Big data-based sales influence factor analysis platform and production improvement platform

Abstract

The invention provides a sales influence factor analysis platform and production improvement platform based on big data, and the platform comprises a first obtaining module which obtains slaughter data including a farm name, a livestock variety and meat quality; acquiring first sales data of the farm including a point-of-sale name, the variety of livestock sold to the point-of-sale, the total weight of a single livestock and the selling time; acquiring second sales data including parts of sold livestock, weights of the parts, unit prices and sales time at the point of sale; the determining module is used for determining the unit price and the unit weight selling duration of the livestock in the first sales data according to the first sales data and the second sales data; and the analysis module is used for establishing a data chain including the farm name, the point-of-sale name, the livestock variety, the meat quality, the unit price of the livestock and the selling duration per unit weight, and analyzing the livestock sales influence factors according to the data chain. According to the method, sales influence factor analysis can be carried out on the commodities which are sold in a decomposition manner by taking the whole commodity as a unit.

Description

Technical Field

[0001] The present invention belongs to the field of big data analysis, and specifically relates to a sales influencing factor analysis platform and a production improvement platform based on big data. Background Art

[0002] At present, the analysis of sales influencing factors is usually based on models and regression analysis. This analysis method is relatively complex and is more suitable for goods sold as a whole. For goods sold in parts, it is difficult to determine from the sales end which part of the goods the part sold belongs to, so it is impossible to comprehensively evaluate the sales influencing factors based on the whole goods. For example, in the field of breeding, farms usually sell livestock to sales points as a whole, and the quality and even breed of livestock sold to sales points each time may be different. However, sales points cannot sell all the livestock purchased last time before each purchase, that is, it is impossible to use all sales data after the sales point purchases as the sales data of the livestock purchased this time, so it is impossible to analyze the impact of the breed and meat quality of a single livestock on sales. With the continuous development of big data applications, it will be possible to obtain data from all parties and determine whether the corresponding sales data of the sales point belongs to the same product based on the data from all parties. Summary of the invention

[0003] The present invention provides a sales influencing factor analysis platform and a production improvement platform based on big data, so as to solve the problem that it is currently impossible to conduct a comprehensive and comprehensive analysis of the sales influencing factors of the goods that are broken down for sale based on the entire goods.

[0004] According to a first aspect of an embodiment of the present invention, there is provided a sales influencing factor analysis platform based on big data, which is applied on a server and includes:

[0005] A first acquisition module is used to acquire slaughter data from various slaughterhouses, wherein the slaughter data includes the name of the farm, the livestock breed, the meat quality, and the total weight of each livestock; for each farm in the slaughter data, the first sales data of the farm is acquired, wherein the first sales data includes the name of the sales point, the livestock breed sold to the corresponding sales point, the total weight of a single livestock, and the first selling time; for each sales point in the first sales data, the second sales data of the sales point is acquired, wherein the second sales data includes the part of the livestock sold, the weight of the part, the unit price, and the second selling time;

[0006] A determination module, configured to determine the unit price and unit weight selling time of the livestock in the first sales data according to the first sales data and the second sales data of the sales point;

[0007] The analysis module is used to establish a data chain including the name of the farm, the name of the sales point, the livestock breed, the meat quality, the unit price of the livestock and the unit weight sales time in the slaughter data, and analyze the factors affecting the livestock sales of the farm based on multiple historical data chains corresponding to different farms.

[0008] In an optional implementation manner, the determining module is specifically configured to:

[0009] Whenever a new first sales data is obtained, the estimated weight of each part of the livestock in the new first sales data is determined according to the weight proportion of each part of the livestock in the total weight and the total weight of a single livestock in the new first sales data;

[0010] Determine the second sales data of the sales point obtained after the first sales time in the new first sales data; arrange the determined second sales data according to the second sales time in the second sales data, and arrange the second sales data with the most recent second sales time at the first place;

