Vehicle enterprise intelligent marketing system and method based on AI content operation

Abstract

The invention relates to the technical field of electronic digital data processing, in particular to a vehicle enterprise intelligent marketing system and method based on AI content operation, and the vehicle enterprise intelligent marketing system based on AI content operation comprises a data collection module, a model training module, a content generation module, a platform publishing module, a data analysis module and a strategy adjustment module. Collecting automobile market data to train an AI model, and calling a video generation model and an image-text generation model to generate an automobile enterprise marketing video and an automobile enterprise marketing image-text according to user requirements; automatically publishing the generated marketing content to each social media and online platform; collecting and analyzing data after each piece of marketing content is published to obtain excellent marketing content; adjusting parameters of the video generation model and the image-text generation model according to the excellent marketing content; according to the method, the AI model can be updated according to the marketing content of the vehicle enterprise, the situation that the generated content does not conform to the actual condition of the vehicle enterprise is avoided, and the marketing effect can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to an intelligent marketing system and method for automobile companies based on AI content operation. Background Art

[0002] With the development of science and technology, the automotive industry is facing unprecedented opportunities and challenges. Traditional automotive marketing methods, such as manually producing marketing videos and pictures, are not only time-consuming and labor-intensive, but also difficult to meet the growing personalized needs.

[0003] In recent years, the rapid development of generative artificial intelligence technology has brought new changes to automobile marketing. AI models can generate high-quality marketing content based on large amounts of data, greatly improving marketing efficiency and effectiveness. However, in existing technologies, AI models are updated based on data collected from other car companies on the Internet. It is impossible to update the AI ​​model based on the marketing content of each car company itself, resulting in the generated content not being in line with the actual situation of the car company, reducing marketing effectiveness. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent marketing system and method for automobile companies based on AI content operation, which can update the AI ​​model according to the marketing content of the automobile company itself, avoid the generated content not conforming to the actual situation of the automobile company, and improve the marketing effect.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present invention provides an intelligent marketing system for automobile enterprises based on AI content operation, including a data collection module, a model training module, a content generation module, a platform publishing module, a data analysis module and a strategy adjustment module;

[0006] The data acquisition module, the model training module, the content generation module, the platform publishing module, the data analysis module and the strategy adjustment module are connected in sequence;

[0007] The data acquisition module is used to collect automobile market data;

[0008] The model training module is used to train the AI ​​model based on the collected automobile market data to obtain a video generation model that can automatically generate automobile enterprise marketing videos, and a picture and text generation model that can automatically generate automobile enterprise marketing pictures and texts;

[0009] The content generation module is used to call the video generation model and the picture and text generation model to generate automobile enterprise marketing videos and automobile enterprise marketing pictures and texts according to user needs;

[0010] The platform publishing module is used to automatically publish the generated automobile enterprise marketing videos and automobile enterprise marketing pictures and texts to various social media and online platforms;

[0011] The data analysis module is used to collect and analyze the data after each car company's marketing video and car company's marketing graphics are released to obtain excellent marketing content;

[0012] The strategy adjustment module is used to adjust the parameters of the video generation model and the image and text generation model according to excellent marketing content.

[0013] Wherein, the platform publishing module includes a content processing unit and a content publishing unit; the content publishing unit is connected to the content processing unit;

[0014] The content processing unit is used to adjust the format of the generated automobile enterprise marketing video and automobile enterprise marketing graphics to adapt them to different social media and online platforms;

[0015] The content publishing unit is used to formulate publishing strategies for various social media and online platforms based on user portraits and platform active time, and automatically publish automobile enterprise marketing videos and automobile enterprise marketing graphics to various social media and online platforms according to the publishing strategies.

[0016] Wherein, the data analysis module includes a user behavior data collection unit, a content scoring unit and a screening unit; the user behavior data collection unit, the content scoring unit and the screening unit are connected in sequence;

[0017] The user behavior data collection unit is used to collect user behavior data of each automobile enterprise marketing video and automobile enterprise marketing graphic, and the user behavior data includes click-through rate, conversion rate, number of user comments and completion rate;

[0018] The content scoring unit is used to score each automobile enterprise marketing video and automobile enterprise marketing graphic according to user behavior data;

[0019] The screening unit is used to compare the scores of the automobile enterprise marketing videos and automobile enterprise marketing pictures and texts with a preset threshold value. When the actual score is greater than the preset threshold value, the content is identified as excellent marketing content.

