CN107818474B

CN107818474B - Method and device for dynamically adjusting product price

Info

Publication number: CN107818474B
Application number: CN201610822402.9A
Authority: CN
Inventors: 吕强; 程恒奇; 李夫收; 金洪伟; 刘心元
Original assignee: Baidu Online Network Technology Beijing Co Ltd
Current assignee: Baidu Online Network Technology Beijing Co Ltd
Priority date: 2016-09-13
Filing date: 2016-09-13
Publication date: 2022-01-18
Anticipated expiration: 2036-09-13
Also published as: CN107818474A

Abstract

The invention provides a method and a device for dynamically adjusting product price, wherein the method comprises the following steps: when the current price period of the product is finished, obtaining the period change information of the product according to the period data of the product in the current price period and the last price period; determining a plurality of pricing units corresponding to the next price period of the product according to the period change information and the dimension information of the product; a price for each pricing unit of the plurality of pricing units during the next price period is determined. According to the scheme of the invention, the product price can be automatically adjusted, the labor input is greatly reduced, the labor cost is saved, and the differentiation of the product can be realized.

Description

Method and device for dynamically adjusting product price

Technical Field

The invention relates to the technical field of computers, in particular to a method and a device for dynamically adjusting product price.

Background

In the prior art, an operator of a product generally implements pricing or price adjustment of the product based on a manual analysis manner, such as manually analyzing each dimension of the product, current share data, pricing sensitivity (historical cyclic ratio data experience), and the like, so as to make a pricing or price adjustment decision based on an analysis result. However, the manual analysis method requires continuous investment of specialized manpower, has high labor cost, is mainly used for judgment based on experience on the basis of historical statistical data, does not have a standard and reliable judgment scheme, and cannot achieve very accurate analysis results, so that a good price adjustment effect cannot be achieved.

Disclosure of Invention

The invention aims to provide a method and a device for dynamically adjusting the price of a product.

According to one aspect of the present invention, there is provided a method for dynamically adjusting the price of a product, wherein the method comprises:

when the current price period of the product is finished, obtaining the period change information of the product according to the period data of the product in the current price period and the last price period;

determining a plurality of pricing units corresponding to the next price period of the product according to the period change information and the dimension information of the product;

a price for each pricing unit of the plurality of pricing units during the next price period is determined.

According to another aspect of the present invention, there is also provided an apparatus for dynamically adjusting the price of a product, wherein the apparatus comprises:

means for determining a plurality of pricing units corresponding to a next price cycle of the product based on the cycle change information and the dimensional information of the product;

Means for determining a price for each pricing unit of the plurality of pricing units during the next price period.

According to still another aspect of the present invention, there is also provided an apparatus for dynamically adjusting the price of a product, the apparatus including:

one or more processors for executing a program to perform,

a memory storing one or more programs,

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method for dynamically adjusting product prices of the present invention.

Compared with the prior art, the invention has the following advantages: the product price can be automatically adjusted, the labor input is greatly reduced, and the labor cost is saved; when the current price period of the product is finished, a plurality of pricing units corresponding to the next price period of the product can be determined according to the period data of the product in the current price period and the last price period and the dimension information of the product, so that the price of each pricing unit in the plurality of pricing units is further determined, the pricing unit in each price period is dynamically determined, and the variable pricing units can automatically identify key elements influencing price sensitivity, realize differentiated pricing of the product and improve the overall target.

Drawings

Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:

FIG. 1 is a schematic flow chart of a method for dynamically adjusting the price of a product in accordance with one embodiment of the present invention;

FIG. 2 is a schematic representation of a dimensional tree of movie tickets in accordance with an example of the invention;

FIG. 3 is a schematic diagram of the partitioning of the dimension tree of FIG. 2 into pricing units according to one example of the invention;

FIG. 4 is a schematic flow chart of a method for dynamically adjusting the price of a product according to another embodiment of the present invention;

FIG. 5 is a schematic diagram of the present invention illustrating the determination of a price for each pricing unit based on a pricing unit queue, for example, movie tickets;

FIG. 6 is a schematic structural diagram of an apparatus for dynamically adjusting the price of a product according to an embodiment of the present invention;

FIG. 7 is a schematic structural diagram of an apparatus for dynamically adjusting the price of a product according to another embodiment of the present invention;

fig. 8 shows a schematic diagram of one implementation of an apparatus for dynamically adjusting prices of products according to the present invention.

The same or similar reference numbers in the drawings identify the same or similar elements.

Detailed Description

Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel, concurrently, or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.

The term "computer device" or "computer" in this context refers to an intelligent electronic device that can execute predetermined processes such as numerical calculation and/or logic calculation by running predetermined programs or instructions, and may include a processor and a memory, wherein the predetermined processes are executed by the processor by executing program instructions prestored in the memory, or the predetermined processes are executed by hardware such as ASIC, FPGA, DSP, or a combination thereof. Computer devices include, but are not limited to, servers, personal computers, laptops, tablets, smart phones, and the like.

The computer devices include, for example, user devices and network devices. Wherein the user equipment includes but is not limited to a PC, a tablet computer, a smart phone, a PDA, etc.; the network device includes, but is not limited to, a single network server, a server group consisting of a plurality of network servers, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of computers or network servers, wherein Cloud Computing is one of distributed Computing, a super virtual computer consisting of a collection of loosely coupled computers. Wherein the computer device can be operated alone to implement the invention, or can be accessed to a network and implement the invention through interoperation with other computer devices in the network. The network in which the computer device is located includes, but is not limited to, the internet, a wide area network, a metropolitan area network, a local area network, a VPN network, and the like.

It should be noted that the user equipment, the network device, the network, etc. are only examples, and other existing or future computer devices may be applicable to the present invention, and are included in the scope of the present invention and are also included by reference.

