CN117350791A - Marketing campaign template customization method and system based on personalized popularization - Google Patents

Marketing campaign template customization method and system based on personalized popularization Download PDF

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CN117350791A
CN117350791A CN202311639367.3A CN202311639367A CN117350791A CN 117350791 A CN117350791 A CN 117350791A CN 202311639367 A CN202311639367 A CN 202311639367A CN 117350791 A CN117350791 A CN 117350791A
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marketing
popularization
sales
personalized
information
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CN117350791B (en
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许娜
李莹
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Beijing 616 Information Technology Co ltd
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    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract

The invention is suitable for the technical field of product marketing, and provides a marketing campaign template customization method and a marketing campaign template customization system based on personalized popularization, wherein the method comprises the following steps: receiving marketing product information input by a user, wherein the marketing product information comprises marketing products, personalized elements and historical sales information; determining product attributes, popularization sales channels and popularization crowds based on the big data and the marketing product information; inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library for matching, wherein the marketing strategy library comprises a plurality of marketing strategies, and each marketing strategy corresponds to the marketing attributes; outputting marketing strategies with the matching degree arranged in the front N, wherein each marketing strategy comprises a personalized expansion scheme, determining the matched personalized expansion scheme based on the personalized elements, and screening to obtain a final marketing strategy; the marketing campaign strategy fully considers the display of the individual elements of the product, and has better effect.

Description

Marketing campaign template customization method and system based on personalized popularization
Technical Field
The invention relates to the technical field of product marketing, in particular to a marketing campaign template customization method and system based on personalized popularization.
Background
The marketing of the activities is a popular means of public switch spreading and marketing in recent years, integrates news effect, advertisement effect, public relations, image spreading and customer relation, creates opportunities for new product promotion and brand display, establishes brand identification and brand positioning, forms a marketing means for rapidly improving brand awareness and reputation, is a special activity for consumer interaction participation in construction, and can further improve the reputation of consumers to brands. Currently, many companies are actively attempting to construct a marketing intelligent platform, and intelligent management and optimization of marketing activities are realized by integrating various data, analysis tools and algorithms. However, the marketing campaign templates given based on the intelligent marketing platform lack personalized service content and cannot well display the personalized elements of the products. Therefore, there is a need to provide a marketing campaign template customization method and system based on personalized popularization, which aims to solve the above problems.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a marketing campaign template customizing method and system based on personalized popularization so as to solve the problems existing in the background art.
The invention is realized in such a way that a marketing campaign template customizing method based on personalized popularization comprises the following steps:
receiving marketing product information input by a user, wherein the marketing product information comprises marketing products, personalized elements and historical sales information, and the historical sales information comprises sales channels, sales data and purchasing groups;
determining product attributes, popularization sales channels and popularization crowds based on the big data and the marketing product information;
inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library for matching, wherein the marketing strategy library comprises a plurality of marketing strategies, each marketing strategy corresponds to a marketing attribute, and the marketing attribute comprises product attribute information, channel information, crowd information and evaluation information;
outputting marketing strategies with the matching degree arranged in the front N, wherein each marketing strategy comprises a personalized expansion scheme, determining the matched personalized expansion scheme based on the personalized elements, and screening to obtain a final marketing strategy;
the step of determining the matched personalized expansion scheme based on the personalized elements specifically comprises the following steps: determining the element type of the personalized element, wherein the element type is a plane element, a stereoscopic element or an abstract display element; judging whether the personalized expansion scheme in the marketing strategy accords with the determined element type, wherein the personalized expansion scheme is marked with the proper element type.
As a further scheme of the invention: the step of determining the product attribute, the popularization sales channel and the popularization crowd based on the big data and the marketing product information specifically comprises the following steps:
inputting the marketing products into a product type attribute library to obtain product attributes;
determining a main sales channel and a main purchasing group according to the historical sales information;
determining recommended sales channels and recommended purchasing groups of the same type of products according to the product attributes;
and determining popularization sales channels and popularization groups according to the main sales channels, the main purchasing groups, the recommended sales channels and the recommended purchasing groups.
