CN110858335A - A method and apparatus for calculating promotion elasticity - Google Patents

Abstract

The invention discloses a method and a device for calculating promotion elasticity, and relates to the technical field of computers. A specific implementation of the method includes: fitting an optimization model based on basic data, so as to calculate the baseline sales volume of the product; dividing the promotion duration in the most fine-grained way to obtain at least one time unit, and then calculating the nominal discount in each time unit Intensity; promotion elasticity is calculated based on actual sales, baseline sales, and nominal discount intensity. This embodiment can solve the problem of lack of analysis of revenue improvement under different discount strengths.

Description

A method and apparatus for calculating promotion elasticity

technical field

The present invention relates to the field of computer technology, and in particular, to a method and device for calculating promotion elasticity.

Background technique

At present, most of the promotion methods are at the business level. Suppliers negotiate with buyers and sellers to provide common and time-tested promotion forms with an acceptable discount, such as: pricing promotion, directly giving lower prices; added value Promotions, giving gifts or invisible services; rewarding promotions, in the form of collecting orders or rebates; commemorative marketing, promotions under special festivals; reward promotions, lottery draws or interactive ways to receive discounts; leveraging promotions, star explosions, etc. ; Zero point promotions, such as as low as 50% off, the lowest on the entire network; seasonal promotions, seasonal product promotions. Of course, there are other types of promotions, so I won't go into details.

In the process of realizing the present invention, the inventor found that there are at least the following problems in the prior art:

The forms of promotion are mostly based on business and marketing levels. The analysis of previous promotion effects found that many promotional activities did not achieve very good results. The superposition of various promotion forms resulted in the actual discounts exceeding expectations. The increase in GMV (Gross Merchandise Volume, which refers to the total turnover in a certain period of time) may actually cause losses to the company.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present invention provide a method and apparatus for calculating promotion elasticity, which can solve the problem of lack of analysis of revenue improvement under different discount strengths.

To achieve the above object, according to an aspect of the embodiments of the present invention, a method for calculating promotion elasticity is provided, including:

Fit the optimization model based on the basic data to calculate the baseline sales volume of the product;

The most fine-grained segmentation of the promotion duration is obtained to obtain at least one time unit, and then the nominal discount strength in each time unit is calculated;

Promotion elasticity is calculated based on actual sales, baseline sales, and nominal discount strength.

Optionally, an optimization model is fitted based on the basic data, thereby calculating the baseline sales volume of the product, including:

Summarize the basic data to get the price variable, time variable, promotion variable, coupon variable and inventory variable of each product;

Taking the actual sales volume as the dependent variable, and taking the price variable, time variable, promotion variable, coupon variable and inventory variable as the independent variable, perform regression analysis on the model to obtain the parameters of each variable;

The parameters of the time variable, promotion variable and coupon variable are all set to zero, and the basic data is substituted into the model to calculate the baseline sales volume of the product.

Optionally, calculate the nominal discount strength within each time unit, including:

For each time unit, the nominal discount strength within that time unit is calculated using the following formula:

Nominal discount strength = 1 - page price × discount 1 × ... × discount N / baseline price.

Optionally, calculate promotion elasticity based on actual sales, baseline sales, and nominal discount strength, including:

According to the most fine-grained time unit, split the actual sales volume and sales baseline to obtain the time sales volume and baseline sales volume in each time unit;

For each time unit, with nominal discount strength as the independent variable and actual sales and baseline sales as the dependent variables, perform the following regression analysis:

After the regression equation is fitted, the coefficient before nominal discount strength is the promotion elasticity.

In addition, according to another aspect of the embodiments of the present invention, there is provided an apparatus for calculating promotion elasticity, including:

The fitting module is used to fit the optimization model based on the basic data, so as to calculate the baseline sales volume of the product;

The segmentation module is used to perform the most fine-grained segmentation of the promotion duration to obtain at least one time unit, and then calculate the nominal discount strength in each time unit;

The calculation module is used to calculate the promotion elasticity based on the actual sales volume, the baseline sales volume and the nominal discount strength.

