WO2018153176A1 - Order processing method and device - Google Patents

Abstract

An order processing method and device. The method comprises: determining identifier information of a target commodity and identifier information of a user who purchases the target commodity (S101); determining a next order time of the target commodity according to the identifier information of the target commodity and the identifier information of the user who purchases the target commodity (S102); when the next order time of the target commodity arrives, automatically placing an order of the target commodity or sending a purchasing prompt to the user (S103).

Description

Order processing method and device Technical field

This document relates to, but is not limited to, the field of computer technology, and in particular, to an order processing method and device.

Background technique

Shopping is an important and necessary behavior for everyone and every family. For both individuals and families, most shopping is for the purchase of consumables such as oil, salt, sauce, vinegar, tea, such as milk powder, laundry detergent, etc. These consumables need to be purchased almost cyclically. . However, when the above consumables are exhausted, they may forget to buy.

In the era of mobile Internet, online shopping has become more convenient and intelligent. When consumables are used up, users usually need to make repeated order purchases on e-commerce websites, or purchase them regularly (fixed cycle).

Summary of the invention

The following is an overview of the topics detailed in this document. This Summary is not intended to limit the scope of the claims.

The embodiment of the invention provides an order processing method and device.

The technical solution of the embodiment of the present invention is implemented as follows:

In a first aspect, an embodiment of the present invention provides an order processing method, where the method includes:

Determining identification information of the target item and identification information of the user who purchased the target item;

Determining, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the next ordering time of the target commodity;

When the next order time of the target item arrives, the target item is automatically placed or a shopping reminder is sent to the user.

In a second aspect, an embodiment of the present invention provides an order processing device, where the device includes:

a first determining module, configured to determine identification information of the target item and identification information of the user who purchased the target item;

a second determining module, configured to determine, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, a next ordering time of the target commodity;

The order module is configured to automatically place an order for the target item or send a shopping reminder to the user when the next order time of the target item arrives.

An embodiment of the present invention provides an order processing method and device, which first determines identification information of a target product and identification information of a user who purchases the target product; and then, according to the identification information of the target product and the purchase of the target product Determining, by the user, the purchase record of the target product, and determining the next order time of the target item according to the purchase record of the user purchasing the target item; the next time the target item is reached When placing an order, the target item is automatically placed or a shopping reminder is sent to the user. In this way, according to the user's purchase record, the user's next purchase time can be predicted, and the user is prompted to make a purchase or automatically place an order, thereby improving the user experience.

Other aspects will be apparent upon reading and understanding the drawings and detailed description.

BRIEF abstract

1 is a schematic flowchart of an implementation process of an order processing method according to an embodiment of the present invention;

2 is a schematic flowchart of an implementation process of another order processing method according to an embodiment of the present invention;

3 is a schematic structural diagram of an order processing device according to an embodiment of the present invention;

4-1 is a schematic flowchart of an implementation process of another order processing method according to an embodiment of the present invention;

Figure 4-2 is a schematic diagram showing the implementation process of the second implementation manner of adding goods to the smart purchase list;

4-3 is a schematic flowchart of implementing an intelligent purchase data according to an embodiment of the present invention;

4-4 is a schematic diagram of a time axis for calculating a next purchase time of an item according to an embodiment of the present invention;

4-5 are schematic diagrams showing a time axis in which a user randomly purchases according to an embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an order processing device according to an embodiment of the present invention.

Embodiments of the invention

The specific technical solutions of the invention will be further described in detail below with reference to the accompanying drawings in the embodiments of the invention. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.

When the consumables are used up, the user needs to make a repetitive order purchase on the e-commerce website, or purchase on a regular (fixed cycle), and it is impossible to intelligently and automatically predict that the user's goods are used up, reminding the user to make up or automatically Single purchase

The embodiment of the present invention provides an order processing method, which is applied to an order processing device, and the order processing device may include a mobile phone, a tablet computer, a notebook computer, and the like in an actual application. FIG. 1 is a schematic flowchart of an implementation process of an order processing method according to an embodiment of the present invention. As shown in FIG. 1 , the method includes:

Step S101, determining identification information of the target item and identification information of the user who purchased the target item;

Here, the order processing list includes identification information of the target item, identification information of the user who purchased the target item, a next order time of the target item, and a purchase method. For example, the identification information of the target product may be a product code, and the identification information of the user who purchases the target product may be an identification code (Identification, ID).

Step S102, determining, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the next ordering time of the target commodity;

Here, the step S102 includes:

Step S102a, determining, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the historical record of the user purchasing the target commodity;

In other embodiments of the present invention, the history of the user purchasing the target item includes at least: a purchase time, a quantity of purchase, and a specification of the target item of the target item purchased by the user.

Step S102b: Determine a next order time of the target item according to the historical record of the user purchasing the target item.

Step S103, when the next order time of the target item arrives, the target item is automatically placed or sent to the user.

Here, before step S103, the method further includes: determining whether the next order time of the target item arrives.

In other embodiments of the present invention, determining whether the next order time of the target item arrives may be implemented by means of message triggering, or may be implemented by means of polling.

If the determining whether the next order time of the target item arrives is achieved by means of message triggering, in a practical application process, a message timing clock of the next order time of the target item may be set. When the system time reaches the time of the message timing clock, a message is triggered which is used to indicate the next order time for the arrival of the target item.

If the determining whether the next order time of the target item arrives is achieved by means of polling, in the actual application process, the timed query task (such as 8:00 every day) is started to query the target item. Whether the next order will arrive.

The preset purchase time may be set as the next order time of the target item is today, or may be set to the next order time of the target item is advanced N days, wherein N is greater than or equal to 1 Natural number.

In the order processing method provided by the embodiment of the present invention, first, identification information of a target product and identification information of a user who purchases the target product are first determined; and then, according to the identification information of the target product and the user who purchases the target product Identification information, determining a purchase record of the target product purchased by the user, and determining a next order time of the target item according to the purchase record of the user purchasing the target item; when the target item is reached next time In a single time, the target item is automatically placed or a shopping reminder is sent to the user. In this way, according to the user's purchase record, the user's next purchase time can be predicted, and the user is prompted to make a purchase or automatically place an order, thereby improving the user experience.