[0020] Wherein, the content scoring unit includes a click rate scoring subunit and a conversion rate scoring subunit;

[0021] The click-through rate scoring subunit is used to compare the click-through rate of the automobile enterprise marketing video and automobile enterprise marketing graphic with a preset threshold value. When the click-through rate is greater than the preset threshold value, it is recorded as 1, otherwise it is recorded as 0;

[0022] The conversion rate scoring subunit is used to compare the conversion rate of the automobile enterprise marketing video and automobile enterprise marketing pictures and texts with a preset threshold. When the conversion rate is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0.

[0023] Wherein, the content scoring unit also includes a comment scoring subunit;

[0024] The conversion rate scoring subunit is used to compare the number of user comments on the automobile enterprise marketing video and automobile enterprise marketing graphic with a preset threshold. When the number of user comments is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0.

[0025] Wherein, the content scoring unit also includes a completion rate scoring subunit;

[0026] The completion rate scoring subunit is used to compare the completion rate of the automobile enterprise marketing video and automobile enterprise marketing graphics with a preset threshold. When the completion rate is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0.

[0027] In a second aspect, the present invention also provides an intelligent marketing method for automobile enterprises based on AI content operation, including:

[0028] Collect automobile market data through data collection module;

[0029] The model training module trains the AI ​​model based on the collected automobile market data to obtain a video generation model that can automatically generate automobile enterprise marketing videos, and a picture and text generation model that can automatically generate automobile enterprise marketing pictures and texts;

[0030] Through the content generation module, according to user needs, the video generation model and the picture and text generation model are called to generate automobile enterprise marketing videos and automobile enterprise marketing pictures and texts;

[0031] The generated car enterprise marketing videos and car enterprise marketing pictures and texts are automatically published to various social media and online platforms through the platform publishing module;

[0032] The data analysis module collects and analyzes the data of each car company's marketing video and marketing graphics after they are released to obtain excellent marketing content;

[0033] The strategy adjustment module is used to adjust the parameters of the video generation model and the image and text generation model based on excellent marketing content.

[0034] The present invention discloses an intelligent marketing system and method for automobile enterprises based on AI content operation. The data acquisition module obtains the latest market trends, consumer preferences, competitor dynamics and other information by subscribing to automobile industry reports issued by professional market research institutions; collects user discussions, evaluations, needs and other information about automobiles by using social media tools; collects user browsing, clicking, purchasing and other behavioral data through websites, APPs and other channels, analyzes user interests, needs and purchase intentions; designs and publishes online questionnaires to collect target users' specific needs, preferences and improvement suggestions for automobile products. The model training module uses deep learning technologies such as convolutional neural networks (CNN), recurrent neural networks (RNN) and generative adversarial networks (GAN) to construct video generation models and graphic generation models. The video generation model collects a large number of automobile advertising videos and uses video frame sequences for training, so that the model can generate coherent and attractive automobile marketing videos. The graphic generation model is based on keywords or reference pictures provided by users, and the training model generates automobile marketing graphics that meet user needs. The content generation module calls the video generation model based on the user input of information such as car model, color, and configuration, and generates personalized car marketing videos. The system calls the picture generation model based on the user input of keywords or uploaded reference pictures, and generates car marketing pictures and texts that meet user needs. The platform publishing module automatically publishes the generated marketing videos and pictures and texts to various social media and online platforms, such as WeChat, Weibo, Douyin, Kuaishou, etc. The publishing process includes content format adaptation and publishing time optimization. The data analysis module collects and analyzes user behavior data of each car company's marketing video and car company's marketing pictures and texts. User behavior data includes click-through rate, conversion rate, number of user comments, and completion rate. The parameters of the video generation model and the picture generation model are adjusted according to excellent marketing content, thereby updating the AI ​​model. The present invention can update the AI ​​model based on the marketing content of the car company itself, avoid the generated content not meeting the actual situation of the car company, and improve the marketing effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0036] Figure 1 It is a schematic diagram of the overall structure of an intelligent marketing system for automobile companies based on AI content operation according to the present invention.