Optionally, the fitting module is used to:

Summarize the basic data to get the price variable, time variable, promotion variable, coupon variable and inventory variable of each product;

Taking the actual sales volume as the dependent variable, and taking the price variable, time variable, promotion variable, coupon variable and inventory variable as the independent variable, perform regression analysis on the model to obtain the parameters of each variable;

The parameters of the time variable, promotion variable and coupon variable are all set to zero, and the basic data is substituted into the model to calculate the baseline sales volume of the product.

Optionally, calculate the nominal discount strength within each time unit, including:

For each time unit, the nominal discount strength within that time unit is calculated using the following formula:

Nominal discount strength = 1 - page price × discount 1 × ... × discount N / baseline price.

Optionally, the computing module is used for:

According to the most fine-grained time unit, split the actual sales volume and sales baseline to obtain the time sales volume and baseline sales volume in each time unit;

For each time unit, with nominal discount strength as the independent variable and actual sales and baseline sales as the dependent variables, perform the following regression analysis:

After the regression equation is fitted, the coefficient before nominal discount strength is the promotion elasticity.

According to another aspect of the embodiments of the present invention, an electronic device is also provided, including:

one or more processors;

storage means for storing one or more programs,

When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any of the above embodiments.

According to another aspect of the embodiments of the present invention, there is also provided a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, implements the method described in any of the foregoing embodiments.

An embodiment of the above invention has the following advantages or beneficial effects: because the technical means of calculating the nominal discount granularity in the most fine-grained time unit and then calculating the promotion elasticity according to the actual sales volume, the baseline sales volume and the nominal discount strength are adopted, it overcomes the The technical problem of lacking the analysis of income improvement under different discount strengths; the present invention is to quantitatively analyze the promotional activities that have been done in the past. The resulting increase in sales, in turn, calculates the promotion elasticity to better guide promotion pricing efforts.

Further effects of the above non-conventional alternatives will be described below in conjunction with specific embodiments.

Description of drawings

The accompanying drawings are used for better understanding of the present invention and do not constitute an improper limitation of the present invention. in:

1 is a schematic diagram of a main process of a method for calculating promotion elasticity according to an embodiment of the present invention;

2 is a schematic diagram of the main flow of a method for calculating promotion elasticity according to a referenced embodiment of the present invention;

3 is a schematic diagram of main modules of an apparatus for calculating promotion elasticity according to an embodiment of the present invention;

4 is an exemplary system architecture diagram to which an embodiment of the present invention may be applied;

FIG. 5 is a schematic structural diagram of a computer system suitable for implementing a terminal device or a server according to an embodiment of the present invention.

Detailed ways

Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, which include various details of the embodiments of the present invention to facilitate understanding and should be considered as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted from the following description for clarity and conciseness.

FIG. 1 is a schematic diagram of a main flow of a method for calculating promotion elasticity according to an embodiment of the present invention. As shown in FIG. 1, as an embodiment of the present invention, the method for calculating promotion elasticity includes:

In step 101, an optimization model is fitted based on the basic data, thereby calculating the baseline sales volume of the product.

Optionally, the step 101 may include: summarizing basic data to obtain price variables, time variables, promotion variables, coupon variables and inventory variables of each commodity; Promotion variables, coupon variables and inventory variables are used as independent variables, and regression analysis is performed on the model to obtain the parameters of each variable; the parameters of time variables, promotion variables and coupon variables are all set to zero, and the basic data is substituted into the model to calculate Get the baseline sales of the item.

The basic data comes from each order. For daily orders, the order is summarized according to the dimension of a single product. The aggregated indicators include page price, transaction price, baseline price, total sales, and inventory status. Inventory status is a number between 0 and 1, indicating whether the goods are sufficient in each warehouse. Therefore, through these basic data, the page price, transaction price, baseline price, total sales and inventory status of each product can be obtained every day.

