CN115131089A - Commodity order generation method suitable for marketing service platform - Google Patents

Commodity order generation method suitable for marketing service platform Download PDF

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CN115131089A
CN115131089A CN202210529504.7A CN202210529504A CN115131089A CN 115131089 A CN115131089 A CN 115131089A CN 202210529504 A CN202210529504 A CN 202210529504A CN 115131089 A CN115131089 A CN 115131089A
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value
order
commodity
inventory
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刘怡
李海俊
刘厚友
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Zhejiang Pistachio Digital Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06Q30/00—Commerce
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    • G06Q30/0601—Electronic shopping [e-shopping]
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    • G06Q10/083—Shipping
    • G—PHYSICS
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The invention discloses a commodity order generation method suitable for a marketing service platform, which is characterized in that when a user logs in the marketing service platform, the potential analysis is automatically carried out on commodities required by the user, the commodities purchased by the user in the past are specifically obtained, the general consumption condition of the user for some consumables is determined according to the purchase quantity and the purchase time of the commodities, a user recommended commodity list is provided according to the consumption condition, and the user can conveniently and quickly select whether to purchase or not; then, after the commodity is adjusted and freely selected, the commodity for placing the order is determined; order generation processing is carried out on the ordered commodities, comprehensive analysis is carried out according to the storage condition of the ordered commodities corresponding to each delivery warehouse and the actual time of receiving the goods by the user, an optimal delivery warehouse is determined, and the benefits of the platform and the user can be balanced conveniently; the invention is simple, effective and easy to use.

Description

Commodity order generation method suitable for marketing service platform
Technical Field
The invention relates to the technical field of order generation, in particular to a commodity order generation method suitable for a marketing service platform.
Background
Patent publication No. CN112465610A discloses an order generation system and an order generation method, wherein the order generation system includes: the service platform is used for receiving the service request, determining a first occupation amount and first service information according to target equipment carried by the service request and attribute information of the target equipment, and sending the first service information to the service intermediate terminal if the first occupation amount is smaller than a second occupation amount corresponding to the service request terminal; the service intermediate terminal is used for adjusting the first service information into second service information according to the historical service order information and the identity information of the service request terminal and the occupation information of the target equipment, and sending the second service information to the service providing terminal; the service provider responds to the first confirmation operation aiming at the second service information and sends a confirmation request carrying the second service information to the service platform; and the service platform is also used for generating a service order based on the second service information. The method and the device improve the generation efficiency of the lease orders.
However, the patent only provides a way for order generation, but before the order is generated, the order assists the user to select and recommend the goods, so that the user can purchase the goods quickly, a reasonable way is lacked, and for the shipment of the goods, the prior art basically carries out the shipment nearby, and does not consider the combination of the warehousing condition and the user requirement, so as to provide a solution based on the reason.
Disclosure of Invention
The invention aims to provide a commodity order generation method suitable for a marketing service platform;
the purpose of the invention can be realized by the following technical scheme:
the commodity order generation method suitable for the marketing service platform specifically comprises the following steps:
the method comprises the following steps: when a user logs in a marketing service platform, the potential analysis is automatically carried out on commodities required by the user, and a placing selection interface is generated according to the potential analysis result; the specific potential analysis mode is as follows:
s1: acquiring a shopping record of a user in the last year, wherein the shopping record comprises the target quantity and the shopping time of a target marker;
s2: integrating all the shopping objects, if the same shopping objects exist, automatically fusing the same shopping objects, marking the value obtained by adding the corresponding object quantity as the total object value, and automatically forming a plurality of records for the corresponding shopping time to obtain a shopping time group, wherein each shopping time in the shopping time group is in one-to-one correspondence with the object quantity;
s3: then marking the corresponding object marker of which the total value of all the targets exceeds X1 as an inertial target, wherein X1 is a value preset by a manager; correspondingly updating the inertia targets, and the corresponding number of the plurality of inertia targets Li, i-1.. n and the shopping time group Gi, i-1.. n; here, Li and Gi are in one-to-one correspondence, which means that Li inertia targets are purchased at the shopping time of Gi, and the order of Gi and Li is from front to back according to the time of the corresponding Gi;
s4: then, an inertial target is selected optionally, and is temporarily marked as a winning target;
s5: and (3) calculating the unit consumption time Di by using a formula, wherein the specific calculation formula is as follows:
Figure BDA0003645605560000021
in the formula, i is 1.. n-1;
s6: when n-1 groups of unit consumption are obtained, performing integrated treatment on the unit consumption to obtain a time consumption range;
s7: then, the last shopping time Gn and the target quantity Ln are obtained, the time length between the time when the user logs in the marketing service platform and the last shopping time Gn is automatically obtained, and the time length is marked as the hanging time length;
s8: determining the suspension loss range by using a formula, which specifically comprises the following steps: the suspension consumption range is Ln (time consumption range + alpha), wherein alpha is an influence factor and is a preset value for managers; when the suspension duration is within the suspension consumption range, automatically generating a recommendation signal, and marking the corresponding object marker as a recommendation marker;
s9: optionally selecting the next inertia target, repeating the steps S4-S9 to obtain all recommendation targets, and automatically combining to form a recommendation target group;
step two: after a user freely selects articles by means of a recommended target group and himself on a marketing service platform, determining good order goods;
step three: and carrying out order generation processing on the order-placed commodities to obtain delivery warehouses of all the order-placed commodities.
