purchase package purchased by the user does not participate in the average group purchase price S ave Calculation.

[0064] It should be noted that although the user has purchased a group purchase package, it is not certain whether the group purchase package is the most suitable for the user. Therefore, further recommendations are needed to determine whether the user chooses to change the group purchase package. If the user chooses to change the group purchase package, the corresponding price will also change, so the average group purchase price S is calculated. ave The group purchase package purchased this time will not be included in the calculation.

[0065] In another preferred embodiment of the present invention, when the commodity quantity fluctuation value f=0, if the commodity quantity N ori =N ave , then stop the subsequent steps and do not recommend the recommended package;

[0066] If the number of products N ori ≠N ave , then execute the subsequent steps normally.

[0067] It should be noted that if the merchant has a fixed group purchase package for a long time, and the user chooses the fixed package every time, at this time, due to the single data, it is impossible to observe the pattern based on the historical purchase records. If the group purchase package purchased by the user this time has not changed, there is no need to recommend the group purchase package to the user, and the subsequent steps will be stopped; if there is a change, it means that the user wants to try a new package, then it is normal at this time.

[0068] In another preferred embodiment of the present invention, the number of products NT of the jth recommended package is obtained. j The number of items in the group purchase package launched by the merchant N x , calculate the difference in the number of goods NC = NT j -N x If the difference in the number of goods NC is less than the preset minimum number of goods N min , at this time, select the lower-priced package as the recommended package.

[0069] It is understandable that if the quantity and price of goods in the recommended package are very close to the group purchase package set by the merchant, the lower-priced package will be given priority as the recommended package to ensure that users can purchase the group purchase package that suits them at a lower price.

[0070] In another preferred embodiment of the present invention, when setting the recommended set meal quantity threshold J, ensure that the j-th commodity quantity NT is calculated in the subsequent steps. j >0 and unit price P(NT j )>0.

[0071] It is worth noting that when setting the recommended package, it is necessary to ensure that the number of items in the group purchase package is greater than 0. If the value of the recommended package quantity threshold J is set too large, the unit price of the items in the recommended package will be negative, which is not in line with common sense. Therefore, it is necessary to ensure that the jth item quantity NT j >0 and unit price P(NT j )>0.

[0072] The present invention is an Internet-based group purchase package intelligent settlement system, which also includes:

[0073] Coupon module: obtains the coupon information in the user account, the coupon information includes the usage requirements of the coupon and the total number of coupons YH;

[0074] According to the coupon usage requirements, the packages that meet the coupon usage requirements are screened out from the merchant's package database and marked as the second category recommended packages, and the second category recommended package with the lowest price is selected as the recommended package;

[0075] Each coupon corresponds to a recommended package, YH recommended packages are screened out, and all recommended packages are displayed to customers.

[0076] It should be noted that when users use the group buying platform, they will receive coupons from the group buying platform or merchants. Using coupons can reduce the cost of purchasing group buying packages. In order to help users choose more favorable packages, recommended packages are selected for users based on coupons. This not only allows users to use coupons in a timely manner and prevent coupons from expiring, but also allows users to purchase suitable packages at a lower price, thereby improving the user experience.

[0077] Furthermore, the more recommended packages there are, the more options there are for users to choose from, and the greater the probability that users will select their favorite packages.

