Marketing data insight decision-making method and system

Abstract

The invention provides a marketing data insight decision-making method and system, and relates to the technical field of data processing, and the method comprises the steps: extracting current marketing point locations to determine a corresponding marketing map, and each marketing point location is provided with at least one fixed marketing end used for marketing interaction; decomposing the historical first marketing data of each fixed marketing end according to a preset dimension to obtain a corresponding marketing label, and marking the fixed marketing ends on a marketing map based on the marketing labels to form marketing districts of different dimensions; decomposing a target corresponding to the insight decision to obtain a corresponding marketing dimension, and determining a plurality of corresponding marketing districts based on the marketing dimension; the marketing points are recombined according to the cross relation of different marketing areas, the marketing decision scheme is generated, the requirements of different areas can be visually displayed, and the targeted marketing scheme is generated in a customized mode according to the requirements of the areas.

Description

Technical Field

[0001] The present invention relates to data processing technology, and in particular to a marketing data insight decision-making method and system. Background Art

[0002] In the process of power data marketing, the population structure and power equipment demand in different regions vary significantly. For example, there is a strong demand for electric vehicle charging piles in urban commercial areas, while old communities are more urgent to optimize household electricity services. In addition, the rationality of the distribution of marketing points and the intensity of marketing resource investment in the same region also directly affect the marketing effect. The traditional marketing model relies on experience judgment or simple data statistics, which makes it difficult to comprehensively and deeply analyze the relationship between marketing data and regional characteristics, resulting in irrational allocation of marketing resources and an inability to meet diverse market demands.

[0003] Existing marketing data processing and decision-making methods have many shortcomings. The layout of marketing locations lacks scientific planning and relies mostly on manual experience or fixed pattern settings. It does not fully consider the actual needs and resource density of the region, which can easily lead to excess marketing resources in some areas, while potential areas are not effectively covered. In addition, existing methods cannot effectively integrate marketing data and geographic spatial information, making it difficult to intuitively display the distribution of marketing resources and regional demand characteristics, resulting in a lack of visual support in the decision-making process, making it difficult to quickly identify problems and optimize marketing plans.

[0004] Therefore, how to visually display the needs of different regions and generate customized and targeted marketing plans based on regional needs has become an urgent problem that needs to be solved. Summary of the Invention

[0005] The present invention provides a marketing data insight decision-making method and system, which can intuitively display the needs of different regions and generate customized targeted marketing plans based on regional needs.

[0006] A first aspect of the present invention provides a marketing data insight decision-making method, comprising: Extract the current marketing points to determine the corresponding marketing map. Each marketing point has at least one fixed marketing terminal for marketing interaction. Decomposing the historical first marketing data of each fixed marketing terminal according to a preset dimension to obtain a corresponding marketing tag, and marking the fixed marketing terminal on the marketing map based on the marketing tag to form marketing areas of different dimensions; Decomposing the objectives corresponding to the insight decisions to obtain corresponding marketing dimensions, and determining corresponding multiple marketing zones based on the marketing dimensions; Reorganize marketing points based on the cross-relationships between different marketing areas and generate marketing decision plans.

[0007] Optionally, in a possible implementation of the first aspect, extracting the current marketing location to determine a corresponding marketing map, each marketing location having at least one fixed marketing terminal for marketing interaction, includes: The server interacts with the management terminal to receive the first positioning area selected by the management terminal, and determines all marketing point locations within the first positioning area as current marketing points; Extracting coordinate information of all marketing points to obtain a first coordinate set; The coordinates in the first coordinate set are traversed and extracted in sequence to obtain a marketing map with a fixed marketing terminal setting density.

[0008] Optionally, in a possible implementation of the first aspect, sequentially traversing and extracting coordinates in the first coordinate set to obtain a marketing map with a fixed marketing terminal setting density includes: The horizontal coordinate value and the vertical coordinate value of each coordinate in the first coordinate set are collected and compared respectively to determine the extreme horizontal coordinate and the extreme vertical coordinate, and an initial marketing map is obtained based on the extreme horizontal coordinate and the extreme vertical coordinate; Generate a map segmentation block based on the initial specifications of the marketing map, and segment the initial marketing map based on the map segmentation block to obtain a plurality of map sub-blocks, wherein the map sub-blocks are larger than or equal to the map segmentation block; The number of fixed marketing terminals in each map sub-block is counted to obtain a marketing map with density.

[0009] Optionally, in a possible implementation of the first aspect, obtaining the initial marketing map based on the extreme value abscissa and the extreme value ordinate includes: Generate a first extreme value line and a second extreme value line based on the maximum and minimum values ​​of the extreme value abscissa; Generate the third extreme value line and the fourth extreme value line based on the maximum and minimum values ​​of the extreme value ordinates; A first extreme value line, a second extreme value line, a third extreme value line, and a fourth extreme value line are determined, and an initial marketing map is generated in the intersection area within the original map.

[0010] Optionally, in a possible implementation of the first aspect, generating map segments based on the initial specifications of the marketing map includes: Get the horizontal and vertical coordinate lengths in the initial specifications of the marketing map; Based on the length of the abscissa and the length of the ordinate, respectively, a preset abscissa interval point position and a preset ordinate interval point position are obtained; Based on the horizontal coordinate interval points and the vertical coordinate interval points, corresponding horizontal line segments and vertical line segments are respectively established on the marketing map, and the map segmentation blocks are obtained based on the minimum units formed by the horizontal line segments and the vertical line segments.

[0011] Optionally, in a possible implementation of the first aspect, counting the number of fixed marketing terminals in each map sub-block to obtain a marketing map with density includes: Perform two-dimensional coordinate encoding on each map sub-block to obtain the corresponding sub-block label; If the fixed marketing terminal is located within a map sub-block, a first coefficient is generated and set corresponding to the sub-block label; If the fixed marketing terminal is located on the dividing line between two adjacent map segments, a second coefficient is generated and set corresponding to the sub-block label, and the first coefficient is greater than the second coefficient; A marketing map with density is obtained based on the first coefficient and the second coefficient of the fixed marketing terminal in each map sub-block.

[0012] Optionally, in a possible implementation of the first aspect, obtaining a marketing map with density based on the first coefficient and the second coefficient of the fixed marketing terminal in each map sub-block includes: Adding the first coefficient and the second coefficient yields a density coefficient; Sorting the map sub-blocks of all the map sub-blocks to obtain the median density coefficient and using it as the benchmark density coefficient, and adding the first color to the benchmark density coefficient; Based on the relationship between the density coefficients of the remaining map sub-blocks and the density coefficient of the benchmark, the first color is adjusted to obtain a marketing map with a density color.

[0013] Optionally, in a possible implementation of the first aspect, adjusting the first color to obtain a marketing map having a density color based on a relationship between density coefficients of the remaining map sub-blocks and a reference density coefficient includes: If the density coefficient of any map sub-block is greater than or equal to the density coefficient of the reference, the density coefficient difference is calculated and multiplied by the first preset value to obtain a difference value, and the pixel value of the reference color corresponding to the reference density coefficient is positively adjusted based on the difference value to obtain the second color; If the density coefficient of any map sub-block is smaller than the density coefficient of the benchmark, the density coefficient difference is calculated and multiplied by the second preset value to obtain a difference value, and the pixel value of the benchmark color corresponding to the benchmark density coefficient is reversely adjusted based on the difference value to obtain the second color.

