CN108830403B - Visual analysis method for tobacco retail customer visiting path based on commercial value calculation - Google Patents
Visual analysis method for tobacco retail customer visiting path based on commercial value calculation Download PDFInfo
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Abstract
The invention relates to a visual analysis method for a tobacco retail customer visit path based on commercial value calculation. Dividing retail user data objects into two-dimensional space grids according to longitude and latitude information of retail users in the tobacco marketing data set; sorting the sales of all non-blank cells in the grids, and selecting a space grid with the highest commercial value in N grids according to the path planning number N selected by a user; respectively carrying out path planning calculation on retail customer object sets in the selected N grids according to a commercial value optimization path planning algorithm to obtain N retail customer visiting paths; and carrying out visualization and analysis of the visiting merchants on the electronic map according to the calculated N retail customer visiting routes, and manually adjusting and recalculating the optimal route by the user according to the analysis result. According to the technical scheme, a plurality of paths with the optimal commercial value can be automatically generated according to the tobacco marketing data and are used for visual analysis of the tobacco retail customer visit planning.
Description
Technical Field
The invention relates to the field of path planning algorithms and data visual analysis methods, in particular to a visual analysis method for a tobacco retail customer visiting path based on commercial value calculation.
Background
The following realistic problems are mainly involved for the tobacco retail customer visit task: 1. the total number of retail terminals on the tobacco market is very large, and exceeds 500 ten thousand households; 2. the walking distance each marketer works daily is limited; 3. the number of households that each salesperson can access each day is limited. Therefore, limited sales personnel cannot visit all retail user terminals, and the cost is too high due to the fact that the number of market workers is increased, so that most enterprises can visit only part of core retail users. Therefore, how to plan daily visit path tasks for large-scale sales teams so that the large-scale sales teams can create higher commercial value under the condition of limited labor cost is a general concern of tobacco manufacturing enterprises.
The traditional path planning method can better solve the problems of path planning between two points and path planning between multiple points. However, the following problems exist in the market visit to the actual task needs: 1. the value between the traditional path planning middle point and the point is equal, but the business value between retail users is different; 2. the primary measure of traditional planning is that the distance of the path is shortest or takes the least time, rather than the sum of the business values of visiting retailers being the highest; 3. in the traditional planning, a single task and a single path are generally planned, but the path planning of multiple persons and multiple-line tasks is not realized, so that the problem of repeated visit can occur when the traditional method is used for executing the multiple-person multiple-line tasks, and the business value maximization cannot be realized; 4. the path planning of a large number of data points in the traditional planning has the problems of low calculation efficiency and the like.
The marketing data contains a large amount of information such as marketing conditions, time and space, and the like, so that the enterprise can analyze and decide the retail user visiting tasks. Therefore, it is of practical significance to research a tobacco retail customer visit path planning method which can realize multi-path intelligent planning in an unsupervised and self-organizing manner according to the parameter setting of the customer and can cover higher commercial value.
Disclosure of Invention
The invention adopts the idea of grid division and commercial value optimization, designs the visual analysis method of the tobacco retail visit path based on commercial value calculation, and can intelligently plan a plurality of retail visit paths according to market sales data and user requirements.
The invention provides the following technical scheme:
a visual analysis method for a tobacco retail customer visit path based on commercial value calculation comprises the following steps:
dividing retail user data objects into two-dimensional space grids according to longitude and latitude information of retail users in the tobacco marketing data set;
preferably, the sales of all non-blank boxes in the grid are sorted, and a space grid with the highest commercial value in the N grids is selected according to the path planning number N selected by the user;
respectively carrying out path planning calculation on retail customer object sets in the selected N grids according to a commercial value optimization path planning algorithm to obtain N retail customer visiting paths;
respectively carrying out path planning calculation on retail customer object sets in the selected N grids according to the commercial value optimized path planning algorithm to obtain N retail customer visiting paths;
and carrying out visualization and visiting merchant analysis on the electronic map according to the calculated N retail customer visiting paths.
Preferably, in the visual analysis method for the tobacco retail customer visit path based on commercial value calculation, the two-dimensional space grid may be obtained by equally dividing the data space in the tobacco marketing data set according to a grid side length parameter L set by a user.
Preferably, in the above-mentioned business value optimized path planning algorithm, the business value is defined as the total sales (or sales, or profit, or tax) in a unit geographic area;
preferably, the above-mentioned commercial value optimized path planning algorithm is:
firstly, in each selected grid, according to a parameter Num of the maximum daily visit retail user number set by the user, Num candidate retail users with the highest commercial value in the grid are selected, a data point with the maximum sum of the longitude value and the dimension value in the grid is taken as a starting point, the retail user with the closest distance is found out from the rest candidate retail users for path connection, and all the Num retail users are connected in sequence and recursively, so that a retail user visit path is obtained;
secondly, in each path of the visit, judging whether the path length exceeds S according to the maximum daily distance parameter S set by the user, if not, finishing the algorithm; otherwise, eliminating retail households at the head end and the tail end of the path until the path length is smaller than S, respectively searching R nearest retail households in the remaining R retail households, and inserting the retail household with the largest commercial value into the visiting path in a shortest path mode;
and finally, judging whether the length of the re-planned path exceeds S, returning to the previous step if the length of the re-planned path exceeds S, and stopping the algorithm if the length of the re-planned path does not exceed S to obtain N retail customer visiting paths with higher commercial value.