Based on the foregoing embodiments, an embodiment of the present invention further provides an order processing method, which is applied to an order processing device. 2 is a schematic flowchart of an implementation process of another order processing method according to an embodiment of the present invention. As shown in FIG. 2, the method includes:

In step S201, the order processing device determines whether the identification information of the item that the user has purchased is in the order processing list.

Here, the order processing device may be an electronic device such as a smart phone, a tablet computer, a notebook computer, a desktop computer or the like.

After the purchase of the commodity is completed, the order processing device determines whether the identification information of the commodity that the user has purchased is in the order processing list, and if the identification information of the purchased commodity is in the order processing list, then proceeds to step S204, if the purchased If the identification information of the item is not in the order processing list, the process proceeds to step S202.

For example, a user with a user ID of 123 purchases a barrel of peanut oil encoded as HS456. After the purchase is completed, the order processing device determines whether the HS 456 is in the order processing list.

Step S202: If the identification information of the item that the user has purchased is not in the order processing list, the order processing device determines whether the number of times the user purchases the purchased item reaches a preset threshold.

Here, if the number of times the user purchases the purchased item reaches a preset threshold, then the process proceeds to step S203, and if the number of times the user purchases the purchased item does not reach the preset threshold, the process ends.

If the identification information of the purchased product of the user is not in the order processing list, determining, according to the identification information of the purchased product and the identification information of the user, the history record of the purchased product by the user, and then according to The user purchases a history record of the purchased product, determines the number of times the user purchases the purchased product, and further determines whether the number of times the user purchases the purchased product reaches a preset threshold.

For example, if the product code HS456 is not in the order processing list, the order processing device queries the history record of the user ID 123, calculates the number of times the user purchases the product coded as HS 456, and determines that the user purchases the product coded as HS 456. Whether the number of times reaches a preset threshold, for example, the preset threshold is 5.

Step S203, if the number of purchases of the purchased item reaches a preset threshold, the order processing device adds the identification information of the item that the user has purchased and the identification information of the user to the order processing list. .

Here, for example, if the user whose user ID is 123 purchases the peanut oil having the product code of HS456 up to 5 times, the user ID 123 and the article code HS 456 are added to the order processing list.

Step S204, the order processing device determines, according to the identification information of the purchased product and the identification information of the user, a history record of the user purchasing the purchased product;

Here, since the purchased merchandise is added to the order processing list, the purchased merchandise in the embodiment of the present invention is the target merchandise in other embodiments of the present invention.

Step S205, the order processing device determines the next order time of the target item according to the history record of the user purchasing the purchased item.

Here, according to the history record of the purchased purchase of the user, determining the next order time of the purchased item, the exemplary embodiment of the present invention provides an exemplary calculation method.

The first calculation method: determining the next order time of the purchased item according to the average consumption speed of the purchased item, including the following steps:

Step S2051a, confirming, according to the history record of the purchased product by the user, confirming the purchase information that the user purchases the purchased product for the first time to the nth purchase of the purchased product;

Here, the purchase information of the purchased item of the nth time is the purchase information of the purchased item that was purchased last time, and the purchase information of the purchased item of the i-th purchase is the purchase time t _i , the quantity of purchase n _i and The specification s _i , i of the purchased product is a natural number between 1 and n;

Step S2051b, determining, according to the purchase information of the first purchase of the purchased item by the user to the nth purchase of the purchased item, the average consumption speed V′ of the purchased item between t ₁ and t _n ;

Here, the total purchase amount of the target commodity between t ₁ and t _n is determined according to the purchase information of the first purchase of the target merchandise by the user to the nth purchase of the target merchandise; according to t ₁ to t _n the target product between the total amount of the purchase and the time t _{t. 1} to determine the difference between the t _n and _{t. 1 n} between the average consumption rate of the target product V '.

In an actual application, the average consumption speed V' of the purchased goods between t ₁ and t _n can be determined according to the formula (2-1).

Wherein, in formula (2-1), t _i is the purchase time of the purchased purchase of the i-th purchase, n _i is the purchase quantity of the purchased product of the i-th purchase, and s _i is the i-th purchase The specifications of the purchased goods, i = 1, 2, ..., n.

Step S2051c, determining the next order time of the purchased item according to the average consumption speed of the purchased item and the purchase information of the target item purchased for the nth time.

Here, the usage time of the target item of the nth purchase is determined according to the average speed of the target item and the purchase information of the target item for the nth purchase; and the purchase time of the target item according to the nth purchase is further The usage duration of the target item purchased for the nth time determines the next order time of the target item.

With V _n represents the n-th time is later purchased goods to the first _n T n + 1 times later time the purchased items consumed t _{n +} n _n S _n velocity between _{1 and n} be the V Obtained by the formula (2-2).

Wherein, in the formula (2-2), n _n is the n th later purchased quantity of purchases, S _n of the n-th later purchased goods specifications.

The formula (2-3) for calculating t _n+1 can be obtained from the formula (2-2):

With the average velocity V' as v _n , ie v _n =V', there is the formula (2-4):

a second calculation method: determining that the average acceleration of the purchased commodity is consumed between the average speeds V′ and t ₁ to t _{n of the} purchased commodity between the t ₁ and t _n-1 The next purchase time of the purchased item, including the following steps:

Step S2052a, confirming, according to the history record of the purchased item by the user, confirming the purchase information of the purchased item to the nth purchase of the purchased item for the first time;

Here, the purchase information of the purchased item of the nth time is the purchase information of the purchased item that was purchased last time, and the purchase information of the purchased item of the i-th purchase is the purchase time t _i , the quantity of purchase n _i and The specification s _i , i of the purchased product is a natural number between 1 and n;

Step S2052b, determining, according to the purchase information of the first purchase of the purchased item by the user to the nth purchase of the purchased item, determining an average speed V′ of the purchased item between t ₁ and t _n-1 And consuming an average acceleration of the purchased item between t ₁ and t _n ;

Here, the average speed V' of the purchased commodity between t ₁ and t _n-1 is determined according to the formula (2-5).