[0014] Optionally, in a possible implementation of the first aspect, marking a fixed marketing terminal on a marketing map based on the marketing tag to form marketing areas of different dimensions includes: Counting the marketing tags of fixed marketing terminals in the same map sub-block to obtain a tag set, and counting the number of fixed marketing terminals corresponding to the marketing tags in the tag set to obtain a first number; Based on the marketing tags, the marketing area corresponding to each map sub-block is obtained, and the tag set is set corresponding to the marketing area.

[0015] Optionally, in a possible implementation of the first aspect, decomposing the goal corresponding to the insight decision to obtain corresponding marketing dimensions, and determining corresponding multiple marketing zones based on the marketing dimensions, includes: Decompose the goals corresponding to the insight decision into the corresponding marketing dimensions, with at least one marketing dimension. A label set of the marketing area corresponding to the marketing dimension of the insight is obtained to obtain the determined multiple marketing areas.

[0016] Optionally, in a possible implementation of the first aspect, the reorganizing marketing points according to the cross-relationships between different marketing areas to generate a marketing decision plan includes: Extract the two-dimensional coordinate code of the determined marketing area and the color corresponding to the density; Divide the marketing area into the largest marketing area based on the two-dimensional coordinate code, determine the center point of each largest marketing area, and calculate a first vector between each marketing area and the center point, wherein the first vector includes at least a length value and an angle value; Based on the first vector and the color corresponding to the density, the marketing point reorganization and marketing decision plan are obtained.

[0017] Optionally, in a possible implementation of the first aspect, obtaining a marketing point reorganization and a marketing decision solution based on the first vector and the color corresponding to the density includes: If the absolute value of the difference between the first vector of a marketing area and other marketing areas is greater than the preset vector value, the corresponding marketing area is retained; If the absolute value of the difference between the first vector of a marketing area and other marketing areas is less than or equal to the preset vector value, the marketing area with the larger color pixel value is retained; Reorganize the retained marketing areas to obtain marketing decisions corresponding to the goals.

[0018] Optionally, in a possible implementation of the first aspect, the reorganizing the retained marketing areas to obtain a marketing decision corresponding to the target includes: If the number of fixed marketing outlets in the marketing area after the reorganization does not meet the number corresponding to the target; Then, the absolute value of the difference of the first vector of the unreserved marketing area is extracted and sorted in descending order to obtain a supplementary sequence; Select the marketing areas in the replenishment sequence in sequence and stop selecting after the number of fixed marketing terminals meets the number corresponding to the target, and reorganize the marketing areas for the second time; If it is determined that the quantity corresponding to the target cannot be met after all marketing areas in the supplementary sequence are selected, a reminder message is output to the management end.

[0019] A second aspect of the present invention provides a marketing data insight decision system, comprising: An extraction module is used to extract the current marketing points and determine the corresponding marketing map. Each marketing point has at least one fixed marketing terminal for marketing interaction. a marking module, configured to decompose the historical first marketing data of each fixed marketing terminal according to a preset dimension to obtain a corresponding marketing tag, and mark the fixed marketing terminal on the marketing map based on the marketing tag to form marketing areas of different dimensions; A determination module is configured to decompose the target corresponding to the insight decision to obtain corresponding marketing dimensions, and determine corresponding multiple marketing areas based on the marketing dimensions; The reorganization module is used to reorganize marketing points according to the cross-relationships of different marketing areas and generate marketing decision plans.

[0020] According to a third aspect of the present invention, a storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the method of the first aspect of the present invention and various possible designs of the first aspect.

[0021] The beneficial effects of the present invention are as follows: 1. The present invention can intuitively display the needs of different regions and generate targeted marketing plans based on regional needs. Among them, the present invention can generate a marketing map with a fixed marketing terminal setting density by extracting the coordinate information of the marketing point, so as to realize the visualization and quantitative analysis of the distribution of marketing resources. First, the present invention determines the marketing point based on the area selected by the management end, and quickly frames the coverage of the marketing point through the extreme values ​​of the coordinates to reduce data redundancy; then, the marketing map is divided into standardized map sub-blocks, and the number of fixed marketing terminals in each map sub-block is counted, and the corresponding coefficients are assigned in combination with the different positions of the fixed marketing terminals to obtain the density coefficient; finally, the median density coefficient is used as a benchmark to intuitively display the density difference through the depth of color, which helps decision makers clearly grasp the current status of the marketing resource layout, provides an intuitive basis for resource optimization and allocation, and avoids wasting resources in inefficient areas.

[0022] 2. The present invention can perform dimensional decomposition based on the first marketing data of the history of a fixed marketing terminal to obtain corresponding marketing tags and marketing areas, so as to generate corresponding marketing plans customized according to the needs of the marketing areas. Among them, by decomposing the historical marketing data of the fixed marketing terminal according to preset dimensions, generating marketing tags and marking them to form marketing areas, the present invention achieves accurate insight and segmentation of market demand, converts marketing data into clear marketing tags according to marketing dimensions, so as to formulate differentiated marketing strategies for different areas, significantly improving the accuracy and effectiveness of marketing activities and meeting the personalized needs of consumers in different regions.

[0023] 3. The present invention reorganizes marketing points by analyzing the cross-relationships of marketing areas, generating scientific and reasonable marketing decision-making plans to achieve optimal allocation of marketing resources. The present invention can extract the two-dimensional coordinate code and density color of the marketing area, calculate the vector relationship between each area and the center point of the largest marketing area, and screen and reorganize marketing points in combination with density features. When the area vector difference is greater than a preset value, the area is retained to ensure device dispersion. When the vector difference is small, areas with large color pixel values ​​are retained first. If the number of fixed marketing terminals is insufficient after reorganization, they are supplemented by screening unretained areas. Thus, marketing areas with different demand types are effectively integrated, duplication of resources is avoided, the reasonable distribution of marketing points is ensured, and the accuracy of data collection and the efficiency of marketing resource utilization are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of a marketing data insight decision-making method provided by the present invention; Figure 2 This is a structural diagram of a marketing data insight decision-making system provided by the present invention. DETAILED DESCRIPTION

[0025] The following specific embodiments are used to describe the technical solution of the present invention in detail. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0026] like Figure 1 As shown, the present invention provides a flowchart of a marketing data insight decision-making method, which includes: S1, extract the current marketing point to determine the corresponding marketing map, each marketing point has at least one fixed marketing terminal for marketing interaction.

[0027] It should be noted that in order to generate customized marketing plans based on the demand information corresponding to different regions, data analysis can be conducted on the current marketing points to determine targeted marketing plans in order to increase sales.

[0028] Understandably, in order to improve marketing data, it is necessary to tailor marketing decisions to different regions to promote product sales. This can be achieved by conducting questionnaires to collect information on customer needs, facilitating the subsequent customization of targeted sales strategies.

[0029] Among them, the marketing point is the currently set marketing location, the marketing map is the geographical display map for marketing activities, and the fixed marketing end is an electronic information collection device with a fixed location, such as a fixed-location data collection device that can generate electronic questionnaires.

[0030] It is worth mentioning that traditional marketing methods usually require personnel to actively distribute questionnaires, which consumes a lot of labor costs. Therefore, a marketing map can be obtained based on the set marketing points, so as to determine the location points corresponding to the fixed marketing end according to the marketing map.