As a further scheme of the invention: the step of determining the popularization sales channel and the popularization crowd according to the main sales channel, the main purchasing crowd, the recommendation sales channel and the recommendation purchasing crowd specifically comprises the following steps:
determining a first proportion value of each sales channel in the main sales channels and a second proportion value of each group of people in the main purchasing group according to the sales data;
calling a third proportion value of each sales channel in the recommended sales channels and a fourth proportion value of each group of people in the recommended purchasing group;
calculating a final proportion value=m1×first proportion value+m2×third proportion value of each sales channel, and calculating a final proportion value=m1×second proportion value+m2×fourth proportion value of each group of people, wherein M1 and M2 are constant coefficients;
and determining popularization sales channels and popularization crowds according to the final proportion value of each sales channel and the final proportion value of each group of crowds.
As a further scheme of the invention: the step of inputting the product attribute, the popularization sales channel and the popularization crowd into the marketing strategy library for matching specifically comprises the following steps:
inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library, and screening all marketing strategies in the marketing strategy library based on the product attributes;
and calculating the matching degree between each screened marketing strategy and the input information, wherein the matching degree=K1×the overlapping degree of the channel information and the popularization sales channel+K2×the overlapping degree of the crowd information and the popularization crowd+K3×the evaluation information, and the K1, the K2 and the K3 are constant coefficients.
As a further scheme of the invention: the method further comprises the steps of: and receiving feedback information of the user, wherein the feedback information comprises a final marketing strategy and a strategy score, and updating corresponding evaluation information according to the strategy score.
Another object of the present invention is to provide a marketing campaign template customization system based on personalized popularization, the system comprising:
the marketing product information module is used for receiving marketing product information input by a user, wherein the marketing product information comprises marketing products, personalized elements and historical sales information, and the historical sales information comprises sales channels, sales data and purchasing groups;
the channel crowd determining module is used for determining product attributes, popularization sales channels and popularization crowds based on the big data and the marketing product information;
the marketing strategy matching module is used for inputting the product attributes, the popularization sales channels and the popularization crowds into the marketing strategy library for matching, the marketing strategy library comprises a plurality of marketing strategies, each marketing strategy corresponds to a marketing attribute, and the marketing attribute comprises product attribute information, channel information, crowd information and evaluation information;
the personalized expansion module is used for outputting marketing strategies with the matching degree arranged in front N, each marketing strategy comprises a personalized expansion scheme, the matched personalized expansion scheme is determined based on the personalized elements, and the final marketing strategy is obtained through screening;
the step of determining the matched personalized expansion scheme based on the personalized elements specifically comprises the following steps: determining the element type of the personalized element, wherein the element type is a plane element, a stereoscopic element or an abstract display element; judging whether the personalized expansion scheme in the marketing strategy accords with the determined element type, wherein the personalized expansion scheme is marked with the proper element type.
As a further scheme of the invention: the channel crowd determination module includes:
the product attribute determining unit is used for inputting the marketing products into the product type attribute library to obtain product attributes;
a main channel crowd unit for determining main sales channels and main purchasing crowd according to the history sales information;
the recommendation channel crowd unit is used for determining recommendation sales channels and recommendation purchasing crowds of the same type of products according to the product attributes;
and the promotion channel crowd unit is used for determining promotion sales channels and promotion crowds according to the main sales channels, the main purchasing crowds, the recommended sales channels and the recommended purchasing crowds.
As a further scheme of the invention: the popularization channel crowd unit comprises:
a proportion value calculating subunit, configured to determine a first proportion value of each of the main sales channels and a second proportion value of each of the main purchasing groups according to the sales data;
the proportion value calling subunit is used for calling a third proportion value of each sales channel in the recommended sales channels and a fourth proportion value of each group of people in the recommended purchasing group;
a final scale value subunit, configured to calculate a final scale value=m1×first scale value+m2×third scale value for each sales channel, and calculate a final scale value=m1×second scale value+m2×fourth scale value for each group of people, where M1 and M2 are constant coefficients;
and the channel crowd determining subunit is used for determining popularization sales channels and popularization crowds according to the final proportion value of each sales channel and the final proportion value of each group of crowds.