It should be pointed out that since there is more than one order volume per day, the page price, transaction price, and baseline price take their respective averages as the page price, transaction price, and baseline price of each product every day.

The price baseline is a fictitious price that refers to the price that consumers can buy the item without any real promotions. It is a rough description of the consumer's perception of the price of a commodity, and it is a psychological price of the commodity in the consumer's mind. When the actual price is higher than the price baseline, consumers generally do not buy it; when the given discount makes the price of the product lower than the price baseline, consumers will buy the product with a high probability. For each commodity, there is a baseline price per day. In an embodiment of the present invention, the following method can be used to calculate the baseline price: take the current time as a benchmark, push forward 30 days, and calculate the average value of transaction prices for 30 days as the baseline price of the day.

Then, based on these aggregated basic data, construct dummy variables such as holidays, types of promotions, and types of coupons. For example, holidays: New Year's Day, New Year's Day, Qingming Festival, 618, Double Eleven, etc.; For example, types of promotions: full discount, direct drop, gifts, sets, etc.;

If the day is New Year's Day, the dummy variable for New Year's Day is 1, otherwise it is 0; the same is true for promotions and coupons, with 1 or 0 as the dummy variable. Calculate the discount strength of various promotions and coupons, such as direct drop promotion discount strength, etc. In addition, construct a time variable, indicating that the day is the day of the year and the week of the year.

After constructing the dummy variables, the dummy variables are input into the model to fit the model. Specifically, take the actual sales as the dependent variable, and use the price variable, time variable, promotion variable, coupon variable and inventory variable as the independent variable to perform regression analysis:

Actual sales ~ price variable + time variable + promotion variable + coupon variable + inventory variable

Optionally, the model can be described as:

Q=c+β ₀ base _price +β ₁ trans _price +β ₂ page _price +β ₃ day _order

+β ₄ week _order +β _i springfestival _flag +…+β _j 618 _flag +…

+β _k 11.11 _flag +…+β _l 12.12 _flag +β _n-8 prometype1 _flag +…

+β _n-7 promotype2 _flag +β _n-6 promotype1 _rate +…

+β _n-5 promotype2 _rate +β _n-4 coupontype1 _flag +…

+β _n-3 coupontype2 _flag +β _n-2 coupontype1 _rate +…

+β _n-1 coupontype2 _rate +β _n stock_state

in:

Q is the actual sales volume, c is a constant, and β is the parameter of each independent variable;

base _price refers to the baseline price, trans _price refers to the transaction price, and page _price refers to the page price;

day _order refers to the day number, and week _order refers to the week number;

The springfestival _flag refers to whether it is the Spring Festival, the 618 _flag refers to whether it is 618, the 11.11 _flag refers to whether it is Double Eleven, the 12.12 _flag refers to whether it is Double Twelve, and the ellipsis part refers to various other holidays, which will not be repeated in this embodiment of the present invention; a variable of 0 or 1;

prometype1 _flag and promotype2 _flag refer to whether to participate in a certain promotion type, coupontype1 _flag and coupontype2 _flag refer to whether to issue a certain coupon type; these are variables of 0 or 1; in addition, the promotion type and coupon type can be based on The actual situation is added and deleted, and the ellipsis part is various other promotion types and coupon types, which are not repeated in this embodiment of the present invention;

promotype1 _rate and promotype2 _rate refer to the nominal discount strength of a certain promotion type, coupontype1 _rate and coupontype2 _rate refer to the nominal discount strength of a certain coupon type; the ellipsis part is the nominal discount strength of various other promotion types, and various other coupons The nominal discount strength of the type is not repeated in this embodiment of the present invention;

stock_state is the comprehensive inventory state of each warehouse, which is a number between 0 and 1.