Determining an average consumption speed v _{1 of} the target commodity between t ₁ and t ₂ according to formula (2-6);

Determining an average consumption speed v _{n-1 of} the target commodity between t ₁ and t _n according to formula (2-7);

The average acceleration of the target commodity consumed between t ₁ and t _n is determined according to the formula (2-8).

Step S2052c, according to the consumption of between ₁ and t _n-1 t is the average velocity purchases V 'and t ₁ to t _n between said average acceleration consumption goods has been purchased, the purchased items is determined The next purchase time.

Here, from equation (2-2), formula (2-9) can be obtained.

Let Δt=t _n+1 -t _n , then formula (2-10) can be obtained from v _n = v _n-1 + aΔt and formula (2-9)

Formula (2-10) is sorted and transformed to obtain the formula (2-11)

aΔt ² +v _n-1 Δt-n _n s _n =0 (2-11);

The average velocity V' of the purchased commodity between t ₁ and t _n-1 is taken as v _n-1 into the formula (2-11), and the quadratic equation of the formula (2-11) is solved. Δt is determined, and according to formula (2-12), the next order time t _{n+1 of the} purchased item is determined. If there is no solution, the first calculation method can be used to determine the next order time t _{n+1 of the} purchased product.

t _n+1 =t _n +Δt (2-12);

Third Calculation Method: The t between the _{consumption. 1} to t _n and t is the average acceleration of purchases _n-1 and t _n between the consuming speed v commodity _n-1, the determination has been The next purchase time of the purchased item, including the following steps:

Step S2053a, confirming, according to the history record of the purchased product by the user, confirming purchase information of the purchased product to the nth purchase of the purchased product for the first time;

Here, the purchase information of the purchased item of the nth time is the purchase information of the purchased item that was purchased last time, and the purchase information of the purchased item of the i-th purchase is the purchase time t _i , the quantity of purchase n _i and The specification s _i , i of the purchased product is a natural number between 1 and n;

Step S2053b, according to the first user to purchase the goods purchased to the n-th information for later purchase the goods purchased and to determine an average _{acceleration. 1} to t t t _n between the consumption of purchased items _n- The consumption speed of the commodity between ₁ and t _n is v _n-1 ;

Here, the consumption speed v _{n-1 of} the article between t _n-1 and t _n is determined according to the formula (2-7), and is determined according to the formulas (2-6), (2-7), and (2-8). The average acceleration of the purchased item is consumed between t ₁ and t _n .

Step S2054c, according to _{t. 1} between the t _n and t are average acceleration consuming the purchased items to t _n-1 of the product between the consuming speed v _{n n-1,} determining the purchased commodity Next purchase time.

Here, the formula (2-7) is substituted into the formula (2-11), and the quadratic equation of the formula (2-11) is solved to obtain Δt, and then according to the formula (2-12), the purchased product is determined. Order time t _{n+1 at} a time. If there is no solution, the first calculation method can be used to determine the next order time t _{n+1 of the} purchased product.

Step S206, the order processing device determines whether the next order time of the purchased item is reached.

Step S207, if the next order time of the purchased item arrives, the order processing device determines the purchase mode set by the user;

Step S208, the order processing device performs the purchase according to the purchase mode set by the user.

It should be noted that the description of the same steps or concepts in the other embodiments may refer to the description in other embodiments, and details are not described herein again.

In the order processing method provided by the embodiment of the present invention, first, identification information of a target product and identification information of a user who purchases the target product are first determined; and then, according to the identification information of the target product and the user who purchases the target product Identification information, determining a purchase record of the target product purchased by the user, and determining a next order time of the target item according to the purchase record of the user purchasing the target item; when the target item is reached next time In a single time, the target item is automatically placed or sent to the user according to the purchase mode set by the user. In this way, according to the user's purchase record, the user's next purchase time can be predicted, and the user is prompted to make a purchase or automatically place an order, thereby improving the user experience.

Based on the foregoing embodiments, an embodiment of the present invention further provides an order processing method, which is applied to an order processing device. In the embodiment of the present invention, the identification information of the target item purchased by the user already exists in the order processing list, and the next purchase time of the target item has been calculated. The order processing method provided by the embodiment of the present invention includes the following steps:

First, the order processing device determines whether the time when the user last purchased the target item is earlier than the next purchase time of the target item in the order processing list; if the time when the user last purchased the target item If the next purchase time of the target item is earlier than the order processing list, the process proceeds to the second step if the user purchases the target item last time no earlier than the next purchase of the target item in the order processing list. Time, the process ends.

Here, because when there are various festivals, the product may be discounted, the user may not have purchased the next purchase time of the target product, and then the next purchase of the target product in the order processing list needs to be updated. time.

In the second step, if the time when the user purchases the product last time is earlier than the next purchase time of the target item in the order processing list, the user is determined according to the historical record of the user purchasing the target item. The remaining amount of the target commodity before the purchase time of the last purchase of the commodity;

Here, the remaining amount of the target item before the time when the user last purchased the item is determined according to the formula (3-1).

m=v _n-1 (t' _n -t _n ) (3-1);

In formula (3-1), m is the remaining amount of the target commodity before the purchase time of the user's most recent purchase of the commodity, and v _n- ¹ is between t _n-1 and t' _n The consumption speed of the commodity, t _n-1 is the time when the user purchases the target commodity for the n-1th time, t' _n is the next purchase time of the target in the order processing list, and t _n is the latest time of the user The time to purchase the target item at a time.

In the third step, the next purchase time of the target item is updated according to the remaining amount of the target item and the history record of the user purchasing the target item.