As a further scheme of the invention: the marketing strategy matching module comprises:
the marketing strategy screening unit is used for inputting the product attributes, the popularization sales channels and the popularization crowds into the marketing strategy library, and screening all marketing strategies in the marketing strategy library based on the product attributes;
and the matching degree calculating unit is used for calculating the matching degree between each screened marketing strategy and the input information, wherein the matching degree=K1×the overlapping degree of the channel information and the popularization sales channel +K2×the overlapping degree of the crowd information and the popularization crowd +K3×the evaluation information, and the K1, the K2 and the K3 are all constant coefficients.
Compared with the prior art, the invention has the beneficial effects that:
the method determines the product attribute, the popularization sales channel and the popularization crowd based on the big data and the marketing product information; inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library for matching, outputting marketing strategies with the matching degree arranged in the front N, wherein each marketing strategy comprises a personalized expansion scheme, determining the matched personalized expansion scheme based on the personalized elements, screening to obtain a final marketing strategy, and determining element types of the personalized elements, wherein the element types are plane elements, three-dimensional elements or abstract display elements; and judging whether the personalized expansion schemes in the marketing strategy are consistent according to the determined element types. Therefore, the marketing campaign strategy fully considers the display of the product personality elements, and is a popularization sales channel and a popularization crowd determined based on big data, and the effect is better.
Drawings
FIG. 1 is a flow chart of a marketing campaign template customization method based on personalized popularization.
FIG. 2 is a flow chart of determining product attributes in a personalized popularization based marketing campaign template customization method.
FIG. 3 is a flow chart of determining promotional sales channels and promotional people in a personalized promotional based marketing campaign template customization method.
FIG. 4 is a flow chart of matching input into a marketing strategy library in a personalized popularization-based marketing campaign template customization method.
Fig. 5 is a schematic diagram of a marketing campaign template customization system based on personalized promotion.
Fig. 6 is a schematic structural diagram of a channel crowd determination module in a personalized popularization-based marketing campaign template customization system.
Fig. 7 is a schematic diagram of a marketing channel crowd unit in a personalized marketing campaign template customization system.
Fig. 8 is a schematic diagram of the structure of a marketing strategy matching module in a marketing campaign template customization system based on personalized popularization.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Specific implementations of the invention are described in detail below in connection with specific embodiments.
As shown in fig. 1, the embodiment of the invention provides a marketing campaign template customizing method based on personalized popularization, which comprises the following steps:
s100, receiving marketing product information input by a user, wherein the marketing product information comprises marketing products, personalized elements and historical sales information, and the historical sales information comprises sales channels, sales data and purchasing groups;
s200, determining product attributes, popularization sales channels and popularization crowds based on big data and marketing product information;
s300, inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library for matching, wherein the marketing strategy library comprises a plurality of marketing strategies, each marketing strategy corresponds to a marketing attribute, and the marketing attribute comprises product attribute information, channel information, crowd information and evaluation information;
s400, outputting marketing strategies with the matching degree arranged in the front N, wherein each marketing strategy comprises a personalized expansion scheme, determining the matched personalized expansion scheme based on the personalized elements, and screening to obtain a final marketing strategy;
it should be noted that, at present, many companies are actively attempting to construct a marketing intelligent platform, and by integrating various data, analysis tools and algorithms, intelligent management and optimization of marketing activities are realized. However, the marketing campaign templates given by the intelligent marketing platform lack personalized service content and cannot well display personalized elements of products, and the embodiment of the invention aims to solve the problems.
