CN109191205A - A kind of price calculation method and terminal device based on prediction model - Google Patents

A kind of price calculation method and terminal device based on prediction model Download PDF

Info

Publication number
CN109191205A
CN109191205A CN201811016903.3A CN201811016903A CN109191205A CN 109191205 A CN109191205 A CN 109191205A CN 201811016903 A CN201811016903 A CN 201811016903A CN 109191205 A CN109191205 A CN 109191205A
Authority
CN
China
Prior art keywords
price
product
sales
target
history
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201811016903.3A
Other languages
Chinese (zh)
Inventor
陈旭东
刘巧玲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Ping An Technology Shenzhen Co Ltd
Original Assignee
Ping An Technology Shenzhen Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ping An Technology Shenzhen Co Ltd filed Critical Ping An Technology Shenzhen Co Ltd
Priority to CN201811016903.3A priority Critical patent/CN109191205A/en
Publication of CN109191205A publication Critical patent/CN109191205A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201Market modelling; Market analysis; Collecting market data
    • G06Q30/0206Price or cost determination based on market factors

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Accounting & Taxation (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Finance (AREA)
  • Marketing (AREA)
  • Game Theory and Decision Science (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Data Mining & Analysis (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The present invention provides a kind of price calculation method and terminal device based on prediction model are suitable for technical field of data processing, this method comprises: obtaining the sales data of product to be fixed a price;Based on the sales volume and sales growth rate in sales data, the life-cycle stages that product to be fixed a price is presently in are identified;Sales data is handled based on life-cycle stages corresponding default processing model, determines the target pricing of product to be fixed a price.The embodiment of the present invention it is adaptive determine arm's length pricing of the product under different product life cycle phase, realize the price to product precise and high efficiency.