Here, the next purchase time of the target item is calculated according to the formula (3-2), and the next purchase time of the target item in the order processing list is updated.

The average velocity V' calculated according to the formula (2-1) is taken as v _n and substituted into the formula (3-2) to calculate t _n+1 .

In other embodiments of the present invention, the second calculation method or the third calculation method provided by the foregoing embodiment may also be used to calculate when the user purchases the target item before the next purchase time of the target item in the order processing list. The next purchase time of the target item.

In the order processing method provided by the embodiment of the present invention, when the user makes a purchase between the next purchase time of the target item, the next purchase time of the target item in the order processing list is recalculated and updated. In this way, the user's next purchase time can be predicted more accurately.

An embodiment of the present invention provides an order processing device. FIG. 3 is a schematic structural diagram of an order processing device according to an embodiment of the present invention. As shown in FIG. 3, the order processing device includes: a data module 301, a setting module 302, and intelligent decision purchase. Module 303, reminder module 304, and order purchase module 305, wherein:

The data module 301 is configured to provide data support.

Here, the data stored in the data module includes at least:

1) Product information

The product information includes a product code, a product identification code, and other information of the product. The item information is usually stored in the form of a table as follows.

Commodity code

Product identification code

Product specifications

other information

Commodity code: A code that uniquely identifies an item in the system. For example, the brand 1 kg (kilogram, kg) is loaded with laundry detergent, coded as 10001, and the brand 2 kg is loaded with laundry detergent, and the code is 10002.

Commodity identification code: It is the category identification code of the product in the system. The only code indicating the type of the product is the mark that the product can be replaced by other brands of the same kind. For example, the brand 1kg laundry liquid, the product identification code is XYY01, the brand 2kg laundry liquid, the product identification code is also XYY01, when the smart purchase, can be replaced as the same type of goods. It can be used with official HS code or system customization.

Product specifications: The packaging specifications of the product, such as 500 grams (gram, g), 1 kg, 52 tablets, 500 ml (milliliter, ml), 1 liter (Liter, L).

Its value is rounded off, such as 500ml, 500g, 24 pieces of product specifications are 500,500,24. We assume that similar products (the same product identification code, such as laundry detergent) basically use the same unit of measure, such as laundry detergent, there will be no brand in grams, and another brand in milliliters. This assumption is basically established. Even if it exists, when you record the product information, you can change its specifications (for example, the capacity can also be calculated based on the density), and specify the same unit size for the same product in the same system.

Other information about the product includes information such as price and inventory, and no restrictions are imposed.

2) Historical order information

The historical order information includes information such as a user identification code, purchased product information, a quantity of goods, and an order time. The historical order information is usually stored in the form of a table as follows.

order number

Commodity code

User ID

Quantity

Order time

Order Number: The number of each order.

The commodity code has the same meaning as the commodity code representation in the product information.

User ID: Uniquely identifies a user and can be USER_ID.

Quantity: refers to the number of purchases of this item in this order.

Order time: The date and time of purchase.

3) User smart purchase list

The user smart purchase list includes a user identification code, a product identification code, a product code, a consumption speed, a possible inventory amount, and a next purchase time. The user smart purchase list is typically stored in a table format as follows.

User ID

Product identification code

Commodity code

Next purchase time

Ways to purchase

The product identification code, the product code, and the user identification code have the same meanings as the product identification code, the commodity code, and the user identification code in the historical order information.

Next purchase time: Estimated users need to make up the goods at this time, used to remind users or purchase.

The method of purchase: the method of “automatically adding a shopping cart and reminding the user” or “purchasing the automatic order”, the embodiment of the invention is not limited or can be extended.

The user smart purchase list can be one table or multiple tables.

The user smart purchase list records the smart purchase data of the user purchasing a certain product (such as laundry detergent). Such as:

1234

XYY01

100001,100002

2016-12-12

02

It can be expressed that the user numbered 1234 needs to purchase the laundry detergent intelligently. It has purchased the brand 1kg laundry liquid (coded as 10001) and the brand 2kg laundry liquid (coded as 10002), the next time for its smart purchase. For December 12, 2016, the purchase method is automatic order purchase (02).

The setting module 302 is configured to set a purchase mode in the smart purchase list or add the product selected by the user to the smart purchase list or delete the product selected by the user from the smart purchase list.

1) Allow users to add an item to smart purchase

For the goods that the user frequently purchases, the system may provide an entry for the product to be added to the smart purchase. After the user operates, the product data is added to the “user smart purchase list” in the data module.

2) Allow users to cancel a smart purchase of an item

For the frequently purchased item that has been added to the smart purchase, the system provides an entry for removing the item from the smart purchase, and after the user operates, the item data is removed from the “user smart purchase list” in the data module.

3) Allow users to select individual products or all purchase methods that can be purchased intelligently: Optional, you can purchase for reminders (automatically add shopping cart, SMS, message or email, etc.), automatically place an order (direct order) ).

A) When the user “adds the item to the smart purchase”, it can be specified whether the purchase method at the time of the smart purchase is a reminder or an automatic order purchase.

B) The system can also provide an entry for all smart purchases to set up purchase methods. After setup, all smart purchases are in a uniform manner.

The smart decision purchasing module 303 is configured to determine whether the merchandise reaches the smart buying opportunity. When the timing is up, the user will be based on the smart purchasing method set by the setting module or the “purchase method” in the “user smart purchase list” in the system. The product is automatically added to the shopping cart and notified by SMS, message or email, or automatically placed to purchase.

The expired smart purchase can be performed in a message-triggered manner or in a polling manner.

Taking the polling method as an example, it is possible to determine whether the smart purchase of the product meets the timing for each user in the “user smart purchase list” by turning on the timed task (for example, 00:00 every day), and the present invention does not limit the present invention. .

The timing of the present invention may be that the "next time of purchase" is today, or may be reminded or purchased by the user N days in advance, and is not limited in the embodiment of the present invention.