For example: For example, an e-commerce company has 5 warehouses across the country, but only 3 warehouses have stock on that day, then the inventory status is 3/5=0.6. This variable is based on the actual status of the day in the sales baseline forecast and does not need to be set to 0.

The basic data of each commodity is arranged in ascending order of time, and then input into the model, the model is fitted, and then the parameters of each variable are obtained.

Since the baseline sales are the daily basic sales without promotions. Therefore, all related parameters such as promotion variables, coupon variables, and time variables in the model are set to zero (the inventory variable does not need to be set to 0, and the actual inventory status of the day shall prevail, which is substituted into the model and does not need to be set to 0), Substitute the basic data into the model, and the predicted sales volume is the baseline sales volume, thereby obtaining the daily baseline sales volume of each product.

In step 102, the most fine-grained segmentation of the promotion duration is performed to obtain at least one time unit, and then the nominal discount strength in each time unit is calculated.

Optionally, for each time unit, the following formula can be used to calculate the nominal discount strength within that time unit:

Nominal discount strength = 1 - page price × discount 1 × ... × discount N / baseline price

Wherein, the page price is the page price within the time unit, and the baseline price is the baseline price within the time unit.

Assuming that there are two types of promotions: direct drop and full discount, and there is an overlap in the promotion duration, the most fine-grained promotion segmentation needs to be carried out. 199-100, the most fine-grained segmentation of the promotion duration, which can be divided into 4 time units from the perspective of the timeline.

After the most fine-grained time unit segmentation is completed, the nominal discount strength of the product in each time unit can be calculated based on the price baseline and the page price.

For example: in the first time unit, the 5% straight down and full subtraction 99-19 can be calculated as:

Nominal discount strength = 1-page price × (1-5%) × (1-19/99) / baseline price

Step 103: Calculate the promotion elasticity according to the actual sales volume, the baseline sales volume and the nominal discount strength.

Since the nominal discount strength in each fine-grained time unit is calculated in step 102, the actual sales of each item in the order are aggregated, and the daily sales baseline is excluded, which is the increase in sales brought about by the promotion.

Specifically, according to the most fine-grained time unit, the actual sales volume and the sales volume baseline are split to obtain the time sales volume and the baseline sales volume in each time unit. The splitting of the most fine-grained actual sales minus the baseline sales is the increase in sales, corresponding to the most fine-grained nominal discount strength. For example, on a certain day, the actual sales volume of a product is 480 pieces, and the duration of the most fine-grained time unit is 12 hours, then the actual sales volume of the product in this time unit is 240 pieces. The splitting method of the baseline sales is the same as the splitting of the actual sales, and will not be repeated here.

Therefore, for each fine-grained time unit, with nominal discount strength as the independent variable and actual sales and baseline sales as the dependent variables, the following regression analysis was performed:

This establishes the relationship between the lift rate and the nominal discount strength, which is equivalent to establishing the relationship between price and sales. After the above regression equation is fitted, the coefficient before the nominal discount strength is the promotion elasticity, which describes the influence of the absolute change of the nominal discount strength on the relative change of the promotion rate.

For example, if you know how much lift you want to achieve, you can find the corresponding nominal discount. Therefore, given the nominal discount strength and price baseline, a reasonable page price can be set for the product, so as to achieve the purpose of pricing.

According to the various embodiments described above, it can be seen that the present invention adopts the technical scheme of calculating the nominal discount granularity in the most fine-grained time unit, and then calculating the promotion elasticity according to the actual sales volume, the baseline sales volume and the nominal discount strength, which solves the problem of lack of The problem of revenue improvement analysis under different discount strengths. However, the present invention performs quantitative analysis on the promotion activities done in the past, under the condition of a given promotion activity, calculates the discount strength based on the baseline price and the sales increase that the promotion activity can bring, and then calculates the promotion elasticity, so as to improve the efficiency of the promotion. Good guide for promotional pricing efforts.

