CN116739676A - Intelligent advertisement marketing system based on big data - Google Patents
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Abstract
The invention aims to provide an intelligent advertisement marketing system based on big data, which adopts big data analysis and an artificial intelligent algorithm to realize deep mining on user characteristics and demands, improves advertisement accuracy and delivery effect, utilizes various data sources to form real user portraits through data integration and characteristic extraction, thereby better knowing user demands and purchasing behavior.
Description
Technical Field
The invention relates to the technical field of advertisement marketing, in particular to an intelligent advertisement marketing system based on big data.
Background
The intelligent marketing is an innovative marketing new concept which applies advanced computer, network, mobile internet, internet of things and other scientific and technological fusion to the modern brand marketing field through creativity, innovation and creative intelligence of people. The intelligent marketing is based on people as a center and network technology, the creative is a core, the content is a basis, and the marketing is consumer personalized marketing for essential purposes, so that the perfect combination of brands and actual effects is realized.
The establishment of the advertising agency is a post of the modernization process of the advertising industry, which is accompanied by the vigorous development of the advertising industry and is the product of the advertising industry developed to a certain historical stage. Only if the commercial economy mode is complete and the division is complete, mass media is developed to the level of specialization and socialization, an advertising company can establish a dominant position in the operation and activity, provide services conforming to the selling rule of the commercial products for advertisers, such as accurately and reasonably using limited advertising fees, scientifically and normally combining methods, and bring the advertising activity into play more effectively with higher planning and design level.
The advertising agency is used as a basic organization form of business of advertisements, receives the entrustment of an advertiser to release the advertisements to the media on the one hand, and provides a legal organization of advertisement design, production or other marketing services on the other hand, and the media is not directly contacted with the advertiser.
The traditional advertising agency is mainly used for advertising marketing around the media which are agency agents, the mode resource allocation is single, the 'regional cross-media advertising agency', 'regional homogeneous media advertising agency', 'regional cross-media advertising agency', 'regional homogeneous media advertising agency' is difficult to meet the requirement of multi-element advertising marketing in the media fusion era, and the advertisement agency is difficult to quickly define the advertisement putting requirement of the advertiser in the process of bidirectional communication with the media and the advertiser due to the characteristic that the media is not directly contacted with the advertiser, so that a large amount of manpower resources are consumed.
Disclosure of Invention
The invention aims to provide an intelligent advertisement marketing system based on big data, which is used for solving the problems in the background technology and is convenient to popularize.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the intelligent advertisement marketing system based on big data comprises a big data acquisition module, a big data preprocessing module, an intelligent algorithm module and an intelligent advertisement putting module, wherein the modules are used for carrying out information interaction based on digital signals;
the big data acquisition module forms a real user portrait through data integration and feature extraction by utilizing various channels such as the Internet, mobile application and the like;
the big data preprocessing module utilizes big data technology to perform feature extraction, data cleaning, analysis and mining on the collected data, so that interests, favorites and purchase intention features of the user are obtained, and region analysis and prediction are performed according to geographic position information of the user;
the intelligent algorithm module adopts artificial intelligent algorithms such as deep learning and the like to model and train data, and generates an intelligent model for analyzing user demands and predicting user behaviors;
the intelligent advertisement putting module accurately puts and adjusts advertisements in real time by utilizing the intelligent model and the big data analysis result, and improves the click rate of the advertisements.
Further, the big data acquisition module comprises the following working steps:
step one: the selection and preparation of data sources, including the determination of the type and source of data to be collected and the preparation of the corresponding access rights and data formats;
step two: the data crawling and collecting method comprises the steps of obtaining data from a data source by utilizing a web crawler, an API (application program interface), a data warehouse tool and a technology, and extracting and collecting the data;
step three: the method comprises the steps of data cleaning and preprocessing, namely cleaning and preprocessing original data after data acquisition, wherein the steps comprise removing repeated data, identifying and processing invalid data, converting data formats, extracting key information and carrying out data normalization;
step four: data storage and management, for large-scale data acquisition, an efficient, reliable and extensible data storage system is established, and meanwhile, data management and backup are carried out to ensure the integrity and the safety of data;
step five: the control and evaluation of the data quality are required to be carried out on the acquired data, and the accuracy, consistency, integrity and timeliness of the data are determined so as to improve the reliability and effectiveness of the data;
step six: subsequent processing and analysis of the data, further processing and analysis of the collected data, data mining, machine learning, predictive analysis to obtain valuable information and knowledge.