[0037] Figure 2 It is a structural schematic diagram of a content scoring unit of an intelligent marketing system for automobile companies based on AI content operation of the present invention.

[0038] Figure 3It is a flow chart of an intelligent marketing method for automobile companies based on AI content operation of the present invention.

[0039] 101-data collection module, 102-model training module, 103-content generation module, 104-platform publishing module, 105-data analysis module, 106-strategy adjustment module, 107-market information collection unit, 108-digital media collection unit, 109-user intention collection unit, 110-content processing unit, 111-content publishing unit, 112-user behavior data collection unit, 113-content scoring unit, 114-screening unit, 115-click rate scoring sub-unit, 116-conversion rate scoring sub-unit, 117-comment scoring sub-unit, 118-completion rate scoring sub-unit. DETAILED DESCRIPTION

[0040] Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but should not be construed as limiting the present invention.

[0041] First, see Figure 1-Figure 2 ,in, Figure 1 It is a schematic diagram of the overall structure of an intelligent marketing system for automobile enterprises based on AI content operation of the present invention. Figure 2 It is a structural schematic diagram of a content scoring unit of an intelligent marketing system for automobile companies based on AI content operation of the present invention.

[0042] The present invention provides an intelligent marketing system for automobile enterprises based on AI content operation, including a data collection module 101, a model training module 102, a content generation module 103, a platform publishing module 104, a data analysis module 105 and a strategy adjustment module 106;

[0043] The data collection module 101, the model training module 102, the content generation module 103, the platform publishing module 104, the data analysis module 105 and the strategy adjustment module 106 are connected in sequence;

[0044] The data collection module 101 is used to collect automobile market data;

[0045] The model training module 102 is used to train the AI ​​model based on the collected automobile market data to obtain a video generation model that can automatically generate automobile enterprise marketing videos, and a picture and text generation model that can automatically generate automobile enterprise marketing pictures and texts;

[0046] The content generation module 103 is used to call the video generation model and the picture and text generation model to generate automobile enterprise marketing videos and automobile enterprise marketing pictures and texts according to user needs;

[0047] The platform publishing module 104 is used to automatically publish the generated automobile enterprise marketing videos and automobile enterprise marketing graphics to various social media and online platforms;

[0048] The data analysis module 105 is used to collect and analyze the data after each automobile enterprise marketing video and automobile enterprise marketing graphic is released to obtain excellent marketing content;

[0049] The strategy adjustment module 106 is used to adjust the parameters of the video generation model and the image and text generation model according to excellent marketing content.

[0050] In this embodiment, the data collection module 101 obtains the latest market trends, consumer preferences, competitor dynamics and other information by subscribing to automobile industry reports issued by professional market research institutions; uses social media tools to collect user discussions, evaluations, needs and other information about automobiles; collects user browsing, clicking, purchasing and other behavioral data through websites, APPs and other channels, analyzes user interests, needs and purchase intentions; designs and publishes online questionnaires to collect target users' specific needs, preferences and improvement suggestions for automobile products. The model training module 102 uses deep learning technology, such as convolutional neural network (CNN), recurrent neural network (RNN) and generative adversarial network (GAN), etc., to construct a video generation model and a picture and text generation model. The video generation model collects a large number of automobile advertising videos and uses video frame sequences for training, so that the model can generate coherent and attractive automobile marketing videos. The picture and text generation model is based on keywords or reference pictures provided by users, and the training model generates automobile marketing pictures and texts that meet user needs. The content generation module 103 generates personalized car marketing videos based on the car model, color, configuration and other information input by the user, and the system calls the video generation model. Based on the user input of keywords or uploaded reference pictures, the system calls the picture generation model to generate car marketing pictures and texts that meet the user's needs. The platform publishing module 104 automatically publishes the generated marketing videos and pictures and texts to various social media and online platforms, such as WeChat, Weibo, Douyin, Kuaishou, etc. The publishing process includes content format adaptation and publishing time optimization. The data analysis module 105 collects and analyzes the user behavior data of each car company's marketing video and car company's marketing pictures and texts. The user behavior data includes click-through rate, conversion rate, number of user comments and completion rate. The parameters of the video generation model and the picture generation model are adjusted according to the excellent marketing content, so as to update the AI ​​model. The present invention can update the AI ​​model according to the marketing content of the car company itself, avoid the generated content not meeting the actual situation of the car company, and improve the marketing effect.