2 is a schematic diagram of the main flow of a method for calculating promotion elasticity according to a referenced embodiment of the present invention, and the method for calculating promotion elasticity may include:

Step 201, summarize the basic data to obtain the price variable, time variable, promotion variable, coupon variable and inventory variable of each commodity;

Step 202, using the actual sales volume as the dependent variable, and using the price variable, the time variable, the promotion variable, the coupon variable and the inventory variable as the independent variables, perform regression analysis on the model, and obtain the parameters of each variable;

Step 203, the parameters of the time variable, the promotion variable and the coupon variable are all set to zero, the basic data is substituted into the model, and the baseline sales volume of the commodity is calculated;

In step 204, the most fine-grained segmentation is performed on the promotion duration to obtain multiple time units;

Step 205, calculating the nominal discount strength in each time unit;

Step 206, according to the most fine-grained time unit, split the actual sales volume and the sales volume baseline to obtain the time sales volume and the baseline sales volume in each time unit;

Step 207 , for each time unit, take the nominal discount strength as the independent variable, and take the actual sales volume and the baseline sales volume as the dependent variable, perform regression analysis, and obtain the promotion elasticity.

In addition, the specific implementation content of the method for calculating the promotion elasticity in a referenced embodiment of the present invention has been described in detail in the method for calculating the promotion elasticity above, so the repeated content will not be described here.

FIG. 3 is a schematic diagram of main modules of an apparatus for calculating promotion elasticity according to an embodiment of the present invention. As shown in FIG. 3 , the apparatus 300 for calculating promotion elasticity includes a fitting module 301 , a segmentation module 302 and a calculation module 303 . Wherein, the fitting module 301 fits the optimization model based on the basic data, so as to obtain the baseline sales volume of the product; the segmentation module 302 performs the most fine-grained segmentation of the promotion duration to obtain at least one time unit, and then calculates each time unit Nominal discount strength within; the calculation module 303 calculates the promotion elasticity according to the actual sales volume, the baseline sales volume and the nominal discount strength.

Optionally, the fitting module 301 summarizes the basic data to obtain the price variable, time variable, promotion variable, coupon variable and inventory variable of each commodity; Variables, coupon variables and inventory variables are used as independent variables, and regression analysis is performed on the model to obtain the parameters of each variable; the parameters of the time variable, promotion variable and coupon variable are all set to zero, and the basic data is substituted into the model. Calculated Baseline sales of the item.

Optionally, calculate the nominal discount strength within each time unit, including:

For each time unit, the nominal discount strength within that time unit is calculated using the following formula:

Nominal discount strength = 1 - page price × discount 1 × ... × discount N / baseline price.

Optionally, the calculation module 303 splits the actual sales volume and the sales volume baseline according to the most fine-grained time unit, and obtains the time sales volume and the baseline sales volume in each time unit; for each time unit, the nominal discount strength is used. As an independent variable, with actual sales and baseline sales as dependent variables, the following regression analysis was performed:

After the regression equation is fitted, the coefficient before nominal discount strength is the promotion elasticity.

According to the various embodiments described above, it can be seen that the present invention adopts the technical scheme of calculating the nominal discount granularity in the most fine-grained time unit, and then calculating the promotion elasticity according to the actual sales volume, the baseline sales volume and the nominal discount strength, which solves the problem of lack of The problem of revenue improvement analysis under different discount strengths. However, the present invention performs quantitative analysis on the promotion activities done in the past, under the condition of a given promotion activity, calculates the discount strength based on the baseline price and the sales increase that the promotion activity can bring, and then calculates the promotion elasticity, so as to improve the efficiency of the promotion. Good guide for promotional pricing efforts.

It should be noted that the specific implementation content of the device for calculating promotion elasticity of the present invention has been described in detail in the method for calculating promotion elasticity described above, so the repeated content will not be described here.