[0011] For each part of the livestock, the weight in the second sales data corresponding to the part is sequentially added, wherein each time the weight in the second sales data is added, it is determined whether the added result is greater than or equal to the estimated weight of the part of the livestock in the new first sales data; if so, the addition is stopped and the added result is used as the actual weight of the part; otherwise, the weight in the next second sales data corresponding to the part is continued to be added;

[0012] For each part of the livestock, determine the second sales data corresponding to the part to be added before stopping the addition, multiply the unit price in the determined second sales data by the weight to obtain the total price of the part; add the total prices of the parts to obtain the total price of the livestock in the new first sales data, add the actual weights of the parts to obtain the actual weight of the livestock in the latest first sales data; divide the total price of the livestock by the actual weight of the livestock to obtain the unit price of the livestock;

[0013] Compare the second sales data corresponding to each part used for addition before stopping the addition, obtain the earliest and latest second sales time in the second sales data, and determine the sales time of the livestock according to the earliest and latest second sales time; divide the sales time of the livestock by the actual weight of the livestock to obtain the sales time per unit weight of the livestock.

[0014] In another optional implementation, the analysis module is further configured to add, in the data chain, a sales time period between the earliest and latest second sales times in the determination module.

[0015] In another optional implementation, the analysis module is further used to grade the sales point according to sales volume, and add the grade corresponding to the sales point and the address range corresponding to the sales point to the data chain, where the address range is a preset range centered on the location of the sales point.

[0016] In another optional implementation, the analysis module is specifically used to use livestock breed, meat quality, sales time period, sales point classification, and sales point address range as sales influencing factors;

[0017] When analyzing the impact of a farm's corresponding influencing factors on sales, first screen out the data chain to be analyzed. In the data chain to be analyzed, except for the influencing factor and the farm name, other influencing factors are the same as the corresponding influencing factors in the corresponding standard data chain of the farm. Then, when the influencing factor changes, the corresponding changes in the unit price of livestock and the selling time per unit weight are analyzed.

[0018] According to a second aspect of an embodiment of the present invention, there is provided a production improvement platform based on big data, characterized in that it comprises a second acquisition module, an input module, an improvement module, and a sales influencing factor analysis platform as claimed in any one of claims 1 to 5;

[0019] The second acquisition module is used to acquire the production data of each farm;

[0020] After the user analyzes the main factors affecting sales through the analysis module, the user inputs his own production data through the input module and selects corresponding farms with the same other influencing factors except the main factor;

[0021] The improvement module is used to compare the user's own production data with the production data of the selected farm, and calculate the improvement cost and improvement cycle.

[0022] In an optional implementation, the production data includes the breeding farm's breeding environment parameters, feed parameters and management mode.

[0023] In another optional implementation, it also includes a control module. After the user uses the improvement module, the control module monitors the user's purchase of means of production based on the comparison result, and determines whether the purpose of the user's production improvement is to adjust the livestock breed, the livestock meat quality, or both the livestock breed and the meat quality; and performs macro-control of the market based on the user's production improvement purpose.

[0024] The beneficial effects of the present invention are:

[0025] 1. Based on the first sales data of the breeding farm and the second sales data of the sales point, the present invention can obtain the unit price of livestock and the sales time per unit weight of livestock, which are used to reflect the overall sales situation of a livestock. Combined with the slaughter data of the slaughterhouse, the overall sales situation of livestock can be associated with the name of the breeding farm, the name of the sales point, the livestock breed, and the meat quality. In this way, for the goods that are sold separately, the sales influencing factors can be comprehensively analyzed based on the entire commodity;

[0026] 2. The present invention integrates the production data of various farms and provides production improvement big data to the farms, so that the farms can continuously improve their breeding strategies according to the market; in addition, the present invention also provides a control module so that government agencies can conduct macro-control of the breeding market. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the structure of an embodiment of a sales influencing factor analysis platform based on big data of the present invention;

[0028] Figure 2 It is a schematic diagram of the structure of an embodiment of a production improvement platform based on big data of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention and to make the above-mentioned purposes, features and advantages of the embodiments of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings.

