CN114926199A - Internet marketing audience accurate analysis method and system - Google Patents
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Abstract
The invention relates to the technical field of Internet marketing, in particular to an accurate analysis method and system for Internet marketing audiences, wherein the analysis method comprises the following steps: acquiring internet data and establishing a user database; classifying according to the user information, establishing a user identification label, and establishing a sub-database; selecting a label matched with a marketing product to screen users meeting the requirement; and (4) sorting the screened users by the number of the matching labels which are accorded with the single user to form a pyramid target audience hierarchy, wherein the target audience hierarchy positioned at the top among the pyramids is the target audience with high matching degree. The invention realizes rapid and multidimensional screening in massive internet data, accurately acquires target audience and provides powerful data support for formulating a distribution scheme. Through multi-level and multi-dimensional data classification, the efficiency of data screening is greatly improved, and meanwhile, the method has the characteristic of high flexibility and is not limited by the types of marketing products and services.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of internet marketing, in particular to a method and a system for accurately analyzing internet marketing audiences.
[ background of the invention ]
The internet marketing has the characteristics of strong cross-time and spatial property, strong interaction and communication property, high information integration degree and high information exchange efficiency, and occupies an increasingly important position in marketing. However, since the data obtained by internet marketing is massive, how to quickly and effectively find out the users matched with the products or services of the enterprises from the massive data is a problem troubling marketers. In order to realize accurate marketing, an analysis method and system are required to be established, which can accurately screen out target customers so as to carry out efficient marketing activities on the target customers.
[ summary of the invention ]
The invention aims to provide a method and a system for accurately analyzing internet marketing audiences, which aim to solve the problem of accurately acquiring target audiences in mass data.
In order to achieve the purpose, the invention adopts the following technical scheme:
an accurate analysis method for internet marketing audiences is characterized by comprising the following steps: specifically, the method comprises the following steps of,
step S1: acquiring internet data and establishing a user database;
step S2: classifying according to the basic information and the behavior information of the user, establishing a user identification label, and establishing a sub-database about user attributes;
step S3: selecting a label matched with a marketing product to screen users meeting the requirement;
step S4: in the users screened in step S3, the number of matching tags that a single user matches is used as a rank, so as to form a pyramid target audience hierarchy, where the target audience hierarchy located at the top between pyramids is the target audience with high matching degree.
As a further improvement of the present invention, the sources of the internet data in step S1 include websites, microblogs, forums, instant messaging software, life sharing software, and short video social software.
As a further improvement of the present invention, in step S2, the user basic information includes any one or more of sex, age, area, educational background, marital status, and average income.
As a further improvement of the present invention, the user behavior information in step S2 includes browsing history, searching history, purchasing history, posting history, and posting history.
As a further improvement of the present invention, in step S2, the user attributes include static attributes, i.e. a set of information related to the user and basically kept inconvenient, and dynamic attributes, i.e. a set of information related to the behavior preference and daily habits of the user and changed with different factors.
As a further improvement of the present invention, in step S2, the user attributes further include psychological attributes, i.e., reactions with the user in the environmental, social and emotional processes, and consumption attributes, i.e., consumption intention, consumption taste and consumption ability displayed by the user' S consumption record.
As a further improvement of the present invention, the screening requirement in step S3 is specifically to determine a plurality of labels according to the attributes and characteristics of the marketing product, set a weight coefficient k for the labels according to the weight, and calculate by using the following formula: impact factor = label 1 *k 1 + tag 2 *k 2 + … + tag n *k n And calculating to obtain the influence factor of each screened user.
The utility model provides an accurate analytic system of internet marketing audience which characterized in that: specifically, the method comprises the following steps of,
the data acquisition module is used for acquiring internet data files;
the database module is used for classifying the user information and forming sub databases of different categories;
the data analysis module is used for analyzing the user information in the database and marking a plurality of labels for the user according to the behavior information of the user;
and the target audience module takes the tags as key words, extracts user information and classifies the user information into different target user hierarchies according to the number of the tags matched by the user.
As a further improvement of the invention, the tag information in the data analysis module can be customized.
As a further improvement of the invention, the data analysis module comprises,
an audio unit for extracting an audio clip file containing keywords from an audio file;
a video unit for extracting a video clip file containing the keyword and the key image from the video file;
and the character unit is used for extracting the text segment file containing the key words from the text class file.
Compared with the prior art, the invention has the beneficial effects that:
1. in massive internet data, rapid and multidimensional screening is realized, target audiences are accurately acquired, and powerful data support is provided for formulating a distribution scheme.
2. The sub-databases with the same theme are formed by classifying and marking the labels for the users, and the efficiency of data screening is greatly improved through multi-level and multi-dimensional data classification.
3. The invention has the characteristic of high flexibility, dynamically manages the target audience by dynamically classifying, grading and integrating the users, and is not limited by the types of marketing products and services.