The methodologies discussed hereinafter, some of which are illustrated by flow diagrams, may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks may be stored in a machine or computer readable medium such as a storage medium. The processor(s) may perform the necessary tasks.

Specific structural and functional details disclosed herein are merely representative and are provided for purposes of describing example embodiments of the present invention. The present invention may, however, be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein.

It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element may be termed a second element, and, similarly, a second element may be termed a first element, without departing from the scope of example embodiments. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be noted that, in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.

The present invention is described in further detail below with reference to the attached drawing figures.

Fig. 1 is a flow chart illustrating a method for dynamically adjusting the price of a product according to an embodiment of the present invention. The method according to the present embodiment includes step S1, step S2, and step S3.

In step S1, when the current price cycle of the product is finished, the computer device obtains cycle variation information of the product according to the cycle data of the product in the current price cycle and the last price cycle.

Wherein one product corresponds to a plurality of consecutive price cycles. It should be noted that the product described in the present invention is not limited to a specific product (e.g. a mobile phone with model "X", a movie ticket for a certain movie), and the product may be a product set with the same price cycle (e.g. movie tickets for multiple movies, etc.), so the solution of this embodiment is not only suitable for dynamically adjusting the price of a specific product, but also suitable for simultaneously adjusting the prices of multiple products with the same price cycle.

It should be noted that, preferably, the number of price cycles of the product may be predetermined, either conditioned or unrestricted; also, the cycle length of each price cycle of a product may be fixed or variable, e.g. the cycle length of subsequent price cycles may be flexibly adjusted. Preferably, a stop condition of the price cycle of the product (such as product listing, etc.) may be set in advance, or the price cycle of the product may be terminated manually.

The period data includes any data generated by the product in a price period, such as price data, sales data, etc. of the product.

The period change information includes any information indicating a period change condition of the product between the current price period and the last price period, such as price change information of the product, sales change information and the like, wherein the price change information is used for indicating a price change condition of the product, and the sales change information is used for indicating a sales change condition of the product. It should be noted that during a pricing cycle, a product may correspond to multiple prices, e.g., movie tickets for a movie may have different prices at different theaters and at different times. Preferably, the periodic variation information of the product can indicate the variation of the product in various dimensions, wherein the dimensions refer to various factors influencing the pricing of the product, such as factors influencing the pricing of movie tickets, including but not limited to: movie title, theater, city, price, etc.

As an example of step S1, for a movie being shown, the period length of each price period of the movie ticket is one day, and when the day ends (i.e., the current price period ends), the computer device obtains the period change information of the movie ticket by comparing the period data of the movie ticket on the day with the period data of the previous day, the period change information indicating that the price of the movie ticket is decreased by 5% and the sales volume is increased by 10%.

In step S2, the computer device determines a plurality of pricing units corresponding to a next price period for the product based on the period variation information and the dimensional information of the product.

The dimension information includes any information related to the pricing dimension of the product, such as a plurality of dimensions corresponding to the product, a dimension value included in each dimension, an association between dimension values, and the like. For example, movie tickets correspond to dimensions including: cinema, city, price; where the theatre includes "starry and" midmovie ", the city includes" shanghai "," beijing "," chengdu "," price "dimensions include 30, 40, 50, where the dimension value included in the" price "dimension is the initial pricing of the movie ticket, such as 30 for some of the shanghai and 40 for another, and the dimension value of the" city "dimension is" shanghai ", the dimension value of the corresponding" price "dimension includes 30 and 40.

Wherein the pricing unit represents the granularity for pricing, i.e. the basic unit for adjusting the price of the product. One pricing unit can correspond to one or more dimension values, and when one pricing unit corresponds to a plurality of dimension values, the plurality of dimension values can correspond to at least one dimension. For example, one pricing unit of the product satisfies "city ═ shanghai" (i.e. all movie scenes in shanghai), the other pricing unit of the product satisfies "city ═ beijing," movie name ═ magic beast "(i.e." magic beast "all movie scenes in beijing), the front end of the above or subsequently appearing equal sign is the dimension, and the rear end of the equal sign is the dimension value.

As a preferable scheme, the step S2 further includes a step S21-1, a step S21-2 and a step S21-3.

In step S21-1, the computer device constructs a dimension tree for the product based on the dimension information for the product.

Fig. 2 is a schematic diagram of a dimensional tree constructed for movie tickets in accordance with an example of the present invention. Wherein the movie ticket comprises the following dimensions: cinema, city, price; wherein, the cinema comprises 'Xingmei' and 'Zhongying', and the city comprises 'Shanghai', 'Beijing' and 'Chengdu'; the prices include 30, 40, 50. It should be noted that fig. 2 only exemplarily shows partial cycle data of the product.

It should be noted that, if the dimension information of the product is not changed, the dimension tree of the product is not changed, and therefore, after the dimension tree of the product is constructed for the first time, the dimension tree may be stored, so that the dimension tree of the product is constructed without repeatedly performing the operation of step S21-1 in the subsequent price period; however, if the dimension information of the product changes (for example, one dimension value of the product is removed), the dimension tree of the product should be reconstructed, so in step S21-1, if there is a previously constructed dimension tree, it can be determined whether the dimension information of the product changes first, if so, the dimension tree of the product is constructed according to the changed dimension information, and if not, the previously constructed dimension tree is directly obtained.

In step S21-2, the computer device calculates a pricing standard entropy corresponding to each dimension value in the dimension tree according to the periodic variation information of the product.

Wherein the pricing standard entropy represents a consistency situation of a periodically varying distribution of the dimension values.