[0030] In the description of the present invention, unless otherwise specified and limited, it should be noted that the term "connection" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the internal connection between two elements. It can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0031] See also Figure 1 , is a schematic diagram of the structure of an embodiment of a sales influencing factor analysis platform based on big data of the present invention. The analysis platform is applied on a server and may include:

[0032] The first acquisition module is used to obtain slaughter data from major slaughterhouses, wherein the slaughter data includes the name of the farm, livestock breed, meat quality and the total weight of each livestock; for each farm in the slaughter data, the first sales data of the farm is obtained, wherein the first sales data includes the name of the sales point, the livestock breed sold to the corresponding sales point, the total weight of a single livestock and the first selling time; for each sales point in the first sales data, the second sales data of the sales point is obtained, wherein the second sales data includes the part of the livestock sold, the weight of the part, the unit price and the second selling time.

[0033] Among them, the slaughter data of the slaughterhouse and the first sales data of the farm can be obtained from the financial data of the slaughterhouse and the farm (such as invoices, etc.), and the second sales data of the sales point can be obtained from the supermarket. As for the retail sales point, the retail sales point can be equipped with an electronic scale, which records the unit price pressed each time, the weighed weight, the calculated price and the weighing time, and sends the recorded weighing information to the server; the first acquisition module obtains the collection information of the corresponding collection code of the retail sales point, and the collection information includes the total collection amount and the collection time; and obtains the electronic scale corresponding to the retail sales point Provided weighing information; for each weighing information, determine whether there is any collection information with a total amount of money close to or equal to the price calculated in the weighing information within a preset time after the weighing time in the weighing information, and if so, use the weighing time in the weighing information as the second selling time to form a second sales data including the weight, unit price and the second selling time in the weighing information; compare the unit prices in each second sales data, determine which part each second sales data corresponds to based on the regular differences in the unit prices of various parts of livestock, and place the determined part in the corresponding second sales data.

[0034] The determination module is used to determine the unit price and unit weight selling time of the livestock in the first sales data according to the first sales data and the second sales data of the sales point.

[0035] The determination module is specifically used to: determine the estimated weight of each part of the livestock in the new first sales data according to the weight proportion of each part of the livestock in the total weight and the total weight of a single livestock in the new first sales data every time a new first sales data is obtained;

[0036] Determine the second sales data of the sales point obtained after the first sales time in the new first sales data (the second sales data of the sales point can be obtained at a set time after the first sales time, and the set time can be the end of the first day after the first sales time, etc.); arrange the determined second sales data according to the second sales time in the second sales data, and put the second sales data with the closest second sales time in the first place (usually the salesperson will sell the inventory first, so the farther the second sales time is from the current time, the more likely the sold part is inventory, and inventory cannot reflect the sales situation of livestock in the new first sales data, so the present invention chooses to put the second sales data with the closest second sales time to the current time in the first place);

[0037] For each part of the livestock, the weight in the second sales data corresponding to the part is sequentially added, wherein each time the weight in the second sales data is added, it is determined whether the added result is greater than or equal to the estimated weight of the part of the livestock in the new first sales data; if so, the addition is stopped and the added result is used as the actual weight of the part; otherwise, the weight in the next second sales data corresponding to the part is continued to be added;

[0038] For each part of the livestock, determine the second sales data corresponding to the part to be added before stopping the addition, multiply the unit price in the determined second sales data by the weight to obtain the total price of the part; add the total prices of the parts to obtain the total price of the livestock in the new first sales data, add the actual weights of the parts to obtain the actual weight of the livestock in the latest first sales data; divide the total price of the livestock by the actual weight of the livestock to obtain the unit price of the livestock;

[0039] Compare the second sales data corresponding to each part used for addition before stopping the addition, obtain the earliest and latest second sales time in the second sales data, and determine the sales time of the livestock according to the earliest and latest second sales time; divide the sales time of the livestock by the actual weight of the livestock to obtain the sales time per unit weight of the livestock.