Further, the object of the step S1 is referred to as the purchased goods, the number of the objects is referred to as the current order number corresponding to the purchased object, and the shopping time is referred to as the order getting time corresponding to the object of the purchase.
Further, the specific way of the centralization processing in step S6 is:
calculating to obtain the average value of Di, and marking the average value as P; and calculating the dispersion value W of the Di according to a formula, wherein the specific calculation formula is as follows:
Figure BDA0003645605560000031
where | is expressed as taking the absolute value of the number in parentheses;
when W is less than or equal to X2, a passing signal is generated, the maximum value of Di and the median of P are rounded and then marked as an upper time consumption limit, the minimum value of Di and the median of P are rounded and then marked as a lower time consumption limit, and the lower time consumption limit and the upper time consumption limit are combined to form a time consumption range;
otherwise, automatically according to | D i Sequentially selecting Di from large to small, deleting the Di when one Di value is selected, and then recalculating dispersion values W of the rest Di until W is less than or equal to X2; automatically acquiring a time-consuming range after the Di meeting the condition is obtained; x2 is a predetermined value.
Further, the order generation processing in the third step is specifically as follows:
s01: obtaining all ordering commodities, and optionally ordering the commodities;
s02: automatically acquiring all warehouses corresponding to the order commodity, and marking the warehouses as warehouses to be selected Cj, j being 1.. m;
s03: acquiring the inventory of the ordering commodity in the warehouse to be selected, and marking the inventory as a remainder value Yj, wherein j is 1.
S04: acquiring a transportation distance between a warehouse to be selected and a corresponding ordering address of a user, wherein the transportation distance refers to the distance between the warehouse to be selected and the ordering address in transportation, and is marked as Kj, and j is 1.. m; acquiring corresponding transportation cost, wherein the transportation cost refers to the transportation fee which needs to be paid for transporting the order-placing goods from the warehouse to be selected to the corresponding order-placing address and corresponds to the marketing service platform, and the transportation cost is marked as Fj, and j is 1.. m;
s05: residual analysis is carried out on the next commodity of the warehouse to be selected, and the time length upper limit Uj and the redundancy quantity value Rj of the corresponding warehouse to be selected are obtained, wherein j is 1.
S06: obtaining a remainder value Yj, a transportation distance Kj, a transportation cost Fj, a time upper limit Uj and a redundancy value Rj of the corresponding ordering commodity in each warehouse to be selected Cj;
s07: calculating the selected median value Qj according to a formula, wherein the specific calculation formula is as follows:
Figure BDA0003645605560000041
in the formula, 0.16, 0.22, 0.24 and 0.38 are all preset weights;
s08: then marking the warehouse to be selected with the maximum corresponding Qj value as a delivery warehouse;
s09: and (4) optionally selecting the next order commodity, repeating the steps S02-S09, and obtaining the delivery warehouse of all the order commodities after all the order commodities are processed.
Further, the specific manner of the residue analysis in step S05 is as follows:
acquiring the inventory value of the corresponding order placing goods, and marking the order placing goods in each inventory as inventory single goods;
acquiring the inventory duration corresponding to each inventory item, wherein the inventory duration refers to the total duration of the corresponding inventory item in the warehouse to be selected;
acquiring the maximum value of the inventory duration, and marking the maximum value as an upper duration limit Uj, j being 1.. m; multiplying the time length upper limit by 0.75 to obtain a value which is marked as a time length lower limit;
acquiring the quantity of the inventory items of which the inventory time length is between the lower time length limit and the upper time length limit, and marking the quantity as a redundancy value Rj, wherein j is 1.