In the embodiment of the invention, firstly, a user is required to determine marketing product information, wherein the marketing product information comprises marketing products, personalized elements and historical sales information, the personalized elements can be colors, shapes, product prominence functions and the like, and the historical sales information comprises one or more sales channels, and each sales channel corresponds to respective sales data and purchasing groups; then, the embodiment of the invention can determine the product attribute, the popularization sales channel and the popularization crowd based on the big data and the marketing product information, wherein the product attribute describes the type and the application of the product, and the popularization sales channel and the popularization crowd are obtained through common analysis based on the big data and the historical sales information, so that the method is more scientific and accurate. Then inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library for matching, wherein the marketing strategy library is established in advance, the marketing strategy library comprises a plurality of marketing strategies, each marketing strategy corresponds to the marketing attributes, the marketing attributes comprise product attribute information, channel information, crowd information and evaluation information, after matching, the marketing strategies with the matching degree arranged in front N are automatically output, N is a preset fixed value, each marketing strategy comprises a personalized expansion scheme, the matched personalized expansion scheme is determined based on the personalized elements, and the final marketing strategy is obtained through screening; in order to determine a consistent personalized expansion scheme, firstly determining the element type of a personalized element, wherein the element type is a plane element, a stereoscopic element or an abstract display element; for example, the color, the plane modeling are plane elements, the three-dimensional modeling and the material are three-dimensional elements, the functional characteristics are abstract display elements, then whether the personalized expansion scheme in the marketing strategy accords or not can be judged according to the determined element types, and the personalized expansion scheme is marked with one or more element types, so that the marketing activity strategy fully considers the display of the personalized elements of the product, and is a popularization sales channel and a popularization crowd determined based on big data, and the effect is better.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of determining product attributes, promotion sales channels and promotion groups based on big data and marketing product information specifically includes:
s201, inputting the marketing products into a product type attribute library to obtain product attributes;
s202, determining main sales channels and main purchasing groups according to historical sales information;
s203, determining recommended sales channels and recommended purchasing groups of the same type of products according to the product attributes;
s204, determining popularization sales channels and popularization crowds according to the main sales channels, the main purchasing crowds, the recommended sales channels and the recommended purchasing crowds.
In the embodiment of the invention, a product type attribute library is established in advance, the product type attribute library comprises all product names, each product name corresponds to the type and the use of a product, and the marketing product is input into the product type attribute library to automatically output the product attribute; then determining a main sales channel and a main purchasing crowd according to the historical sales information, wherein the sales of the main sales channel accounts for more than A% of the total sales, and the sales of the main purchasing crowd accounts for more than B% of the total sales; and then determining the recommended sales channels and recommended purchasing groups of the same type of products according to the product attributes, specifically, establishing an attribute recommendation information base in advance, wherein the attribute recommendation information base comprises all product attributes, each product attribute corresponds to the recommended sales channels and the recommended purchasing groups, each sales channel in the recommended sales channels is marked with a third proportion value, and each group of groups in the recommended purchasing groups is marked with a fourth proportion value. Finally, the promotion sales channel and the promotion crowd can be determined according to the main sales channel, the main purchasing crowd, the recommended sales channel and the recommended purchasing crowd.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of determining a promotion sales channel and a promotion group according to a main sales channel, a main purchasing group, a recommended sales channel, and a recommended purchasing group specifically includes:
s2041, determining a first proportion value of each sales channel in the main sales channels and a second proportion value of each group of people in the main purchasing group according to the sales data;
s2042, calling a third proportion value of each sales channel in the recommended sales channels and a fourth proportion value of each group of people in the recommended purchasing group;
s2043, calculating a final scale value=m1×first scale value+m2×third scale value for each sales channel, and calculating a final scale value=m1×second scale value+m2×fourth scale value for each group of people, M1 and M2 being constant coefficients;
s2044, determining popularization sales channels and popularization crowds according to the final proportion value of each sales channel and the final proportion value of each group of crowds.
In the embodiment of the invention, the main sales channel and the recommended sales channel can both comprise one or more sales channels, the main purchasing group and the recommended purchasing group can both comprise one or more purchasing groups, a first proportion value of each sales channel in the main sales channel and a second proportion value of each group of groups in the main purchasing group are determined according to sales data, the first proportion value of each sales channel refers to the sales volume ratio obtained through the sales channel, and the second proportion value of each group of groups refers to the sales volume ratio obtained through the group; then, a third proportion value of each sales channel in the recommended sales channels and a fourth proportion value of each group of people in the recommended purchasing group are called; then, the final proportion value=m1×first proportion value+m2×third proportion value of each sales channel can be calculated, the final proportion value=m1×second proportion value+m2×fourth proportion value of each group of people is calculated, M1 and M2 are constant coefficients, the larger M1 indicates that the influence of historical sales information is more, the larger M2 indicates that the influence degree of sales information of similar products is more, and M1 and M2 can be adaptively adjusted according to the user requirements, and finally the popularization sales channel and the popularization crowd are determined according to the final proportion value of each sales channel and the final proportion value of each group of people.