[0078] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An Internet-based group purchase package intelligent settlement system, characterized in that: include: Information acquisition module: Mark the group purchase package purchased by the user as the original package and obtain the price S of the original package ori and the number of items in the group purchase package N ori , and calculate the unit price P of the product ori =S ori / N ori ; Information processing module: The merchant obtains the consumption record of the user who purchased the group purchase package in this store and obtains the verification time T of the i-th group purchase package i , the price of group purchase package i and the number of items in the group purchase package N i , where i is a positive integer; Calculate the purchase time interval ΔT i =T i -T i-1 , where ΔT i Represents the time interval between the verification of the i-th group purchase package and the i-1-th group purchase package, and calculates the average verification time The average group purchase price of group purchase packages purchased by users Where I represents the total number of times group purchase packages are purchased; Information calculation module: Calculate the user's purchasing power coefficient X according to the average verification time and the average group purchase price. The calculation formula of the purchasing power coefficient X is as follows: X=γ·log(1+ΔT ave )Save; Wherein, γ represents a preset first adjustment coefficient; Calculate the product quantity fluctuation value Among them, N ave Represents the average number of items in the group purchase package purchased by the user, and sets 2J first recommended packages according to the fluctuation value of the number of items, where J is the preset first recommended package quantity threshold, and the number of items in the jth first recommended package is NT j =N ori +ρ·(jJ)·f, where ρ is the preset change value of the commodity quantity; Information output module: according to the price function Calculate the unit price P(NT j ), where μ represents the preset price change coefficient; Calculate the recommended price ST of the jth first recommended package j =P(NT j )*NT j , the number of items in the first recommended package is NT j ; Obtain the merchant's package database, filter out the group purchase packages in the package database that are close to the recommended price and quantity of goods as recommended packages, and display the recommended packages to customers.

2. According to claim 1, an Internet-based group purchase package intelligent settlement system is characterized in that: The method of selecting the group purchase packages in the group purchase package database that are similar to the recommended price and quantity of goods as the recommended packages specifically includes: The price fluctuation range of the jth first recommended package [ST j -A,ST j +A] and commodity quantity fluctuation range [NT j -B,NT j +B], where A is the preset price fluctuation coefficient and B is the preset commodity quantity fluctuation coefficient; The group purchase packages in the group purchase package database are screened and the group purchase package prices are within the price fluctuation range [ST j -A,ST j +A] and the quantity of the product is within the fluctuation range of the quantity of the product [NT j -B,NT j +B] is marked as a candidate package, and the comprehensive value K of the i-th candidate package is calculated. i =|ST j -S i_pre |+|NT j -N i_pre |, select the candidate package with the smallest comprehensive value as the recommended package, where S i_pre represents the price of the i-th selected package, N j_pre Represents the number of items in the i-th package to be selected.

3. The Internet-based group purchase package intelligent settlement system according to claim 2, characterized in that: If the comprehensive values ​​of the alternative packages are equal, the alternative package with the lower price will be selected as the recommended package.

4. The Internet-based group purchase package intelligent settlement system according to claim 1, characterized in that: If the purchase time interval ΔT i ≤η, the i-th group purchase package and the i-1-th group purchase package are regarded as one group purchase package, and the price and quantity of goods of the i-th group purchase package and the i-1-th group purchase package are added respectively, where η represents the preset minimum time interval.

5. The Internet-based group purchase package intelligent settlement system according to claim 1, characterized in that: Calculate the average group purchase price S ave When the group purchase package purchased by the user does not participate in the average group purchase price S ave Calculation.

6. The Internet-based group purchase package intelligent settlement system according to claim 1, characterized in that: When the commodity quantity fluctuation value f = 0, if the commodity quantity N ori =N ave , then stop the subsequent steps and do not recommend the recommended package; If the number of products N ori ≠N ave , then execute the subsequent steps normally.

7. The Internet-based group purchase package intelligent settlement system according to claim 1, characterized in that: Get the number of items in the jth recommended package NT j The number of items in the group purchase package launched by the merchant N x , calculate the difference in the number of goods NC = NT j -N x If the difference in the number of goods NC is less than the preset minimum number of goods N min , at this time, select the lower-priced package as the recommended package.

8. The Internet-based group purchase package intelligent settlement system according to claim 1, characterized in that: When setting the recommended package quantity threshold J, ensure that the j-th item quantity NT is calculated in the subsequent steps j >0 and unit price P(NT j )>0.

9. An Internet-based group purchase package intelligent settlement system, characterized in that: Also includes: Coupon module: obtains the coupon information in the user account, the coupon information includes the usage requirements of the coupon and the total number of coupons YH; According to the coupon usage requirements, the packages that meet the coupon usage requirements are screened out from the merchant's package database and marked as the second category recommended packages, and the second category recommended package with the lowest price is selected as the recommended package; Each coupon corresponds to a recommended package, YH recommended packages are screened out, and all recommended packages are displayed to customers.

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