Preferably, for a dimension value of a product, the computer device calculates the pricing standard entropy H corresponding to the dimension value according to the periodic variation information of all nodes under the dimension value in the dimension tree based on the following formula:

H＝-rPP*ln(rPP)-rPN*ln(rPN)-rNP*ln(rNP)-rNN*ln(rNN)

Wherein, rPP |/SUM, rPN |/PN |/SUM, rNP |/SUM, rNN |/SUM, NN | + | NN |/SUM, SUM | + | PP | + | PN | + | NP | + | NN |, ln represents a natural logarithm with e as the base. Wherein, the definitions of PP, PN, NP, NN are given in Table 1:

TABLE 1

Wherein, the delta period sales represents the period sales volume change of each node under the dimension value, the delta period price represents the period price change of each node under the dimension value, the upward arrow represents a non-negative value (i.e. a positive value or 0), and the downward arrow represents a negative value. Based on table 1, PP can be calculated from nodes where the corresponding Δ periodic sales and Δ periodic prices are both non-negative values, PN can be calculated from nodes where the corresponding Δ periodic sales are non-negative values and the Δ periodic prices are negative values, NP can be calculated from nodes where the corresponding Δ periodic sales are negative values and the Δ periodic prices are non-negative values, and NN can be calculated from nodes where the corresponding Δ periodic sales and the corresponding Δ periodic prices are both negative values.

It should be noted that the above formula is only an example and not a limitation of the present invention, and those skilled in the art understand that other implementations capable of calculating the pricing criterion entropy of each node in the dimension tree should also be included in the scope of the present invention.

In step S21-3, the computer device divides the dimension tree into a plurality of pricing units corresponding to a next price period of the product according to the calculated pricing standard entropy for each dimension value and based on a standard entropy minimization principle.

The standard entropy minimum principle refers to that a dividing operation is executed based on a dimension value with the minimum pricing standard entropy.

As an example, fig. 3 is a schematic diagram of dividing the dimension tree shown in fig. 2 into a plurality of pricing units according to an example of the present invention, and first, the computer device determines that the pricing standard entropy corresponding to the dimension value "shanghai" is minimum according to the pricing standard entropy of each dimension value in the dimension tree shown in fig. 2, and then the computer device divides the dimension tree into a tree including "shanghai" and a tree not including "shanghai"; then, for the tree containing "shanghai", the computer device determines that the pricing standard entropy of the dimension value "30" in the tree is minimum, and then the computer device further divides the tree containing "shanghai" into a tree containing "30" and a tree not containing "30"; for trees that do not contain "shanghai", the computer device determines that the pricing criterion entropy of the dimension value "30" is minimal, and the computer device further divides the trees that do not contain "shanghai" into trees that contain "30" and trees that do not contain "30". In fig. 3, "MIN ═ X" indicates that the pricing standard entropy of the dimension value X is minimum, "NON-X" indicates that X is not included, and X is a dimension value, such as "NON-shanghai" indicates that "shanghai" is not included.

Specifically, the implementation manner of dividing the dimension tree into a plurality of pricing units corresponding to the next price period of the product by the computer device according to the calculated pricing standard entropy of each node and based on the standard entropy minimum principle includes, but is not limited to:

1) and the computer equipment divides the dimension tree into a preset number of pricing units corresponding to the next price period of the product according to the pricing standard entropy and on the basis of a standard entropy minimum principle.

For example, the predetermined number is 4, the computer device divides the dimension Tree into Tree1 and Tree2 according to the pricing standard entropy and based on the standard entropy minimum principle; then, the computer device divides the Tree1 into Tree11 and Tree12, divides the Tree2 into Tree21 and Tree22, and takes Tree11, Tree12, Tree21 and Tree22 as 4 pricing units corresponding to the next price period of the product according to the pricing standard entropy and based on a standard entropy minimum principle.

For another example, the predetermined number is 3, the computer device divides the dimension Tree into Tree1 and Tree2 according to the pricing standard entropy and based on the standard entropy minimum principle; then, the computer device selects Tree1 based on a predetermined rule (such as a larger number of nodes, etc.), and divides Tree1 into Tree11 and Tree12 based on a standard entropy minimization principle, and takes Tree11, Tree12 and Tree2 as 3 pricing units corresponding to the next price period of the product.

2) And the computer equipment divides the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the pricing standard entropy and the preset support degree and based on a standard entropy minimum principle.

Wherein the predetermined support represents a support condition that a predetermined pricing unit needs to satisfy, such as a predetermined support indicating a sales volume greater than 1000.

For example, the computer device divides the dimension tree into two trees meeting a predetermined support degree according to the pricing standard entropy of each dimension value of the product and based on the standard entropy minimum principle; for each tree obtained by dividing, the computer equipment further divides the tree into two trees meeting the preset support degree according to the pricing standard entropy of each dimension value of the product and based on the principle of minimum standard entropy; by analogy, support cannot obtain trees that satisfy a predetermined support degree.

It should be noted that, when the dimension tree cannot be divided into pricing units satisfying a predetermined support degree, the whole dimension tree can be used as one pricing unit.

It should be noted that the above implementations 1) and 2) of the step S21-3 may be combined. For example, the computer device divides the dimension tree into two trees meeting a predetermined support degree according to the pricing standard entropy of each dimension value of the product and based on the standard entropy minimum principle; for each tree obtained by dividing, the computer equipment further divides the tree into two trees meeting the preset support degree according to the pricing standard entropy of each dimension value of the product and based on the principle of minimum standard entropy; and the rest is repeated until the trees meeting the preset support degree cannot be obtained or the preset number of trees are obtained through the dividing operation.

