Marketing activity promotion method and system based on data analysis

Abstract

The invention relates to a marketing activity promotion method and system based on data analysis, and relates to the field of product marketing technology, and the method comprises the steps: obtaining marketing promotion funds and feasible putting points; according to the price matching relationship, determining a feasible putting price corresponding to the feasible putting point; randomly selecting any number of feasible putting points from the feasible putting points for combination to generate a putting set, determining a set putting price according to the putting set, and defining the putting set of which the set putting price is not greater than the marketing promotion fund as an effective set; determining a delivery effect value corresponding to the feasible delivery point according to a preset effect matching relationship; performing calculation on the delivery effect values corresponding to the feasible delivery points in each effective set to determine an overall marketing effect value; and determining an overall marketing effect value with the maximum value according to a sorting rule, and determining an actual putting point according to the effective set corresponding to the overall marketing effect value. The marketing activity promotion method and device have the effect of facilitating marketing activity promotion.

Description

Technical Field

[0001] The present application relates to the field of product marketing technology, and in particular to a marketing activity promotion method and system based on data analysis. Background Art

[0002] Marketing promotion refers to a series of plans and activities taken by a company or individual to increase the awareness of products, services or brands, attract potential customers and increase sales. These activities can include advertising, public relations, sales promotions, social media marketing, content marketing, event marketing and other forms, aiming to establish and maintain contact with the target market through effective communication strategies.

[0003] In the related art, offline advertising marketing is a method of promoting marketing activities. Generally, the advertising points are determined by analyzing the flow of people at various locations where advertising can be placed, so that marketing activities can be effectively promoted.

[0004] In the above-mentioned related technologies, when conducting advertising promotion, there will generally be marketing activity funds, and how to achieve effective promotion of advertising without exceeding the activity funds is the top priority of advertising marketing. The commonly used method is to determine the promotion plan by having staff conduct mental analysis based on market data. This method is not only more dependent on manpower, but also has no more objective data to reflect the pros and cons of the plan, which is not convenient for promoting marketing activities and there is still room for improvement. Summary of the invention

[0005] In order to facilitate the promotion of marketing activities, the present application provides a marketing activity promotion method and system based on data analysis.

[0006] In the first aspect, the present application provides a marketing activity promotion method based on data analysis, which adopts the following technical solution: A marketing activity promotion method based on data analysis, comprising: Obtain marketing promotion funds and feasible placement points; Determine the feasible delivery price corresponding to the feasible delivery point according to the preset price matching relationship; Randomly select any number of feasible delivery points from the feasible delivery points and combine them to generate a delivery set, and sum up the feasible delivery prices of each feasible delivery point in the delivery set to determine the set delivery price, and define the delivery set whose set delivery price is not greater than the marketing promotion funds as a valid set; Determine the delivery effect value corresponding to the feasible delivery point based on the preset effect matching relationship; Calculate the delivery effect values ​​corresponding to the feasible delivery points in each effective set to determine the overall marketing effect value; The overall marketing effect value with the largest value is determined according to the preset sorting rules, and the actual delivery point is determined according to the valid set corresponding to the overall marketing effect value.

[0007] Optionally, the method further includes a step of determining an effect matching relationship, the step comprising: Get the type of advertisement being served; Determine the potential user characteristics corresponding to the type of advertisement to be delivered based on the preset feature matching relationship; A detection interval with a width of a preset detection duration is established on a preset time axis with the current time point as the rear end point, and a position area image of each feasible delivery point is obtained in real time within the detection interval; Performing feature analysis based on each location area image to define a user including any potential user feature as a potential user, and counting all potential users to determine a potential quantity; Calculations are performed based on the potential quantity and preset quantity calculation parameters to determine the delivery effect value corresponding to the feasible delivery point, and an effect matching relationship is established based on the feasible delivery point and the delivery effect value.