[0040] The analysis module is used to establish a data chain including the name of the farm, the name of the sales point, the livestock breed, the meat quality, the unit price of the livestock and the unit weight sales time in the slaughter data, and analyze the factors affecting the livestock sales of the farm based on multiple historical data chains corresponding to different farms.

[0041] The analysis module is further used to add a sales time period between the earliest and latest second sales times in the determination module to the data chain. The analysis module is further used to classify the sales point according to the sales volume, and add the corresponding grade of the sales point and the corresponding address range of the sales point to the data chain, wherein the address range is a preset range centered on the location of the sales point.

[0042] The analysis module is specifically used to use livestock breed, meat quality, sales time period, sales point classification, and sales point address range as sales influencing factors;

[0043] When analyzing the impact of a farm's corresponding influencing factors on sales, first select the data chain to be analyzed. In the data chain to be analyzed, except for the influencing factor and the name of the farm, the other influencing factors are the same as the corresponding influencing factors in the standard data chain corresponding to the farm. Then analyze the changes in the unit price and unit weight of livestock when the influencing factor changes. The analysis operation can be completed by the user's selection operation, including selecting the corresponding influencing factor as to be analyzed, and selecting other influencing factors except the influencing factor to be analyzed as not to be analyzed. At this time, the analysis module will automatically select the data chain to be analyzed and perform data analysis.

[0044] It can be seen from the above embodiments that the present invention can obtain the unit price of livestock and the selling time per unit weight of livestock, which are used to reflect the overall sales situation of a livestock, based on the first sales data of the breeding farm and the second sales data of the sales point. Combined with the slaughtering data of the slaughterhouse, the overall sales situation of livestock can be associated with the name of the breeding farm, the name of the sales point, the livestock breed, and the meat quality. In this way, for the goods that are broken down and sold, a comprehensive and comprehensive analysis of the factors affecting their sales can be carried out based on the entire commodity.

[0045] In addition, the present invention also provides a production improvement platform based on big data, which can be applied on a server and can include a second acquisition module, an input module, an improvement module and the above-mentioned sales influencing factor analysis platform;

[0046] The second acquisition module is used to acquire the production data of each farm;

[0047] After the user analyzes the main factors affecting sales through the analysis module, the user inputs his own production data through the input module and selects corresponding farms with the same influencing factors except the main factor (the user can send selection information to the second acquisition module through the input module, so that the second acquisition module sends the production data of the selected farm to the improvement module);

[0048] The improvement module is used to compare the user's own production data with the production data of the selected farm and calculate the improvement cost and improvement cycle. The production data may include the farm's breeding environment parameters, feed parameters and management mode.

[0049] The production improvement platform may also include a control module, which monitors the user's purchase of means of production based on the comparison result after the user uses the improvement module, and determines whether the purpose of the user's production improvement is to adjust the livestock breed, the livestock meat quality, or both the livestock breed and the meat quality; and performs macro-control of the market based on the user's production improvement purpose.

[0050] As can be seen from the above embodiments, the present invention provides production improvement big data to the farms by integrating the production data of each farm, so that the farms can continuously improve their breeding strategies according to the market. In addition, the present invention also provides a control module so that government agencies can conduct macro-control of the breeding market.

[0051] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0052] It will be appreciated that the invention is not limited to the precise construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from its scope. The scope of the invention is governed solely by the appended claims.

Claims

1. A sales influencing factor analysis platform based on big data, characterized in that: Applied on the server, including: A first acquisition module is used to acquire slaughter data from various slaughterhouses, wherein the slaughter data includes the name of the farm, the livestock breed, the meat quality, and the total weight of each livestock; for each farm in the slaughter data, the first sales data of the farm is acquired, wherein the first sales data includes the name of the sales point, the livestock breed sold to the corresponding sales point, the total weight of a single livestock, and the first selling time; for each sales point in the first sales data, the second sales data of the sales point is acquired, wherein the second sales data includes the part of the livestock sold, the weight of the part, the unit price, and the second selling time; A determination module, configured to determine the unit price and unit weight selling time of the livestock in the first sales data according to the first sales data and the second sales data of the sales point; The analysis module is used to establish a data chain including the name of the farm, the name of the sales point, the livestock breed, the meat quality, the unit price of the livestock and the unit weight sales time in the slaughter data, and analyze the factors affecting the livestock sales of the farm based on multiple historical data chains corresponding to different farms.