Description

A kind of price calculation method and terminal device based on prediction model
Technical field
The invention belongs to technical field of data processing, more particularly to the price calculation method based on prediction model and terminal are set It is standby.
Background technique
Present price fixing method is all manually to fix a price, as the type for developing product in market is more and more abundant, fixed It is extremely low to need to expend a large amount of human and material resources efficiency when valence, simultaneously because present market situation becomes increasingly complex, In price, factor in need of consideration is more and more, and influence of these factors with the variation of time to price is not yet Together, therefore, existing to be difficult to meet the actual demand of price fixing using artificial price.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of price calculation method and terminal device based on prediction model, To solve the problems, such as in the prior art manually to price fixing low efficiency inaccuracy.
The first aspect of the embodiment of the present invention provides a kind of price calculation method based on prediction model, comprising:
Obtain the sales data of product to be fixed a price;
Based on the sales volume and sales growth rate in the sales data, identify what the product to be fixed a price was presently in Life-cycle stages;
The sales data is handled based on the life-cycle stages corresponding default processing model, is determined The target pricing of the product to be fixed a price out.
The second aspect of the embodiment of the present invention provides a kind of terminal device, and the terminal device includes memory, processing Device, the computer program that can be run on the processor is stored on the memory, and the processor executes the calculating Following steps are realized when machine program.
Obtain the sales data of product to be fixed a price;
Based on the sales volume and sales growth rate in the sales data, identify what the product to be fixed a price was presently in Life-cycle stages;
The sales data is handled based on the life-cycle stages corresponding default processing model, is determined The target pricing of the product to be fixed a price out.
The third aspect of the embodiment of the present invention provides a kind of computer readable storage medium, comprising: is stored with computer Program, which is characterized in that realize when the computer program is executed by processor as described above based on the price of prediction model The step of calculation method.
Existing beneficial effect is the embodiment of the present invention compared with prior art: the embodiment of the present invention is based on product in difference The sale characteristics of demand of life cycle is provided with corresponding different processing model, and according to the currently practical locating life of product After the life period selects corresponding processing model, the sales data of product is handled using corresponding processing model, it is adaptive That answers determines arm's length pricing of the product under different product life cycle phase, realizes the price to product precise and high efficiency.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these Attached drawing obtains other attached drawings.
Fig. 1 is the implementation process schematic diagram for the price calculation method based on prediction model that the embodiment of the present invention one provides;
Fig. 2 is the implementation process schematic diagram of the price calculation method provided by Embodiment 2 of the present invention based on prediction model;
Fig. 3 is the implementation process schematic diagram for the price calculation method based on prediction model that the embodiment of the present invention three provides;
Fig. 4 is the implementation process schematic diagram for the price calculation method based on prediction model that the embodiment of the present invention four provides;
Fig. 5 is the implementation process schematic diagram for the price calculation method based on prediction model that the embodiment of the present invention five provides;
Fig. 6 is the structural schematic diagram for the price computing device based on prediction model that the embodiment of the present invention six provides;
Fig. 7 is the schematic diagram for the terminal device that the embodiment of the present invention seven provides.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
Fig. 1 shows the implementation flow chart of the price calculation method based on prediction model of the offer of the embodiment of the present invention one, Details are as follows:
S101 obtains the sales data of product to be fixed a price.
Wherein, sales data refers to the related data of product sale, such as time of sale, the corresponding sales volume of different time And sales growth rate etc. of the product in selling time.
S102 identifies the production that product to be fixed a price is presently in based on the sales volume and sales growth rate in sales data Product life cycle phase.
Wherein, sales growth rate refers to product in the ratio between the sales growth volume in the current year and prior year gross sales amount, this year Degree sales growth volume is the difference that current year income from sales subtracts previous year income from sales.Product life cycle refer to product from It puts goods on the market to the overall process experienced that updates and withdraw from the market, consumer demand when being sold in the market according to product And the factors such as product market situation are divided, the product life cycle successively includes introducing phase, growth stage, maturity period and declines Move back phase four-stage.The characteristics of due to different phase, is different, and when carrying out price fixing, practical main purpose is also different Sample, for example, introduce the phase when consumer product is not understood that, consumer buy product a possibility that it is smaller sale slowly, therefore this Stage main purpose is that product promotion is gone out, and improves occupation rate of market, so that consumer slowly recognizes and receives product, growth Consumer has had certain understanding to product when the phase, and product market gradually expands, and the purpose in this stage mainly occupies city Simultaneously obtain profit, and when to the maturity period, known to consumer, the market of product tends to saturation and stablizes product, therefore The main purpose in maturity period is to guarantee profit on sales.
In embodiments of the present invention, the life cycle phase that product is presently in is identified using sales growth rate method, i.e., Judge life-cycle stages locating for product, according to the sales growth rate of product and sales volume to determine for subsequent product Specific determine of valence method provides reference.