As another preferable mode of the step S2, the step S2 includes the steps of: the computer equipment obtains a plurality of dimension sets corresponding to the products according to the periodic variation information and the dimension information of the products, wherein at least one periodic variation condition of each object contained in one dimension set is the same or similar; next, the computer device determines a plurality of pricing units corresponding to a next price cycle of the product based on the plurality of sets of dimensions.

The periodic variation condition includes, but is not limited to, a price variation condition, a sales variation condition, and the like, and the periodic variation condition of each dimension or dimension value of the product can be obtained based on the periodic variation information of the product.

Wherein, the objects included in the dimension set can be the dimension or dimension value of the product. Preferably, it can be determined which dimensions or periodic variation of dimension values are the same or similar based on the increase or decrease of sales, the increase or decrease of price, and the like. For example, if the sales increase range for the dimension value "shanghai" is 15% and the sales increase range for the dimension value "beijing" is 12%, the periodic variation of the dimension values "shanghai" and "beijing" can be considered to be similar.

The computer equipment can obtain a plurality of dimension sets corresponding to the products according to the periodic variation information and the dimension information of the products in various modes such as statistical analysis and clustering.

Wherein the computer device can determine a pricing unit based on the set of one or more dimensions. For example, the computer device may directly treat a dimension set as a pricing unit, or, when a pricing unit determined based on a dimension set fails to meet a predetermined support, combine the dimension set with other dimension sets to determine a pricing unit that meets the predetermined support.

It should be noted that the above examples are only for better illustrating the technical solutions of the present invention, and not for limiting the present invention, and those skilled in the art should understand that any implementation manner of determining a plurality of pricing units corresponding to the next price period of the product according to the period variation information and the dimension information of the product should be included in the scope of the present invention.

In step S3, the computer device determines a price for each pricing unit of the plurality of pricing units during the next price period.

In particular, the computer device may employ various implementations to determine the price of each pricing unit of the plurality of pricing units during the next price period.

As an alternative, for each pricing unit of the plurality of pricing units, calculating a marginal benefit for that pricing unit; determining a price for each pricing unit of the plurality of pricing units during the next price period based on the marginal benefit. This alternative will be described in detail in the following embodiments.

As another alternative, for each pricing unit, the computer device increases or decreases the price of the pricing unit based on the periodic variation of the pricing unit.

For example, in step S2, the computer device obtains two pricing units corresponding to the next price period of the product based on the sales change information and the dimension information of the product: u1 and U2, wherein the periodic sales volume of U1 is increased, and the periodic sales volume of U2 is decreased; in step S3, the computer device increases the price of U1 and decreases the price of U2 according to the cyclic variation of U1 and U2.

It should be noted that the price increase or decrease may be fixed or adjustable, for example, different price ranges may correspond to different periodic variations.

It should be noted that the above examples are only for better illustrating the technical solution of the present invention, and not for limiting the present invention, and those skilled in the art should understand that any implementation manner for determining the price of each pricing unit in the plurality of pricing units during the next price period should be included in the scope of the present invention.

It should be noted that, each time one price period of the product is over, the computer device executes the solution of the present embodiment to determine a plurality of pricing units corresponding to the next price period and the price of each pricing unit. It should be further noted that the computer device may dynamically adjust the price of the product based on the solution of the embodiment after the second price period of the product is over; preferably, the price of a product during its first price period is generally predetermined, and the price of a product during its second price period may be predetermined or determined based on the period data of the first price period.

In the prior art, an operator of a product generally implements pricing or price adjustment of the product based on a manual analysis manner, such as manually analyzing each dimension of the product, current share data, pricing sensitivity (historical cyclic ratio data experience), and the like, so as to make a pricing or price adjustment decision based on an analysis result. However, the manual analysis method requires continuous investment of specialized manpower, has high labor cost, is mainly used for judgment based on experience on the basis of historical statistical data, does not have a standard and reliable judgment scheme, so that the analysis result cannot be very accurate, and further results in poor effect.

There are also solutions for pricing individual products based on machine learning, which the present invention finds requires the collection of large amounts of historical data, requires long periods, and cannot be applied to all products.

According to the scheme of the embodiment, the product price can be automatically adjusted, the labor input is greatly reduced, and the labor cost is saved; when the current price cycle of the product is finished, a plurality of pricing units corresponding to the next price cycle of the product can be determined according to cycle data of the product in the current price cycle and the last price cycle and dimension information of the product, so that the price of each pricing unit in the pricing units is further determined, the pricing unit in each price cycle is dynamically determined, and key elements influencing price sensitivity can be automatically identified through variable pricing units, so that differentiated pricing of the product is realized, and the overall goal is improved; through periodic iteration, the strategy of market/competitive products can be well coped with, and the method can be suitable for any product.

Fig. 4 is a flowchart illustrating a method for dynamically adjusting the price of a product according to another embodiment of the present invention. The method according to the present embodiment includes step S1, step S2, and step S3, wherein the step S3 further includes step S31 and step S32. The steps S1 and S2 have been described in detail with reference to the embodiment shown in fig. 1, and are not described herein again.

In step S31, for each pricing unit of the plurality of pricing units determined in step S2, the computer device calculates a marginal gain for that pricing unit.

Wherein the computer device can calculate the marginal benefit of the pricing unit based on the following formula:

marginal profit of pricing unit | [ delta ] periodic sales volume/[ delta ] periodic price | ]

In step S32, the computer device determines a price for each pricing unit of the plurality of pricing units during a next price period based on the calculated marginal profit.

In particular, implementations in which the computer device determines the price of each pricing unit of the plurality of pricing units during the next price period based on the calculated marginal profit include, but are not limited to:

1) the computer device determines a price for each pricing unit of the plurality of pricing units during the next price period based on the marginal benefit and preset limit information.