According to the sequence of the retail users visiting, the calculated N retail users visiting paths are visualized on an electronic map, and the sales conditions of the retail users planning visiting in the path planning are analyzed and displayed;
optionally, the analysis content of the sales condition includes the number of the visiting retailers, the total distance length, the total time spent on the visiting distance, the total sales amount of the visiting retailers, and the sales amount information of the retailers;
optionally, the user adjusts the visiting retail user according to the visualization result of the route planning of the tobacco retail user, recalculates the shortest route and visualizes the shortest route;
optionally, when the user is not satisfied with the analysis result of the path of approach generated by the re-planning, repeating the previous step to perform manual adjustment and recalculation; when satisfied, the visual analysis is finished.
Compared with the prior art, the technical scheme provided by the invention at least has the following beneficial effects: the invention provides a visual analysis method for the visiting path of a tobacco retail user based on commercial value calculation, which can be set according to the user requirement and intelligently calculate a plurality of visiting paths of the retail user from market sales data, and is characterized in that: 1. retail households visiting between multiple routes are not duplicated; 2. the total amount of the commercial value of the retail customers contained in the single path (or multiple paths) in the planning is a better result after global calculation; 3. the user can adjust the user according to the visual analysis result of the planned path, and recalculate the shortest path, and make full use of the knowledge and experience of the user to make up the deficiency of the system calculation.
Drawings
FIG. 1 is a flowchart of a method for visually analyzing the visit path of a tobacco retailer based on commercial value calculation according to a preferred embodiment of the present invention;
FIG. 2 is a flowchart illustrating a detailed method for visually analyzing the visit path of a tobacco retailer based on commercial value calculation according to a second preferred embodiment of the present invention;
fig. 3 is a visualization illustration of a retail customer visit path planning of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Example 1
The embodiment provides a visual analysis method for a tobacco retail customer visit path based on commercial value calculation, as shown in fig. 1, comprising the following steps:
s1: and dividing the retail user data object into two-dimensional space grids according to the longitude and latitude information of the retail user in the tobacco marketing data set.
S2: and sequencing the sales of all non-blank boxes in the grids, and selecting the space grid with the highest commercial value in the N grids according to the path planning number N selected by the user.
S3: and respectively carrying out path planning calculation on the retail user object sets in the selected N grids according to a commercial value optimization path planning algorithm to obtain N retail user visiting paths.
S4: and carrying out visualization and analysis of the visiting merchants on the electronic map according to the calculated N retail customer visiting routes, and manually adjusting and recalculating the optimal route by the user according to the analysis result.
In the scheme, N areas with the highest commercial value are found through a grid division technology, the optimal path of the tobacco retail customer visiting is calculated through iteration in the N areas according to the optimization idea, then the calculated result is visualized and analyzed for the conditions of the commercial customers, finally the result calculated by the system is corrected by the user according to personal knowledge and experience, the shortest path is recalculated and visualized, and the interactive visual analysis is repeated until the user obtains a satisfied path planning result. This has mainly 3 benefits: 1. the massive marketing data are subjected to grid division, so that the calculation efficiency is accelerated; 2. the obtained path planning result is a result of global optimization through precise calculation, so that the result is more accurate than the result obtained by a person according to experience, and the coverage range of commercial value is larger; 3. through visual analysis, people can manually correct defects calculated by the system, and points and paths which do not conform to the reality in the real world are eliminated, so that the knowledge and experience of people are fully utilized.
Example 2
In the above step S1, the method can be divided into two steps. An implementation manner is provided in this embodiment, which includes:
specifically, as shown in fig. 2, the method includes the following steps:
s11: equally dividing the data space in the tobacco marketing data set according to the grid side length parameter L set by the user to obtain a two-dimensional space grid;
s12: and dividing the retail user data object into two-dimensional space grids according to the longitude and latitude information of the retail user in the tobacco marketing data set.