S103 handles sales data based on the corresponding default processing model of life-cycle stages, determines The target pricing of product to be fixed a price.
Since the price main purpose of different phase product is different, if directly being united using a set of pricing method One price, will cause practical price to be unable to satisfy each stage actual demand, to situations such as unreasonable of fixing a price occur.Therefore, In order to meet product in the actual demand in each stage, the arm's length pricing of product in the market, this hair under each stage are realized It can carry out the setting of price processing model in bright embodiment in the actual demand in each stage for product in advance, and in determination Out after life-cycle stages, chooses corresponding processing model and handled to determine that the stage corresponding product is fixed Valence.Wherein specifically processing model can be all to be able to satisfy the said goods different phase target requirement by technical staff's sets itself Model, including but not limited to such as introducing the phase, the case where according to the practical price and occupation rate of market of like product Determine the price of product, it is fixed when for growth stage analysis product sale when being promoted with meeting the needs of target market occupation rate Relationship between valence and occupation rate of market and profit, then determine finally to fix a price based on the relationship.
Sale characteristics of demand of the embodiment of the present invention based on product in different life is provided with corresponding different place Model is managed, and after locating life cycle currently practical according to product selects corresponding processing model, utilizes corresponding place Reason model handles the sales data of product, and adaptive determines conjunction of the product under different product life cycle phase Reason price, realizes the price to product precise and high efficiency.
A kind of specific implementation of model is handled as the embodiment of the present invention one, it is contemplated that when product is in the introducing phase When, main purpose is to promote product product is recognized by consumer as soon as possible, possesses certain market as soon as possible and occupies Rate, in order to realize the purpose, sales data further includes preset target market occupation rate and minimum price in the embodiment of the present invention, It can identify whether product is in the introducing phase according to sales growth rate and sales volume simultaneously, as shown in Fig. 2, the embodiment of the present invention Two, comprising:
S201, when sales growth rate is in default first growth rate range, and sales volume is less than default sales volume threshold value, Life-cycle stages are determined to introduce the phase.
Wherein, the first specific value of growth rate range can be set according to actual conditions by technical staff, it is contemplated that at product Illustrate that it is gradually recognized receiving by consumer when the phase of introducing, its sales volume and sales growth rate are all relatively low at this time, very To the case where sales growth rate is negative is likely to occur, it is preferred that the first growth rate range higher limit does not answer excessive, lower limit value Should be less than zero, it is less than 10% that the first growth rate range, which such as can be set,.Sales volume refers to that product is total in the sale in the current year Amount increases according only to sale at this time due to finding that the sales growth rate of introducing phase and maturity period product is all relatively low in actual conditions Long rate is often difficult to differentiate between two stages, but the sales volume due to introducing phase product is far below the maturity period, and the present invention is implemented Two stages are further distinguished by one sales volume threshold value of setting in example, to guarantee the accurate of stage identification Property, sales volume threshold value specific size can be by technical staff according to product actual conditions sets itself.
S202, obtains the product information of product to be fixed a price, and filters out the product information of product information Yu product to be fixed a price Similarity is higher than the price product of threshold value.
S203, history price and historic market occupation rate based on product of having fixed a price, the preset prediction model of training.
Wherein, product information includes but is not limited to type, function and the specification of such as product, and the threshold value of similarity can be by Technical staff's sets itself according to actual needs.
Shorter in view of introducing phase product selling time in actual conditions, sales volume and occupation rate of market data etc. are gone through History sales data is less, it is difficult to be directly used in sample data analysis, be recognized and connect by user simultaneously because itself introducing phase product The degree of receipts with regard to relatively low, therefore in the sales data of this work-in-process be in fact it is extremely unstable, it is unstable with these When data are as sample data analysis, it tends to be difficult to obtain the relationship between accurately and effectively occupation rate of market and price.Cause This, in the embodiment of the present invention and the data such as some sales volumes of unused product itself are as sample data analysis, but adopt It has taken the history price to similar product of having fixed a price and historic market occupation rate analyze as sample data and training is pre- Survey model.Wherein prediction model can choose the common prediction model such as neural network model or regressive prediction model, can also make With the prediction model of technical staff's designed, designed, not limit herein.
S204 is handled target market occupation rate based on trained prediction model, determines prediction price.
S205 is adjusted prediction price based on minimum price, obtains target pricing.
Wherein, target market occupation rate is set by technical staff according to the practical popularization demand for introducing phase product, with Guarantee that final promotion effect, minimum price are set by technical staff according to the factors demand such as actual cost of product, to ensure The reasonability finally fixed a price.Due to being found in actual conditions, generally required if product wishes that occupation rate of market is higher in the introducing phase Certain reduction is carried out in price, therefore often will appear in actual conditions in order to occupy market, and phase price fixing pole is introduced The case where low even lower than cost, will not be too low in order to guarantee finally to fix a price, that is, guarantee that the reasonability finally fixed a price, the present invention are real A minimum price can be also arranged while target market occupation rate is arranged by applying example, in the target using prediction model to setting Occupation rate of market obtains corresponding prediction price after being handled after, judge whether prediction price is greater than minimum price, if greatly In then directly as final price, if being not more than, by minimum price as final price.