[0031] It is not difficult to understand that marketing data is the electricity marketing data corresponding to the power grid, mainly including electricity sales, electricity bill recovery rate, line loss rate, customer satisfaction, etc. These sales data are closely related to the flow of people and demand corresponding to different regions. Therefore, the current marketing points can be extracted to determine the marketing map, so as to generate targeted insight decisions later.

[0032] In some embodiments, a specific implementation of step S1 (extracting the current marketing location to determine the corresponding marketing map, where each marketing location has at least one fixed marketing terminal for marketing interaction) includes: S11, the server interacts with the management terminal to receive the first positioning area selected by the management terminal, and determines all marketing point positions within the first positioning area as current marketing points.

[0033] It is understandable that power companies usually divide management units according to administrative regions (such as provinces, cities, and districts). Management personnel are more accustomed to conducting business based on administrative boundaries. By receiving the first positioning area selected by the management side, irrelevant points can be filtered out, and marketing data within the target area can be focused, reducing the amount of data processing while improving the targeted analysis.

[0034] Among them, the management end is an information terminal for marketing data management, the first positioning area is a pre-set administrative area, the marketing point location is the service center location for power data marketing, and there can be multiple marketing point locations in one area.

[0035] Through the above implementation, the present invention can improve the accuracy of data analysis, avoid data mixing across administrative regions, and ensure that subsequent density calculations and label analysis are limited to a reasonable range.

[0036] S12: extracting coordinate information of all marketing points to obtain a first coordinate set.

[0037] It can be understood that the first coordinate set is a location set of geographic coordinate information of marketing points, wherein the coordinate information is the geographic longitude and latitude coordinates corresponding to the marketing points, and the first coordinate set is a set of coordinate information corresponding to all current marketing points.

[0038] Through the above implementation, the present invention can obtain the coordinate information corresponding to each marketing point so that each point has a unique and determined position on the map, which is convenient for subsequent partitioning and data analysis and processing.

[0039] S13, traversing and extracting the coordinates in the first coordinate set in sequence to obtain a marketing map with a fixed marketing terminal setting density.

[0040] It can be understood that density calculation can reveal the spatial distribution characteristics of marketing points, quantify the intensity of resource allocation, and generate density with fixed marketing end settings through traversal and extraction of coordinates, so that the corresponding density information can be displayed on the map to obtain a marketing map, which is convenient for quickly identifying hot spots and cold spots, that is, potential areas to be developed, through density differences.

[0041] The setting density is the density of fixed marketing terminals set in a certain area, and the marketing map is a map that can reflect marketing information, for example, a map with a visual display of the setting density.

[0042] In some embodiments, a specific implementation of step S13 (the step of sequentially traversing and extracting coordinates in the first coordinate set to obtain a marketing map with a fixed marketing terminal setting density) includes: S131, respectively collect and compare the horizontal coordinate value and the vertical coordinate value of each coordinate in the first coordinate set, determine the extreme horizontal coordinate and the extreme vertical coordinate, and obtain an initial marketing map based on the extreme horizontal coordinate and the extreme vertical coordinate.

[0043] Understandably, power marketing points may be distributed across a large geographic area (e.g., across multiple urban areas), and directly processing the entire map data would result in computational redundancy. By extracting the extreme abscissa values ​​(maximum and minimum) and ordinate values ​​for all points in the first coordinate set, we can quickly define the minimum rectangular area actually covered by the marketing points, avoiding processing irrelevant blank areas. In other words, the spatial boundaries of the marketing points are determined by the coordinate extremes, establishing the initial analysis scope.

[0044] Among them, the abscissa value is the numerical value corresponding to the abscissa, the ordinate value is the numerical value corresponding to the ordinate, the extreme abscissa is the maximum and minimum values ​​corresponding to the abscissa, and the extreme ordinate is the maximum and minimum values ​​corresponding to the ordinate.

[0045] Through the above implementation, the present invention can determine the regional scope of the current marketing point based on the first coordinate set, ensuring that the generated marketing map just contains all points, avoiding analysis deviations caused by artificially setting the range too large or too small, so that only the map area related to the marketing point can be processed subsequently to reduce the amount of data.

[0046] In some embodiments, a specific implementation of step S131 (obtaining an initial marketing map based on the extreme value abscissa and the extreme value ordinate) includes: S1311 , generating a first extreme value line and a second extreme value line based on the maximum value and the minimum value of the extreme value horizontal coordinate.

[0047] It can be understood that the maximum and minimum values ​​of the extreme horizontal coordinate represent the farthest endpoints of the marketing point in the east-west direction respectively. Generating these two straight lines perpendicular to the horizontal axis (the first extreme line and the second extreme line) can clearly define the spatial boundaries of the marketing point in the east-west direction.

[0048] The first extreme value line is the region boundary line corresponding to the maximum value in the extreme value horizontal coordinate, and the second extreme value line is the region boundary line corresponding to the minimum value in the extreme value horizontal coordinate.

[0049] For example, if the maximum value is 116.50°E and the minimum value is 116.30°E, then the two extreme value lines are located at these two longitude positions respectively.

[0050] Through the above implementation, the present invention can convert abstract coordinate extreme values ​​into visual boundary lines, which is convenient for subsequent area division. At the same time, it ensures that all marketing points are located between the two lines to avoid missing points.

[0051] S1312: Generate a third extreme value line and a fourth extreme value line based on the maximum value and the minimum value of the extreme value vertical coordinate.

[0052] It's understandable that the maximum and minimum values ​​of the extreme vertical coordinate represent the farthest north-south endpoints of the marketing location, respectively. Generating these two lines perpendicular to the vertical axis (the third extreme value line and the fourth extreme value line) clearly defines the spatial boundaries of the marketing location in the north-south direction.

[0053] Among them, the third extreme value line is the region boundary line corresponding to the maximum value in the extreme value horizontal coordinate, and the fourth extreme value line is the region boundary line corresponding to the minimum value in the extreme value horizontal coordinate.

[0054] For example, if the maximum value is 39.95°N and the minimum value is 39.85°N, the two extreme lines are located at these two latitudes respectively.

[0055] S1313 , determining a first extreme value line, a second extreme value line, a third extreme value line, and a fourth extreme value line, and generating an initial marketing map in the intersection area within the original map.

[0056] It can be understood that the rectangular area formed by the intersection of four extreme lines (two horizontal and two vertical) on the original map is the minimum circumscribed rectangle containing all marketing points. By extracting this area as the initial marketing map, the original large-scale map data can be cropped into a small-scale data containing only target points. The intersection area may contain a small number of blank areas without marketing points (such as rectangular corners), but the processing range has been greatly reduced compared to the original map.

[0057] Through the above implementation, the present invention can achieve regional focus, ensuring that all analysis operations are only targeted at the actual distribution areas of marketing points, avoiding wasting resources in areas with no data, so as to reduce the amount of data for subsequent density calculations, area division and other operations, and improve algorithm efficiency.

[0058] S132: Generate a map segmentation block based on the initial specifications of the marketing map, and segment the initial marketing map based on the map segmentation block to obtain a plurality of map sub-blocks, wherein the map sub-blocks are larger than or equal to the map segmentation block.