Further, after the third step, the following steps are required:
and generating an order according to the delivery warehouse and the ordering situation, and scheduling delivery.
The invention has the beneficial effects that:
when a user logs in a marketing service platform, the method and the system automatically perform potential analysis on the commodities required by the user, specifically acquire the commodities purchased by the user in the past, determine the approximate consumption condition of the user for some consumables according to the purchase quantity and the shopping time of the commodities, and provide a user recommended commodity list according to the consumption condition, so that the user can conveniently and quickly select whether to purchase the consumables; then, after the free selection of the articles is adjusted by the user, ordering goods are determined;
the order generation processing is carried out on the ordered commodities, and an optimal delivery warehouse is determined according to the storage condition of the ordered commodities corresponding to each delivery warehouse and the time of actually receiving the commodities by the user, so that the benefits of both the platform and the user can be balanced conveniently; the invention is simple, effective and easy to use.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a commodity order generation method suitable for a marketing service platform according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the present invention is a method for generating a commodity order suitable for a marketing service platform, which specifically includes the following steps:
the method comprises the following steps: when a user logs in a marketing service platform, the potential analysis is automatically carried out on commodities required by the user, and a placing selection interface is generated according to the potential analysis result; the specific potential analysis mode is as follows:
s1: acquiring a shopping record of a user in the last year, wherein the shopping record comprises the target quantity and the shopping time of a target marker; the purchasing object is referred to as a purchased commodity, the target quantity is referred to as the current order placing quantity of the corresponding purchasing targets, and the shopping time is referred to as the order placing time of the corresponding purchasing object;
s2: integrating all the shopping marks, if the same shopping marks exist, automatically fusing the same shopping marks, marking the value obtained by adding the corresponding number of the marks as a total value of the marks, and automatically forming a plurality of records for the corresponding shopping time to obtain a shopping time group, wherein each shopping time in the shopping time group is in one-to-one correspondence with the number of the marks;
s3: marking all the corresponding object markers with the total value exceeding X1 as inertial markers, wherein X1 is a value preset by a manager; correspondingly updating the inertia targets, and the corresponding number of the plurality of inertia targets Li, i-1.. n and the shopping time group Gi, i-1.. n; li and Gi are in one-to-one correspondence, which means that Li inertia targets are purchased at the purchase time of Gi, wherein the order of Gi and Li is arranged in front of the corresponding Gi according to the sequence of the time from front to back;
s4: then, an inertial target is selected optionally, and is temporarily marked as a winning target;
s5: and (3) calculating the unit consumption time Di by using a formula, wherein the specific calculation formula is as follows:
Figure BDA0003645605560000061
in the formula, i is 1.. n-1;
s6: when n-1 groups of unit consumption are obtained, carrying out integrated treatment on the unit consumption, specifically comprising the following steps:
calculating to obtain the average value of Di, and marking the average value as P; calculating the dispersion value W of Di according to a formula, wherein the specific calculation formula is as follows:
Figure BDA0003645605560000062
where | is expressed as taking the absolute value of the number in parentheses;
when W is less than or equal to X2, a passing signal is generated, the maximum value of Di and the median of P are rounded and then marked as an upper time-consuming limit, the minimum value of Di and the median of P are rounded and then marked as a lower time-consuming limit, and the lower time-consuming limit and the upper time-consuming limit are combined to form a time-consuming range;
otherwise, automatically according to | D i Sequentially selecting Di from large to small, deleting the Di when one Di value is selected, and then recalculating dispersion values W of the rest Di until W is less than or equal to X2; after the Di meeting the condition is obtained, automatically obtaining a time-consuming range according to the method; x2 is a predetermined number;
s7: then, the last shopping time Gn and the target quantity Ln are obtained, the time length between the time when the user logs in the marketing service platform and the last shopping time Gn is automatically obtained, and the time length is marked as the hanging time length;
s8: determining the suspension loss range by using a formula, specifically: the suspension consumption range is Ln (time consumption range + alpha), wherein alpha is an influence factor and is a preset value for managers; when the suspension duration is within the suspension consumption range, automatically generating a recommendation signal, and marking the corresponding object marker as a recommendation marker;
s9: optionally selecting the next inertia target, repeating the steps S4-S9 to obtain all recommendation targets, and automatically combining to form a recommendation target group;
step two: after a user freely selects articles by means of a recommended target group and himself on a marketing service platform, determining good order goods;
step three: order generation processing is carried out on the order-placed commodity, and the specific mode of order generation processing is as follows:
s01: obtaining all ordering commodities, and optionally ordering the commodities;
s02: automatically acquiring all warehouses corresponding to the order commodity, and marking the warehouses as warehouses to be selected Cj, j being 1.. m;
s03: acquiring the inventory of the ordering commodity in the warehouse to be selected, and marking the inventory as a remainder value Yj, wherein j is 1.