The reminding module 304 is configured to automatically add the expired smart purchased item to the shopping cart, and notify the user by means of a short message, information or mail. Notifications can also be attached to recommendations.

The order purchase module 305 is configured to generate an order for purchasing an item, and complete the order follow-up process. A conventional module in an e-commerce system.

The embodiment of the present invention further provides an order processing method, which is applied to an order processing device. FIG. 4-1 is a schematic flowchart of an implementation of an order processing method according to an embodiment of the present invention. As shown in FIG. 4-1, the method includes:

In step S401, the item is added to the smart purchase list.

Here, the item is added to the smart purchase list to add the item identification code of the item to the smart purchase list. In the embodiment of the present invention, step S401 can be implemented in the following two ways:

In the first implementation, an item is added to the smart purchase list according to an operation on the portal provided by the user based on the order processing device for the regular purchase item (which can be provided only to the frequently purchased item).

In the second implementation manner, after the purchase of the product is finished, the product is added to the smart purchase list according to the purchase information of the product.

Here, FIG. 4-2 is a schematic diagram of an implementation process of the second implementation manner of adding an item to the smart purchase list. As shown in FIG. 4-2, the following steps are included:

In step S421, it is determined whether the item is purchased or not.

Here, if the purchase of the product is completed, the process proceeds to step S422, and if the item is not purchased, the process ends.

Step S422, determining whether the product identification code of the product exists in the smart purchase list.

Here, if the product identification code of the product exists in the smart purchase list, the process proceeds to step S402, and if the product identification code of the product does not exist in the smart purchase list, the process proceeds to step S423.

Step S423, determining whether the number of purchases of the item is greater than a preset threshold.

Here, when the item identification code of the item does not exist in the smart purchase list, searching for the history of the user purchasing the item according to the item identification code of the item and the user identification code of the user who purchased the item Recording, determining whether the number of purchases of the commodity is greater than a preset threshold N, and if the number of purchases of the commodity is greater than a preset threshold N, proceeding to step S424, if the number of purchases of the commodity is not greater than a preset threshold, Then the process ends.

That is, if the item is a normal purchase (the item identification code is not in the smart purchase list), the item is automatically added to the smart purchase list according to a preset rule; if the item is a smart purchase (the item identification code is in the smart purchase) Checklist), directly adjust the smart purchase data. The rule for automatic purchase of goods is “history purchases are greater than N times”, N system is customized.

Step S424, adding the item to the smart purchase list.

In step S402, the smart purchase data is adjusted.

4-3 is a schematic flowchart of an implementation process of adjusting smart purchase data according to an embodiment of the present invention. As shown in FIG. 4-3, the step S402 adjusts the smart purchase data to include:

In step S402a, it is determined whether the product identification code of the added product exists in the smart purchase list.

Here, the smart purchase list in the embodiment of the present invention is the same as the content and function stored in the order processing list in other embodiments of the present invention.

If the product identification code of the product exists in the smart purchase list, the process proceeds to step S402c, and if the product identification code of the product does not exist in the smart purchase list, the process proceeds to step S402b.

If step S401 is implemented by the first implementation, the product identification code and the product code are directly added to the smart purchase list, and the smart purchase list data is calculated and set.

Step S402b, adding the product identification code of the product to the smart purchase list.

Here, for example, after purchasing a brand of laundry detergent, if the product identification code does not exist in the smart list, that is, if the product has not been purchased (for example, the laundry liquid has not been purchased), the product identification code and the product are added to the smart purchase list. , calculate and reset smart purchase data.

Step S402c, determining whether the commodity code of the commodity exists in the smart purchase list.

Here, if the product code of the item exists in the smart purchase list, the process proceeds to step S402e, and if the item code of the item does not exist in the smart purchase list, the process proceeds to step S402d.

That is to say, for example, after purchasing the brand-one laundry liquid, if the product identification code exists in the smart list, that is, the product is purchased (for example, the laundry liquid is bought), if the product code of the product does not exist in the smart purchase list ( Brand-one laundry detergent), the product code of the product is added to the smart purchase list (previously purchased may be brand two laundry detergent). If the merchandise code of the merchandise already exists in the smart purchase list, the process proceeds to step S402e to calculate and reset the smart purchase data.

Step S402d, adding the product code of the product to the smart purchase list.

In step S402e, the smart purchase data is calculated and reset, in particular, the next purchase time. The embodiment of the present invention recommends a method, but is not limited thereto.

The next purchase time in the embodiment of the present invention is the same as the next order time in the other embodiments.

4-4 is a schematic diagram of a time axis for calculating the next purchase time of an item according to an embodiment of the present invention. For ease of understanding, the identifier in FIG. 4-4 is first described.

t indicates the purchase time, which is the time of a purchase.

n indicates the quantity purchased, which is the quantity of goods purchased at a time.

s indicates the specifications of the purchased product.

The above data are obtained as data support.

As shown in Figure 4-4, t ₁ , n ₁ , s ₁ are the time, quantity and product specifications of the first purchase of a certain product; t _n , n _n , s _n are the nth purchase of a certain product respectively. Time, quantity and product specifications.

T is the time interval, T1 is the time interval of the second purchase and the first purchase, and Tn-1 is the time interval of the nth purchase and the n-1th purchase.

Here, the concept of speed and acceleration is introduced.

The speed v is the speed at which the user consumes the product.

The acceleration a is a physical quantity describing the speed of the speed change, a = Δv / Δt, and the embodiment of the present invention uses the average acceleration.

v is the speed of consumption of the product, specifically

That is, in time t, n s specifications of goods are consumed, and v _n is the speed at which n _n s _n is consumed between the nth and n+1th purchases, and is calculated by the formula (4-1); v _n-1 is the speed at which n _n-1 s _n-1 is consumed between the n-1th and the nth purchase, and is calculated by the formula (4-2).