[0059] It is understandable that the initial marketing map is a continuous geographical area and density calculation cannot be performed directly. By dividing it into multiple map sub-blocks (such as grids), the continuous space can be converted into discrete units, making it easier to count the number of fixed marketing terminals in each unit. The size of the map segment determines the granularity of the density analysis, such as a 1km×1km grid or a 100m×100m grid, which needs to be dynamically adjusted according to the distribution density of the marketing points and the analysis accuracy requirements.

[0060] Among them, the initial specification is the initial distance length corresponding to the marketing map, the map segmentation block is the grid block that divides the map, and the map sub-block is the area block after the marketing map is divided according to the map segmentation block. Among them, the map segmentation block is the smallest segmentation unit, so the map sub-block is greater than or equal to the map segmentation block.

[0061] It is not difficult to understand that the marketing map is divided into regions according to the map blocks to achieve standardized analysis units, that is, the unified grid division makes the density calculation results comparable.

[0062] In some embodiments, the specific implementation of step S132 (generating map segments based on the initial specifications of the marketing map) includes: S1321, obtaining the horizontal coordinate length and the vertical coordinate length in the initial specification of the marketing map.

[0063] It is understandable that the generation of map segments needs to be based on the actual size of the marketing map. By calculating the horizontal coordinate length (east-west span) and vertical coordinate length (north-south span) of the initial marketing map, the actual physical scope of the map can be determined.

[0064] The length of the horizontal axis is the distance length in the horizontal direction corresponding to the initial specification in the marketing map, and the length of the vertical axis is the distance length in the vertical direction corresponding to the initial specification in the marketing map.

[0065] For example, if the length of the horizontal axis is 10 km and the length of the vertical axis is 8 km, a reasonable grid size needs to be designed based on this size (such as generating 10×8 grids at 1 km intervals).

[0066] Through the above implementation, the present invention can dynamically adjust the segmentation strategy according to the actual size of the map to avoid the grid being too large or too small, and ensure that the generated grid completely covers the marketing map area without missing any data.

[0067] S1322: Obtain preset horizontal coordinate interval points and vertical coordinate interval points based on the horizontal coordinate length and the vertical coordinate length, respectively.

[0068] It is understandable that the preset horizontal and vertical axis interval points determine the size of the grid, and the spatial granularity of the density analysis is controlled by determining the interval points of the grid division.

[0069] The horizontal coordinate interval points are interval points determined by the horizontal coordinate length, and the vertical coordinate interval points are interval points determined by the vertical coordinate length.

[0070] For example, if the length of the horizontal coordinate is 10km and the interval point is set to 1km, then 10 interval points will be generated in the east-west direction (dividing 10km into 10 segments). Similarly, if the length of the vertical coordinate is 8km and the interval point is 1km, then 8 interval points will be generated in the north-south direction. These interval points constitute the boundaries of the grid.

[0071] S1323: establishing corresponding horizontal and vertical line segments on the marketing map based on the horizontal and vertical interval points, and obtaining map segments based on the minimum units formed by the horizontal and vertical line segments.

[0072] It can be understood that vertical line segments perpendicular to the horizontal axis are drawn according to the interval points of the horizontal coordinate, and horizontal line segments perpendicular to the vertical axis are drawn according to the interval points of the vertical coordinate. The smallest rectangular unit formed by the intersection of these line segments is the map segmentation block. A regular grid is generated by crossing the horizontal and vertical line segments to construct the basic unit of density statistics.

[0073] The horizontal line segment is a horizontal segment, the vertical line segment is a vertical segment, and the map segmentation block is the smallest unit block formed by the horizontal line segment and the vertical line segment.

[0074] For example, 10×8 interval points can generate 10×8=80 grids, each of which serves as an independent statistical unit.

[0075] Through the above implementation, the present invention can convert continuous geographic space into discrete data structure, adapt computer processing logic, improve the efficiency of subsequent density calculation, and the regular grid facilitates efficient statistics of the number of marketing terminals in each unit and supports fast spatial query.

[0076] S133: Count the number of fixed marketing terminals in each map sub-block to obtain a marketing map with density.

[0077] It is understandable that simple map segmentation only divides spatial units and cannot reflect the density of marketing resources in each region. By counting the number of fixed marketing terminals in each sub-block, the spatial distribution of marketing points can be converted into a quantifiable density indicator, and the discrete point distribution can be converted into continuous density information, thereby realizing the quantitative expression of marketing resource distribution.

[0078] For example, a commercial area may have a large number of fixed marketing terminals due to large customer traffic and a high density value, while a remote area may have a small number of fixed marketing terminals and a low density value. This quantitative result helps to intuitively display the spatial differences in marketing resources and provide a basis for subsequent decision-making.

[0079] Through the above implementation methods, the present invention can convert the abstract distribution of marketing resources into intuitive density data, which is convenient for decision makers to quickly identify resource-intensive areas and resource-scarce areas, and provide quantitative support for the optimal allocation of marketing resources, such as adding fixed marketing terminals in low-density areas.

[0080] In some embodiments, a specific implementation of step S133 (the step of counting the number of fixed marketing terminals in each map sub-block to obtain a marketing map with density) includes: S1331, perform two-dimensional coordinate encoding on each map sub-block to obtain the corresponding sub-block label, It is understandable that as the map is divided into multiple sub-blocks, a unified way is needed to distinguish and locate each sub-block. Two-dimensional coordinate encoding (similar to the row and column numbers of a grid) can give each sub-block a unique "identity tag".

[0081] Among them, the sub-block label is the corresponding number label of the map sub-block, such as 11, 12, 13, etc.

[0082] For example, the map is divided into a 10×10 grid by rows and columns, the upper left corner sub-block is encoded as 11, and the lower right corner is encoded as 1010. This encoding method facilitates subsequent independent data statistics, query and analysis of each sub-block, avoiding data confusion between sub-blocks.

[0083] Through the above implementation, the present invention can assign a unique two-dimensional coordinate code to each map sub-block, thereby achieving accurate identification and management of the sub-blocks.

[0084] S1332: If the fixed marketing terminal is located within a map sub-block, a first coefficient is generated and set corresponding to the sub-block label.

[0085] It can be understood that when a fixed marketing end is completely located within a certain map sub-block, a higher coefficient is assigned to the sub-block to highlight its resource density. Since the map is divided into regions, the corresponding fixed marketing end may fall inside the map sub-block or on the boundary of an adjacent sub-block. Among them, when the fixed marketing end is within the map sub-block, it means that the fixed marketing end completely belongs to the density of the corresponding map sub-block and contributes more to its density. Therefore, the first coefficient (such as 1) is generated for this type of sub-block and is bound to the sub-block label for subsequent density calculations.

[0086] The first coefficient is a density coefficient value corresponding to a fixed marketing terminal being completely within a map sub-block, and may be pre-set.

[0087] For example, if a sub-block has three fixed marketing terminals, each with a coefficient of 1, the density contribution of the sub-block is 3. This method can accurately reflect the actual resource usage within the sub-block.

[0088] S1333: If the fixed marketing terminal is located on the dividing line between two adjacent map segments, a second coefficient is generated and set corresponding to the sub-block label, and the first coefficient is greater than the second coefficient.