Another specific implementation of model is handled as the embodiment of the present invention one, it is contemplated that when product is in the growth stage When consumer there is certain understanding to product, therefore growth stage main purpose occupies market and obtains profit, for reality The now purpose, in the embodiment of the present invention sales data fix a price comprising history, history profit margin, historical sales total value and history city While these historic sales datas of occupation rate, can also be provided with this stage wishes the target rate of return reached, target marketing Total value and target market occupation rate quantify this stage purpose, identifying that product is in the growth stage according to sales growth rate And then corresponding final price is calculated using these data, as shown in figure 3, the embodiment of the present invention three, comprising:
S301, when sales growth rate is in default second growth rate range, judgement life-cycle stages are the growth stage When.
More and more consumers starts to receive and use product when being in the growth stage in view of product, is product pin at this time It sells the fastest-rising stage, is i.e. in sales growth rate highest period, can accurately identify produce according only to sales growth rate at this time Whether product are in the stage, without how considering specific sales volume.Wherein, the second specific value of growth rate range can be by technology Personnel are set according to actual conditions, it is preferable that can be set greater than the second growth rate range or equal to 10%.
S302 calculates target pricing based on formula (1):
Wherein, a and b is the constant term greater than 0, and a+b=1 and a > b, TarPri2 are target pricing, and TarPri1 is to go through History price, MatShare2 are target market occupation rate, and MatShare1 is historic market occupation rate,
C is to be equal to 1 constant term greatly, and PftMgn2 is target rate of return, and PftMgn1 is history profit margin, and GosSle2 is mesh Gross sales amount is marked, GosSle1 is historical sales total value.
After determining that product is in the growth stage, by history price, the history profit margin, historical sales in sales data Total value and these historic sales datas of historic market occupation rate and target rate of return, target marketing total value and target market account for There is rate to be substituting to above-mentioned formula (1), that is, in the case where can determine that the occupation rate of market needed for meeting target and profit, accurately Reasonable final price.
Another specific implementation of model is handled as the embodiment of the present invention one, it is contemplated that when product is in the maturity period When, the market known to consumer has tended to be saturated product, and occupation rate of market has been difficult to happen large change at this time, Therefore the main purpose in maturity period is to guarantee profit on sales, and in order to realize the purpose, sales data is being wrapped in the embodiment of the present invention While containing history price, history profit margin and these historic sales datas of historical sales total value, it is uncommon to be also provided with this stage Hope the target rate of return reached and target marketing total value, after identifying that product is in the maturity period according to sales growth rate, These data are recycled to calculate corresponding final price, as shown in figure 4, the embodiment of the present invention four, comprising:
S401 presets third growth rate range when sales growth rate is in, and sales volume is greater than or equal to default sales volume When threshold value, determine that life-cycle stages are the maturity period.
Market tends to be saturated when wherein, due to the maturity period, and sale is larger and relatively stable, therefore corresponding sale increases Long rate is typically small, if being often difficult to distinguish maturity period and introducing phase at this time according only to sales growth rate, therefore this hair A sales volume threshold value is provided in bright embodiment to distinguish two stages.Wherein the value of sales volume threshold value should be with present invention reality Apply identical in example two or greater than the sales volume threshold value in the embodiment of the present invention two, the value of third growth rate range both can be with The first growth rate range in the embodiment of the present invention two is identical, can also be different, is specifically set according to actual needs by technical staff It is fixed, it is preferable that may be configured as 1%~10%.
S402, based on history price, history profit margin and historical sales total value, the preset prediction model of training.
After determining that product is in the maturity period, in order to realize in the feelings for meeting target rate of return and target marketing total value Accurate reasonable price is carried out to product under condition, first has to determine price and the relationship between profit margin and gross sales amount.It examines Consider product when reaching the maturity period and sold a period of time, is provided with more available historic sales data, therefore this hair Bright embodiment can carry out the instruction of prediction model using history price, history profit margin and historical sales total value as sample data Practice building.Wherein prediction model can choose the common prediction model such as neural network model or regressive prediction model, can also make With the prediction model of technical staff's designed, designed, not limit herein.
S403 is based on trained prediction model, handles target rate of return and target marketing total value, obtain target Price.
After obtaining trained prediction model, the target rate of return of setting and target marketing total value are input to prediction Model is handled, that is, can determine that final price.