Wherein the preset restriction information includes any preset restriction information related to the sale of the product, preferably, the preset restriction information includes but is not limited to: preset budget information, and preset ROI (Return On Investment) information. The preset budget information includes any limit information related to the budget (i.e., subsidy) of the product, such as the total budget invested for the product, the budget invested for each price period, and the like. Wherein the preset ROI information comprises any restriction information related to the ROI, such as a target ROI.

Preferably, the computer device sorts the pricing units according to the marginal profit to obtain a pricing unit queue; then, the computer device obtains a pricing unit from one end of the pricing unit queue with larger marginal profit in turn without replacing and adds subsidies, and/or obtains a pricing unit from the other end of the pricing unit queue in turn without replacing and reduces subsidies according to the preset limit information and the preset subsidy rule, so that the price of each pricing unit can be determined.

As one example, the computer device orders the determined plurality of pricing units according to the corresponding marginal profit from greater to lesser, resulting in a pricing unit queue as shown in FIG. 5: pricing unit 1, pricing unit 2, …, pricing unit n, where | Δ ticketing/. DELTA subsidy | represents marginal profit for the pricing unit. In step S32, the computer apparatus performs the following operations:

i) if the current ROI is larger than the target ROI, the computer equipment sequentially obtains a pricing unit from the front end of the pricing unit queue without putting back, increases subsidies of the obtained pricing unit until the current ROI is smaller than the target ROI, and executes operation ii); if the pricing unit queue is empty, the operation ends. When a subsidy of a pricing unit is added, the current RO1 is (. DELTA.Total waterflow + Unit waterflow)/(. DELTA.Total subsidy + Unit subsidy), where the. DELTA.Total waterflow is the change in the total ticket output, the Unit waterflow is the ticket output of the pricing unit, the. DELTA.Total subsidy is the change in the total subsidy, and the Unit subsidy is the subsidy of the pricing unit.

ii) if the current ROI is smaller than the target ROI, the computer equipment sequentially obtains a pricing unit from the rear end of the pricing unit queue without being placed back, reduces subsidies of the obtained pricing unit until the current ROI is larger than the target ROI, and executes operation i); if the pricing unit queue is empty, the operation ends. When the subsidy for a pricing unit is reduced, the current RO1 is (total flow water-unit flow water)/(totalsubsidy-unit subsidy).

Then, upon completion of the operations, for each pricing unit, the computer device may determine the price for that pricing unit based on the subsidy added or subtracted to the pricing unit.

2) The computer device obtains two pricing units with the highest and lowest absolute values of marginal profit from the plurality of pricing units at a time without putting back, and performs the following operations on the two pricing units:

and reducing the price of the pricing unit with the lowest absolute value of the corresponding marginal profit in the two pricing units, and increasing the price of the other pricing unit in the two pricing units, wherein the reduced price value is the same as the increased price value.

Preferably, the price decreased or increased each time two pricing units are obtained without replacement is different, such as a first decreased or increased price of 10 dollars, a second decreased or increased price of 5 dollars, etc.

As one example, in step S2, the computer device determines four pricing units corresponding to the next price period for the product: r1, R2, R3 and R4. In step S31, the computer device calculates the marginal benefits of the four pricing units as: t1, T2, T3, T4, and T1< T2< T3< T4. In step S32, the computer device first obtains T1 and T4 from the four pricing units without replacement (with the lowest marginal profit for T1 and the highest marginal profit for T4), and lowers the price of T1 by 5 dollars and raises the price of T4 by 5 dollars; next, the computer device takes the remaining T2 and T3, and lowers the price of T2 by 4 dollars and raises the price of T3 by 4 dollars.

In this implementation, if only one pricing unit currently remains, the price of the pricing unit may not be changed, or the price of the pricing unit may be increased or decreased based on the predetermined rule.

It should be noted that the above examples are only for better illustrating the technical solution of the present invention, and not for limiting the present invention, and those skilled in the art should understand that any implementation of determining the price of each pricing unit of the plurality of pricing units during the next price period according to the marginal profit should be included in the scope of the present invention.

According to the scheme of the embodiment, the price of each pricing unit during the next price period of the product can be determined according to the calculated marginal profit of each pricing unit; and, the price of each pricing unit can be further determined by combining preset limit information so as to realize the maximization of the target under the limited conditions (such as maximum running water, highest return rate and the like).

Fig. 6 is a schematic structural diagram of an apparatus for dynamically adjusting the price of a product according to an embodiment of the present invention. The device for dynamically adjusting the price of a product (hereinafter referred to as "dynamic pricing device") comprises a first obtaining device 1, a first determining device 2 and a second determining device 3.

The first obtaining device 1 is configured to obtain the period change information of the product according to the period data of the product in the current price period and the last price period when the current price period of the product is finished.

As an example, for a movie being shown, the period length of each price period of the movie ticket is one day, and when one day ends (that is, the current price period ends), the first obtaining device 1 obtains the period change information of the movie ticket by comparing the period data of the movie ticket on the day with the period data of the previous day, the period change information indicating that the price of the movie ticket is decreased by 5% and the sales volume is increased by 10%.

The first determination device 2 determines a plurality of pricing units corresponding to the next price cycle of the product according to the cycle change information and the dimension information of the product.

Preferably, the first determining device 2 further comprises a constructing device (not shown), a first calculating device (not shown), and a first dividing device (not shown).

The construction device is used for constructing the dimension tree of the product according to the dimension information of the product.