[0089] It can be understood that when the fixed marketing end is located exactly on the dividing line between two sub-blocks, its resource contribution to the two sub-blocks should be evenly distributed. Therefore, a second coefficient (such as 0.5) is generated and set corresponding to the labels of the two adjacent sub-blocks at the same time.

[0090] The second coefficient is the density coefficient value corresponding to the fixed marketing end being on the dividing line of the map segmentation block, which can be preset.

[0091] For example, if a marketing terminal is located on the boundary line between sub-block A and sub-block B, a coefficient of 0.5 will be included in the density calculation of sub-blocks A and B. This processing method avoids the density statistical deviation caused by the boundary position and ensures the fairness of density statistics.

[0092] S1334: Obtain a marketing map with density based on the first coefficient and the second coefficient of the fixed marketing terminal in each map sub-block.

[0093] It can be understood that the first coefficient and the second coefficient of the fixed marketing end in each map sub-block are combined to calculate the sub-block density and generate the final density map. By summarizing and visualizing the density coefficients of all sub-blocks (such as heat map rendering), a complete marketing map with density information is formed. This map intuitively shows the density of marketing resources in each region.

[0094] In some embodiments, a specific implementation of step S134 (obtaining a marketing map with density based on the first coefficient and the second coefficient of the fixed marketing terminal in each map sub-block) includes: S1341: Add the first coefficient and the second coefficient to obtain a density coefficient.

[0095] It can be understood that the density coefficient is the setting density of the fixed marketing terminal in the corresponding map area, that is, the sum of the first coefficient and the second coefficient.

[0096] For example, if a sub-block contains 2 fully covered marketing terminals (coefficient 1×2) and 1 border marketing terminal (coefficient 0.5), the density coefficient is 2+0.5=2.5.

[0097] S1342: Sort the map sub-blocks of all the map sub-blocks to obtain a median density coefficient and use it as a benchmark density coefficient, and add a first color to the benchmark density coefficient.

[0098] It is understandable that the median is the middle value of the data distribution, is not affected by extreme values, and can robustly reflect the overall level. After sorting the density coefficients of all sub-blocks, the median is taken as the benchmark (for example, the median density coefficient is 1.8) and assigned the first color (such as yellow) to represent the "average density level". This benchmark selection method is suitable for skewed distribution data, avoiding the situation where a few high-density sub-blocks raise the overall benchmark, causing most sub-blocks to be misjudged as "low density".

[0099] It is not difficult to understand that when the density coefficient corresponding to the map sub-block is higher than the density coefficient of the benchmark, the color can be darkened according to the difference value. When the density coefficient is lower than the benchmark, the color of the first map sub-block can be lightened so that people can intuitively distinguish the density values ​​corresponding to different areas.

[0100] The color corresponding to the density coefficient with the first color as the reference may be preset, such as yellow.

[0101] S1343: Based on the relationship between the density coefficients of the remaining map sub-blocks and the density coefficient of the benchmark, adjust the first color to obtain a marketing map with a density color.

[0102] It can be understood that for sub-blocks with density coefficients higher than the median, the color is deepened according to the excess (for example, the red component increases by 20% for every 0.5 unit excess), and for sub-blocks below the median, the color brightness is reduced according to the gap (for example, the blue component increases by 20% for every 0.5 unit below). This dynamic adjustment makes the color change proportional to the density difference. For example, a sub-block with a density coefficient of 3.0 (higher than the median 1.2) is displayed dark red, and a coefficient of 1.0 (lower than the median 0.8) is displayed dark green. The color is dynamically adjusted according to the difference between the density coefficient and the benchmark to achieve a visual mapping of the density level.

[0103] Through the above-mentioned implementation manner, the present invention can intuitively display density differences, and the color depth directly reflects the density level, so that users can quickly locate key areas without checking the numerical values.

[0104] In some embodiments, a specific implementation of step S1343 (adjusting the first color to obtain a marketing map having a density color based on the relationship between the density coefficients of the remaining map sub-blocks and the density coefficient of the benchmark) includes: S13431, if the density coefficient of any map sub-block is greater than or equal to the density coefficient of the benchmark, then calculate the density coefficient difference and multiply it by the first preset value to obtain a difference value, and based on the difference value, positively adjust the pixel value of the benchmark color corresponding to the benchmark density coefficient to obtain the second color.

[0105] It can be understood that in the marketing map, the more people there are, the greater the setting density of the corresponding fixed sales terminals will be. By calculating the difference between the sub-block density coefficient and the benchmark value and multiplying it by the first preset value (such as 0.8), the numerical difference is converted into a quantifiable color adjustment range.

[0106] For example, the base density coefficient is 2.0, and the coefficient of a sub-block is 3.0. The difference value of 1.0 multiplied by 0.8 is 0.8, which is used to increase the brightness of the base color (such as yellow) or change the hue (gradually toward red). Positive adjustment means that the color saturation and brightness increase, making high-density areas more conspicuous on the map and easier for decision makers to quickly identify.

[0107] Among them, the first preset value is a pre-set weight value of a density coefficient greater than the benchmark, the density coefficient difference is the difference between the density coefficient greater than the benchmark and the density coefficient of the benchmark, the difference value is a deviation value for adjusting the first color, and the second color is the set color of the map sub-block of the non-benchmark density coefficient.

[0108] Through the above-mentioned implementation manner, the present invention can present high-density areas with more vivid and bright colors, forming a visual focus on the map, which is convenient for locating core marketing areas.

[0109] S13432: If the density coefficient of any map sub-block is smaller than the density coefficient of the benchmark, the density coefficient difference is calculated and multiplied by a second preset value to obtain a difference value, and the pixel value of the benchmark color corresponding to the benchmark density coefficient is reversely adjusted based on the difference value to obtain the second color.

[0110] It can be understood that when the sub-block density coefficient is lower than the benchmark, the benchmark color is reversely adjusted by quantifying the difference value, and the low-density area is represented by a lighter or cooler color. The low-density area usually represents an area with insufficient marketing resources or to be developed. The difference between the sub-block density coefficient and the benchmark value is calculated and multiplied by the second preset value (such as 0.6) to convert the difference into a basis for color adjustment.

[0111] The first preset value is a preset weight value of a density coefficient that is smaller than a reference value.

[0112] For example, if the base density coefficient is 2.0 and the coefficient of a sub-block is 1.5, the difference of 0.5 multiplied by 0.6 is 0.3. This value is used to reduce the brightness of the base color (such as yellow) or change the hue (gradually toward green). The reverse adjustment makes the color tend to be darker or cooler, forming a visual contrast with the high-density area, which not only weakens the non-key areas but also facilitates the identification of resource-scarce areas.

[0113] Through the above-mentioned implementation mode, the present invention can clearly distinguish high-density and low-density areas through the contrast of warm and cold tones and the difference in brightness, and construct a visual sense of hierarchy in the map. The cold color presentation of low-density areas can intuitively prompt decision makers to areas where they need to increase resource investment or optimize layout, and assist in formulating targeted strategies.

[0114] S2. Decompose the historical first marketing data of each fixed marketing terminal according to preset dimensions to obtain corresponding marketing tags, and mark the fixed marketing terminal on the marketing map based on the marketing tags to form marketing areas of different dimensions.