[0051] Further, the data collection module 101 includes a market information collection unit 107 and a digital media collection unit 108;

[0052] The market information collection unit 107 is used to obtain market trends, consumer preferences and competitor dynamic information of the automotive industry;

[0053] The digital media collection unit 108 is used to collect popular videos and pictures related to automobile companies from various social media and online platforms.

[0054] In this embodiment, the market information collection unit 107 obtains the latest market trends, consumer preferences, competitor dynamics and other information by subscribing to automobile industry reports issued by professional market research institutions; designs and publishes online questionnaires to collect target users' specific needs, preferences and improvement suggestions for automobile products. The digital media collection unit 108 collects popular videos and pictures related to automobile companies from various social media and online platforms such as Weibo hot searches, Douyin topics, and Xiaohongshu notes.

[0055] Furthermore, the data collection module 101 also includes a user intention collection unit 109;

[0056] The user intention collection unit 109 is used to collect the user's interests, needs and purchase intentions regarding automobiles.

[0057] In this embodiment, the user intention collection unit 109 collects user browsing, clicking, purchasing and other behavior data through channels such as websites and apps, and analyzes user interests, needs and purchasing intentions.

[0058] Further, the platform publishing module 104 includes a content processing unit 110 and a content publishing unit 111; the content publishing unit 111 is connected to the content processing unit 110;

[0059] The content processing unit 110 is used to adjust the format of the generated automobile enterprise marketing video and automobile enterprise marketing graphics to adapt them to different social media and online platforms;

[0060] The content publishing unit 111 is used to formulate publishing strategies for various social media and online platforms based on user portraits and platform active time, and automatically publish automobile enterprise marketing videos and automobile enterprise marketing graphics to various social media and online platforms according to the publishing strategies.

[0061] In this embodiment, the content processing unit 110 adjusts the format and size of the generated automobile enterprise marketing content according to the characteristics of platforms such as Weibo, Douyin, and Kuaishou, to ensure that the content can be well displayed on platforms such as Weibo, Douyin, and Kuaishou. The content publishing unit 111 formulates personalized publishing strategies based on data such as user portraits and platform active time, such as selecting time periods with high user activity to publish content to increase content exposure.

[0062] Further, the data analysis module 105 includes a user behavior data collection unit 112, a content scoring unit 113 and a screening unit 114; the user behavior data collection unit 112, the content scoring unit 113 and the screening unit 114 are connected in sequence;

[0063] The user behavior data collection unit 112 is used to collect user behavior data of each automobile enterprise marketing video and automobile enterprise marketing graphic, and the user behavior data includes click-through rate, conversion rate, number of user comments and completion rate;

[0064] The content scoring unit 113 is used to score each automobile enterprise marketing video and automobile enterprise marketing graphic according to the user behavior data;

[0065] The screening unit 114 is used to compare the scores of the automobile enterprise marketing videos and automobile enterprise marketing pictures and texts with a preset threshold value. When the actual score is greater than the preset threshold value, the content is identified as excellent marketing content.

[0066] In this embodiment, the user behavior data collection unit 112 collects user behavior data of each automobile company's marketing video and automobile company's marketing pictures and texts, and the user behavior data includes click-through rate, conversion rate, number of user comments and completion rate. The content scoring unit 113 scores each automobile company's marketing video and automobile company's marketing pictures and texts according to the click-through rate, conversion rate, number of user comments and completion rate. The screening unit 114 compares the scores of the automobile company's marketing videos and automobile company's marketing pictures and texts with a preset threshold. When the actual score is greater than the preset threshold, the content is identified as excellent marketing content. The excellent marketing content is used as data to update the video generation model and the picture generation model to make them conform to the situation of each automobile company.