Further, the big data preprocessing module comprises the following working steps:
step one: data cleaning, namely performing duplicate removal, missing value processing and abnormal value processing on the data to ensure the consistency and the integrity of the data;
step two: data integration, which is to combine, de-duplicate, disambiguate and convert the data of multiple data sources to obtain a data set with higher consistency and integrity;
step three: data conversion, which performs standardization, discretization, serialization and normalization operation on the data to simplify the data processing and analysis process;
step four: data protocol, defining attribute and range of data, and standardizing format and content of data so as to reduce difference between different data;
step five: data dimension reduction, namely selecting, sampling and compressing the data to reduce the dimension and complexity of the data and simplify the analysis and modeling process;
step six: and data aggregation, namely grouping, summarizing and transforming the data to obtain higher-level data summarization and statistics results.
Further, the intelligent advertisement delivery module comprises the following working steps:
step one: ad spot prediction, which predicts web pages or applications that a user may access by statistical analysis of user data to determine an optimal ad spot;
step two: user portrait analysis, namely establishing a detailed portrait of a user, collecting user behavior data and interest preference data, and making data support for the following advertisement delivery;
step three: analyzing target audience, namely analyzing data of shopping behaviors, searching behaviors and browsing behaviors of a user, determining the target audience, and pushing related advertisements aiming at the target audience;
step four: the advertisement effect evaluation is carried out, the advertisement is monitored in real time and the effect evaluation is carried out, and real-time adjustment is carried out according to indexes of click rate and conversion rate;
step five: intelligent bidding forms a market between the advertisement space and the advertiser in a bidding mode, and automatically sets an optimal bidding strategy according to the throwing effect and the competition condition of the advertisement space;
step six: and adjusting the strategy in real time according to the feedback data of the advertisement effect, and adjusting the strategy of advertisement delivery in time so as to optimize keywords, pictures or links in the advertisement and improve the advertisement display and click rate.
As an improvement, the invention has the following beneficial effects:
the intelligent advertisement marketing system based on big data adopts big data analysis and an artificial intelligent algorithm to realize deep mining on user characteristics and demands, improves advertisement accuracy and delivery effect, utilizes various data sources to form real user portraits through data integration and characteristic extraction, so as to better know user demands and purchasing behaviors.
Drawings
FIG. 1 is a flow chart of a big data based intelligent advertising marketing system of the present invention;
Detailed Description
In order to make the contents of the present invention more clearly understood, the technical solutions in 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.
The intelligent advertisement marketing system based on big data comprises a big data acquisition module, a big data preprocessing module, an intelligent algorithm module and an intelligent advertisement putting module, wherein the modules are used for carrying out information interaction based on digital signals;
the big data acquisition module forms a real user portrait through data integration and feature extraction by utilizing various channels such as the Internet, mobile application and the like;
the big data preprocessing module utilizes big data technology to perform feature extraction, data cleaning, analysis and mining on the collected data, so that interests, favorites and purchase intention features of the user are obtained, and region analysis and prediction are performed according to geographic position information of the user;
the intelligent algorithm module adopts artificial intelligent algorithms such as deep learning and the like to model and train data, and generates an intelligent model for analyzing user demands and predicting user behaviors;
the intelligent advertisement putting module accurately puts and adjusts advertisements in real time by utilizing the intelligent model and the big data analysis result, and improves the click rate of the advertisements.
The big data acquisition module comprises the following working steps:
step one: the selection and preparation of data sources, including the determination of the type and source of data to be collected and the preparation of the corresponding access rights and data formats;
step two: the data crawling and collecting method comprises the steps of obtaining data from a data source by utilizing a web crawler, an API (application program interface), a data warehouse tool and a technology, and extracting and collecting the data;
step three: the method comprises the steps of data cleaning and preprocessing, namely cleaning and preprocessing original data after data acquisition, wherein the steps comprise removing repeated data, identifying and processing invalid data, converting data formats, extracting key information and carrying out data normalization;
step four: data storage and management, for large-scale data acquisition, an efficient, reliable and extensible data storage system is established, and meanwhile, data management and backup are carried out to ensure the integrity and the safety of data;
step five: the control and evaluation of the data quality are required to be carried out on the acquired data, and the accuracy, consistency, integrity and timeliness of the data are determined so as to improve the reliability and effectiveness of the data;
step six: subsequent processing and analysis of the data, further processing and analysis of the collected data, data mining, machine learning, predictive analysis to obtain valuable information and knowledge.