Determine the average speed of purchasing such goods between t ₁ and t _n according to formula (4-3):

Determine the average acceleration according to formula (4-4):

Substituting the formula (4-1) and the formula (4-2) into the formula (4-4) yields the formula (4-5), that is,

Now it needs to be calculated that the n+1th purchase time t _n+1 can be as follows:

1) Calculate t _n+1 based on the average speed.

Taking the average velocity V' as v _n , that is, let v _n =V', then the formula (4-1) is transformed to obtain the formula (4-6):

Let v _n =V', then substituting the formula (4-3) into the formula (4-6) to obtain the formula (4-7):

Here, in the formula (4-7), all the parameters are known numbers, and the n+1th purchase time of the commodity can be determined by the formula (4-7).

2) Calculate t _n+1 based on the average speed and the average acceleration.

Let Δt=t _n+1 -t _n , the formula (4-6) can be transformed into the formula (4-8):

Substituting the formula (4-9) into the formula (4-8) yields the formula (4-10):

v _n = v _n-1 + aΔt (4-9);

Transform the formula (4-10) to get the formula (4-11):

aΔt ² +v _n-1 Δt-n _n s _n =0 (4-11);

The average speed V' of the purchased commodity between t ₁ and t _n-1 is determined according to the formula (4-12).

The average velocity V' of the purchased commodity between t ₁ and t _n-1 is taken as v _n-1 into the formula (4-11), and the quadratic equation of the formula (4-11) is solved. Δt is determined, and according to formula (4-13), the next purchase time t _{n+1 of the} purchased product is determined. If there is no solution, the first calculation method can be used to determine the next purchase time t _{n+1 of the} purchased product.

t _n+1 = t _n + Δt (4-13).

3) Calculate t _n+1 based on instantaneous velocity and average acceleration

Substituting the formula (4-2) into the formula (4-11) and solving the quadratic equation of the formula (4-11) can obtain Δt, and then determining the purchased product next time according to the formula (4-13). Purchase time t _n+1 . If there is no solution, the first calculation method can be used to determine the next purchase time t _{n+1 of the} purchased product.

In order to solve the impact of a random purchase (ie, a purchase before the arrival of the smart purchase time, such as a discounted product, the user actively performs the purchase) on the smart purchase, the following method can be adopted. In Figure 4-5, the nth purchase is a random purchase before the arrival of its smart purchase time t _n '.

Before the arrival of the smart purchase t _n ', the user performed a random purchase t _n . The judgment condition may be that the purchase time t _{n is} earlier than the next purchase time t _n 'M days calculated by the system and the commodity is a discount promotion, and the M may be customized by the system, such as half a month or the like.

In this case, it can be considered that the margin m of the user possessing the commodity at time t _n can be obtained by the formula (4-14):

m=v _n-1 Δt=v _n-1 (t' _n -t _n ) (4-14);

Then, the calculation method of t _n+1 takes the average velocity V′ as v _n (v _n =V′) as an example, and is calculated as follows:

then

In the same way, the same idea is used to calculate t _n+1 with average acceleration and instantaneous velocity.

At the same time, it can be concluded that the larger n is, the more stable v is, the more accurate the calculation of the smart purchase time is.

In step S403, the smart purchase is performed due to expiration.

Here, step S403 is a function performed by the intelligent decision purchase module in other embodiments of the present invention, and determines whether the commodity reaches the smart purchase timing. If the purchase timing of the commodity is reached, the smart purchase method set by the user in the setting module or The “purchase method” in the “user smart purchase list” in the system is for the user to automatically add the product to the shopping cart and send a notification by means of SMS, information or mail, or automatically place an order to purchase. It can also be recommended.

In other embodiments of the invention, expired smart purchases may be performed in a message triggered manner or in a polled manner.

Taking the polling method as an example, it is possible to determine whether the smart purchase item meets the timing for each user in the “user smart purchase list” by turning on the timed task (for example, 00:00 every day), and the time condition can be met. It is "the next purchase time" is today, or it may be a reminder or purchase for the user N days in advance, and the present invention is not limited.

In addition, in the smart purchase of the same product identification code (the same type of goods, such as laundry detergent), there may be multiple purchases of brand A and multiple purchases of brand B. When making smart purchases, the system can automatically purchase A or automatically purchase. B, you can also choose which item to buy according to certain rules (buy more, or recently purchased).

In the embodiment of the present invention, by analyzing the time, quantity, and specification (capacity, weight, etc.) of the product purchased by the user, the time of the product is calculated and predicted (ie, the next purchase) Time), automatic reminder or automatic purchase at the end, to achieve the purpose of making up the supply for the user in time.

Based on the foregoing embodiments, an embodiment of the present invention provides an order processing method, which is applied to an order processing device, where the method includes the following steps:

In the first step, after the purchase of the same item 5 times, the order processing device provides an entry for the item to be added to the smart purchase. The user clicks on the portal and sets the smart purchase method for the item as "purchase reminder"

In the second step, the order processing device directly adds the product identification code and the product code to the smart purchase list, and calculates and sets the time of the next smart purchase.

Here, the order processing device calculates the next smart purchase time of the item in accordance with a method provided in other embodiments of the present invention.

In the third step, the order processing device intelligently makes a purchase. When the order processing device confirms the smart purchase time of the product, the product is added to the shopping cart according to the setting of the user, and information or mail is used. Reminder, at the same time, you can also recommend similar products.

By adopting the intelligent purchasing method provided in the embodiment of the invention, the user can be automatically supplemented with the supply, which saves the user's effort and effort. At the same time, avoid situations where nothing is available because you forgot to buy.

Based on the foregoing embodiments, an embodiment of the present invention further provides an order processing method, which is applied to an order processing device, and the method includes the following steps:

The first step, after purchasing the same item 5 times, the order processing device automatically adds the item to the smart purchase list.

Here, the order processing device automatically adds the item to the smart purchase list including the order processing device adding at least the item identification code and the item code of the item to the smart purchase list.

In the second step, after the order processing device adds the product identification code and the product code to the smart purchase list, the next smart purchase time is calculated and set.