[0008] Optionally, after the potential users are determined, the step of determining the effect matching relationship further includes: Counting the potential user features corresponding to a single potential user to determine the number of matching features; Calculation is performed based on the number of matching features and preset quality calculation parameters to determine the quality impact value; The impact effect value is determined by summing up all the quality impact values, and the impact effect value is calculated with the delivery effect value to update the delivery effect value.

[0009] Optionally, after the effective set is determined, the marketing activity promotion method based on data analysis also includes: Determine the distance between any two feasible placement points in the effective set; Determine whether there is a situation where the distance between points is less than the preset propagation influence distance; If there is no situation where the distance between points is less than the preset propagation influence distance, the determined valid set is maintained; If there is a situation where the distance between points is less than the preset propagation influence distance, the determined valid set will be eliminated.

[0010] Optionally, after the overall marketing effect value is determined, the marketing activity promotion method based on data analysis also includes: Determine whether there are at least two effective sets with the same and maximum overall marketing effect values; If there are not at least two valid sets with the same and largest overall marketing effect value, the actual delivery point is determined according to the valid set with the largest overall marketing effect value; If there are at least two valid sets with the same overall marketing effect value and the largest value, then the valid set with the largest overall marketing effect value is defined as the feasible set; The set delivery price with the smallest value is determined according to the sorting rules among all feasible sets, and the actual delivery point is determined according to the feasible set corresponding to the set delivery price.

[0011] Optionally, after the overall marketing effect value is determined, the marketing activity promotion method based on data analysis also includes: Determine whether there are at least two feasible sets with the same and minimum set delivery prices; If there are no at least two feasible sets with the same and smallest set delivery prices, the actual delivery point is determined according to the feasible set with the smallest set delivery price; If there are at least two feasible sets with the same and smallest set delivery prices, the feasible set with the smallest set delivery price is defined as the candidate set, and the feasible delivery points in the candidate set are defined as the candidate delivery points; The influence area is delineated with the alternative delivery point as the center and the preset influence distance as the radius, and the alternative delivery points in each influence area are counted to determine the number inside the area; A regional internal quantity is randomly selected from all regional internal quantities as the standard internal quantity, and the remaining regional internal quantities are defined as comparative internal quantities; Calculate the quantity deviation value according to the standard internal quantity and all the comparison internal quantities, and determine the quantity deviation value with the smallest value according to the sorting rule, and define the quantity deviation value as the representative deviation value; The representative deviation value with the smallest value is determined according to the sorting rule, and the actual delivery point is determined according to the candidate set corresponding to the representative deviation value.

[0012] Optionally, after the representative deviation value is determined, the marketing activity promotion method based on data analysis also includes: Determine whether there are at least two candidate sets with the same and smallest representative deviation values; If there are not at least two candidate sets with the same and smallest representative deviation values, the actual delivery point is determined according to the candidate set with the smallest representative deviation value; If there are at least two candidate sets with the same and smallest representative deviation values, the candidate set with the smallest representative deviation value is defined as the candidate set, and the influence coverage range is determined according to the influence area of ​​the candidate delivery points in the candidate set, and the coverage area is determined according to the influence coverage range; The coverage area with the largest value is determined according to the sorting rules, and the candidate delivery point is determined according to the candidate set corresponding to the coverage area.

[0013] In the second aspect, the present application provides a marketing activity promotion system based on data analysis, which adopts the following technical solutions: A marketing activity promotion system based on data analysis, comprising: Acquisition module, used to obtain marketing promotion funds and feasible placement points; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module determines the feasible delivery price corresponding to the feasible delivery point according to the preset price matching relationship; The processing module randomly selects any number of feasible delivery points from the feasible delivery points to combine them to generate a delivery set, and performs sum calculation based on the feasible delivery prices of each feasible delivery point in the delivery set to determine the set delivery price, and the processing module defines the delivery set whose set delivery price determined by the judgment module is not greater than the marketing promotion funds as a valid set; The processing module determines the delivery effect value corresponding to the feasible delivery point according to the preset effect matching relationship; The processing module calculates the delivery effect values ​​corresponding to the feasible delivery points in each effective set to determine the overall marketing effect value; The processing module determines the overall marketing effect value with the largest value according to a preset sorting rule, and determines the actual delivery point according to the valid set corresponding to the overall marketing effect value.