S04: acquiring a transportation distance between a warehouse to be selected and a corresponding ordering address of a user, wherein the transportation distance refers to the distance between the warehouse to be selected and the ordering address in transportation, and is marked as Kj, and j is 1.. m; acquiring corresponding transportation cost, wherein the transportation cost refers to the transportation fee which is required to be paid for transporting the order placing commodities from the to-be-selected warehouse to the corresponding order placing address and corresponds to the marketing service platform, and the transportation cost is marked as Fj, and j is 1.. m;
s05: and performing remainder analysis on the commodities to be sorted in the warehouse, wherein the concrete remainder analysis mode is as follows:
acquiring the inventory value of the corresponding order placing commodity, and marking the order placing commodity of each inventory as an inventory item;
acquiring the inventory duration corresponding to each inventory item, wherein the inventory duration refers to the total inventory duration of the corresponding inventory item in the warehouse to be selected;
acquiring the maximum value of the inventory duration, and marking the maximum value as an upper duration limit Uj, j being 1.. m; multiplying the time length upper limit by 0.75 to obtain a value which is marked as a time length lower limit;
acquiring the quantity of the inventory items when the inventory duration of the inventory items is between the lower limit of the duration and the upper limit of the duration, and marking the quantity as a redundancy value Rj, j being 1.. m;
s06: obtaining a remainder value Yj, a transportation distance Kj, a transportation cost Fj, a time upper limit Uj and a redundancy value Rj of the corresponding ordering commodity in each warehouse to be selected Cj;
s07: calculating the selected median value Qj according to a formula, wherein the specific calculation formula is as follows:
Figure BDA0003645605560000081
in the formula, 0.16, 0.22, 0.24 and 0.38 are all preset weights;
s08: then marking the warehouse to be selected with the maximum corresponding Qj value as a delivery warehouse;
s09: optionally selecting the next order commodity, repeating the steps S02-S09, and obtaining a delivery warehouse of all the order commodities after all the order commodities are processed;
step four: and generating an order according to the delivery warehouse and the ordering situation, and scheduling delivery.
Although one embodiment of the present invention has been described in detail, the description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.

Claims (6)

1. The commodity order generation method suitable for the marketing service platform is characterized by comprising the following steps:
the method comprises the following steps: when a user logs in a marketing service platform, the potential analysis is automatically carried out on commodities required by the user, and a placing selection interface is generated according to the potential analysis result; the specific potential analysis mode is as follows:
s1: acquiring a shopping record of a user in the last year, wherein the shopping record comprises the target quantity and the shopping time of a target marker;
s2: integrating all the shopping marks, if the same shopping marks exist, automatically fusing the same shopping marks, marking the value obtained by adding the corresponding number of the marks as a total value of the marks, and automatically forming a plurality of records for the corresponding shopping time to obtain a shopping time group, wherein each shopping time in the shopping time group is in one-to-one correspondence with the number of the marks;
s3: marking all the corresponding object markers with the total value exceeding X1 as inertial markers, wherein X1 is a value preset by a manager; correspondingly updating the inertia targets, and corresponding target numbers Li, i-1.. n and shopping time groups Gi, i-1.. n of the inertia targets; here, Li and Gi are in one-to-one correspondence, which means that Li inertia targets are purchased at the shopping time of Gi, and the order of Gi and Li is from front to back according to the time of the corresponding Gi;
s4: then, an inertial target is selected optionally, and is temporarily marked as a winning target;
s5: and (3) calculating the unit consumption time Di by using a formula, wherein the specific calculation formula is as follows:
Figure FDA0003645605550000011
n-1 in the formula;
s6: when n-1 groups of unit consumption are obtained, performing integrated treatment on the unit consumption to obtain a time consumption range;
s7: then, the last shopping time Gn and the target quantity Ln are obtained, the time length between the time when the user logs in the marketing service platform and the last shopping time Gn is automatically obtained, and the time length is marked as the hanging time length;
s8: determining the suspension loss range by using a formula, specifically: the suspension consumption range is Ln (time consumption range + alpha), wherein alpha is an influence factor and is a preset value for managers; when the suspension duration is within the suspension range, automatically generating a recommendation signal, and marking the corresponding object marker as a recommendation marker;
s9: optionally selecting the next inertia target, repeating the steps S4-S9 to obtain all recommendation targets, and automatically combining to form a recommendation target group;
step two: after the user freely selects articles by means of the recommended target group and the user on the marketing service platform, determining the order-placing commodities;
step three: and carrying out order generation processing on the order-placed commodities to obtain delivery warehouses of all the order-placed commodities.