4. According to the invention, through careful analysis of consumption data of the target client, efficient marketing is realized for different consumer groups in the target market according to the user behavior characteristics.
[ description of the drawings ]
FIG. 1 is a flow chart of the analysis method of the present invention.
[ detailed description ] embodiments
The technical solution of the present invention will be clearly and completely described with reference to the following examples. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the scope of the present invention.
As shown in fig. 1, an internet marketing audience accurate analysis method is characterized in that: the method specifically comprises the following steps:
step S1: and acquiring internet data and establishing a user database. The sources of the internet data comprise websites, microblogs, forums, instant messaging software, life sharing software and short video social software. The websites comprise a search engine, an e-commerce website, a video website, a travel website, a music website and a brand official website. The forums include living forums, technical forums, sticking bars and food forums. The instant messaging software comprises WeChat and QQ. The life sharing software comprises small red books and bean petals. The short video social software comprises tremble, fast hand and watermelon video.
Step S2: and classifying according to the user basic information and the behavior information, establishing a user identification label, and establishing a sub-database related to the user attribute. The user basic information comprises gender, age, region, education background, marital conditions and average income, and is the most basic attribute division of the user and has the characteristic of relative stability. The user behavior information comprises browsing records, searching records, purchasing records, posting records and replying records, and is relatively unstable and is easily influenced by factors such as time, environment, emotion and the like. The user attributes include static attributes, dynamic attributes, psychological attributes, and consumption attributes. The static attributes are the set of information associated with the user that remains substantially inconvenient, and the basic information attributes are the static attributes. The dynamic attribute is information set which is related to the behavior preference and daily habits of the user and changes along with different factors. The psychological attributes are the reaction of the user in the environmental, social and emotional processes, and the consumption attributes are the consumption intention, consumption preference and consumption capacity displayed by the consumption record of the user. The user behavior information belongs to the dynamic attribute. The identification tag for distinguishing the user characteristics can be customized from the point of view of the marketing product.
Step S3: and selecting the labels matched with the marketing products to screen users meeting the requirements. The screening requirement specifically comprises the steps of determining a plurality of labels according to the attributes and characteristics of the marketing product, setting a weight coefficient k for the labels according to the weight, and calculating by adopting the following formula: impact factor = label 1 *k 1 + tag 2 *k 2 + … + tag n *k n And calculating to obtain the influence factor of each screened user.
Step S4: and (4) sorting the users screened in the step (S3) by taking the number of the matching labels and the calculated value of the influence factor which are met by the single user as factors to form a pyramid target audience hierarchy. The users with more labels and higher values of the influence factors are in a target audience hierarchy with a sharp pyramid interval, namely, the target audience with high matching degree.
An accurate analysis system for internet marketing audience, which comprises,
and the data acquisition module is used for acquiring the Internet data files, acquiring browsing information of a user on a website through the crawler technology of the Internet and searching related data through the Internet.
And the database module is used for classifying the user information and forming sub-databases of different categories.
And the data analysis module is used for analyzing the user information in the database, marking a plurality of labels for the user according to the behavior information of the user, and customizing the label information. The data analysis module comprises an audio unit, a video unit and a character unit. The audio unit is used for extracting the audio clip file containing the key words from the audio file. And the video unit is used for extracting the video clip file containing the key words and the key images from the video file. And the character unit is used for extracting the text segment file containing the key words from the text class file. And the information of the label is freely edited according to the characteristics of the marketing product and the marketing service, and the user information in the database is dynamically managed.
And the target audience module takes the tags as key words, extracts user information and classifies the user information into different target user hierarchies according to the number of the tags matched by the user. When the user information is extracted, a plurality of labels can be selected as key words, and the target audience is further accurately locked among the labels through establishing a logical relation of a sum or an OR.
Claims (10)
1. An Internet marketing audience accurate analysis method is characterized by comprising the following steps: specifically, the method comprises the following steps of,
step S1: acquiring internet data and establishing a user database;
step S2: classifying according to the user basic information and the behavior information, establishing a user identification label, and establishing a sub-database about user attributes;
step S3: selecting a label matched with a marketing product to screen users meeting the requirement;
step S4: in the users screened in step S3, the number of matching tags that a single user matches is used as a rank, so as to form a pyramid target audience hierarchy, where the target audience hierarchy located at the top between pyramids is the target audience with high matching degree.
2. The method for accurately analyzing the internet marketing audience as claimed in claim 1, wherein: the sources of the internet data in the step S1 include websites, microblogs, forums, instant messaging software, life sharing software, and short video social software.
3. The method for accurately analyzing the internet marketing audience as claimed in claim 1, wherein: the user basic information in step S2 includes any one or more of gender, age, location, education background, marital status, and average income.
4. The method for accurately analyzing internet marketing audience of claim 1, wherein: the user behavior information in the step S2 includes browsing history, search history, purchase history, posting history, and posting history.