FIG. 4 illustrates an exemplary system architecture 400 to which the method of calculating promotion elasticity or the method of calculating promotion elasticity may be applied.

As shown in FIG. 4 , the system architecture 400 may include terminal devices 401 , 402 , and 403 , a network 404 and a server 405 . The network 404 is a medium used to provide a communication link between the terminal devices 401 , 402 , 403 and the server 405 . The network 404 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user can use the terminal devices 401, 402, 403 to interact with the server 405 through the network 404 to receive or send messages and the like. Various communication client applications may be installed on the terminal devices 401 , 402 and 403 , such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only examples).

The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

The server 405 may be a server that provides various services, for example, a background management server that provides support for shopping websites browsed by the terminal devices 401 , 402 , and 403 (just an example). The background management server can analyze and process the received product information query request and other data, and feed back the processing results (such as target push information, product information—just an example) to the terminal device.

It should be noted that the method for calculating the promotion elasticity provided by the embodiment of the present invention is generally executed on the server 405 , and accordingly, the apparatus for calculating the promotion elasticity is generally set in the server 405 . The method for calculating the promotion elasticity provided by the embodiment of the present invention may also be executed on the terminal devices 401 , 402 , and 403 .

It should be understood that the numbers of terminal devices, networks and servers in FIG. 4 are merely illustrative. There can be any number of terminal devices, networks and servers according to implementation needs.

Referring to FIG. 5 below, it shows a schematic structural diagram of a computer system 500 suitable for implementing a terminal device according to an embodiment of the present invention. The terminal device shown in FIG. 5 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present invention.

As shown in FIG. 5, a computer system 500 includes a central processing unit (CPU) 501 which can be loaded into a random access memory (RAM) 503 according to a program stored in a read only memory (ROM) 502 or a program from a storage section 508 Instead, various appropriate actions and processes are performed. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501 , the ROM 502 , and the RAM 503 are connected to each other through a bus 504 . An input/output (I/O) interface 505 is also connected to bus 504 .

The following components are connected to the I/O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc. ; and a communication section 509 including a network interface card such as a LAN card, a modem, and the like. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I/O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 510 as needed so that a computer program read therefrom is installed into the storage section 508 as needed.

In particular, the processes described above with reference to the flowcharts may be implemented as computer software programs in accordance with the disclosed embodiments of the present invention. For example, embodiments disclosed herein include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the method illustrated in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network via the communication portion 509 and/or installed from the removable medium 511 . When the computer program is executed by the central processing unit (CPU) 501, the above-described functions defined in the system of the present invention are performed.

It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples of computer readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable Programmable read only memory (EPROM or flash memory), fiber optics, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code therein. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device . Program code embodied on a computer readable medium may be transmitted using any suitable medium including, but not limited to, wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams or flowchart illustrations, and combinations of blocks in the block diagrams or flowchart illustrations, can be implemented in special purpose hardware-based systems that perform the specified functions or operations, or can be implemented using A combination of dedicated hardware and computer instructions is implemented.

The modules involved in the embodiments of the present invention may be implemented in a software manner, and may also be implemented in a hardware manner. The described modules can also be provided in the processor, for example, it can be described as: a processor includes a fitting module, a segmentation module and a calculation module, wherein the names of these modules do not constitute the module under certain circumstances. its own limitations.

As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or may exist alone without being assembled into the device. The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by a device, the device includes: fitting an optimization model based on basic data, so as to obtain a baseline sales volume of commodities; The most fine-grained division of the duration is carried out to obtain at least one time unit, and then the nominal discount strength in each time unit is calculated; the promotion elasticity is calculated according to the actual sales volume, the baseline sales volume and the nominal discount strength.