[0067] Further, the content scoring unit 113 includes a click rate scoring subunit 115 and a conversion rate scoring subunit 116;

[0068] The click rate scoring subunit 115 is used to compare the click rate of the automobile enterprise marketing video and automobile enterprise marketing graphic with a preset threshold value. When the click rate is greater than the preset threshold value, it is recorded as 1, otherwise it is recorded as 0;

[0069] The conversion rate scoring subunit 116 is used to compare the conversion rate of the automobile enterprise marketing video and automobile enterprise marketing graphics with a preset threshold value. When the conversion rate is greater than the preset threshold value, it is recorded as 1, otherwise it is recorded as 0.

[0070] In this embodiment, the click-through rate scoring subunit 115 compares the click-through rate of the car company's marketing videos and car company's marketing graphics with a preset threshold. When the click-through rate is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0. The standards of each platform are different. For example, the click-through rate threshold of marketing content posted to Douyin can be set to 4%, and content exceeding 4% is recorded as 1. The conversion rate scoring subunit 116 compares the conversion rate of the car company's marketing videos and car company's marketing graphics with a preset threshold. When the conversion rate is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0. For example, the conversion rate threshold of marketing content posted to Douyin and Kuaishou can be set to 15%.

[0071] Furthermore, the content scoring unit 113 also includes a comment scoring subunit 117;

[0072] The conversion rate scoring subunit 116 is used to compare the number of user comments on the automobile enterprise marketing video and automobile enterprise marketing graphics with a preset threshold. When the number of user comments is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0.

[0073] In this embodiment, the threshold number of user comments on the video and graphic marketing content posted to Douyin can be set to 1w, and the marketing content with more than 1w user comments is recorded as 1.

[0074] Furthermore, the content scoring unit 113 also includes a completion rate scoring subunit 118;

[0075] The completion rate scoring subunit 118 is used to compare the completion rate of the automobile enterprise marketing video and automobile enterprise marketing graphics with a preset threshold value. When the completion rate is greater than the preset threshold value, it is recorded as 1, otherwise it is recorded as 0.

[0076] In this embodiment, the completion rate threshold of the video and graphic marketing content posted to Douyin can be set to 30%, and the marketing content with a completion rate exceeding 30% is recorded as 1.

[0077] The present invention provides an intelligent marketing system for automobile enterprises based on AI content operation, which obtains the latest market trends, consumer preferences, competitor dynamics and other information by subscribing to automobile industry reports released by professional market research institutions; uses social media tools to collect user discussions, evaluations, needs and other information about automobiles; collects user browsing, clicking, purchasing and other behavioral data through websites, APPs and other channels, analyzes user interests, needs and purchase intentions; designs and publishes online questionnaires to collect target users' specific needs, preferences and improvement suggestions for automobile products. The model training module 102 uses deep learning technologies such as convolutional neural networks (CNN), recurrent neural networks (RNN) and generative adversarial networks (GAN) to construct video generation models and image generation models; according to the user input of automobile model, color, configuration and other information, the system calls the video generation model to generate personalized automobile marketing videos; according to the user input of keywords or upload of reference pictures, the system calls the image generation model to generate automobile marketing pictures and texts that meet user needs. The platform publishing module 104 automatically publishes the generated marketing videos and pictures and texts to various social media and online platforms, such as WeChat, Weibo, Douyin, Kuaishou, etc. The publishing process includes content format adaptation and publishing time optimization. The data analysis module 105 collects and analyzes the user behavior data of each automobile enterprise's marketing video and automobile enterprise's marketing graphics and texts, and scores each automobile enterprise's marketing video and automobile enterprise's marketing graphics and texts according to the click-through rate, conversion rate, number of user comments and completion rate. There are four items in total, namely, click-through rate, conversion rate, number of user comments and completion rate. The four scores of the same marketing content are added together, and when it is greater than 2, it is evaluated as excellent marketing content. Subsequently, the parameters of the video generation model and the graphic generation model are adjusted according to the excellent marketing content, thereby updating the AI ​​model. The present invention can update the AI ​​model according to the marketing content of the automobile enterprise itself, avoid the generated content not conforming to the actual situation of the automobile enterprise, and improve the marketing effect.