[0014] In summary, the present application includes at least one of the following beneficial technical effects: When conducting advertising marketing, the situation of each delivery point can be analyzed to automatically generate a suitable promotion plan, thereby facilitating the promotion of marketing activities; Potential users can be identified by analyzing the flow of people at each delivery point, so that the specific delivery effect of each delivery point can be known and the delivery effect can be quantified; When selecting a promotion plan, you can comprehensively consider the scope of impact of the promotion in order to determine the only most appropriate promotion plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flowchart of the marketing campaign promotion method based on data analysis.

[0016] Figure 2 It is a module flow chart of the marketing activity promotion method based on data analysis. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 2 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0018] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0019] The present application embodiment discloses a marketing activity promotion method based on data analysis, referring to Figure 1 The method flow of the marketing activity promotion method based on data analysis includes the following steps: Step S100: Obtain marketing promotion funds and feasible delivery points.

[0020] Marketing promotion funds are the funds preset for the organization's current marketing campaign promotion, that is, the funds available for marketing promotion; feasible placement points are locations where advertisements can be placed, which can be input by staff.

[0021] Step S101: Determine a feasible delivery price corresponding to a feasible delivery point according to a preset price matching relationship.

[0022] The feasible placement price is the price required for advertising placement at a feasible placement point. The price matching relationship between the two is determined and entered in advance by the staff.

[0023] Step S102: Randomly select any number of feasible delivery points from the feasible delivery points and combine them to generate a delivery set, and sum up the feasible delivery prices of each feasible delivery point in the delivery set to determine the set delivery price, and define the delivery set whose set delivery price is not greater than the marketing promotion funds as a valid set.

[0024] A delivery set is a set of feasible delivery points obtained by combining any number of feasible delivery points. For example, if there are two delivery points A and B, three delivery sets can be generated, namely A, B and AB. The set delivery price is the price required for advertising based on the feasible delivery points in the delivery set, which is determined by adding the feasible delivery prices corresponding to the feasible delivery points in the delivery set. When the set delivery price is not greater than the marketing promotion funds, it means that the promotion plan is feasible in terms of funds. At this time, it is determined as a valid set to distinguish between different delivery sets, which is convenient for subsequent analysis.

[0025] Step S103: Determine the delivery effect value corresponding to the feasible delivery point according to the preset effect matching relationship.

[0026] The delivery effect value is the advertising effect that will be produced after the current advertisement is delivered to the feasible delivery point. Different feasible delivery points have different numbers of people and qualities of people flow, so the delivery effect values ​​that can be produced are also different. The effect matching relationship between the two can be processed by the staff in advance through observation and entry, or it can be determined according to the method of steps S200-S204.

[0027] Step S104: Calculate the delivery effect values ​​corresponding to the feasible delivery points in each effective set to determine the overall marketing effect value.

[0028] The overall marketing effect value refers to the impact effect value that can be achieved when advertising is delivered according to the feasible delivery points in the effective set, and is obtained by adding the delivery effect values ​​corresponding to each feasible delivery point in the effective set.

[0029] Step S105: Determine the overall marketing effect value with the largest value according to a preset sorting rule, and determine the actual delivery point according to the valid set corresponding to the overall marketing effect value.

[0030] The sorting rule is a method set by the staff to sort the size of values, such as the bubble method. The sorting rule can be used to determine the overall marketing effect value with the largest value. That is, at this time, the advertising marketing effect is the best under the effective set corresponding to the overall marketing effect value. At this time, the feasible delivery points in the corresponding effective set are determined as the actual delivery points for advertising marketing promotion.