It should be noted that, if the dimension information of the product is not changed, the dimension tree of the product is not changed, so that after the dimension tree of the product is constructed for the first time, the dimension tree can be stored, and the construction device does not need to be triggered to repeatedly execute operations to construct the dimension tree of the product in the subsequent price period; however, if the dimension information of the product changes (for example, one dimension value of the product is removed), the dimension tree of the product should be reconstructed, so that if the previously constructed dimension tree exists, the construction device can first determine whether the dimension information of the product changes, if so, construct the dimension tree of the product according to the changed dimension information, and if not, directly obtain the previously constructed dimension tree.

And the first calculation device calculates the pricing standard entropy corresponding to each dimension value in the dimension tree according to the periodic variation information of the product.

Preferably, for a dimension value of a product, the first calculating means calculates the pricing standard entropy H corresponding to the dimension value according to the periodic variation information of all nodes under the dimension value in the dimension tree based on the following formula:

H＝-rPP*ln(rPP)-rPN*ln(rPN)-rNP*ln(rNP)-rNN*ln(rNN)

Wherein, rPP |/SUM, rPN |/PN |/SUM, rNP |/SUM, rNN |/SUM, NN | + | NN |/SUM, SUM | + | PP | + | PN | + | NP | + | NN |, ln represents a natural logarithm with e as the base. The definitions of PP, PN, NP, NN are shown in Table 1.

And the first dividing device divides the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the calculated pricing standard entropy of each dimension value and based on the standard entropy minimum principle.

As an example, fig. 3 is a schematic diagram of dividing the dimension tree shown in fig. 2 into a plurality of pricing units according to an example of the present invention, first, the first dividing device determines that the pricing standard entropy corresponding to the dimension value "shanghai" is the minimum according to the pricing standard entropy of each dimension value in the dimension tree shown in fig. 2, and then the first dividing device divides the dimension tree into a tree including "shanghai" and a tree not including "shanghai"; then, for the tree containing "shanghai", the first partitioning device determines that the pricing standard entropy of the dimension value "30" in the tree is minimum, and then the first partitioning device further partitions the tree containing "shanghai" into the tree containing "30" and the tree not containing "30"; for trees that do not contain "shanghai", the first dividing means determines that the pricing criterion entropy of the dimension value "30" is minimal, and then the first dividing means further divides the trees that do not contain "shanghai" into trees that contain "30" and trees that do not contain "30". In fig. 3, "MIN ═ X" indicates that the pricing standard entropy of the dimension value X is minimum, "NON-X" indicates that X is not included, and X is a dimension value, such as "NON-shanghai" indicates that "shanghai" is not included.

Specifically, the implementation manner of the first partitioning device partitioning the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the calculated pricing standard entropy of each node and based on the standard entropy minimum principle includes, but is not limited to:

1) the first dividing means further comprises a second dividing means (not shown). And the second dividing device divides the dimension tree into a preset number of pricing units corresponding to the next price period of the product according to the pricing standard entropy and on the basis of a standard entropy minimum principle.

For example, the predetermined number is 4, the second dividing device divides the dimension Tree into Tree1 and Tree2 according to the pricing standard entropy and based on the standard entropy minimum principle; then, the second dividing device divides the Tree1 into Tree11 and Tree12, divides the Tree2 into Tree21 and Tree22, and takes Tree11, Tree12, Tree21 and Tree22 as 4 pricing units corresponding to the next price period of the product according to the pricing standard entropy and based on the standard entropy minimum principle.

For another example, the predetermined number is 3, the second dividing device divides the dimension Tree into Tree1 and Tree2 according to the pricing standard entropy and based on the standard entropy minimum principle; then, the second dividing means selects Tree1 based on a predetermined rule (e.g. the number of nodes is large, etc.), and divides Tree1 into Tree11 and Tree12 based on the standard entropy minimization principle, and takes Tree11, Tree12 and Tree2 as 3 pricing units corresponding to the next price period of the product.

2) The first dividing means further comprises a third dividing means (not shown). And the third dividing device is used for dividing the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the pricing standard entropy and the preset support degree and based on the standard entropy minimum principle.

For example, the third dividing means divides the dimension tree into two trees satisfying a predetermined support degree according to the pricing standard entropy of each dimension value of the product and based on the standard entropy minimum principle; for each tree obtained by division, the third division device further divides the tree into two trees meeting the preset support degree according to the pricing standard entropy of each dimension value of the product and based on the principle of minimum standard entropy; by analogy, support cannot obtain trees that satisfy a predetermined support degree.

It should be noted that the above-mentioned implementations 1) and 2) of the first dividing means may be combined. For example, the first dividing device divides the dimension tree into two trees meeting the preset support degree according to the pricing standard entropy of each dimension value of the product and based on the principle of minimum standard entropy; for each tree obtained by dividing, the first dividing device further divides the tree into two trees meeting the preset support degree according to the pricing standard entropy of each dimension value of the product and based on the principle of minimum standard entropy; and the rest is repeated until the trees meeting the preset support degree cannot be obtained or the preset number of trees are obtained through the dividing operation.

As another preferable aspect of the first determining means 2, the first determining means 2 includes second obtaining means (not shown) and third determining means (not shown). The second obtaining device is used for obtaining a plurality of dimension sets corresponding to the products according to the periodic variation information and the dimension information of the products, wherein at least one periodic variation condition of each object contained in one dimension set is the same or similar; then, a third determining device determines a plurality of pricing units corresponding to a next price period of the product according to the plurality of dimension sets.

The second obtaining device can obtain a plurality of dimension sets corresponding to the products according to the periodic variation information and the dimension information of the products through various modes such as statistical analysis and clustering.

Wherein the third determining means may determine a pricing unit based on the set of one or more dimensions. For example, the third determining means may directly use one dimension set as a pricing unit, or, when a pricing unit determined based on one dimension set cannot satisfy a predetermined support, combine the dimension set with other dimension sets to determine a pricing unit satisfying the predetermined support.