2. The sales influencing factor analysis platform based on big data according to claim 1 is characterized in that: The determination module is specifically used for: Whenever a new first sales data is obtained, the estimated weight of each part of the livestock in the new first sales data is determined according to the weight proportion of each part of the livestock in the total weight and the total weight of a single livestock in the new first sales data; Determine the second sales data of the sales point obtained after the first sales time in the new first sales data; arrange the determined second sales data according to the second sales time in the second sales data, and arrange the second sales data with the most recent second sales time at the first place; For each part of the livestock, the weight in the second sales data corresponding to the part is sequentially added, wherein each time the weight in the second sales data is added, it is determined whether the added result is greater than or equal to the estimated weight of the part of the livestock in the new first sales data; if so, the addition is stopped and the added result is used as the actual weight of the part; otherwise, the weight in the next second sales data corresponding to the part is continued to be added; For each part of the livestock, determine the second sales data corresponding to the part to be added before stopping the addition, multiply the unit price in the determined second sales data by the weight to obtain the total price of the part; add the total prices of the parts to obtain the total price of the livestock in the new first sales data, add the actual weights of the parts to obtain the actual weight of the livestock in the latest first sales data; divide the total price of the livestock by the actual weight of the livestock to obtain the unit price of the livestock; Compare the second sales data corresponding to each part used for addition before stopping the addition, obtain the earliest and latest second sales time in the second sales data, and determine the sales time of the livestock according to the earliest and latest second sales time; divide the sales time of the livestock by the actual weight of the livestock to obtain the sales time per unit weight of the livestock.

3. The sales influencing factor analysis platform based on big data according to claim 2 is characterized in that: The analysis module is further used to add a sales time period between the earliest and latest second sales times in the determination module to the data chain.

4. The sales influencing factor analysis platform based on big data according to claim 3 is characterized in that: The analysis module is also used to classify the sales point according to the sales volume, and add the corresponding grade of the sales point and the corresponding address range of the sales point to the data chain, where the address range is a preset range centered on the location of the sales point.

5. The sales influencing factor analysis platform based on big data according to claim 4 is characterized in that: The analysis module is specifically used to use livestock breed, meat quality, sales time period, sales point classification, and sales point address range as sales influencing factors; When analyzing the impact of a farm's corresponding influencing factors on sales, first screen out the data chain to be analyzed. In the data chain to be analyzed, except for the influencing factor and the farm name, other influencing factors are the same as the corresponding influencing factors in the corresponding standard data chain of the farm. Then, when the influencing factor changes, the corresponding changes in the unit price of livestock and the selling time per unit weight are analyzed.

6. A production improvement platform based on big data, characterized in that: It comprises a second acquisition module, an input module, an improvement module and a sales influencing factor analysis platform as claimed in any one of claims 1 to 5; The second acquisition module is used to acquire the production data of each farm; After the user analyzes the main factors affecting sales through the analysis module, the user inputs his own production data through the input module and selects corresponding farms with the same other influencing factors except the main factor; The improvement module is used to compare the user's own production data with the production data of the selected farm, and calculate the improvement cost and improvement cycle.

7. The production improvement platform based on big data according to claim 6, characterized in that: The production data include the breeding farm's breeding environment parameters, feed parameters and management mode.

8. The production improvement platform based on big data according to claim 6, characterized in that: It also includes a control module. After the user uses the improvement module, the control module monitors the user's purchase of means of production based on the comparison result, and determines whether the purpose of the user's production improvement is to adjust the breed of livestock, the quality of livestock meat, or both the breed of livestock and the quality of meat; and performs macro-control of the market based on the user's production improvement purpose.

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