According to the technical solution of the embodiment of the present invention, because the technical means of calculating the nominal discount granularity in the most fine-grained time unit, and then calculating the promotion elasticity according to the actual sales volume, the baseline sales volume and the nominal discount strength are adopted, the lack of different discount strengths is overcome. The technical problem of the analysis of income improvement under the following circumstances; the present invention is to quantitatively analyze the promotion activities done in the past, and under the situation of a given promotion activity, calculate the discount strength based on the baseline price and the sales promotion that the promotion activities can bring, Promotion elasticity is then calculated to better guide promotional pricing efforts.

The above-mentioned specific embodiments do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. a method for calculating promotion elasticity, is characterized in that, comprises: Fit the optimization model based on the basic data to calculate the baseline sales volume of the product; The most fine-grained segmentation of the promotion duration is obtained to obtain at least one time unit, and then the nominal discount strength in each time unit is calculated; Promotion elasticity is calculated based on actual sales, baseline sales, and nominal discount strength. 2. method according to claim 1, is characterized in that, based on basic data fitting optimization model, thereby calculates the baseline sales volume of commodity, comprising: Summarize the basic data to get the price variable, time variable, promotion variable, coupon variable and inventory variable of each product; Taking the actual sales volume as the dependent variable, and taking the price variable, time variable, promotion variable, coupon variable and inventory variable as the independent variable, perform regression analysis on the model to obtain the parameters of each variable; The parameters of the time variable, promotion variable and coupon variable are all set to zero, and the basic data is substituted into the model to calculate the baseline sales volume of the product. 3. method according to claim 1, is characterized in that, calculating the nominal discount intensity in each time unit, comprises: For each time unit, the nominal discount strength within that time unit is calculated using the following formula: Nominal discount strength = 1 - page price × discount 1 × ... × discount N / baseline price. 4. method according to claim 1, is characterized in that, according to actual sales volume, baseline sales volume and nominal discount strength, calculate promotion elasticity, comprising: According to the most fine-grained time unit, split the actual sales volume and sales baseline to obtain the time sales volume and baseline sales volume in each time unit; For each time unit, with nominal discount strength as the independent variable and actual sales and baseline sales as the dependent variables, perform the following regression analysis:

After the regression equation is fitted, the coefficient before nominal discount strength is the promotion elasticity. 5. A device for calculating promotion elasticity, comprising: The fitting module is used to fit the optimization model based on the basic data, so as to calculate the baseline sales volume of the product; The segmentation module is used to perform the most fine-grained segmentation of the promotion duration to obtain at least one time unit, and then calculate the nominal discount strength in each time unit; The calculation module is used to calculate the promotion elasticity based on the actual sales volume, the baseline sales volume and the nominal discount strength. 6. The device according to claim 5, wherein the fitting module is used for: Summarize the basic data to get the price variable, time variable, promotion variable, coupon variable and inventory variable of each product; Taking the actual sales volume as the dependent variable, and taking the price variable, time variable, promotion variable, coupon variable and inventory variable as the independent variable, perform regression analysis on the model to obtain the parameters of each variable; The parameters of the time variable, promotion variable and coupon variable are all set to zero, and the basic data is substituted into the model to calculate the baseline sales of the product. 7. The device according to claim 5, wherein calculating the nominal discount strength in each time unit comprises: For each time unit, the nominal discount strength within that time unit is calculated using the following formula: Nominal discount strength = 1 - page price × discount 1 × ... × discount N / baseline price. 8. The apparatus according to claim 5, wherein the computing module is used for: According to the most fine-grained time unit, split the actual sales volume and sales baseline to obtain the time sales volume and baseline sales volume in each time unit; For each time unit, with nominal discount strength as the independent variable and actual sales and baseline sales as dependent variables, the following regression analysis was performed:

After the regression equation is fitted, the coefficient before nominal discount strength is the promotion elasticity. 9. An electronic device, characterized in that, comprising: one or more processors; storage means for 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 one of claims 1-4. 10. A computer-readable medium on which a computer program is stored, characterized in that, when the program is executed by a processor, the method according to any one of claims 1-4 is implemented.

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