[0115] It should be noted that since the number of people in different age groups in different regions is inconsistent, and the demand for power products in different age groups is also different, for example, the number of electric bicycles and electric vehicles used is different, the number of electric bicycle charging piles and electric vehicle charging piles that need to be installed will also be different, which will have a certain impact on electricity sales. Therefore, the first marketing data collected by the fixed marketing end in the historical time period can be analyzed to determine the corresponding electricity demand, so as to facilitate subsequent targeted marketing design based on the needs of different regions.

[0116] It is understandable that simple marketing data (such as electricity sales and customer satisfaction) lacks intuitive business orientation. By decomposing the data through preset dimensions (such as population characteristics, consumption preferences, and power equipment requirements), the potential needs behind the data can be explored, and these labels can be marked on the marketing map. The scattered fixed marketing ends can be clustered according to business characteristics to form marketing areas with clear attributes, such as "high charging pile demand areas", which facilitates the subsequent formulation of differentiated marketing strategies for different areas.

[0117] Among them, the first marketing data is the marketing data collected by the fixed marketing end corresponding to the historical time period, the preset dimension is the pre-set dimension, such as age, power demand and other dimensions, the marketing label is the prompt label corresponding to the marketing data, such as the elderly area, high power demand area, etc., and the marketing area is to combine the areas with the same label and are connected to obtain an area with multiple sub-areas corresponding to the same label.

[0118] In some embodiments, a specific implementation of step S2 (marking a fixed marketing terminal on a marketing map based on the marketing tag to form marketing areas of different dimensions) includes: S21, counting the marketing tags of fixed marketing terminals in the same map sub-block to obtain a tag set, and counting the number of fixed marketing terminals corresponding to the marketing tags in the tag set to obtain a first number.

[0119] It is understandable that the same map sub-block can have multiple fixed marketing terminals or multiple marketing tags. Therefore, the marketing tags in the same map sub-block can be counted to obtain a tag set, and the first quantity corresponding to each marketing tag can be counted, so that the power demand corresponding to the map sub-block can be intuitively reflected according to the first quantity corresponding to the marketing tag, so as to generate a customized marketing strategy.

[0120] The tag set is a set of marketing tags for fixed marketing terminals in the same map sub-block, and the first number is the number of marketing tags corresponding to fixed marketing terminals.

[0121] S22, obtaining the marketing area corresponding to each map sub-block based on the marketing tag, and setting the tag set corresponding to the marketing area.

[0122] It is understandable that the label attributes of a single map sub-block may have limitations. By combining adjacent sub-blocks with the same label (for example, multiple adjacent sub-blocks are all labeled as "high electric vehicle power demand"), the demand coverage can be expanded and marketing areas with economies of scale can be formed. Based on the label set, spatially connected map sub-blocks with the same label are merged into marketing areas to form geographical units with unified business attributes.

[0123] Through the above implementation methods, the present invention can integrate scattered demands, form geographical units with actual planning value, improve resource allocation efficiency, and each marketing area corresponds to a clear set of labels, which facilitates the formulation of marketing strategies that meet regional needs.

[0124] S3, decomposing the target corresponding to the insight decision to obtain corresponding marketing dimensions, and determining corresponding multiple marketing areas based on the marketing dimensions.

[0125] It is understandable that insight decisions are decomposed according to the purpose of the insight, so as to determine the corresponding marketing dimensions. For example, when the insight purpose is for the elderly and children, the corresponding marketing dimension is only the impact dimension corresponding to the elderly and children. When the corresponding electricity sales volume is concerned, the corresponding marketing dimension is the electricity demand dimension. According to different dimensions (such as population, electricity usage behavior), the corresponding areas are matched to improve the fit between services and needs.

[0126] Among them, the marketing dimension is the promotion dimension corresponding to the marketing data, which is determined based on the insight purpose.

[0127] In some embodiments, a specific implementation of step S3 (decomposing the target corresponding to the insight decision to obtain corresponding marketing dimensions, and determining corresponding multiple marketing zones based on the marketing dimensions) includes: S31. Decompose the goal corresponding to the insight decision to determine the marketing dimension corresponding to the insight. There must be at least one marketing dimension.

[0128] It is understandable that if the purpose of the insight involves electricity demand, it is necessary to superimpose electricity-related dimensions such as "average household electricity consumption" and "charging pile coverage rate". Each dimension corresponds to a set of data collection and analysis rules (such as calculating the proportion of elderly people through demographic data, and obtaining the location of charging piles through power grid ledger data) to ensure that the dimensions are quantifiable and verifiable.

[0129] Among them, the number of dimensions depends on the complexity of the goal. A single goal, such as "improving elderly customer satisfaction", can correspond to one core dimension, while a complex goal, such as "optimizing household electricity services and promoting new energy", requires the coordination of multiple dimensions.

[0130] S32, obtaining a label set of the marketing area corresponding to the marketing dimension of the insight, and obtaining the determined multiple marketing areas.

[0131] It can be understood that through the matching algorithm of marketing dimensions and area labels, geographical areas that meet the goals are screened out to form decision-making execution units.

[0132] Among them, the areas corresponding to the same marketing dimensions are combined into the same marketing area. Therefore, multiple marketing areas can be determined according to different marketing dimensions, so that targeted marketing decisions can be generated according to the needs of different marketing areas in the future.

[0133] S4, reorganize the marketing points according to the cross-relationships of different marketing areas and generate marketing decision plans.

[0134] It is understandable that by analyzing the spatial intersection relationship and density distribution of marketing areas, the marketing points can be reorganized and optimized to achieve the global optimal resource allocation. That is, different marketing areas, such as the "high elderly customer area" and the "high charging pile demand area", may have spatial overlap or complementary relationships.

[0135] For example, if an area is both "densely populated with elderly customers" and "lowly covered by charging piles," it is necessary to comprehensively consider both types of demands and formulate a differentiated strategy. By quantifying the cross-relationships between areas (such as spatial distance and demand intensity), scattered marketing points can be recombined into more efficient service units to avoid duplicate resource investment or blank areas.

[0136] Among them, the marketing decision plan is a marketing plan based on marketing data.

[0137] In some embodiments, a specific implementation of step S4 (reorganizing marketing points based on the cross-relationships between different marketing areas to generate a marketing decision plan) includes: S41, extracting the two-dimensional coordinate code of the determined marketing area and the color corresponding to the density.

[0138] It should be noted that when deploying equipment, it is necessary to disperse the equipment as much as possible within the area. Since the number of people in the area is fixed, dispersing the equipment can maximize the accuracy of data collection.

[0139] It can be understood that extracting the spatial coding and density characteristics of the marketing area builds the basis for quantitative analysis. Among them, the two-dimensional coordinate code uniquely identifies the geographical location of each marketing area, and the color corresponding to the density quantifies the demand intensity of the area. Extracting these two characteristics can convert the abstract marketing area into a computable spatial vector and numerical indicator for subsequent equipment distribution.

[0140] S42, dividing the maximum marketing area based on the two-dimensional coordinate coding of the marketing area, determining the center point of each maximum marketing area, and calculating the first vector between each marketing area and the center point, wherein the first vector includes at least a length value and an angle value.

[0141] It can be understood that the map segments corresponding to the two-dimensional coordinate codes of the marketing areas are combined to obtain the maximum marketing area, and the center point of the maximum marketing area is determined, so as to determine the first vector between the marketing area and the center point, so as to facilitate the subsequent determination of the dispersion of the fixed marketing terminal installation based on the first vector, so as to improve the accuracy of data collection.