In the above step S3, the method can be divided into two steps. An implementation manner is provided in this embodiment, which includes:
specifically, as shown in fig. 2, the method includes the following steps:
s31: in each selected grid, according to a parameter Num of the maximum daily visit retail user number set by a user, selecting Num candidate retail users with the highest commercial value in the grid, taking a data point with the maximum sum of the longitude value and the dimension value in the grid as a starting point, finding out the nearest retail user from the remaining candidate retail users for path connection, and connecting all Num retail users in a recursion mode in sequence to obtain a visit path of the retail users;
s32: in each visiting path, judging whether the path length exceeds S according to the maximum visiting distance parameter S every day set by a user, and if not, finishing the algorithm; otherwise, eliminating retail households at the head end and the tail end of the path until the path length is smaller than S, respectively searching R nearest retail households in the remaining R retail households, and inserting the retail household with the largest commercial value into the path for visiting in a shortest path mode;
s33: judging whether the path length after re-planning exceeds S or not, and jumping to the step S32 if the path length after re-planning exceeds S; if the number of the retail customers is not exceeded, the algorithm is stopped, and N retail customer visit paths with higher commercial values are obtained.
In the above step S4, the method can be divided into three steps. An implementation manner is provided in this embodiment, which includes:
specifically, as shown in fig. 2, the method includes the following steps:
s41: according to the sequence of the visits of the retail customers, the calculated N paths of the visits of the retail customers are visualized on an electronic map, and the sales conditions of the retail customers planning the visits in the path planning are analyzed and displayed;
s42: the user adjusts the visited retail user according to the visualized result of the route planning of the tobacco retail user, recalculates the shortest route and visualizes the shortest route;
s43: when the user is not satisfied with the analysis result of the re-planned and generated walking path, jumping to step S42; if satisfactory, the process proceeds to step S44.
S44: and finishing the planning and analysis of the visiting path of the tobacco retail customer.
While preferred embodiments of the present invention have been described, alterations and modifications to these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
Claims (3)
1. A visual analysis method for a tobacco retail customer visit path based on commercial value calculation is characterized by comprising the following steps:
dividing retail user data objects into two-dimensional space grids according to longitude and latitude information of retail users in the tobacco marketing data set;
sorting the commercial values of all the non-empty grids in the grid, and selecting N spatial grids with the highest commercial value from the divided two-dimensional spatial grids according to the path planning number N selected by a user;
respectively carrying out path planning calculation on retail customer object sets in the selected N grids according to a commercial value optimization path planning algorithm to obtain N retail customer visiting paths;
performing visualization and analysis of visiting merchants on the electronic map according to the calculated N retail customer visiting paths, and manually adjusting and recalculating an optimal path by a user according to an analysis result;
wherein the commercial value is a total amount of sales or profit or tax per geographic area;
the commercial value optimized path planning algorithm comprises the following steps: in each selected grid, according to a parameter Num of the maximum daily visit retail user number set by a user, selecting Num candidate retail users with the highest commercial value in the grid, taking a data point with the maximum sum of the longitude value and the dimension value in the grid as a starting point, finding out the nearest retail user from the remaining candidate retail users for path connection, and connecting all Num retail users in a recursion mode in sequence to obtain a visit path of the retail users; then, in each path of the visit, judging whether the path length exceeds S according to the maximum daily distance parameter S set by the user, and if not, finishing the algorithm; otherwise, eliminating retail households at the head end and the tail end of the path until the path length is smaller than S, respectively searching R nearest retail households in the remaining R retail households, and inserting the retail household with the largest commercial value into the path for visiting in a shortest path mode; and finally, judging whether the path length after re-planning exceeds S, returning to the previous step if the path length exceeds S, and stopping the algorithm if the path length does not exceed S to obtain N retail customer visiting paths with higher commercial value.
2. The commercial value calculation-based visual analysis method for tobacco retail customer visit paths according to claim 1, wherein: the two-dimensional space grid is obtained by equally dividing the data space in the tobacco marketing data set by a grid side length parameter L set by a user.
3. The visual tobacco retailer visit path analysis method based on commercial value calculation as claimed in claim 1, wherein the visit merchant analysis includes the number of visit retailers, the total distance length, the total time spent on the visit, the total sales of the visit retailers and the sales information of the retail outlets; according to the sequence of the visits of the retail customers, the calculated N paths of the visits of the retail customers are visualized on an electronic map, and the sales conditions of the retail customers planning the visits in the path planning are analyzed and displayed; the user adjusts the visited retail user according to the visualized result of the route planning of the tobacco retail user, recalculates the shortest route and visualizes the shortest route; when the user is not satisfied with the analysis result of the path of the visit generated by the re-planning, the previous step is repeated to carry out artificial adjustment and recalculation; when satisfied, the visual analysis is finished.
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| CN112308315A (en) * | 2020-10-29 | 2021-02-02 | 广西中烟工业有限责任公司 | Multi-point intelligent path planning method and system |
| CN112734200A (en) * | 2020-12-31 | 2021-04-30 | 贵州省烟草公司六盘水市公司 | Tobacco product retail point planning grid query system and method based on electronic map |
| CN117094743B (en) * | 2023-08-25 | 2024-01-26 | 中国烟草总公司广东省公司 | Automatic cigarette retail market data statistical analysis system and method |
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