Here, the order processing device calculates the next smart purchase time of the item in accordance with a method provided in other embodiments of the present invention.

In the third step, the order processing device intelligently makes a purchase, and when the order processing device determines that the smart purchase time of the product is reached, according to the unified setting of the user in the system of the order processing device (for example, the user is set to automatic Purchase), generate orders for goods, automatically purchase for users, payment methods can be cash on delivery or automatic deductions set by the user in the system.

The embodiment of the invention further provides an order processing method, which is applied to a shopping device. The method includes the following steps:

In the first step, the order processing device performs a smart purchase, and the smart purchase of the product ends.

In the second step, the order processing device calculates and sets the time of the next smart purchase of the item.

Here, the order processing device calculates the next smart purchase time of the item in accordance with a method provided in other embodiments of the present invention.

In the third step, the smart order processing device performs intelligent decision purchase, and when confirming the smart purchase time of the product, the product is added to the shopping cart according to the unified setting of the user in the system (for example, the user equipment is a reminder purchase) And remind you by means of information or email, and you can also recommend similar products.

An embodiment of the present invention provides an order processing device. FIG. 5 is a schematic structural diagram of an order processing device according to an embodiment of the present invention. As shown in FIG. 5, the order processing device 500 includes: a first determining module 501 and a second determining module. 502 and an order module 503, wherein:

The first determining module 501 is configured to determine identification information of the target item and identification information of the user who purchased the target item;

The second determining module 502 is configured to determine a next purchase time of the target commodity according to the identification information of the target commodity and the identification information of the user who purchases the target commodity;

Here, the second determining module 502 includes:

a first determining unit, configured to determine, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the history record of the user purchasing the target commodity;

The second determining unit is configured to determine a next purchase time of the target item according to the history record of the user purchasing the target item.

Here, the second determining unit includes:

a first determining subunit, configured to determine purchase information of the first purchase of the target item by the user to the nth purchase of the target item according to a history record of the user purchasing the target item; wherein, the nth The purchase information of the target product is the purchase information of the target product purchased for the last time, and the purchase information of the target product for the i-th purchase is the purchase time t _i , the purchase quantity n _i and the specification of the target product s _i , i is a natural number between 1 and n;

a second determining subunit, configured to determine an average consumption speed V′ of the target item between t ₁ and t _n according to purchase information of the first purchase of the target item by the user to the nth purchase of the target item ;

The third determining subunit is configured to determine a next purchase time of the target item according to an average consumption speed of the target item.

a fourth determining subunit, configured to determine purchase information of the first purchase of the target item by the user to the nth purchase of the target item according to a history record of the user purchasing the target item; wherein, the nth The purchase information of the target product is the purchase information of the target product purchased for the last time, and the purchase information of the target product for the i-th purchase is the purchase time t _i , the purchase quantity n _i and the specification of the target product s _i , i is a natural number between 1 and n;

Fifth determining sub-unit, provided to the user according to the first order to the n-th target commodity purchase commodity purchase information of the target is determined between t ₁ to t _n-1 of the target product of the average consumption rate V _{'. 1} and t to t _n between the average consumption of the acceleration of the target product;

a sixth determining subunit, configured to determine that the average acceleration of the target commodity is consumed between the average speeds V′ and t ₁ to t _n of the target commodity consumed between the t ₁ and t _n-1 The next purchase time of the target item.

a seventh determining subunit, configured to confirm purchase information of the first purchase of the target item to the nth purchase of the target item according to a history record of the user purchasing the target item; wherein, the nth The purchase information of the target product is the purchase information of the target product purchased for the last time, and the purchase information of the target product for the i-th purchase is the purchase time t _i , the purchase quantity n _i and the specification of the target product s _i , i is a natural number between 1 and n;

Determining an eighth sub-unit, according to the user setting determines the first purchase of the target n-th product to later purchase information of the target product ₁ and the average acceleration of the target commodity consumption t _n t between t The consumption speed of the commodity between _n-1 and t _n is v _n-1 ;

Determining a ninth sub-unit, according to _{the. 1} to t _n t between the target commodity consumption average acceleration and t _n-1 and t _n between the consuming speed v commodity _n-1, determining the The next purchase time of the target item.

The ordering module 503 is configured to automatically place an order for the target item or send a shopping reminder to the user when the next purchase time of the target item arrives.

Here, the order processing device further includes:

a first determining module, configured to determine whether the identification information of the purchased product is in the order processing list;

a second determining module, configured to determine whether the number of purchases of the purchased item reaches a preset threshold if the identification information of the purchased item is not in the order processing list;

The adding module is configured to add the identification information of the purchased item to the order processing list if the number of purchases of the purchased item reaches a preset threshold.

a third determining module, configured to determine whether a purchase time of the last purchase of the item by the user is earlier than a next purchase time of the target item in the order processing list;

a third determining module, configured to determine, if the purchase time of the last purchase of the item by the user is earlier than a next purchase time of the target item in the order processing list, according to the historical record of the user purchasing the target item The remaining amount of the target item before the purchase time of the user last purchased the item;

The update module is configured to update a next purchase time of the target item according to a remaining amount of the target item and a history of the user purchasing the target item.

It should be noted here that the description of the above embodiment of the order processing device is similar to the description of the above method embodiment, and has the same advantageous effects as the method embodiment, and therefore will not be described again. For the technical details that are not disclosed in the embodiment of the present invention, please refer to the description of the method embodiment of the present invention for the sake of space saving, and therefore no further details are provided.

The embodiment of the invention further provides a computer readable storage medium storing computer executable instructions, which are implemented by the processor to implement the method described in the foregoing embodiments.