The second determining means 3 determines the price of each pricing unit of the plurality of pricing units during the next price period.

In particular, the second determining means 3 may employ a variety of implementations to determine the price of each pricing unit of the plurality of pricing units during the next price period.

As another alternative, for each pricing unit, the second determining means 3 increases or decreases the price of the pricing unit according to the corresponding periodic variation of the pricing unit.

For example, the first determination means 2 obtains two pricing units corresponding to the next price cycle of the product, based on the sales change information and the dimension information of the product: u1 and U2, wherein the periodic sales volume of U1 is increased, and the periodic sales volume of U2 is decreased; the second determining means 3 raises the price of U1 and lowers the price of U2 according to the cyclic variation of U1 and U2.

It should be noted that, each time one price period of the product is over, the first obtaining means 1, the first determining means 2 and the second determining means 3 are triggered to perform operations to determine the pricing units corresponding to the next price period and the price of each pricing unit. It should be further noted that the product price can be dynamically adjusted based on the solution of the embodiment after the second price period of the product is finished; preferably, the price of a product during its first price period is generally predetermined, and the price of a product during its second price period may be predetermined or determined based on the period data of the first price period.

Fig. 7 is a schematic structural diagram of an apparatus for dynamically adjusting the price of a product according to another embodiment of the present invention. The dynamic pricing means according to the present embodiment comprises first obtaining means 1, first determining means 2 and second determining means 3, wherein said second determining means 3 further comprises second calculating means 31 and fourth determining means 32. The first obtaining device 1 and the first determining device 2 have been described in detail in the embodiment shown in fig. 6, and are not described herein again.

For each pricing unit of the plurality of pricing units, the second calculating means 31 calculates a marginal benefit for that pricing unit.

Wherein the second calculating means 31 may calculate the marginal benefit of the pricing unit based on the following formula:

The fourth determining means 32 is adapted to determine the price of each pricing unit of the plurality of pricing units during the next price period based on the calculated marginal benefit.

In particular, implementations of the fourth determining means 32 for determining the price of each pricing unit of the plurality of pricing units during the next price period based on the calculated marginal profit include, but are not limited to:

1) the fourth determining means 32 further comprises fifth determining means (not shown). Fifth determining means for determining a price of each pricing unit of the plurality of pricing units during the next price period based on the marginal profit and preset limit information.

Preferably, the fifth determining means further comprises sorting means (not shown) and first pricing means (not shown). The sequencing device is used for sequencing the pricing units according to the marginal profit to obtain a pricing unit queue; and the first pricing device is used for sequentially obtaining a pricing unit from one end with larger marginal profit in the pricing unit queue without replacing and increasing subsidies according to the preset limit information and a preset subsidy rule, and/or sequentially obtaining a pricing unit from the other end of the pricing unit without replacing and reducing subsidies, so that the price of each pricing unit can be determined.

As an example, the sorting means sorts the determined pricing units according to the corresponding marginal profit from large to small, resulting in a pricing unit queue as shown in fig. 5: pricing unit 1, pricing unit 2, …, pricing unit n, where | Δ ticketing/. DELTA subsidy | represents marginal profit for the pricing unit. The first pricing means performs the following operations:

i) if the current ROI is larger than the target ROI, the first pricing device sequentially obtains a pricing unit from the front end of the pricing unit queue without putting back, subsidies of the obtained pricing unit are increased until the current ROI is smaller than the target ROI, and operation ii) is executed; if the pricing unit queue is empty, the operation ends. When a subsidy of a pricing unit is added, the current RO1 is (. DELTA.Total waterflow + Unit waterflow)/(. DELTA.Total subsidy + Unit subsidy), where the. DELTA.Total waterflow is the change in the total ticket output, the Unit waterflow is the ticket output of the pricing unit, the. DELTA.Total subsidy is the change in the total subsidy, and the Unit subsidy is the subsidy of the pricing unit.

ii) if the current ROI is smaller than the target ROI, the first pricing device sequentially obtains a pricing unit from the rear end of the pricing unit queue without being placed back, decreases subsidies of the obtained pricing unit until the current ROI is larger than the target ROI, and executes operation i); if the pricing unit queue is empty, the operation ends. When the subsidy for a pricing unit is reduced, the current RO1 is (total flow water-unit flow water)/(totalsubsidy-unit subsidy).

Then, when the operation ends, for each pricing unit, the first pricing means may determine the price of the pricing unit based on the subsidy added or subtracted by the pricing unit.

2) The fourth determining means 32 further comprises second pricing means (not shown). The second pricing unit obtains two pricing units with the highest and lowest absolute values of the marginal profit from the plurality of pricing units at a time without putting back, and performs the following operations on the two pricing units:

As an example, the first determining means 2 determines four pricing units corresponding to the next price period of the product: r1, R2, R3 and R4. The marginal benefits calculated by the second calculating device 31 of the four pricing units are respectively: t1, T2, T3, T4, and T1< T2< T3< T4. The second pricing device firstly obtains T1 and T4 (the marginal profit of T1 is lowest, and the marginal profit of T4 is highest) from the four pricing units without returning, reduces the price of T1 by 5 yuan, and increases the price of T4 by 5 yuan; then, the second pricing device takes the remaining T2 and T3, lowers the price of T2 by 4 dollars, and raises the price of T3 by 4 dollars.

The present invention also provides an apparatus for dynamically adjusting the price of a product, the apparatus comprising:

one or more processors for executing a program to perform,

a memory storing one or more programs,

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the above-described method for dynamically adjusting the price of a product.

Fig. 8 shows a schematic diagram of one implementation of an apparatus for dynamically adjusting prices of products according to the present invention. The device 400 includes a memory 410 and a processor 420. The memory 410 stores one or more programs that, when executed by the processor 420, the processor 420 implements the above-described method for dynamically adjusting the price of a product.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.