[0031] The step of determining the effect matching relationship is also included, and the step includes: Step S200: Obtain the type of advertisement to be delivered.

[0032] The type of advertisement placed is the type of advertisement currently required for marketing promotion, such as game type, cosmetic type, clothing type, etc., which is manually input by the staff.

[0033] Step S201: determining potential user features corresponding to the type of advertisement delivered according to a preset feature matching relationship.

[0034] Potential user characteristics are the characteristics of users who may consume the products corresponding to the advertisements. Taking cosmetics as an example, the potential user characteristics may include female gender, age 18-45 years old, etc. Different types of advertisements have different potential user characteristics. The feature matching relationship between the two is determined and entered in advance by the staff.

[0035] Step S202: establishing a detection interval with a width of a preset detection duration on a preset time axis with the current time point as the rear end point, and acquiring a position area image of each feasible delivery point in real time within the detection interval.

[0036] The time axis is a coordinate axis formed by the combination of various time points, which points from the time points that have passed to the time points that have not yet arrived. The detection duration is a fixed duration set by the staff, such as 1 day. A detection interval is established to facilitate the acquisition and analysis of data within the detection duration; the location area image is an image obtained at a feasible delivery point, which can be obtained by an image shooting device installed at the feasible delivery point; at the same time, if it is too costly to set up a shooting device at each feasible delivery point, the staff can carry a shooting device to each feasible delivery point to take pictures and record.

[0037] Step S203: Perform feature analysis based on each location area image to define a user including any potential user feature as a potential user, and count all potential users to determine the potential number.

[0038] The location area image is an image that includes images of people in the passing crowd. The location of the person image in the image can be determined through feature analysis, and then the person image can be analyzed to find out whether the person has potential user characteristics. For example, the age can be estimated by scanning the face of the person image, and the gender can be known by combining the clothing. The corresponding feature analysis method can establish a recognition database in advance through deep learning, and then input the image into the recognition database for analysis and processing; when any potential user feature is included, it means that the user has the possibility of purchasing the currently marketed product, and at this time it is defined as a potential user to distinguish different users; the potential number is the number of potential users determined within the detection time. When a person is in different location area images and is identified, it is counted as only one potential user.

[0039] Step S204: Calculate the delivery effect value corresponding to the feasible delivery point according to the potential quantity and the preset quantity calculation parameters, and build an effect matching relationship according to the feasible delivery point and the delivery effect value.

[0040] The quantity calculation parameters are fixed parameters set by the staff for calculating the potential quantity. By multiplying the potential quantity by the quantity calculation parameters, the delivery effect value that reflects the effect of advertising delivery can be obtained, thereby achieving the pairing between feasible delivery points and delivery effect values ​​to successfully build an effect matching relationship.

[0041] After the potential users are identified, the steps to determine the effect matching relationship also include: Step S300: Counting the potential user features corresponding to a single potential user to determine the number of matching features.

[0042] The number of matching features is the number of potential user features matched by a single potential user. For example, a single potential user may match both the potential user feature of age and the potential user feature of gender.

[0043] Step S301: Calculate the quality impact value according to the number of matching features and preset quality calculation parameters.

[0044] The quality calculation parameters are fixed parameters set by the staff to calculate the quality of potential users. The quality impact value is a numerical value that reflects the impact of user quality on the delivery effect value, and is determined by multiplying the number of matching features by the quality calculation parameters.

[0045] Step S302: performing a sum calculation based on all quality impact values ​​to determine an impact effect value, and calculating the impact effect value and the delivery effect value to update the delivery effect value.

[0046] The impact effect value is the total value that reflects the impact of the current user quality on the delivery effect. The larger the number of matching features, the more potential user features a single potential user matches, that is, the greater the possibility that the potential user will make a purchase. Therefore, the delivery effect value is updated by adding the impact effect value to the delivery effect value to make the determined delivery effect value more accurate.