5. The method for accurately analyzing the internet marketing audience as claimed in claim 1, wherein: the user attributes in step S2 include static attributes, i.e., a set of information related to the user that is basically inconvenient to keep, and dynamic attributes, i.e., a set of information related to the user' S behavior preference and daily habits that changes as different factors change.
6. The method for accurately analyzing the internet marketing audience as claimed in claim 1, wherein: the user attributes in step S2 further include psychological attributes, i.e., reactions with the user in the environmental, social, and emotional processes, and consumption attributes, i.e., consumption intention, consumption taste, and consumption ability displayed by the consumption record of the user.
7. The method for accurately analyzing the internet marketing audience as claimed in claim 1, wherein: the screening requirement in step S3 is specifically to determine a plurality of labels according to the attributes and characteristics of the marketing product, set a weight coefficient k for the labels according to the weight, and calculate by using the following formula: influence factor = label 1 × k1+ label 2 × k2+ … + label n × kn, and the influence factor of each user selected is calculated.
8. The utility model provides an accurate analytic system of internet marketing audience which characterized in that: specifically, the method comprises the following steps of,
the data acquisition module is used for acquiring internet data files;
the database module is used for classifying the user information and forming sub databases of different categories;
the data analysis module is used for analyzing the user information in the database and marking a plurality of labels for the user according to the behavior information of the user;
and the target audience module takes the tags as key words, extracts user information, and classifies the user information into different target user hierarchies according to the number of the tags matched by the user.
9. The system for accurately analyzing internet marketing audience of claim 8, wherein: the tag information in the data analysis module can be customized.
10. The system for accurately analyzing internet marketing audience of claim 8, wherein: the data analysis module comprises a data analysis module and a data analysis module,
an audio unit for extracting an audio clip file containing keywords from an audio file;
a video unit for extracting a video clip file containing the keyword and the key image from the video file;
and the character unit is used for extracting the text segment file containing the key words from the text class file.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115222461A (en) * | 2022-09-19 | 2022-10-21 | 杭州数立信息技术有限公司 | Intelligent marketing accurate recommendation method |
| CN116664196A (en) * | 2023-05-29 | 2023-08-29 | 济宁政和信息技术有限公司 | Internet-based data processing system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101923689A (en) * | 2009-06-15 | 2010-12-22 | ***通信集团公司 | Method for determining advertising information launched audience and related device thereof |
| WO2020015112A1 (en) * | 2018-07-20 | 2020-01-23 | 平安科技（深圳）有限公司 | Product function recommendation method, terminal device and computer-readable storage medium |
| CN110942337A (en) * | 2019-10-31 | 2020-03-31 | 天津中科智能识别产业技术研究院有限公司 | Accurate tourism marketing method based on internet big data |
| CN112037041A (en) * | 2020-09-02 | 2020-12-04 | 中国银行股份有限公司 | Product recommendation method, device and equipment based on bank outlet number calling machine |
| CN114387061A (en) * | 2022-01-12 | 2022-04-22 | 平安普惠企业管理有限公司 | Product pushing method and device, electronic equipment and readable storage medium |
| CN114429371A (en) * | 2022-04-06 | 2022-05-03 | 新石器慧通（北京）科技有限公司 | Unmanned vehicle-based commodity marketing method and device, electronic equipment and storage medium |
-
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- 2022-05-05 CN CN202210482368.0A patent/CN114926199A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101923689A (en) * | 2009-06-15 | 2010-12-22 | ***通信集团公司 | Method for determining advertising information launched audience and related device thereof |
| WO2020015112A1 (en) * | 2018-07-20 | 2020-01-23 | 平安科技（深圳）有限公司 | Product function recommendation method, terminal device and computer-readable storage medium |
| CN110942337A (en) * | 2019-10-31 | 2020-03-31 | 天津中科智能识别产业技术研究院有限公司 | Accurate tourism marketing method based on internet big data |
| CN112037041A (en) * | 2020-09-02 | 2020-12-04 | 中国银行股份有限公司 | Product recommendation method, device and equipment based on bank outlet number calling machine |
| CN114387061A (en) * | 2022-01-12 | 2022-04-22 | 平安普惠企业管理有限公司 | Product pushing method and device, electronic equipment and readable storage medium |
| CN114429371A (en) * | 2022-04-06 | 2022-05-03 | 新石器慧通（北京）科技有限公司 | Unmanned vehicle-based commodity marketing method and device, electronic equipment and storage medium |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115222461A (en) * | 2022-09-19 | 2022-10-21 | 杭州数立信息技术有限公司 | Intelligent marketing accurate recommendation method |
| CN115222461B (en) * | 2022-09-19 | 2023-01-10 | 杭州数立信息技术有限公司 | Intelligent marketing accurate recommendation method |
| CN116664196A (en) * | 2023-05-29 | 2023-08-29 | 济宁政和信息技术有限公司 | Internet-based data processing system |
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