Claims

1. A method for dynamically adjusting the price of a product, wherein the method comprises:

determining a price for each pricing unit of the plurality of pricing units during the next price period;

the determining a plurality of pricing units corresponding to a next price cycle of the product according to the cycle change information and the dimension information of the product comprises:

constructing a dimension tree of the product according to the dimension information of the product;

calculating a pricing standard entropy corresponding to each dimension value in the dimension tree according to the periodic variation information;

and dividing the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the pricing standard entropy and based on a standard entropy minimum principle.

2. The method of claim 1, wherein the step of partitioning the dimension tree into a plurality of pricing units corresponding to a next price period of the product according to the pricing criteria entropy and based on a criteria entropy minimization principle comprises:

And dividing the dimension tree into a preset number of pricing units corresponding to the next price period of the product according to the pricing standard entropy and based on a standard entropy minimum principle.

3. The method of claim 1, wherein the step of partitioning the dimension tree into a plurality of pricing units corresponding to a next price period of the product according to the pricing criteria entropy and based on a criteria entropy minimization principle comprises:

and dividing the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the pricing standard entropy and the preset support degree and based on a standard entropy minimum principle.

4. The method of claim 1, wherein the step of determining the price of each pricing unit of the plurality of pricing units during the next price period comprises:

for each pricing unit of the plurality of pricing units, calculating a marginal benefit for the pricing unit;

determining a price for each pricing unit of the plurality of pricing units during the next price period based on the marginal benefit.

5. The method of claim 4, wherein the step of determining the price of each pricing unit of the plurality of pricing units during the next price period based on the marginal gain comprises:

And determining the price of each pricing unit in the plurality of pricing units during the next price period according to the marginal profit and preset limit information.

6. The method of claim 5, wherein the preset restriction information comprises at least one of:

-preset budget information;

-preset ROI information.

7. The method of claim 5, wherein the step of determining the price of each pricing unit of the plurality of pricing units during the next price period based on the marginal return and preset limit information comprises:

sequencing the pricing units according to the marginal profit to obtain a pricing unit queue;

and according to the preset limit information and a preset subsidy rule, obtaining a pricing unit from one end of the pricing unit queue with larger marginal profit in sequence without replacing and increasing subsidies, and/or obtaining a pricing unit from the other end of the pricing unit sequence without replacing and reducing subsidies.

8. The method of claim 4, wherein the step of determining the price of each pricing unit of the plurality of pricing units during the next price period based on the marginal gain comprises:

Obtaining two pricing units with the highest and lowest absolute value of marginal profit from the plurality of pricing units at a time without putting back, and performing the following operations on the two pricing units:

9. An apparatus for dynamically adjusting the price of a product, wherein the apparatus comprises:

means for determining a price for each pricing unit of the plurality of pricing units during the next price period;

means for determining a plurality of pricing units corresponding to a next price cycle of the product based on the cycle change information and the dimensional information for the product, comprising:

Means for constructing a dimension tree of the product based on the dimension information of the product;

means for calculating a pricing standard entropy corresponding to each dimension value in the dimension tree according to the period variation information;

and dividing the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the pricing standard entropy and on the basis of a standard entropy minimum principle.

10. The apparatus of claim 9, wherein the means for partitioning the dimension tree into a plurality of pricing units corresponding to a next price period of the product according to the pricing criteria entropy and based on a criteria entropy minimization principle comprises:

and dividing the dimension tree into a preset number of pricing units corresponding to the next price period of the product according to the pricing standard entropy and on the basis of a standard entropy minimum principle.

11. The apparatus of claim 9, wherein the means for partitioning the dimension tree into a plurality of pricing units corresponding to a next price period of the product according to the pricing criteria entropy and based on a criteria entropy minimization principle comprises:

And dividing the dimension tree into a plurality of pricing units corresponding to the next price period of the product according to the pricing standard entropy and a preset support degree and based on a standard entropy minimum principle.

12. The apparatus of claim 9, wherein the means for determining the price of each pricing unit of the plurality of pricing units during the next price period comprises:

means for calculating, for each pricing unit of the plurality of pricing units, a marginal benefit for that pricing unit;

means for determining a price for each pricing unit of the plurality of pricing units during the next price period based on the marginal benefit.

13. The apparatus of claim 12, wherein the means for determining the price of each pricing unit of the plurality of pricing units during the next price period based on the marginal benefit comprises:

means for determining a price for each pricing unit of the plurality of pricing units during the next price period based on the marginal benefit and preset limit information.

14. The apparatus of claim 13, wherein the preset restriction information comprises at least one of:

-preset budget information;

-preset ROI information.

15. The apparatus of claim 13, wherein the means for determining the price of each pricing unit of the plurality of pricing units during the next price period based on the marginal return and preset limit information comprises:

means for sorting the pricing units according to the marginal profit to obtain a pricing unit queue;

and the device is used for acquiring a pricing unit and increasing subsidies from one end with larger marginal profit in the pricing unit queue without replacing the pricing unit in sequence and/or acquiring a pricing unit and reducing subsidies from the other end of the pricing unit in sequence without replacing the pricing unit according to the preset limit information and a preset subsidy rule.

16. The apparatus of claim 12, wherein the means for determining the price of each pricing unit of the plurality of pricing units during the next price period based on the marginal benefit comprises:

means for obtaining two pricing units of the marginal profit having the highest and lowest absolute values at a time without being placed back from the plurality of pricing units, and performing the following operations for the two pricing units:

17. An apparatus, comprising:

one or more processors for executing a program to perform,

a memory storing one or more programs,

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-8.