Should explanatorily, the embodiments of the present invention two, the embodiment of the present invention three and the embodiment of the present invention four are to this The refinement scheme of the processing model of a kind of different product life cycle phase sales data of inventive embodiments, when according to practical application Demand it is different, both can be combined application with the embodiment of the present invention one in the form of single embodiment, can also with times The form and the embodiment of the present invention one of meaning quantity embodiment combination are combined application.
As the embodiment of the present invention five, it is contemplated that in actual conditions, the embodiments of the present invention one to the embodiment of the present invention Finally price is not necessarily unique numerical value obtained in four, it is also possible to which a range is such as set in the embodiment of the present invention two When fixed target market occupation rate is a range rather than a fixed value, the final price obtained at this time also will be a model It encloses, this have the advantage that, can more fix a price selection space to the businessman of sale product, with real to different consumers Border situation demand is adjusted flexibly.In order to improve the accuracy rate of price, the embodiment of the present invention is not unique for final price Situation determines the corresponding final price of the client according to the actual conditions of the consumer (client) of purchase product, such as Fig. 5 institute Show, comprising:
S501 obtains the consumer record that client treats price product, and determines that client's is important etc. based on consumer record Grade.
Since consumer record situation of the different consumers to product is different, if some are consumers steady in a long-term, some It is scattered consumer, in order to attract consumer to buy product as much as possible, while guarantees that sale price meets above-described embodiment Calculated price situation can give different prices for these different consumers in the embodiment of the present invention.
Wherein consumer record includes buying the record number such as number, the quantity of price and purchase bought every time of product According to.The method for determining client's important level with specific reference to consumer record can not be limited herein by technical staff's sets itself, packet It includes but is not limited to reach a certain threshold value as first to the standard for being respectively provided with every kind of consumer record data one quantization, such as bought number When be quantified as corresponding a certain score value, then weight calculation, and root are carried out to the score value of obtained each consumer record data According to final weight calculation as a result, determining corresponding important level.
S502 determines the corresponding price of client based on important level from multiple prices that target pricing includes.
In order to confirm the corresponding price of different consumers, the pre-set consumer's important level of the embodiment of the present invention with Relationship between difference price, after recording the evaluation to carry out important level to it according to the real consumption of consumer, then root Final price is determined from obtained multiple prices according to important level.Wherein, due to the embodiments of the present invention one to four Obtained in price actual value size and quantity cannot achieve determination, therefore carrying out important level and relationship setting of fixing a price When, it is preferable that it can be set to ratio conversion, such as highest important level in important level range determined corresponding to what is obtained Highest is fixed a price in valence, and the lowest class corresponds to minimum price, and it is corresponding final fixed proportionally to calculate each important level Valence determines its final price further according to the actual important level of consumer.
In embodiments of the present invention, it is contemplated that sales data feature and price correspond in different product life cycle phase Purpose it is different, carried out being respectively set for processing model for the feature of introducing phase, growth stage and maturity period respectively.It is specific and The characteristics of speech, phase sales volume is less and unstable for introducing, while its object is to the popularizations of product, utilizes like product Historic sales data train and construct prediction model, and utilize the minimum price of obtained prediction model and setting to carry out The calculating finally fixed a price determines, while ensure that the validity to product promotion, ensure that price will not be too low, to protect The Accuracy and high efficiency of the price fixing in the phase of introducing is demonstrate,proved.For the growth stage, since main purpose is both accounted for comprising market Have rate propulsion again include profit acquisition, therefore, in the embodiment of the present invention combine some data of product historical sales with And occupation rate of market, profit margin and the gross sales amount reached needed for the work-in-process target, it is corresponding final to be calculated Price, so that the price in the stage can meet two aspect demands of occupation rate of market and profit simultaneously, realizes to growth The price of phase efficiently and accurately.For the maturity period, since product has sold a period of time at this time, market tends to be saturated, therefore Main purpose at this time is to ensure certain profit on sales, therefore the embodiment of the present invention can sell according to product and obtain Data are analyzed, and to determine the relationship between price and profit, then calculate the corresponding price of profit needed for target, from And realize the precise and high efficiency price to the maturity period.Finally it is directed to the difference of each consumer's concrete condition, the embodiment of the present invention The determination of unique price is also carried out, different prices is preferential, and realization is being protected to guarantee to give for consumer's actual conditions Card sale price meets above-mentioned calculated price situation simultaneously, and attraction consumer buys product as much as possible.Therefore the present invention Embodiment realizes the precise and high efficiency price to each different phase difference consumer of product, meets the practical need of price fixing It asks.
Corresponding to the method for foregoing embodiments, Fig. 6 shows the price provided in an embodiment of the present invention based on prediction model The structural block diagram of computing device, for ease of description, only parts related to embodiments of the present invention are shown.The exemplary base of Fig. 6 It can be the price calculation method based on prediction model of the offer of previous embodiment one in the price computing device of prediction model Executing subject.