2. The method for generating a commodity order suitable for a marketing service platform according to claim 1, wherein the object is referred to as a purchased commodity in step S1, the object number is referred to as a current order placing number corresponding to the purchase object, and the shopping time is referred to as an order placing time corresponding to the object.
3. The method for generating a commodity order suitable for a marketing service platform according to claim 1, wherein the step S6 is centralized in a specific manner:
calculating to obtain the average value of Di, and marking the average value as P; and calculating the dispersion value W of the Di according to a formula, wherein the specific calculation formula is as follows:
Figure FDA0003645605550000021
where | is expressed as taking the absolute value of the number in parentheses;
when W is less than or equal to X2, a passing signal is generated, the maximum value of Di and the median of P are rounded and then marked as an upper time-consuming limit, the minimum value of Di and the median of P are rounded and then marked as a lower time-consuming limit, and the lower time-consuming limit and the upper time-consuming limit are combined to form a time-consuming range;
otherwise, automatically according to | D i Sequentially selecting Di from large to small, deleting the Di when selecting one Di value, and then recalculating the dispersion value W of the rest Di until the dispersion value W is less than or equal to X2; automatically acquiring a time-consuming range after the Di meeting the condition is obtained; x2 is a preset number.
4. The method for generating a commodity order suitable for a marketing service platform according to claim 1, wherein the order generation processing in the third step is specifically:
s01: obtaining all ordering commodities, and optionally ordering the commodities;
s02: automatically acquiring all warehouses corresponding to the order placing commodity, and marking the warehouses as warehouses to be selected Cj, wherein j is 1.
S03: acquiring the inventory quantity of the next commodity in the warehouse to be selected, and marking the inventory quantity as a remainder value Yj, wherein j is 1.. m;
s04: acquiring a transportation distance between a warehouse to be selected and a corresponding ordering address of a user, wherein the transportation distance refers to the distance between the warehouse to be selected and the ordering address in transportation, and is marked as Kj, and j is 1.. m; acquiring corresponding transportation cost, wherein the transportation cost refers to the transportation fee which needs to be paid for transporting the order-placing goods from the warehouse to be selected to the corresponding order-placing address and corresponds to the marketing service platform, and the transportation cost is marked as Fj, and j is 1.. m;
s05: residual analysis is carried out on the next commodity of the warehouse to be selected, and the time length upper limit Uj and the redundancy quantity value Rj of the corresponding warehouse to be selected are obtained, wherein j is 1.
S06: obtaining a remainder value Yj, a transportation distance Kj, a transportation cost Fj, a time upper limit Uj and a redundancy value Rj of the corresponding ordering commodity in each warehouse to be selected Cj;
s07: calculating the selected median value Qj according to a formula, wherein the specific calculation formula is as follows:
Figure FDA0003645605550000031
in the formula, 0.16, 0.22, 0.24 and 0.38 are all preset weights;
s08: then marking the warehouse to be selected with the maximum corresponding Qj value as a delivery warehouse;
s09: and (5) selecting the next order commodity, repeating the steps S02-S09, and obtaining the delivery warehouses of all the order commodities after all the order commodities are processed.
5. The method for generating a commodity order suitable for a marketing service platform according to claim 4, wherein the remaining analysis in step S05 is carried out by:
acquiring the inventory value of the corresponding order placing commodity, and marking the order placing commodity of each inventory as an inventory item;
acquiring the inventory duration corresponding to each inventory item, wherein the inventory duration refers to the total inventory duration of the corresponding inventory item in the warehouse to be selected;
acquiring the maximum value of the inventory duration, and marking the maximum value as an upper duration limit Uj, wherein j is 1.. m; multiplying the time length upper limit by 0.75 to obtain a value which is marked as a time length lower limit;
acquiring the quantity of the inventory items of which the inventory time length is between the lower limit of the inventory time length and the upper limit of the inventory time length, and marking the quantity as a redundancy value Rj, j-1.. m.
6. The method of claim 4, wherein after the step three, the following steps are further performed:
and generating an order according to the delivery warehouse and the ordering situation, and scheduling delivery.
CN202210529504.7A 2022-05-16 2022-05-16 Commodity order generation method suitable for marketing service platform Pending CN115131089A (en)

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