As shown in fig. 4, as a preferred embodiment of the present invention, the step of inputting product attributes, promotion sales channels and promotion groups into a marketing strategy library for matching specifically includes:
s301, inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library, and screening all marketing strategies in the marketing strategy library based on the product attributes;
s302, calculating the matching degree between each screened marketing strategy and the input information, wherein the matching degree=K1×the overlapping degree of channel information and popularization sales channels+K2×the overlapping degree of crowd information and popularization crowd+K3×evaluation information, and K1, K2 and K3 are all constant coefficients.
In the embodiment of the invention, after the product attribute, the promotion sales channel and the promotion crowd are input into the marketing strategy library, all marketing strategies in the marketing strategy library are firstly screened based on the product attribute, only marketing strategies containing the product attribute in the marketing attribute are reserved, then the matching degree between each screened marketing strategy and the input information (promotion sales channel and promotion crowd) is calculated, the matching degree = K1 x the overlapping degree of channel information and promotion sales channel + K2 x the overlapping degree of crowd information and promotion crowd + K3 x evaluation information, the overlapping degree of channel information and promotion sales channel = 2 x the number of channels in the same channel information and promotion sales channel/(the number of channels in channel information + the number of channels in promotion sales channel), and the overlapping degree of crowd information and promotion crowd = 2 x the number of the same crowd in the crowd/(the number of people in crowd information + the number of people in promotion crowd).
In the embodiment of the invention, the method further comprises the following steps: and receiving feedback information of the user, wherein the feedback information comprises a final marketing strategy and a strategy score, and updating the corresponding evaluation information according to the strategy score, so that the evaluation information corresponding to each marketing strategy is more accurate.
As shown in fig. 5, the embodiment of the present invention further provides a marketing campaign template customization system based on personalized popularization, where the system includes:
the marketing product information module 100 is configured to receive marketing product information input by a user, where the marketing product information includes a marketing product, a personalized element, and historical sales information, and the historical sales information includes sales channels, sales data, and purchasing groups;
channel crowd determination module 200 for determining product attributes, promotional sales channels, and promotional crowd based on big data and marketing product information;
the marketing strategy matching module 300 is configured to input product attributes, promotion sales channels and promotion groups into a marketing strategy library for matching, where the marketing strategy library includes a plurality of marketing strategies, each marketing strategy corresponds to a marketing attribute, and the marketing attribute includes product attribute information, channel information, crowd information and evaluation information;
the personalized expansion module 400 is configured to output marketing strategies with matching degree arranged in the front N, each marketing strategy includes a personalized expansion scheme, determine a matched personalized expansion scheme based on the personalized elements, and screen to obtain a final marketing strategy;
the step of determining the matched personalized expansion scheme based on the personalized elements specifically comprises the following steps: determining the element type of the personalized element, wherein the element type is a plane element, a stereoscopic element or an abstract display element; judging whether the personalized expansion scheme in the marketing strategy accords with the determined element type, wherein the personalized expansion scheme is marked with the proper element type.
As shown in fig. 6, as a preferred embodiment of the present invention, the channel group determining module 200 includes:
a product attribute determining unit 201, configured to input the marketing product into a product type attribute library, to obtain a product attribute;
a main channel crowd unit 202 for determining a main sales channel and a main purchasing crowd according to the history sales information;
a recommendation channel crowd unit 203 for determining recommendation sales channels and recommendation purchase crowd of the same type of products according to the product attributes;
the promotion channel crowd unit 204 is configured to determine a promotion sales channel and a promotion crowd according to a main sales channel, a main purchase crowd, a recommended sales channel, and a recommended purchase crowd.