Referring to Fig. 6, being somebody's turn to do the price computing device based on prediction model includes:
Data acquisition module 61, for obtaining the sales data of product to be fixed a price.
Phase identification module 62, for based on the sales volume and sales growth rate in the sales data, described in identification The life-cycle stages that product to be fixed a price is presently in.
Pricing module 63, for being based on the corresponding default processing model of the life-cycle stages to the sale number According to being handled, the target pricing of the product to be fixed a price is determined.
Further, pricing module 63, comprising:
Product screening mould, for obtaining the product information of the product to be fixed a price, and filter out product information and it is described to The product information similarity of price product is higher than the price product of threshold value.
First model training module, for based on the product of having fixed a price history price and historic market occupation rate, The preset prediction model of training.
First price prediction module, for being carried out based on the trained prediction model to the target market occupation rate Prediction price is determined in processing.
Price modified module obtains the target for being adjusted based on the minimum price to prediction price Price.
Further, pricing module 63, comprising:
Price computing module, for calculating the target pricing based on following formula:
Wherein, a and b is the constant term greater than 0, and a+b=1 and a > b, TarPri2 are target pricing, and TarPri1 is to go through History price, MatShare2 are target market occupation rate, and MatShare1 is historic market occupation rate,c To be equal to 1 constant term greatly, PftMgn2 is target rate of return, and PftMgn1 is history profit margin, and GosSle2 is that target marketing is total Volume, GosSle1 are historical sales total value.
Further, pricing module 63, comprising:
Second model training module, for based on history price, the history profit margin and the historical sales Total value, the preset prediction model of training.
Second price prediction module, for being based on the trained prediction model, to the target rate of return and described Target marketing total value is handled, and the target pricing is obtained.
Further, it is somebody's turn to do the price computing device based on prediction model, further includes:
Client is obtained to the consumer record of the product to be fixed a price, and determines the client's based on the consumer record Important level.
Based on the important level from multiple prices that the target pricing includes, determine that the client is corresponding fixed Valence.
Each module realizes the mistake of respective function in price computing device provided in an embodiment of the present invention based on prediction model Journey specifically refers to the description of aforementioned embodiment illustrated in fig. 1 one, and details are not described herein again.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit It is fixed.
Although will also be appreciated that term " first ", " second " etc. are used in some embodiment of the present invention in the text Various elements are described, but these elements should not be limited by these terms.These terms are used only to an element It is distinguished with another element.For example, the first table can be named as the second table, and similarly, the second table can be by It is named as the first table, without departing from the range of various described embodiments.First table and the second table are all tables, but It is them is not same table.
Fig. 7 is the schematic diagram for the terminal device that one embodiment of the invention provides.As shown in fig. 7, the terminal of the embodiment is set Standby 7 include: processor 70, memory 71, and the computer that can be run on the processor 70 is stored in the memory 71 Program 72.The processor 70 realizes above-mentioned each price calculating side based on prediction model when executing the computer program 72 Step in method embodiment, such as step 101 shown in FIG. 1 is to 106.Alternatively, the processor 70 executes the computer journey The function of each module/unit in above-mentioned each Installation practice, such as the function of module 61 to 66 shown in Fig. 6 are realized when sequence 72.
The terminal device 7 can be the calculating such as desktop PC, notebook, palm PC and cloud server and set It is standby.The terminal device may include, but be not limited only to, processor 70, memory 71.It will be understood by those skilled in the art that Fig. 7 The only example of terminal device 7 does not constitute the restriction to terminal device 7, may include than illustrating more or fewer portions Part perhaps combines certain components or different components, such as the terminal device can also include input sending device, net Network access device, bus etc..
Alleged processor 70 can be central processing unit (Central Processing Unit, CPU), can also be Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field- Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic, Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor Deng.
The memory 71 can be the internal storage unit of the terminal device 7, such as the hard disk or interior of terminal device 7 It deposits.The memory 71 is also possible to the External memory equipment of the terminal device 7, such as be equipped on the terminal device 7 Plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card dodge Deposit card (Flash Card) etc..Further, the memory 71 can also both include the storage inside list of the terminal device 7 Member also includes External memory equipment.The memory 71 is for storing needed for the computer program and the terminal device Other programs and data.The memory 71, which can be also used for temporarily storing, have been sent or data to be sent.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program generation Code can be source code form, object identification code form, executable file or certain intermediate forms etc..The computer-readable medium It may include: any entity or device, recording medium, USB flash disk, mobile hard disk, magnetic that can carry the computer program code Dish, CD, computer storage, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), electric carrier signal, telecommunication signal and software distribution medium etc..
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations;Although referring to aforementioned reality Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features;And these are modified Or replacement, the essence of corresponding technical solution is departed from the spirit and scope of the technical scheme of various embodiments of the present invention, it should all It is included within protection scope of the present invention.