The big data preprocessing module comprises the following working steps:
step one: data cleaning, namely performing duplicate removal, missing value processing and abnormal value processing on the data to ensure the consistency and the integrity of the data;
step two: data integration, which is to combine, de-duplicate, disambiguate and convert the data of multiple data sources to obtain a data set with higher consistency and integrity;
step three: data conversion, which performs standardization, discretization, serialization and normalization operation on the data to simplify the data processing and analysis process;
step four: data protocol, defining attribute and range of data, and standardizing format and content of data so as to reduce difference between different data;
step five: data dimension reduction, namely selecting, sampling and compressing the data to reduce the dimension and complexity of the data and simplify the analysis and modeling process;
step six: and data aggregation, namely grouping, summarizing and transforming the data to obtain higher-level data summarization and statistics results.
The intelligent advertisement delivery module comprises the following working steps:
step one: ad spot prediction, which predicts web pages or applications that a user may access by statistical analysis of user data to determine an optimal ad spot;
step two: user portrait analysis, namely establishing a detailed portrait of a user, collecting user behavior data and interest preference data, and making data support for the following advertisement delivery;
step three: analyzing target audience, namely analyzing data of shopping behaviors, searching behaviors and browsing behaviors of a user, determining the target audience, and pushing related advertisements aiming at the target audience;
step four: the advertisement effect evaluation is carried out, the advertisement is monitored in real time and the effect evaluation is carried out, and real-time adjustment is carried out according to indexes of click rate and conversion rate;
step five: intelligent bidding forms a market between the advertisement space and the advertiser in a bidding mode, and automatically sets an optimal bidding strategy according to the throwing effect and the competition condition of the advertisement space;
step six: and adjusting the strategy in real time according to the feedback data of the advertisement effect, and adjusting the strategy of advertisement delivery in time so as to optimize keywords, pictures or links in the advertisement and improve the advertisement display and click rate.
The above description is illustrative of the present invention and is not intended to be limiting, but is to be construed as being included within the spirit and scope of the present invention.
Claims (4)
1. The intelligent advertisement marketing system based on big data comprises a big data acquisition module, a big data preprocessing module, an intelligent algorithm module and an intelligent advertisement putting module, wherein the modules are used for carrying out information interaction based on digital signals;
the big data acquisition module forms a real user portrait through data integration and feature extraction by utilizing various channels such as the Internet, mobile application and the like;
the big data preprocessing module utilizes big data technology to perform feature extraction, data cleaning, analysis and mining on the collected data, so that interests, favorites and purchase intention features of the user are obtained, and region analysis and prediction are performed according to geographic position information of the user;
the intelligent algorithm module adopts artificial intelligent algorithms such as deep learning and the like to model and train data, and generates an intelligent model for analyzing user demands and predicting user behaviors;
the intelligent advertisement putting module accurately puts and adjusts advertisements in real time by utilizing the intelligent model and the big data analysis result, and improves the click rate of the advertisements.
2. The big data based intelligent advertising marketing system of claim 1, wherein the big data collection module comprises the following operative steps:
step one: the selection and preparation of data sources, including the determination of the type and source of data to be collected and the preparation of the corresponding access rights and data formats;
step two: the data crawling and collecting method comprises the steps of obtaining data from a data source by utilizing a web crawler, an API (application program interface), a data warehouse tool and a technology, and extracting and collecting the data;
step three: the method comprises the steps of data cleaning and preprocessing, namely cleaning and preprocessing original data after data acquisition, wherein the steps comprise removing repeated data, identifying and processing invalid data, converting data formats, extracting key information and carrying out data normalization;
step four: data storage and management, for large-scale data acquisition, an efficient, reliable and extensible data storage system is established, and meanwhile, data management and backup are carried out to ensure the integrity and the safety of data;
step five: the control and evaluation of the data quality are required to be carried out on the acquired data, and the accuracy, consistency, integrity and timeliness of the data are determined so as to improve the reliability and effectiveness of the data;
step six: subsequent processing and analysis of the data, further processing and analysis of the collected data, data mining, machine learning, predictive analysis to obtain valuable information and knowledge.
3. The big data based intelligent advertising marketing system of claim 1, wherein the big data preprocessing module comprises the following working steps:
step one: data cleaning, namely performing duplicate removal, missing value processing and abnormal value processing on the data to ensure the consistency and the integrity of the data;
step two: data integration, which is to combine, de-duplicate, disambiguate and convert the data of multiple data sources to obtain a data set with higher consistency and integrity;
step three: data conversion, which performs standardization, discretization, serialization and normalization operation on the data to simplify the data processing and analysis process;
step four: data protocol, defining attribute and range of data, and standardizing format and content of data so as to reduce difference between different data;
step five: data dimension reduction, namely selecting, sampling and compressing the data to reduce the dimension and complexity of the data and simplify the analysis and modeling process;
step six: and data aggregation, namely grouping, summarizing and transforming the data to obtain higher-level data summarization and statistics results.