[0078] Second, see Figure 3 , Figure 3 It is a flow chart of an intelligent marketing method for automobile companies based on AI content operation of the present invention.

[0079] The present invention also provides an intelligent marketing method for automobile enterprises based on AI content operation, including:

[0080] S1 collects automobile market data through the data collection module 101;

[0081] S2 trains the AI ​​model according to the collected automobile market data through the model training module 102 to obtain a video generation model capable of automatically generating automobile enterprise marketing videos, and a picture and text generation model capable of automatically generating automobile enterprise marketing pictures and texts;

[0082] S3 generates a car enterprise marketing video and car enterprise marketing pictures and texts by calling a video generation model and a picture and text generation model according to user needs through the content generation module 103;

[0083] S4 automatically publishes the generated automobile enterprise marketing video and automobile enterprise marketing pictures and texts to various social media and online platforms through the platform publishing module 104;

[0084] S5 collects and analyzes the data of each automobile enterprise's marketing video and automobile enterprise's marketing graphics and texts after they are released through the data analysis module 105 to obtain excellent marketing content;

[0085] S6 adjusts the parameters of the video generation model and the image and text generation model according to the excellent marketing content through the strategy adjustment module 106.

[0086] The present invention discloses an intelligent marketing method for automobile enterprises based on AI content operation. The data collection module 101 obtains the latest market trends, consumer preferences, competitor dynamics and other information by subscribing to automobile industry reports issued by professional market research institutions; collects user discussions, evaluations, needs and other information about automobiles by using social media tools; collects user browsing, clicking, purchasing and other behavioral data through websites, APPs and other channels, analyzes user interests, needs and purchase intentions; designs and publishes online questionnaires to collect target users' specific needs, preferences and improvement suggestions for automobile products. The model training module 102 uses deep learning technology, such as convolutional neural network (CNN), recurrent neural network (RNN) and generative adversarial network (GAN), etc., to construct a video generation model and a picture and text generation model. The video generation model collects a large number of automobile advertising videos and uses video frame sequences for training, so that the model can generate a coherent and attractive automobile marketing video. The picture and text generation model is based on keywords or reference pictures provided by users, and the training model generates automobile marketing pictures and texts that meet user needs. The content generation module 103 generates personalized car marketing videos based on the car model, color, configuration and other information input by the user, and the system calls the video generation model. Based on the user input of keywords or uploaded reference pictures, the system calls the picture generation model to generate car marketing pictures and texts that meet the user's needs. The platform publishing module 104 automatically publishes the generated marketing videos and pictures and texts to various social media and online platforms, such as WeChat, Weibo, Douyin, Kuaishou, etc. The publishing process includes content format adaptation and publishing time optimization. The data analysis module 105 collects and analyzes the user behavior data of each car company's marketing video and car company's marketing pictures and texts. The user behavior data includes click-through rate, conversion rate, number of user comments and completion rate. The parameters of the video generation model and the picture generation model are adjusted according to the excellent marketing content, so as to update the AI ​​model. The present invention can update the AI ​​model according to the marketing content of the car company itself, avoid the generated content not meeting the actual situation of the car company, and improve the marketing effect.

[0087] What is disclosed above is only one or more preferred embodiments of the present application, and cannot be used to limit the scope of rights of the present application. Ordinary technicians in this field can understand that all or part of the processes of implementing the above embodiments and equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. An intelligent marketing system for automobile enterprises based on AI content operation, characterized in that: It includes data collection module, model training module, content generation module, platform publishing module, data analysis module and strategy adjustment module; The data acquisition module, the model training module, the content generation module, the platform publishing module, the data analysis module and the strategy adjustment module are connected in sequence; The data acquisition module is used to collect automobile market data; The model training module is used to train the AI ​​model based on the collected automobile market data to obtain a video generation model that can automatically generate automobile enterprise marketing videos, and a picture and text generation model that can automatically generate automobile enterprise marketing pictures and texts; The content generation module is used to call the video generation model and the picture and text generation model to generate automobile enterprise marketing videos and automobile enterprise marketing pictures and texts according to user needs; The platform publishing module is used to automatically publish the generated automobile enterprise marketing videos and automobile enterprise marketing pictures and texts to various social media and online platforms; The data analysis module is used to collect and analyze the data after each car company's marketing video and car company's marketing graphics are released to obtain excellent marketing content; The strategy adjustment module is used to adjust the parameters of the video generation model and the image and text generation model according to excellent marketing content.