[0142] Among them, the first vector is the vector between the center of the marketing area and the center point of the largest marketing area, including a length value and an angle value. The length value is the distance between the center of the marketing area and the center point of the largest marketing area, and the angle value is the angle between the line between the center of the marketing area and the center point of the largest marketing area and the preset direction.

[0143] S43, obtaining a marketing point reorganization and a marketing decision plan based on the first vector and the color corresponding to the density.

[0144] It can be understood that by combining the length and angle of the first vector and the demand intensity represented by the density color, the optimal layout of marketing points can be automatically planned. This allows the decision-making plan to be updated in real time to support agile response when changes in regional demand cause changes in vector characteristics.

[0145] In some embodiments, a specific implementation of step S43 (obtaining a marketing point reorganization and a marketing decision plan based on the first vector and the color corresponding to the density) includes: S431: If it is determined that the absolute value of the difference between the first vector of a marketing area and other marketing areas is greater than a preset vector value, the corresponding marketing area is retained.

[0146] It can be understood that when the absolute value of the first vector difference between a marketing area and other areas (that is, the comprehensive value of the length difference and the angle difference) exceeds the preset vector value, it means that the corresponding areas are far away, which complies with the principle of equipment dispersion, that is, the current number of devices is reasonably distributed in the corresponding area, and thus, the corresponding marketing area can be retained.

[0147] The preset vector value is a pre-set vector value.

[0148] S432: If it is determined that the absolute value of the difference between the first vector of a marketing area and other marketing areas is less than or equal to a preset vector value, the marketing area with a larger color pixel value is retained.

[0149] It is understandable that for marketing areas with similar vectors, through density and color comparison, areas with high demand intensity are retained first to maximize resource utility. If the absolute value of the vector difference between two areas is small, it means that their spatial position and demand direction are highly overlapped, that is, there are more resources in different areas with similar distances. It is possible to consider merging services and achieving equipment dispersion to improve the accuracy of data collection. Therefore, areas with large color pixel values ​​are retained first.

[0150] S433, reorganize the retained marketing areas to obtain marketing decisions corresponding to the goals.

[0151] It is understandable that reorganizing these areas (such as clustering by geographical location and grouping by demand type) can generate targeted decision-making plans. Through screening and reorganization, complex area relationships can be transformed into clear action plans. Each decision is associated with a specific geographical area and demand type, which is convenient for the execution team to quickly understand and implement.

[0152] In some embodiments, a specific implementation of step S433 (reorganizing the retained marketing areas to obtain marketing decisions corresponding to the target) includes: S4331, if the number of fixed marketing terminals in the marketing area after reorganization does not meet the number corresponding to the target.

[0153] It is understandable that the number of fixed marketing terminals changes dynamically according to the regional personnel. When the marketing area is reorganized and it is determined that the number of corresponding fixed marketing terminals is insufficient, the previously unretained marketing areas can be screened subsequently so that the number of fixed marketing terminals meets the preset requirements.

[0154] Among them, if the number of fixed marketing terminals in the reorganized marketing area is lower than the target set value, the area may not be able to effectively collect marketing data, that is, the accuracy of the marketing data may be reduced.

[0155] S4332: extract the absolute value of the difference of the first vector of the unreserved marketing area, and sort it in descending order to obtain a supplementary sequence.

[0156] It can be understood that in order to achieve the most decentralized installation of fixed marketing equipment, so as to cover the marketing areas to the greatest extent and improve the accuracy of data collection, the absolute value of the difference of the first vector of the unretained marketing areas can be extracted and sorted in descending order to obtain a supplementary sequence, so that areas that are farther away can be pre-screened to retain the fixed marketing ends within the first area.

[0157] The supplementary sequence is a sequence of marketing areas obtained by arranging the corresponding marketing areas in descending order according to the absolute values ​​of the differences of the first vectors of the unreserved marketing areas.

[0158] S4333, select the marketing areas in the supplementary sequence in turn and stop selecting after the number of fixed marketing terminals meets the number corresponding to the target, and reorganize the marketing areas for the second time.

[0159] It can be understood that the areas are selected in sequence starting from the top of the supplementary sequence (with the largest distance). The number of fixed marketing terminals is recalculated each time an area is supplemented until the target value is met. For example, when the second area is supplemented, the total number of marketing terminals reaches the target value of 500, and the selection is stopped. After the area is selected, the vector center point and density distribution need to be recalculated to ensure that the area structure after the secondary reorganization is reasonable.

[0160] S4334: If it is determined that the quantity corresponding to the target cannot be met after all marketing areas in the supplementary sequence are selected, a reminder message is output to the management end.

[0161] Understandably, if, after all areas in the replenishment sequence have been selected, the number of fixed marketing terminals still falls short of the target (e.g., only 400 against a target of 500), this indicates insufficient device coverage. In this case, a reminder message, such as "There is a shortage of 100 service terminals in area XX. We recommend adding new fixed marketing terminals," will be sent to the management team to guide manual intervention.

[0162] like Figure 2 As shown, the present invention provides a structural diagram of a marketing data insight decision system, which includes: An extraction module is used to extract the current marketing points and determine the corresponding marketing map. Each marketing point has at least one fixed marketing terminal for marketing interaction. a marking module, configured to decompose the historical first marketing data of each fixed marketing terminal according to a preset dimension to obtain a corresponding marketing tag, and mark the fixed marketing terminal on the marketing map based on the marketing tag to form marketing areas of different dimensions; A determination module is configured to decompose the target corresponding to the insight decision to obtain corresponding marketing dimensions, and determine corresponding multiple marketing areas based on the marketing dimensions; The reorganization module is used to reorganize marketing points according to the cross-relationships of different marketing areas and generate marketing decision plans.

[0163] The present invention also provides a storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided in the various embodiments described above.

[0164] The storage medium may be a computer storage medium or a communication medium. A communication medium includes any medium that facilitates the transfer of a computer program from one location to another. A computer storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, a storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and the storage medium may be located in an application-specific integrated circuit (ASIC). In addition, the ASIC may be located in a user device. Of course, the processor and the storage medium may also exist as discrete components in a communication device. The storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0165] The present invention also provides a program product, which includes execution instructions stored in a storage medium. At least one processor of a device can read the execution instructions from the storage medium, and at least one processor executes the execution instructions so that the device implements the methods provided in the various embodiments described above.

[0166] In the above-mentioned terminal or server embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0167] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. Marketing data insight decision-making method, characterized by: include: Extract the current marketing points to determine the corresponding marketing map. Each marketing point has at least one fixed marketing terminal for marketing interaction. Decomposing the historical first marketing data of each fixed marketing terminal according to a preset dimension to obtain a corresponding marketing tag, and marking the fixed marketing terminal on the marketing map based on the marketing tag to form marketing areas of different dimensions; Decomposing the objectives corresponding to the insight decisions to obtain corresponding marketing dimensions, and determining corresponding multiple marketing zones based on the marketing dimensions; Reorganize marketing points based on the cross-relationships between different marketing areas and generate marketing decision plans.