4. The intelligent advertisement marketing system based on big data of claim 1, wherein the intelligent advertisement delivery module comprises the following working steps:
step one: ad spot prediction, which predicts web pages or applications that a user may access by statistical analysis of user data to determine an optimal ad spot;
step two: user portrait analysis, namely establishing a detailed portrait of a user, collecting user behavior data and interest preference data, and making data support for the following advertisement delivery;
step three: analyzing target audience, namely analyzing data of shopping behaviors, searching behaviors and browsing behaviors of a user, determining the target audience, and pushing related advertisements aiming at the target audience;
step four: the advertisement effect evaluation is carried out, the advertisement is monitored in real time and the effect evaluation is carried out, and real-time adjustment is carried out according to indexes of click rate and conversion rate;
step five: intelligent bidding forms a market between the advertisement space and the advertiser in a bidding mode, and automatically sets an optimal bidding strategy according to the throwing effect and the competition condition of the advertisement space;
step six: and adjusting the strategy in real time according to the feedback data of the advertisement effect, and adjusting the strategy of advertisement delivery in time so as to optimize keywords, pictures or links in the advertisement and improve the advertisement display and click rate.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117196724A (en) * | 2023-10-17 | 2023-12-08 | 广东广信通信服务有限公司 | Marketing method, system, equipment and storable medium based on big data |
| CN117237024A (en) * | 2023-11-14 | 2023-12-15 | 深圳市诚王创硕科技有限公司 | Popularization method and system for marketing |
| CN117391742A (en) * | 2023-10-18 | 2024-01-12 | 广州电力交易中心有限责任公司 | Method for analyzing market operation economy |
| CN117522486A (en) * | 2024-01-08 | 2024-02-06 | 深圳市华熠网络有限公司 | Intelligent advertisement putting system and method for electronic commerce |
| CN117808535A (en) * | 2023-12-29 | 2024-04-02 | 深圳博十强志科技有限公司 | Advertisement putting method and system based on user big data analysis |
| CN117829914A (en) * | 2024-03-04 | 2024-04-05 | 长春大学 | Digital media advertisement effect evaluation system |
| CN117934080A (en) * | 2024-03-18 | 2024-04-26 | 长沙掌控智能科技有限公司 | Sharing benefit optimization method and system based on intelligent popularization tool |
| CN118229363A (en) * | 2024-05-23 | 2024-06-21 | 青岛纯品科技有限公司 | Intelligent advertisement putting system based on big data |
| CN118379095A (en) * | 2024-06-26 | 2024-07-23 | 金数信息科技(苏州)有限公司 | Advertisement putting and adjusting system and method |
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- 2023-06-20 CN CN202310741954.7A patent/CN116739676A/en active Pending
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117196724A (en) * | 2023-10-17 | 2023-12-08 | 广东广信通信服务有限公司 | Marketing method, system, equipment and storable medium based on big data |
| CN117391742A (en) * | 2023-10-18 | 2024-01-12 | 广州电力交易中心有限责任公司 | Method for analyzing market operation economy |
| CN117237024A (en) * | 2023-11-14 | 2023-12-15 | 深圳市诚王创硕科技有限公司 | Popularization method and system for marketing |
| CN117237024B (en) * | 2023-11-14 | 2024-02-20 | 深圳市诚王创硕科技有限公司 | Popularization method and system for marketing |
| CN117808535A (en) * | 2023-12-29 | 2024-04-02 | 深圳博十强志科技有限公司 | Advertisement putting method and system based on user big data analysis |
| CN117522486A (en) * | 2024-01-08 | 2024-02-06 | 深圳市华熠网络有限公司 | Intelligent advertisement putting system and method for electronic commerce |
| CN117522486B (en) * | 2024-01-08 | 2024-04-02 | 深圳市华熠网络有限公司 | Intelligent advertisement putting system and method for electronic commerce |
| CN117829914A (en) * | 2024-03-04 | 2024-04-05 | 长春大学 | Digital media advertisement effect evaluation system |
| CN117829914B (en) * | 2024-03-04 | 2024-05-10 | 长春大学 | Digital media advertisement effect evaluation system |
| CN117934080A (en) * | 2024-03-18 | 2024-04-26 | 长沙掌控智能科技有限公司 | Sharing benefit optimization method and system based on intelligent popularization tool |
| CN118229363A (en) * | 2024-05-23 | 2024-06-21 | 青岛纯品科技有限公司 | Intelligent advertisement putting system based on big data |
| CN118379095A (en) * | 2024-06-26 | 2024-07-23 | 金数信息科技(苏州)有限公司 | Advertisement putting and adjusting system and method |
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