Those of ordinary skill in the art will appreciate that all or some of the steps, systems, and functional blocks/units of the methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical units; for example, one physical component may have multiple functions, or one function or step may be composed of several physical The components work together. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer readable medium, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and nonvolatile, implemented in any method or technology for storing information, such as computer readable instructions, data structures, program modules, or other data. , removable and non-removable media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridge, magnetic tape, magnetic disk storage or other magnetic storage device, or may Any other medium used to store the desired information and that can be accessed by the computer. Moreover, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and can include any information delivery media.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

The above is only an alternative embodiment of the present invention and is not intended to limit the scope of the present invention.

Industrial applicability

The embodiment of the invention can predict the next purchase time of the user according to the purchase record of the user, and remind the user to make a purchase or automatically place an order, thereby improving the user experience.

Claims (11)

1. An order processing method, the method comprising:

   Determining identification information of the target item and identification information of the user who purchased the target item (S101);

   Determining a next order time of the target item according to the identification information of the target item and the identification information of the user who purchases the target item (S102);

   When the next order time of the target item arrives, the target item is automatically placed or a shopping reminder is sent to the user (S103).
2. The method according to claim 1, wherein the determining the next order time of the target item according to the identification information of the target item and the identification information of the user who purchases the target item comprises:

   Determining, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, a history record of the user purchasing the target commodity;

   Determining the next order time of the target item according to the historical record of the user purchasing the target item.
3. The method of claim 1 further comprising:

   Determining whether the identification information of the purchased product is in the order processing list before determining the identification information of the target item and the identification information of the user who purchased the target item;

   If the identification information of the purchased item is not in the order processing list, determining whether the purchase quantity of the purchased item reaches a preset threshold;

   If the number of purchases of the purchased item reaches a preset threshold, the identification information of the purchased item is added to the order processing list.
4. The method of claim 2, wherein the determining the next order time of the target item according to the historical record of the user purchasing the target item comprises:

   Pursuing the history record of the target item purchased by the user, confirming that the user purchases the target item for the first time to purchase information of the target item for the nth time; wherein, the nth purchase of the target item is purchased The information is purchase information of the last purchase of the target product;

   Determining an average of the target merchandise between the first purchase of the target merchandise and the nth purchase of the target merchandise according to purchase information of the first purchase of the target merchandise by the user to the nth purchase of the target merchandise Consumption speed

   Determining a next order time of the target item based on an average consumption speed of the target item and purchase information of the target item purchased for the nth time.
5. The method according to claim 4, wherein said determining, based on said first purchase of said target item by said user to purchase information of said target item for nth time, first purchase said target item to nth The average consumption rate of the target goods between the target goods purchased, including:

   Determining, according to the purchase information of the first purchase of the target item by the user to the nth purchase of the target item, the purchase of the target item between the first purchase of the target item and the nth purchase of the target item Total amount

   a time difference between the total purchase amount of the target commodity between the first purchase of the target merchandise and the nth purchase of the target merchandise, and the first purchase of the target merchandise to the nth purchase of the target merchandise The average consumption speed of the target item between the first purchase of the target item and the nth purchase of the target item.
6. The method according to claim 4, wherein the determining the next order time of the target item based on the average consumption speed of the target item and the purchase information of the nth purchase of the target item comprises:

   Determining a usage duration of the target item purchased for the nth time according to an average speed of the target item and purchase information of the nth purchase of the target item;

   The next order time of the target item is determined according to the purchase time of the target item of the nth purchase and the usage time of the target item of the nth purchase.
7. The method of claim 2, wherein the determining the next order time of the target item according to the historical record of the user purchasing the target item comprises:

   Pursuing the history record of the target item purchased by the user, confirming that the user purchases the target item for the first time to purchase information of the target item for the nth time; wherein, the nth purchase of the target item is purchased The information is purchase information of the last purchase of the target product;

   Determining, according to the purchase information of the first purchase of the target item by the user to the nth purchase of the target item, the first purchase of the target item to the n-1th purchase of the target item, the consumption of the target The average speed of the commodity and the average acceleration of the target commodity between the first purchase of the target commodity and the nth purchase of the target commodity;

   Determining an average speed of consuming the target item between the first purchase of the target item to the n-1th purchase of the target item, and purchasing the target item for the first time to the nth purchase of the target item The average acceleration of the target item is consumed between, and the next purchase time of the target item is determined.
8. The method of claim 2, wherein the determining the next order time of the target item according to the historical record of the user purchasing the target item comprises:

   Pursuing the history record of the target item purchased by the user, confirming that the user purchases the target item for the first time to purchase information of the target item for the nth time; wherein, the nth purchase of the target item is purchased The information is purchase information of the last purchase of the target product;

   Determining, according to the purchase information of the first purchase of the target item by the user to the nth purchase of the target item, the first purchase of the target item to the nth purchase of the target item, the consumption of the target item The average acceleration and the consumption speed of the commodity between the n-1th purchase of the target merchandise and the nth purchase of the target merchandise;

   And consuming the average acceleration of the target commodity between the first purchase of the target merchandise to the nth purchase of the target merchandise and the n-1th purchase of the target merchandise to the nth purchase of the target merchandise The speed of consumption of the item is determined, and the next purchase time of the target item is determined.
9. The method of claim 1 further comprising:

   Determining whether the purchase time of the last purchase of the item by the user is earlier than the next order time of the target item in the order processing list;

   If the user purchases the item for the last time, the purchase time is earlier than the next order time of the target item in the order processing list;

   Determining, according to a history record of the user purchasing the target item, a remaining amount of the target item before a purchase time of the user purchasing the item last time;

   Updating the next order time of the target item according to the remaining amount of the target item and the history record of the user purchasing the target item.
10. An order processing device (500), the device (500) comprising:

    a first determining module (501) configured to determine identification information of the target item and identification information of the user who purchased the target item;

    The second determining module (502) is configured to determine, according to the identification information of the target commodity and the identification information of the user who purchases the target commodity, the next ordering time of the target commodity;

    The order module (502) is configured to automatically place an order or send a shopping reminder to the target when the next order time of the target item arrives.
11. A computer readable storage medium storing computer executable instructions that, when executed by a processor, implement the method of any one of claims 1 to 9.

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