[0047] After the effective set is determined, the marketing promotion methods based on data analysis also include: Step S400: Determine the distance between any two feasible delivery points in the effective set.

[0048] The distance between points is the straight-line distance between two feasible placement points.

[0049] Step S401: Determine whether there is a situation where the distance between points is less than a preset propagation influence distance.

[0050] The communication impact distance is the minimum distance that the advertisement can be propagated outward in theory after being placed in a single location. The purpose of the judgment is to find out whether the advertising placement effect overlaps due to the close distance.

[0051] Step S4011: If there is no situation where the distance between points is less than the preset propagation influence distance, the determined valid set is maintained.

[0052] When there is no situation where the distance between points is less than the preset propagation influence distance, it means that there will be no large-scale overlap of advertising effects. At this time, the determined effective set can be maintained to continue the analysis.

[0053] Step S4012: If there is a situation where the distance between points is less than the preset propagation influence distance, the determined valid set is eliminated.

[0054] When there are points whose distance is less than the preset propagation influence distance, it means that there is a large overlap in the delivery effects of at least two feasible delivery points, resulting in poor overall advertising delivery effect. At this time, the corresponding effective set will be eliminated to reduce useless analysis.

[0055] After the overall marketing effect value is determined, the marketing activity promotion methods based on data analysis also include: Step S500: Determine whether there are at least two valid sets with the same and maximum overall marketing effect values.

[0056] The purpose of the judgment is to find out whether there are multiple valid sets that meet the requirements, so as to determine the actual delivery point.

[0057] Step S5001: If there are not at least two valid sets with the same and largest overall marketing effect value, then the actual delivery point is determined according to the valid set with the largest overall marketing effect value.

[0058] When there are not at least two valid sets with the same and largest overall marketing effect values, it means that only a unique valid set that meets the requirements can be used to determine the actual delivery point. At this time, the actual delivery point can be determined normally based on the valid set.

[0059] Step S5002: If there are at least two valid sets with the same overall marketing effect value and the largest value, the valid set with the largest overall marketing effect value is defined as a feasible set.

[0060] When there are at least two valid sets with the same and largest overall marketing effect value, it means that there are multiple valid sets that meet the requirements. At this time, they are defined as feasible sets to distinguish different valid sets and facilitate subsequent analysis.

[0061] Step S501: Determine the set delivery price with the smallest value among all feasible sets according to the sorting rules, and determine the actual delivery point according to the feasible set corresponding to the set delivery price.

[0062] The sorting rules can be used to determine the set delivery price with the smallest value among all feasible sets, that is, the feasible set that can achieve the same delivery effect while requiring the lowest marketing funds. At this time, the actual delivery point can be determined based on the feasible set.

[0063] After the overall marketing effect value is determined, the marketing activity promotion methods based on data analysis also include: Step S600: Determine whether there are at least two feasible sets with the same and minimum set delivery prices.

[0064] The purpose of the judgment is to find out whether there are multiple feasible sets that meet the set release price requirements.

[0065] Step S6001: If there are not at least two feasible sets with the same and minimum set delivery prices, the actual delivery point is determined according to the feasible set with the minimum set delivery price.

[0066] When there are not at least two feasible sets with the same and smallest set delivery prices, it means that there is only one feasible set that meets the requirements. In this case, the actual delivery point can be determined normally.

[0067] Step S6002: If there are at least two feasible sets with the same and smallest set delivery prices, the feasible set with the smallest set delivery price is defined as the candidate set, and the feasible delivery points in the candidate set are defined as the candidate delivery points.

[0068] When there are at least two feasible sets with the same and smallest set delivery prices, it means that there are multiple feasible sets that meet the requirements. At this time, they are defined as alternative sets to distinguish different feasible sets for subsequent analysis. At the same time, alternative delivery points are defined to facilitate subsequent analysis.