2. The intelligent marketing system for automobile enterprises based on AI content operation as claimed in claim 1, characterized in that: The platform publishing module includes a content processing unit and a content publishing unit; the content publishing unit is connected to the content processing unit; The content processing unit is used to adjust the format of the generated automobile enterprise marketing video and automobile enterprise marketing graphics to adapt them to different social media and online platforms; The content publishing unit is used to formulate publishing strategies for various social media and online platforms based on user portraits and platform active time, and automatically publish automobile enterprise marketing videos and automobile enterprise marketing graphics to various social media and online platforms according to the publishing strategies.

3. The intelligent marketing system for automobile enterprises based on AI content operation as claimed in claim 2, characterized in that: The data analysis module includes a user behavior data collection unit, a content scoring unit and a screening unit; the user behavior data collection unit, the content scoring unit and the screening unit are connected in sequence; The user behavior data collection unit is used to collect user behavior data of each automobile enterprise marketing video and automobile enterprise marketing graphic, and the user behavior data includes click-through rate, conversion rate, number of user comments and completion rate; The content scoring unit is used to score each automobile enterprise marketing video and automobile enterprise marketing graphic according to user behavior data; The screening unit is used to compare the scores of the automobile enterprise marketing videos and automobile enterprise marketing pictures and texts with a preset threshold value. When the actual score is greater than the preset threshold value, the content is identified as excellent marketing content.

4. The intelligent marketing system for automobile enterprises based on AI content operation as claimed in claim 3, characterized in that: The content scoring unit includes a click rate scoring subunit and a conversion rate scoring subunit; The click-through rate scoring subunit is used to compare the click-through rate of the automobile enterprise marketing video and automobile enterprise marketing graphic with a preset threshold value. When the click-through rate is greater than the preset threshold value, it is recorded as 1, otherwise it is recorded as 0; The conversion rate scoring subunit is used to compare the conversion rate of the automobile enterprise marketing video and automobile enterprise marketing pictures and texts with a preset threshold. When the conversion rate is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0.

5. The intelligent marketing system for automobile enterprises based on AI content operation as claimed in claim 4, characterized in that: The content scoring unit also includes a review scoring subunit; The conversion rate scoring subunit is used to compare the number of user comments on the automobile enterprise marketing video and automobile enterprise marketing graphic with a preset threshold. When the number of user comments is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0.

6. The intelligent marketing system for automobile enterprises based on AI content operation as claimed in claim 5, characterized in that: The content scoring unit also includes a completion rate scoring subunit; The completion rate scoring subunit is used to compare the completion rate of the automobile enterprise marketing video and automobile enterprise marketing graphics with a preset threshold. When the completion rate is greater than the preset threshold, it is recorded as 1, otherwise it is recorded as 0.

7. An intelligent marketing method for automobile enterprises based on AI content operation, applied to an intelligent marketing system for automobile enterprises based on AI content operation as claimed in any one of claims 1 to 6, characterized in that: include: Collect automobile market data through data collection module; The model training module trains the AI ​​model based on the collected automobile market data to obtain a video generation model that can automatically generate automobile enterprise marketing videos, and a picture and text generation model that can automatically generate automobile enterprise marketing pictures and texts; Through the content generation module, according to user needs, the video generation model and the picture and text generation model are called to generate automobile enterprise marketing videos and automobile enterprise marketing pictures and texts; The generated car enterprise marketing videos and car enterprise marketing pictures and texts are automatically published to various social media and online platforms through the platform publishing module; The data analysis module collects and analyzes the data of each car company's marketing video and marketing graphics after they are released to obtain excellent marketing content; The strategy adjustment module is used to adjust the parameters of the video generation model and the image and text generation model based on excellent marketing content.

Images