2. The method according to claim 1, characterized in that The current marketing location is extracted to determine the corresponding marketing map, and each marketing location has at least one fixed marketing terminal for marketing interaction, including: The server interacts with the management terminal to receive the first positioning area selected by the management terminal, and determines all marketing point locations within the first positioning area as current marketing points; Extracting coordinate information of all marketing points to obtain a first coordinate set; The coordinates in the first coordinate set are traversed and extracted in sequence to obtain a marketing map with a fixed marketing terminal setting density.

3. The method according to claim 2, characterized in that The step of sequentially traversing and extracting the coordinates in the first coordinate set to obtain a marketing map with a fixed marketing terminal setting density includes: The horizontal coordinate value and the vertical coordinate value of each coordinate in the first coordinate set are collected and compared respectively to determine the extreme horizontal coordinate and the extreme vertical coordinate, and an initial marketing map is obtained based on the extreme horizontal coordinate and the extreme vertical coordinate; Generate a map segmentation block based on the initial specifications of the marketing map, and segment the initial marketing map based on the map segmentation block to obtain a plurality of map sub-blocks, wherein the map sub-blocks are larger than or equal to the map segmentation block; The number of fixed marketing terminals in each map sub-block is counted to obtain a marketing map with density.

4. The method according to claim 3, characterized in that The initial marketing map is obtained based on the extreme value abscissa and the extreme value ordinate, including: Generate a first extreme value line and a second extreme value line based on the maximum and minimum values ​​of the extreme value abscissa; Generate the third extreme value line and the fourth extreme value line based on the maximum and minimum values ​​of the extreme value ordinates; A first extreme value line, a second extreme value line, a third extreme value line, and a fourth extreme value line are determined, and an initial marketing map is generated in the intersection area within the original map.

5. The method according to claim 3, characterized in that The process of generating map segments based on the initial specifications of the marketing map includes: Get the horizontal and vertical coordinate lengths in the initial specifications of the marketing map; Based on the length of the abscissa and the length of the ordinate, respectively, a preset abscissa interval point position and a preset ordinate interval point position are obtained; Based on the horizontal coordinate interval points and the vertical coordinate interval points, corresponding horizontal line segments and vertical line segments are respectively established on the marketing map, and the map segmentation blocks are obtained based on the minimum units formed by the horizontal line segments and the vertical line segments.

6. The method according to claim 3, characterized in that The step of counting the number of fixed marketing terminals in each map sub-block to obtain a marketing map with density includes: Perform two-dimensional coordinate encoding on each map sub-block to obtain the corresponding sub-block label; If the fixed marketing terminal is located within a map sub-block, a first coefficient is generated and set corresponding to the sub-block label; If the fixed marketing terminal is located on the dividing line between two adjacent map segments, a second coefficient is generated and set corresponding to the sub-block label, and the first coefficient is greater than the second coefficient; A marketing map with density is obtained based on the first coefficient and the second coefficient of the fixed marketing terminal in each map sub-block.

7. The method according to claim 6, characterized in that The method of obtaining a marketing map having density based on the first coefficient and the second coefficient of the fixed marketing terminal in each map sub-block includes: Adding the first coefficient and the second coefficient yields a density coefficient; Sorting the map sub-blocks of all the map sub-blocks to obtain the median density coefficient and using it as the benchmark density coefficient, and adding the first color to the benchmark density coefficient; Based on the relationship between the density coefficients of the remaining map sub-blocks and the density coefficient of the benchmark, the first color is adjusted to obtain a marketing map with a density color.

8. The method according to claim 7, characterized in that The step of adjusting the first color based on the relationship between the density coefficients of the remaining map sub-blocks and the density coefficient of the benchmark to obtain a marketing map having a density color includes: If the density coefficient of any map sub-block is greater than or equal to the density coefficient of the reference, the density coefficient difference is calculated and multiplied by the first preset value to obtain a difference value, and the pixel value of the reference color corresponding to the reference density coefficient is positively adjusted based on the difference value to obtain the second color; If the density coefficient of any map sub-block is smaller than the density coefficient of the benchmark, the density coefficient difference is calculated and multiplied by the second preset value to obtain a difference value, and the pixel value of the benchmark color corresponding to the benchmark density coefficient is reversely adjusted based on the difference value to obtain the second color.

9. The method according to claim 1, characterized in that The step of marking a fixed marketing terminal on a marketing map based on the marketing tag to form marketing areas of different dimensions includes: Counting the marketing tags of fixed marketing terminals in the same map sub-block to obtain a tag set, and counting the number of fixed marketing terminals corresponding to the marketing tags in the tag set to obtain a first number; Based on the marketing tags, the marketing area corresponding to each map sub-block is obtained, and the tag set is set corresponding to the marketing area.

10. The method according to claim 1, characterized in that Decomposing the target corresponding to the insight decision to obtain corresponding marketing dimensions, and determining corresponding multiple marketing areas based on the marketing dimensions, including: Decompose the goals corresponding to the insight decision into the corresponding marketing dimensions, with at least one marketing dimension. A label set of the marketing area corresponding to the marketing dimension of the insight is obtained to obtain the determined multiple marketing areas.

11. The method according to claim 3, characterized in that The reorganization of marketing points based on the cross-relationships between different marketing areas to generate a marketing decision plan includes: Extract the two-dimensional coordinate code of the determined marketing area and the color corresponding to the density; Divide the marketing area into the largest marketing area based on the two-dimensional coordinate code, determine the center point of each largest marketing area, and calculate a first vector between each marketing area and the center point, wherein the first vector includes at least a length value and an angle value; Based on the first vector and the color corresponding to the density, the marketing point reorganization and marketing decision plan are obtained.

12. The method according to claim 11, characterized in that The marketing point reorganization and marketing decision plan based on the first vector and the color corresponding to the density include: If the absolute value of the difference between the first vector of a marketing area and other marketing areas is greater than the preset vector value, the corresponding marketing area is retained; If the absolute value of the difference between the first vector of a marketing area and other marketing areas is less than or equal to the preset vector value, the marketing area with the larger color pixel value is retained; Reorganize the retained marketing areas to obtain marketing decisions corresponding to the goals.

13. The method according to claim 12, characterized in that The reorganization of the retained marketing areas to obtain marketing decisions corresponding to the goals includes: If the number of fixed marketing outlets in the marketing area after the reorganization does not meet the number corresponding to the target; Then, the absolute value of the difference of the first vector of the unreserved marketing area is extracted and sorted in descending order to obtain a supplementary sequence; Select the marketing areas in the replenishment sequence in sequence and stop selecting after the number of fixed marketing terminals meets the number corresponding to the target, and reorganize the marketing areas for the second time; If it is determined that the quantity corresponding to the target cannot be met after all marketing areas in the supplementary sequence are selected, a reminder message is output to the management end.

14. Marketing data insight decision system, characterized by: include: An extraction module is used to extract the current marketing points and determine the corresponding marketing map. Each marketing point has at least one fixed marketing terminal for marketing interaction. a marking module, configured to decompose the historical first marketing data of each fixed marketing terminal according to a preset dimension to obtain a corresponding marketing tag, and mark the fixed marketing terminal on the marketing map based on the marketing tag to form marketing areas of different dimensions; A determination module is configured to decompose the target corresponding to the insight decision to obtain corresponding marketing dimensions, and determine corresponding multiple marketing areas based on the marketing dimensions; The reorganization module is used to reorganize marketing points according to the cross-relationships of different marketing areas and generate marketing decision plans.

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