Claims (10)

1. a kind of price calculation method based on prediction model characterized by comprising
Obtain the sales data of product to be fixed a price;
Based on the sales volume and sales growth rate in the sales data, the product that the product to be fixed a price is presently in is identified Life cycle phase;
The sales data is handled based on the life-cycle stages corresponding default processing model, determines institute State the target pricing of product to be fixed a price.
2. the price calculation method based on prediction model as described in claim 1, which is characterized in that the sales data is also wrapped Preset target market occupation rate and minimum price are included, when the sales growth rate is in default first growth rate range, and institute When stating sales volume and being less than default sales volume threshold value, determine the life-cycle stages for the introducing phase, the default processing mould Treatment process of the type to the sales data, comprising:
The product information of the product to be fixed a price is obtained, and filters out the product information phase of product information with the product to be fixed a price It is higher than the price product of threshold value like degree;
History price and historic market occupation rate based on the product of having fixed a price, the preset prediction model of training;
The target market occupation rate is handled based on the trained prediction model, determines prediction price;
Prediction price is adjusted based on the minimum price, obtains the target pricing.
3. the price calculation method based on prediction model as described in claim 1, which is characterized in that the sales data is also wrapped Include preset target rate of return, target marketing total value and target market occupation rate and history price, history profit margin, history Gross sales amount and historic market occupation rate preset the second growth rate range when the sales growth rate is in, determine the product When life cycle phase is the growth stage, treatment process of the default processing model to the sales data, comprising:
The target pricing is calculated based on following formula:
Wherein, a and b is the constant term greater than 0, a+b=1 and a > b, TarPri2 are target pricing, and TarPri1 is fixed for history Valence, MatShare2 are target market occupation rate, and MatShare1 is historic market occupation rate,C is big Equal to 1 constant term, PftMgn2 is target rate of return, and PftMgn1 is history profit margin, and GosSle2 is target marketing total value, GosSle1 is historical sales total value.
4. the price calculation method based on prediction model as described in claim 1, which is characterized in that the sales data is also wrapped Preset target rate of return and target marketing total value and history price, history profit margin and historical sales total value are included, when described Sales growth rate is in default third growth rate range, and when the sales volume is greater than or equal to default sales volume threshold value, determines The life-cycle stages are the maturity period, treatment process of the default processing model to the sales data, comprising:
Based on history price, the history profit margin and the historical sales total value, the preset prediction model of training;
Based on the trained prediction model, the target rate of return and the target marketing total value are handled, obtained The target pricing.
5. the price calculation method based on prediction model as described in Claims 1-4 any one, which is characterized in that described When in target pricing including multiple prices, after the target pricing for determining the product to be fixed a price, further includes:
Client is obtained to the consumer record of the product to be fixed a price, and determines that the client's is important based on the consumer record Grade;
Based on the important level from multiple prices that the target pricing includes, the corresponding price of the client is determined.
6. a kind of terminal device, which is characterized in that the terminal device includes memory, processor, is stored on the memory There is the computer program that can be run on the processor, the processor realizes following step when executing the computer program It is rapid:
Obtain the sales data of product to be fixed a price;
Based on the sales volume and sales growth rate in the sales data, the product that the product to be fixed a price is presently in is identified Life cycle phase;
The sales data is handled based on the life-cycle stages corresponding default processing model, determines institute State the target pricing of product to be fixed a price.
7. terminal device as claimed in claim 6, which is characterized in that the sales data further includes that preset target market accounts for There are rate and minimum price, presets the first growth rate range when the sales growth rate is in, and the sales volume is less than default pin When the amount of selling threshold value, the life-cycle stages are determined for the introducing phase, the default processing model is to the sales data Treatment process, comprising:
The product information of the product to be fixed a price is obtained, and filters out the product information phase of product information with the product to be fixed a price It is higher than the price product of threshold value like degree;
History price and historic market occupation rate based on the product of having fixed a price, the preset prediction model of training;
The target market occupation rate is handled based on the trained prediction model, determines prediction price;
Prediction price is adjusted based on the minimum price, obtains the target pricing.
8. terminal device as claimed in claim 6, which is characterized in that the sales data further includes preset target profit Rate, target marketing total value and target market occupation rate and history price, history profit margin, historical sales total value and history city Occupation rate, when the sales growth rate is in default second growth rate range, determine the life-cycle stages at When long-term, treatment process of the default processing model to the sales data, comprising:
The target pricing is calculated based on following formula:
Wherein, a and b is the constant term greater than 0, a+b=1 and a > b, TarPri2 are target pricing, and TarPri1 is fixed for history Valence, MatShare2 are target market occupation rate, and MatShare1 is historic market occupation rate,C is big Equal to 1 constant term, PftMgn2 is target rate of return, and PftMgn1 is history profit margin, and GosSle2 is target marketing total value, GosSle1 is historical sales total value.
9. terminal device as claimed in claim 6, which is characterized in that the sales data further includes preset target rate of return With target marketing total value and history price, history profit margin and historical sales total value, preset when the sales growth rate is in Third growth rate range, and when the sales volume is greater than or equal to default sales volume threshold value, determine the product life cycle rank Section is the maturity period, treatment process of the default processing model to the sales data, comprising:
Based on history price, the history profit margin and the historical sales total value, the preset prediction model of training;
Based on the trained prediction model, the target rate of return and the target marketing total value are handled, obtained The target pricing.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists In when the computer program is executed by processor the step of any one of such as claim 1 to 5 of realization the method.
CN201811016903.3A 2018-09-03 2018-09-03 A kind of price calculation method and terminal device based on prediction model Pending CN109191205A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811016903.3A CN109191205A (en) 2018-09-03 2018-09-03 A kind of price calculation method and terminal device based on prediction model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811016903.3A CN109191205A (en) 2018-09-03 2018-09-03 A kind of price calculation method and terminal device based on prediction model