As shown in fig. 7, as a preferred embodiment of the present invention, the promotion channel crowd unit 204 includes:
a proportion value calculating subunit 2041 for determining a first proportion value for each of the main sales channels and a second proportion value for each of the main purchasing groups according to the sales data;
a proportion value retrieving subunit 2042 for retrieving a third proportion value for each of the recommended sales channels and a fourth proportion value for each of the recommended purchasing groups;
a final scale value subunit 2043 for calculating a final scale value=m1×first scale value+m2×third scale value for each sales channel, and calculating a final scale value=m1×second scale value+m2×fourth scale value for each group of people, where M1 and M2 are constant coefficients;
channel group determination subunit 2044 is configured to determine a popularization sales channel and a popularization group according to the final proportion value of each sales channel and the final proportion value of each group of groups.
As shown in fig. 8, as a preferred embodiment of the present invention, the marketing strategy matching module 300 includes:
the marketing strategy screening unit 301 is configured to input product attributes, promotion sales channels and promotion groups into the marketing strategy library, and screen all marketing strategies in the marketing strategy library based on the product attributes;
and the matching degree calculating unit 302 is configured to calculate a matching degree between each screened marketing strategy and the input information, wherein the matching degree=k1×the overlapping degree between the channel information and the popularization sales channel+k2×the overlapping degree between the crowd information and the popularization crowd+k3×the evaluation information, and each of K1, K2 and K3 is a constant coefficient.
The foregoing description of the preferred embodiments of the present invention should not be taken as limiting the invention, but rather should be understood to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
Other embodiments of the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims (9)

1. The marketing campaign template customizing method based on personalized popularization is characterized by comprising the following steps of:
receiving marketing product information input by a user, wherein the marketing product information comprises marketing products, personalized elements and historical sales information, and the historical sales information comprises sales channels, sales data and purchasing groups;
determining product attributes, popularization sales channels and popularization crowds based on the big data and the marketing product information;
inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library for matching, wherein the marketing strategy library comprises a plurality of marketing strategies, each marketing strategy corresponds to a marketing attribute, and the marketing attribute comprises product attribute information, channel information, crowd information and evaluation information;
outputting marketing strategies with the matching degree arranged in the front N, wherein each marketing strategy comprises a personalized expansion scheme, determining the matched personalized expansion scheme based on the personalized elements, and screening to obtain a final marketing strategy;
the step of determining the matched personalized expansion scheme based on the personalized elements specifically comprises the following steps: determining the element type of the personalized element, wherein the element type is a plane element, a stereoscopic element or an abstract display element; judging whether the personalized expansion scheme in the marketing strategy accords with the determined element type, wherein the personalized expansion scheme is marked with the proper element type.
2. The personalized popularization-based marketing campaign template customization method of claim 1, wherein the step of determining product attributes, popularization sales channels and popularization crowds based on big data and marketing product information comprises the following steps:
inputting the marketing products into a product type attribute library to obtain product attributes;
determining a main sales channel and a main purchasing group according to the historical sales information;
determining recommended sales channels and recommended purchasing groups of the same type of products according to the product attributes;
and determining popularization sales channels and popularization groups according to the main sales channels, the main purchasing groups, the recommended sales channels and the recommended purchasing groups.
3. The personalized popularization-based marketing campaign template customizing method according to claim 2, wherein the step of determining the popularization sales channel and the popularization crowd according to the main sales channel, the main purchasing crowd, the recommended sales channel and the recommended purchasing crowd specifically comprises:
determining a first proportion value of each sales channel in the main sales channels and a second proportion value of each group of people in the main purchasing group according to the sales data;
calling a third proportion value of each sales channel in the recommended sales channels and a fourth proportion value of each group of people in the recommended purchasing group;
calculating a final proportion value=m1×first proportion value+m2×third proportion value of each sales channel, and calculating a final proportion value=m1×second proportion value+m2×fourth proportion value of each group of people, wherein M1 and M2 are constant coefficients;
and determining popularization sales channels and popularization crowds according to the final proportion value of each sales channel and the final proportion value of each group of crowds.
4. The personalized popularization-based marketing campaign template customizing method according to claim 1, wherein the step of inputting the product attribute, the popularization sales channel and the popularization crowd into the marketing strategy library for matching specifically comprises the following steps:
inputting product attributes, popularization sales channels and popularization crowds into a marketing strategy library, and screening all marketing strategies in the marketing strategy library based on the product attributes;
and calculating the matching degree between each screened marketing strategy and the input information, wherein the matching degree=K1×the overlapping degree of the channel information and the popularization sales channel+K2×the overlapping degree of the crowd information and the popularization crowd+K3×the evaluation information, and the K1, the K2 and the K3 are constant coefficients.
5. The personalized popularization-based marketing campaign template customization method of claim 1, further comprising: and receiving feedback information of the user, wherein the feedback information comprises a final marketing strategy and a strategy score, and updating corresponding evaluation information according to the strategy score.
6. A marketing campaign template customization system based on personalized promotion, the system comprising:
the marketing product information module is used for receiving marketing product information input by a user, wherein the marketing product information comprises marketing products, personalized elements and historical sales information, and the historical sales information comprises sales channels, sales data and purchasing groups;
the channel crowd determining module is used for determining product attributes, popularization sales channels and popularization crowds based on the big data and the marketing product information;
the marketing strategy matching module is used for inputting the product attributes, the popularization sales channels and the popularization crowds into the marketing strategy library for matching, the marketing strategy library comprises a plurality of marketing strategies, each marketing strategy corresponds to a marketing attribute, and the marketing attribute comprises product attribute information, channel information, crowd information and evaluation information;
the personalized expansion module is used for outputting marketing strategies with the matching degree arranged in front N, each marketing strategy comprises a personalized expansion scheme, the matched personalized expansion scheme is determined based on the personalized elements, and the final marketing strategy is obtained through screening;
the step of determining the matched personalized expansion scheme based on the personalized elements specifically comprises the following steps: determining the element type of the personalized element, wherein the element type is a plane element, a stereoscopic element or an abstract display element; judging whether the personalized expansion scheme in the marketing strategy accords with the determined element type, wherein the personalized expansion scheme is marked with the proper element type.
7. The personalized promotion based marketing campaign template customization system of claim 6, wherein the channel crowd determination module comprises:
the product attribute determining unit is used for inputting the marketing products into the product type attribute library to obtain product attributes;
a main channel crowd unit for determining main sales channels and main purchasing crowd according to the history sales information;
the recommendation channel crowd unit is used for determining recommendation sales channels and recommendation purchasing crowds of the same type of products according to the product attributes;
and the promotion channel crowd unit is used for determining promotion sales channels and promotion crowds according to the main sales channels, the main purchasing crowds, the recommended sales channels and the recommended purchasing crowds.
8. The personalized promotion-based marketing campaign template customization system of claim 7, wherein the promotion channel crowd unit comprises:
a proportion value calculating subunit, configured to determine a first proportion value of each of the main sales channels and a second proportion value of each of the main purchasing groups according to the sales data;
the proportion value calling subunit is used for calling a third proportion value of each sales channel in the recommended sales channels and a fourth proportion value of each group of people in the recommended purchasing group;
a final scale value subunit, configured to calculate a final scale value=m1×first scale value+m2×third scale value for each sales channel, and calculate a final scale value=m1×second scale value+m2×fourth scale value for each group of people, where M1 and M2 are constant coefficients;
and the channel crowd determining subunit is used for determining popularization sales channels and popularization crowds according to the final proportion value of each sales channel and the final proportion value of each group of crowds.
9. The personalized promotion-based marketing campaign template customization system of claim 6, wherein the marketing strategy matching module comprises:
the marketing strategy screening unit is used for inputting the product attributes, the popularization sales channels and the popularization crowds into the marketing strategy library, and screening all marketing strategies in the marketing strategy library based on the product attributes;
and the matching degree calculating unit is used for calculating the matching degree between each screened marketing strategy and the input information, wherein the matching degree=K1×the overlapping degree of the channel information and the popularization sales channel +K2×the overlapping degree of the crowd information and the popularization crowd +K3×the evaluation information, and the K1, the K2 and the K3 are all constant coefficients.
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