[0069] Step S601: defining an influence area with the candidate delivery point as the center and the preset influence distance as the radius, and counting the candidate delivery points in each influence area to determine the number inside the area.

[0070] The influence distance is the maximum distance at which an advertisement can be transmitted in theory. The influence area is defined to facilitate observation of the specific effect of each alternative delivery point. The number within the area is the number of alternative delivery points within a single influence area.

[0071] Step S602: randomly selecting a region internal quantity from all region internal quantities as a standard internal quantity, and defining the remaining region internal quantities as comparison internal quantities.

[0072] Define standard internal quantities and comparative internal quantities to distinguish internal quantities in different regions for subsequent analysis.

[0073] Step S603: Calculate the quantity deviation value according to the standard internal quantity and all the comparison internal quantities, and determine the quantity deviation value with the smallest value according to the sorting rule, and define the quantity deviation value as the representative deviation value.

[0074] The quantity deviation value is a value that reflects the deviation between the selected standard internal quantity and the other comparative internal quantities. The quantity deviation value also reflects whether the standard internal quantity can represent the other comparative internal quantities. The smaller the standard internal quantity is, the smaller the deviation between the standard internal quantity and the other comparative internal quantities is, and the more the standard internal quantity can represent the other comparative internal quantities. The calculation formula of the quantity deviation value is: , Where is the quantity deviation value, is the standard internal quantity, For the A comparative internal quantity, To compare the number of internal quantities; the minimum quantity deviation value can be determined through the sorting rules, that is, the corresponding quantity deviation value at this time is the best quantity deviation value that can be achieved by the alternative set. At this time, it is defined as a representative deviation value to distinguish different quantity deviation values, which is convenient for subsequent analysis.

[0075] Step S604: Determine the representative deviation value with the smallest value according to the sorting rule, and determine the actual delivery point according to the candidate set corresponding to the representative deviation value.

[0076] The representative deviation value with the smallest value can be determined through the sorting rules. That is, at this time, the distribution of the alternative delivery points in the corresponding alternative set is relatively uniform, and there will not be a situation where the delivery points in one place are too concentrated and the delivery points in another place are too sparse, so that each delivery point can achieve a better advertising and marketing effect. At this time, the actual delivery point can be determined based on the alternative set.

[0077] After the representative deviation value is determined, the marketing activity promotion method based on data analysis also includes: Step S700: Determine whether there are at least two candidate sets with the same and smallest representative deviation values.

[0078] The purpose of the judgment is to find out whether there are multiple candidate sets that meet the representative deviation value requirements, so as to facilitate the subsequent determination of the actual delivery point.

[0079] Step S7001: If there are not at least two candidate sets with the same and smallest representative deviation values, the actual delivery point is determined according to the candidate set with the smallest representative deviation value.

[0080] When there are not at least two candidate sets with the same and smallest representative deviation values, it means that there is only one candidate set that meets the representative deviation value. In this case, the actual delivery point can be determined based on the candidate set.

[0081] Step S7002: If there are at least two alternative sets with the same and smallest representative deviation values, the alternative set with the smallest representative deviation value is defined as the candidate set, and the impact coverage range is determined based on the impact area of ​​the alternative delivery points in the candidate set, and the coverage area is determined based on the impact coverage range.

[0082] When there are at least two alternative sets with the same and smallest representative deviation values, it means that there are multiple alternative sets that meet the requirements. At this time, they are determined as candidate sets to distinguish different alternative sets, which is convenient for subsequent analysis; the impact coverage range is the range covered by all impact areas corresponding to each alternative delivery point in the candidate set, and the coverage area is the area value of the impact coverage range.

[0083] Step S701: Determine the coverage area with the largest value according to the sorting rule, and determine the candidate delivery point according to the candidate set corresponding to the coverage area.

[0084] The sorting rules can be used to determine the coverage area with the largest value, that is, the area of ​​coverage overlap in the current situation is the smallest, which means that the marketing communication effect is the best. At this time, the alternative delivery points can be determined based on the candidate set.

[0085] Reference Figure 2 Based on the same inventive concept, an embodiment of the present invention provides a marketing activity promotion system based on data analysis, including: Acquisition module, used to obtain marketing promotion funds and feasible placement points; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module determines the feasible delivery price corresponding to the feasible delivery point according to the preset price matching relationship; The processing module randomly selects any number of feasible delivery points from the feasible delivery points to combine them to generate a delivery set, and performs sum calculation based on the feasible delivery prices of each feasible delivery point in the delivery set to determine the set delivery price, and the processing module defines the delivery set whose set delivery price determined by the judgment module is not greater than the marketing promotion funds as a valid set; The processing module determines the delivery effect value corresponding to the feasible delivery point according to the preset effect matching relationship; The processing module calculates the delivery effect values ​​corresponding to the feasible delivery points in each effective set to determine the overall marketing effect value; The processing module determines the overall marketing effect value with the largest value according to the preset sorting rules, and determines the actual delivery point according to the valid set corresponding to the overall marketing effect value; An effect matching relationship determination module is used to construct and determine the effect matching relationship; The delivery effect value update module updates the delivery effect value according to the quality of each potential user; The effective set analysis module is used to analyze and eliminate some effective sets that do not meet the requirements; The effective set screening module is used to screen the effective sets that meet the requirements; A feasible set screening module is used to screen the feasible sets that meet the requirements; The candidate set screening module is used to screen the candidate sets that meet the requirements.

[0086] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

Claims

1. A marketing activity promotion method based on data analysis, characterized in that: include: Obtain marketing promotion funds and feasible placement points; Determine the feasible delivery price corresponding to the feasible delivery point according to the preset price matching relationship; Randomly select any number of feasible delivery points from the feasible delivery points and combine them to generate a delivery set, and sum up the feasible delivery prices of each feasible delivery point in the delivery set to determine the set delivery price, and define the delivery set whose set delivery price is not greater than the marketing promotion funds as a valid set; Determine the delivery effect value corresponding to the feasible delivery point based on the preset effect matching relationship; Calculate the delivery effect values ​​corresponding to the feasible delivery points in each effective set to determine the overall marketing effect value; The overall marketing effect value with the largest value is determined according to the preset sorting rules, and the actual delivery point is determined according to the valid set corresponding to the overall marketing effect value.

2. The marketing activity promotion method based on data analysis according to claim 1 is characterized in that: The step of determining the effect matching relationship is also included, and the step includes: Get the type of advertisement being served; Determine the potential user characteristics corresponding to the type of advertisement to be delivered based on the preset feature matching relationship; A detection interval with a width of a preset detection duration is established on a preset time axis with the current time point as the rear end point, and a position area image of each feasible delivery point is obtained in real time within the detection interval; Performing feature analysis based on each location area image to define a user including any potential user feature as a potential user, and counting all potential users to determine a potential quantity; Calculations are performed based on the potential quantity and preset quantity calculation parameters to determine the delivery effect value corresponding to the feasible delivery point, and an effect matching relationship is established based on the feasible delivery point and the delivery effect value.

3. The marketing activity promotion method based on data analysis according to claim 2 is characterized in that: After the potential users are identified, the steps to determine the effect matching relationship also include: Counting the potential user features corresponding to a single potential user to determine the number of matching features; Calculation is performed based on the number of matching features and preset quality calculation parameters to determine the quality impact value; The impact effect value is determined by summing up all the quality impact values, and the impact effect value is calculated with the delivery effect value to update the delivery effect value.

4. The marketing activity promotion method based on data analysis according to claim 1 is characterized in that: After the effective set is determined, the marketing promotion methods based on data analysis also include: Determine the distance between any two feasible placement points in the effective set; Determine whether there is a situation where the distance between points is less than the preset propagation influence distance; If there is no situation where the distance between points is less than the preset propagation influence distance, the determined valid set is maintained; If there is a situation where the distance between points is less than the preset propagation influence distance, the determined valid set will be eliminated.

5. The marketing activity promotion method based on data analysis according to claim 1 is characterized in that: At After the overall marketing effect value is determined, the marketing activity promotion methods based on data analysis also include: Determine whether there are at least two effective sets with the same and maximum overall marketing effect values; If there are not at least two valid sets with the same and largest overall marketing effect value, the actual delivery point is determined according to the valid set with the largest overall marketing effect value; If there are at least two valid sets with the same overall marketing effect value and the largest value, then the valid set with the largest overall marketing effect value is defined as the feasible set; The set delivery price with the smallest value is determined according to the sorting rules among all feasible sets, and the actual delivery point is determined according to the feasible set corresponding to the set delivery price.

6. The marketing activity promotion method based on data analysis according to claim 5 is characterized in that: At After the overall marketing effect value is determined, the marketing activity promotion methods based on data analysis also include: Determine whether there are at least two feasible sets with the same and minimum set delivery prices; If there are no at least two feasible sets with the same and smallest set delivery prices, the actual delivery point is determined according to the feasible set with the smallest set delivery price; If there are at least two feasible sets with the same and smallest set delivery prices, the feasible set with the smallest set delivery price is defined as the candidate set, and the feasible delivery points in the candidate set are defined as the candidate delivery points; The influence area is delineated with the alternative delivery point as the center and the preset influence distance as the radius, and the alternative delivery points in each influence area are counted to determine the number inside the area; A regional internal quantity is randomly selected from all regional internal quantities as the standard internal quantity, and the remaining regional internal quantities are defined as comparative internal quantities; Calculate the quantity deviation value according to the standard internal quantity and all the comparison internal quantities, and determine the quantity deviation value with the smallest value according to the sorting rule, and define the quantity deviation value as the representative deviation value; The representative deviation value with the smallest value is determined according to the sorting rule, and the actual delivery point is determined according to the candidate set corresponding to the representative deviation value.

7. The marketing activity promotion method based on data analysis according to claim 6 is characterized in that: After the representative deviation value is determined, the marketing activity promotion method based on data analysis also includes: Determine whether there are at least two candidate sets with the same and smallest representative deviation values; If there are not at least two candidate sets with the same and smallest representative deviation values, the actual delivery point is determined according to the candidate set with the smallest representative deviation value; If there are at least two candidate sets with the same and smallest representative deviation values, the candidate set with the smallest representative deviation value is defined as the candidate set, and the influence coverage range is determined according to the influence area of ​​the candidate delivery points in the candidate set, and the coverage area is determined according to the influence coverage range; The coverage area with the largest value is determined according to the sorting rules, and the candidate delivery point is determined according to the candidate set corresponding to the coverage area.

8. A marketing activity promotion system based on data analysis, characterized in that: include: Acquisition module, used to obtain marketing promotion funds and feasible placement points; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module determines the feasible delivery price corresponding to the feasible delivery point according to the preset price matching relationship; The processing module randomly selects any number of feasible delivery points from the feasible delivery points to combine them to generate a delivery set, and performs sum calculation based on the feasible delivery prices of each feasible delivery point in the delivery set to determine the set delivery price, and the processing module defines the delivery set whose set delivery price determined by the judgment module is not greater than the marketing promotion funds as a valid set; The processing module determines the delivery effect value corresponding to the feasible delivery point according to the preset effect matching relationship; The processing module calculates the delivery effect values ​​corresponding to the feasible delivery points in each effective set to determine the overall marketing effect value; The processing module determines the overall marketing effect value with the largest value according to a preset sorting rule, and determines the actual delivery point according to the valid set corresponding to the overall marketing effect value.

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