Publications (1)

Publication Number Publication Date
CN109191205A true CN109191205A (en) 2019-01-11

Family

ID=64917802

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811016903.3A Pending CN109191205A (en) 2018-09-03 2018-09-03 A kind of price calculation method and terminal device based on prediction model

Country Status (1)

Country Link
CN (1) CN109191205A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111047354A (en) * 2019-11-27 2020-04-21 北京三快在线科技有限公司 Time-sharing pricing implementation method and device, electronic equipment and storage medium
CN111798256A (en) * 2019-04-08 2020-10-20 阿里巴巴集团控股有限公司 Method for determining fare, method, device and system for acquiring data
TWI718809B (en) * 2019-12-16 2021-02-11 財團法人工業技術研究院 Revenue forecasting method, revenue forecasting system and graphical user interface
CN112668746A (en) * 2019-10-15 2021-04-16 深圳怡化电脑股份有限公司 Standby module demand prediction method and device, storage medium and equipment
CN113674040A (en) * 2020-05-15 2021-11-19 浙江大搜车软件技术有限公司 Vehicle quotation method, computer device and computer-readable storage medium

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111798256A (en) * 2019-04-08 2020-10-20 阿里巴巴集团控股有限公司 Method for determining fare, method, device and system for acquiring data
CN112668746A (en) * 2019-10-15 2021-04-16 深圳怡化电脑股份有限公司 Standby module demand prediction method and device, storage medium and equipment
CN111047354A (en) * 2019-11-27 2020-04-21 北京三快在线科技有限公司 Time-sharing pricing implementation method and device, electronic equipment and storage medium
TWI718809B (en) * 2019-12-16 2021-02-11 財團法人工業技術研究院 Revenue forecasting method, revenue forecasting system and graphical user interface
CN113674040A (en) * 2020-05-15 2021-11-19 浙江大搜车软件技术有限公司 Vehicle quotation method, computer device and computer-readable storage medium
CN113674040B (en) * 2020-05-15 2023-11-21 浙江大搜车软件技术有限公司 Vehicle quotation method, computer device and computer-readable storage medium

Similar Documents

Publication Publication Date Title
CN109191205A (en) A kind of price calculation method and terminal device based on prediction model
Wangphanich et al. Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems–a simulation approach
CN106408341A (en) Goods sales volume prediction method and device, and electronic equipment
Huang et al. Optimal inventory control with sequential online auction in agriculture supply chain: An agent-based simulation optimisation approach
Shi et al. A portfolio approach to managing procurement risk using multi-stage stochastic programming
CN102282551A (en) Automated decision support for pricing entertainment tickets
Gong et al. Split-award contracts with investment
Liefers et al. A successful broker agent for power tac
CN111192161A (en) Electric power market trading object recommendation method and device
Bessler et al. Econometric developments in agricultural and resource economics: the first 100 years
Babic et al. An analysis of power trading agent competition 2014
CN109325818A (en) A kind of Products Show method, computer readable storage medium and terminal device
CN110363468B (en) Method and device for determining purchase order, server and readable storage medium
Proselkov et al. Financial ripple effect in complex adaptive supply networks: an agent-based model
Block et al. A multi-agent energy trading competition
Fujiwara Study on combinatorial auction mechanism for resource allocation in cloud computing environment
CN110210959A (en) Analysis method, device and the storage medium of financial data
CN109886299A (en) A kind of user draws a portrait method, apparatus, readable storage medium storing program for executing and terminal device
US9633357B2 (en) Net utility determination based on product replacement and service plan coverage decisions
Bergstrom Regulation of externalities
CN111047354A (en) Time-sharing pricing implementation method and device, electronic equipment and storage medium
Oh et al. A reinforcement learning-based demand response strategy designed from the Aggregator’s perspective
CN115829600A (en) Batch-zero integrated marketing volume price optimization method and system
Renna Simulation-based tool to analyse the effect of order acceptance policy in a make-to-order manufacturing system
US11409925B2 (en) Systems and methods for simulation of electricity value ecosystem using agent based modeling approach

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination