CN117094752A - Product sales intention group analysis system - Google Patents
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Abstract
The invention relates to the field of intent analysis, and discloses a product sales intent group analysis system, which comprises: the product parameter analysis module is used for acquiring a product to be sold for analysis and extracting key information from product parameters; the comparison module is used for comparing the products with similar products to identify similarity and difference coefficients among the products; the similar definition output module is used for analyzing similarity parameters of the products to be sold and similar products, outputting common keywords and labels and forming similar keyword sets; the difference definition output module is used for analyzing the difference parameters of the products to be sold and the like, outputting difference keywords and labels and forming a difference keyword set; through attribute analysis and similar and different keyword set prediction, the system can more accurately identify potential target groups, help enterprises to accurately locate markets, and support decision-making in a data-driven manner through capturing and analyzing a large amount of network data.
Description
Technical Field
The invention relates to the technical field of intent analysis, in particular to a product sales intent group analysis system.
Background
By analyzing the data, the enterprise can determine which people are interested in their products or services, thereby precisely locating the target customer group, providing personalized recommendations, advertisements, or sales information for each potential customer to improve customer satisfaction and sales conversion, and typically helping the enterprise understand and identify potential purchasers of their products or services through a product sales intent group analysis system, so as to more effectively formulate sales and marketing strategies;
however, existing product sales intent group analysis systems also have limitations, such as:
1. the method has the advantages that the accurate analysis and comparison of similar products and existing products are lacking, the automation completion degree is insufficient, the network data are difficult to acquire in real time for updating analysis, and the grasping degree of market change trend is insufficient;
2. the potential target crowd has poor classifying capability, corresponding sales strategies are difficult to formulate according to different attributes of the target crowd, and the improvement of the sales volume of products is limited.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a product sales intention group analysis system, which can effectively solve the problems that the prior art lacks accurate analysis and comparison of similar products and existing products, has insufficient automatic completion degree, is difficult to acquire network data in real time for updating analysis, has insufficient grasping degree on market change trend, has poor classifying ability on potential target groups, is difficult to formulate corresponding sales strategies according to different attributes of the target groups, and has limited promotion on the sales volume of the products.
In order to achieve the above object, the present invention is achieved by the following technical scheme;
the invention discloses a product sales intention group analysis system, which comprises:
the product parameter analysis module is used for acquiring a product to be sold for analysis and extracting key information from product parameters;
the comparison module is used for comparing the products with similar products to identify similarity and difference coefficients among the products;
the similar definition output module is used for analyzing similarity parameters of the products to be sold and similar products, outputting common keywords and labels and forming similar keyword sets;
the difference definition output module is used for analyzing the difference parameters of the products to be sold and the like, outputting difference keywords and labels and forming a difference keyword set;
the data grabbing module is used for grabbing information about similar products from the Internet and extracting key information;
the information grabbing module is used for grabbing and arranging purchasing crowd information of similar products and extracting key information;
the attribute analysis module is used for analyzing the key information of the purchasing crowd acquired by the information grabbing module and analyzing and identifying potential target groups;
the prediction module is used for analyzing the difference keyword set and predicting the characteristics and functions of products attractive to potential intention groups;
the trend analysis module is used for analyzing the change trend of the intent group and identifying market trend coefficients as reference values of future sales strategies.
Further, the key information attribute extracted by the product parameter analysis module includes: product model, specification and performance.
Further, the attribute of the information captured by the data capturing module includes: social media reviews, news articles, and review videos.
Further, the purchasing crowd information of the similar products captured and arranged by the information capturing module comprises: age, gender, geographic location, hobbies, purchasing preferences, profession, and income level.
Furthermore, the information grabbing module classifies by adopting a clustering algorithm, and evaluates the clustering effect through a DB index, wherein the calculation formula is as follows:
；
where k represents the number of clusters,representing the average distance between samples within the ith cluster; />Representing the average distance between samples within the j-th cluster; />Representing the distance between the center of the i-th cluster and the center of the j-th cluster.
Still further, the trend analysis module is interactively connected with a market research module through a wireless network, and the market research module is used for providing market research information, including competition analysis and market share evaluation.
Furthermore, the competition analysis content of the market research module classifies the purchasing population into different classifications according to the analysis result, and the classification attribute comprises: demographic data, purchasing behavior, and preferences for each population.
Further, the market research module generates sales strategy suggestions for formulating product improvement, pricing strategy and market location for different groups according to the results of the attribute analysis.
Further, the product parameter analysis module is in interactive connection with the comparison module through a wireless network, the comparison module is in interactive connection with the similar definition output module through a wireless network, the similar definition output module is in interactive connection with the difference definition output module through a wireless network, the difference definition output module is in interactive connection with the data grabbing module through a wireless network, the data grabbing module is in interactive connection with the information grabbing module through a wireless network, the information grabbing module is in interactive connection with the attribute analysis module through a wireless network, the attribute analysis module is in interactive connection with the prediction module through a wireless network, and the prediction module is in interactive connection with the trend analysis module through a wireless network.
Compared with the known public technology, the technical scheme provided by the invention has the following beneficial effects:
according to the invention, through attribute analysis and similar and different keyword set prediction, the system can more accurately identify potential target groups, help enterprises accurately locate markets, support decision making in a data-driven manner by grabbing and analyzing a large amount of network data, reduce subjectivity of decisions, and a trend analysis module can help enterprises track market movement and timely adjust sales strategies to adapt to changes.
According to the invention, through difference keyword definition and user feedback analysis, the system can help enterprises to improve products, market demands are met, manual workload is reduced by modularized design and data grabbing automation, efficiency is improved, the system can be customized and expanded according to demands of different markets and products, and different business scenes are adapted.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a schematic diagram of a framework of a product sales intent group analysis system;
reference numerals in the figure respectively represent 1, a product parameter analysis module; 2. comparison module; 3. the same class defines the output module; 4. a difference definition output module; 5. a data grabbing module; 6. an information grabbing module; 7. an attribute analysis module; 8. a prediction module; 9. a trend analysis module; 10. and a market research module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is further described below with reference to examples.
Example 1: a product sales intention group analysis system of the present embodiment, as shown in FIG. 1, includes:
the product parameter analysis module 1 is configured to obtain a product to be sold for analysis, extract key information from product parameters, and the extracted key information attribute includes: product model, specification and performance;
the comparison module 2 is used for comparing the products with similar products to identify the similarity and the difference coefficient between the products;
the similar definition output module 3 is used for analyzing similarity parameters of the products to be sold and similar products, outputting common keywords and labels and forming similar keyword sets;
the difference definition output module 4 is used for analyzing the difference parameters of the products to be sold and the like, outputting difference keywords and labels and forming a difference keyword set;
the data capturing module 5 is configured to capture information about similar products from the internet, extract key information, and attributes of the captured information include: social media comments, news articles, and assessment videos;
the information grabbing module 6 is used for grabbing and arranging the purchasing crowd information of the similar products and extracting key information;
the attribute analysis module 7 is used for analyzing the key information of the purchasing crowd acquired by the information grabbing module 6 and analyzing and identifying potential target groups;
a prediction module 8 for analyzing the set of difference keywords, predicting product characteristics and functions that are attractive to the potential intent population;
the trend analysis module 9 is used for analyzing the change trend of the intent group and identifying market trend coefficients as reference values of future sales strategies.
In the embodiment, through systematic attribute discrimination and keyword setting prediction of the same group and the different groups, the system can accurately position potential target consumer groups, so that enterprises can more accurately lock markets, the pure subjectivity of decision is reduced in a data driving mode, a large amount of network data is collected and analyzed through the system, the important role of the data in enterprise decision is further enhanced, and a trend analysis module provides a dynamic market tracking function for enterprises, so that the enterprises can timely adjust and optimize sales strategies according to market changes;
in addition, through accurate definition of keyword differences and effective analysis of user feedback, the system provides powerful support for improving products for enterprises to better meet market demands, the modularized design and the data acquisition automation of the system are achieved, the whole working efficiency is remarkably improved while manual intervention is reduced, the system can be customized and expanded according to specific demands of different markets and product characteristics, and therefore diversified business scenes can be flexibly adapted.
Example 2: the embodiment also provides a classification measure, where the purchasing crowd information of the similar products captured and arranged by the information capturing module 6 includes: age, gender, geographic location, hobbies, purchasing preferences, occupation, and income level;
the information grabbing module 6 adopts a clustering algorithm to classify, and evaluates the clustering effect through a DB index, wherein the calculation formula is as follows:
；
where k represents the number of clusters,representing the average distance between samples within the ith cluster; />Representing the average distance between samples within the j-th cluster; />Representing the distance between the center of the i-th cluster and the center of the j-th cluster.
In the embodiment, the index of the clustering quality is evaluated by calculating the similarity among the clusters, the smaller the DB index is, the better the clustering quality is, different K values can be tried when the K value is determined, the corresponding DB index is calculated, and the K value with the smallest DB index is selected as the number of the clusters.
Example 3: in this embodiment, as shown in fig. 1, the trend analysis module 9 is interactively connected with a market research module 10 through a wireless network, the market research module 10 is configured to provide market research information, including competition analysis and market share evaluation, and the competition analysis content of the market research module 10 classifies purchasing groups into different classifications according to analysis results, where classification attributes include: demographic data, purchasing behavior and preferences of the various groups, the market research module 10 generates sales strategy suggestions for formulating product improvements, pricing strategies and market positioning for the different groups based on the results of the attribute analysis.
When the embodiment is implemented, the system can help an enterprise determine which people are interested in products or services of the enterprise through analyzing the data, so that a target customer group is accurately positioned, and the system can help the enterprise predict sales and market demands through trend analysis and prediction, so that production and inventory can be planned better.
In summary, the system can accurately position potential target consumer groups through systematic attribute discrimination and keyword setting prediction of the same groups and different groups, so that enterprises can more accurately lock markets, the pure subjectivity of decision is reduced in a data driving mode, a large amount of network data is collected and analyzed through the system, the important role of the data in enterprise decision is further enhanced, and a trend analysis module provides a dynamic market tracking function for enterprises, so that the enterprises can timely adjust and optimize sales strategies according to market changes;
in addition, through accurate definition of keyword differences and effective analysis of user feedback, the system provides powerful support for improving products for enterprises to better meet market demands, the modularized design and the data acquisition automation of the system are achieved, the whole working efficiency is remarkably improved while manual intervention is reduced, the system can be customized and expanded according to specific demands of different markets and product characteristics, and therefore diversified business scenes can be flexibly adapted.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; while the invention has been described in detail with reference to the foregoing embodiments, it will be appreciated by those skilled in the art that variations may be made in the techniques described in the foregoing embodiments, or equivalents may be substituted for elements thereof; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. A system for analyzing a population of intent to sell a product, comprising:
the product parameter analysis module (1) is used for acquiring a product to be sold for analysis and extracting key information from product parameters;
the comparison module (2) is used for comparing the products with similar products to identify the similarity and the difference coefficient between the products;
the similar definition output module (3) is used for analyzing similarity parameters of the products to be sold and similar products, outputting common keywords and labels and forming similar keyword sets;
the difference definition output module (4) is used for analyzing the difference parameters of the products to be sold and the like, outputting difference keywords and labels and forming a difference keyword set;
the data grabbing module (5) is used for grabbing information about similar products from the Internet and extracting key information;
the information grabbing module (6) is used for grabbing and arranging the purchasing crowd information of the similar products and extracting key information;
the attribute analysis module (7) is used for analyzing the key information of the purchasing crowd acquired by the information grabbing module (6) and analyzing and identifying potential target groups;
a prediction module (8) for analyzing the set of difference keywords, predicting product characteristics and functions that are attractive to the potential intent population;
and the trend analysis module (9) is used for analyzing the change trend of the intent group and identifying market trend coefficients as reference values of future sales strategies.
2. The system for analyzing a population of sales intention of a product according to claim 1, wherein the key information attribute extracted by the product parameter analyzing module (1) comprises: product model, specification and performance.
3. A system for analysis of a group of sales intention of a product according to claim 1, characterized in that the attributes of the information captured by the data capturing module (5) comprise: social media reviews, news articles, and review videos.
4. The system according to claim 1, wherein the purchasing crowd information of the similar products captured and arranged by the information capturing module (6) includes: age, gender, geographic location, hobbies, purchasing preferences, profession, and income level.
5. The system for analyzing the sales intention group of the product according to claim 1, wherein the information grabbing module (6) classifies the product by adopting a clustering algorithm, and evaluates the clustering effect by using a DB index, and the calculation formula is as follows:
；
where k represents the number of clusters,representing the average distance between samples within the ith cluster; />Representing the average distance between samples within the j-th cluster; />Representing the distance between the center of the i-th cluster and the center of the j-th cluster.
6. The system for analyzing the sales intention group of the product according to claim 1, wherein the trend analysis module (9) is interactively connected with a market research module (10) through a wireless network, and the market research module (10) is used for providing market research information, including competition analysis and market share evaluation.
7. The system for analyzing the sales intention group of products according to claim 6, wherein the competitive analysis contents of the market research module (10) divide the purchasing population into different categories according to the analysis result, and the classification attributes thereof include: demographic data, purchasing behavior, and preferences for each population.
8. The system of claim 6, wherein the market research module (10) generates sales strategy suggestions for formulating product improvements, pricing strategies, and market positioning for different groups based on results of the attribute analysis.
9. The system for analyzing the sales intention group of the product according to claim 1, wherein the product parameter analyzing module (1) is interactively connected with the comparing module (2) through a wireless network, the comparing module (2) is interactively connected with the homogeneous definition output module (3) through a wireless network, the homogeneous definition output module (3) is interactively connected with the differential definition output module (4) through a wireless network, the differential definition output module (4) is interactively connected with the data capturing module (5) through a wireless network, the data capturing module (5) is interactively connected with the information capturing module (6) through a wireless network, the information capturing module (6) is interactively connected with the attribute analyzing module (7) through a wireless network, the attribute analyzing module (7) is interactively connected with the predicting module (8) through a wireless network, and the predicting module (8) is interactively connected with the trend analyzing module (9) through a wireless network.
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Application publication date: 20231121 |