Automatic video generation method based on marketing scene

Abstract

The invention relates to the technical field of marketing, and discloses an automatic video generation method based on a marketing scene. According to the invention, personalized marketing videos can be generated according to different marketing scenes and user requirements, the pertinence and attraction of the videos are improved, and the marketing effect is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of marketing technology, and more specifically, to a method for automatically generating videos based on marketing scenarios. Background Art

[0002] In the current market environment, marketing videos have become an important means for companies to promote their products and services. However, traditional video production methods require a professional video production team, involving multiple complex links such as script writing, shooting, editing, and adding special effects, with a long production cycle and high costs. Moreover, for different marketing scenarios, such as new product launches, holiday promotions, brand promotions, etc., videos of different styles and contents need to be produced, which further increases the difficulty and workload of production.

[0003] With the development of artificial intelligence technology, although some automated video production tools have emerged, most of them have single functions and are unable to accurately create and customize video content according to complex and changeable marketing scenarios, making it difficult to meet the diverse marketing needs of enterprises. For this reason, we propose an automated video generation method based on marketing scenarios. Summary of the invention

[0004] In order to overcome the deficiencies of the prior art, the present invention provides a method for automatically generating videos based on marketing scenarios to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a method for automatically generating videos based on marketing scenarios, comprising the following steps;

[0006] S1: Marketing scenario identification and classification;

[0007] (1) Data collection: Collect the company’s past marketing activity data, as well as various marketing video cases on the market, and analyze their scene characteristics and elements.

[0008] (2) Scenario classification model construction: Using machine learning algorithms, marketing scenarios are divided into multiple categories such as new product launches, holiday promotions, brand stories, user cases, etc., and corresponding feature labels are set for each category.

[0009] (3) Real-time scenario recognition: When a new marketing demand is input, key information is extracted through natural language processing technology, and the constructed scenario classification model is used for real-time recognition to determine the marketing scenario category to which it belongs.

[0010] S2: Material library construction and management;

[0011] (1) Material collection: Collect a wide range of video materials, as well as copywriting materials related to different marketing scenarios, such as slogans, product introductions, etc.

[0012] (2) Material annotation and classification: The collected materials are annotated in detail. According to the annotation information, the materials are classified and stored in different databases to establish a structured material library.

[0013] (3) Material update and maintenance: Regularly update the material library, add new materials, and eliminate outdated or low-quality materials. At the same time, according to user feedback and usage data, optimize the annotation and classification of materials to improve the retrieval efficiency and accuracy of materials.

[0014] S3: Automatic script generation;

[0015] (1) Script template design: Design corresponding script templates for different marketing scenarios.

[0016] (2) Parametric generation: According to the identified marketing scenario category, select the corresponding template from the script template library. Then, combine the input marketing requirements and relevant materials in the material library to generate specific script content in a parametric way.

[0017] (3) Script optimization and review: Use natural language processing and image recognition technologies to preliminarily optimize the generated script, check for grammar errors, logical coherence of the pictures, etc., and provide an interface for manual review, allowing marketers to conduct a final review and modification of the script to ensure that the script meets the marketing goals and brand image.

[0018] S4: Video synthesis and special effect addition;

[0019] (1) Video synthesis: According to the generated script, extract corresponding materials such as videos, pictures, and audio from the material library, and perform video synthesis in accordance with the order and requirements of the script. Use the automated interface of video editing software to achieve fast splicing, cutting, and synthesis of videos.

[0020] (2) Special effect addition: Automatically add corresponding special effects according to the needs of the marketing scenario and video style, such as transition effects, animation effects, subtitle effects, etc.

[0021] (3) Video rendering and output: After completing video synthesis and special effect addition, perform rendering processing on the video, select appropriate video formats, resolutions, and frame rates, output high-quality marketing videos, and provide a video preview function to facilitate users to conduct a final check and adjustment before output.

[0022] As a preferred technical solution of the present invention, the marketing activity data includes activity themes, target audiences, marketing effects, etc.

[0023] As a preferred technical solution of the present invention, the video materials include enterprise product display videos, brand promotion clips, animation materials, music materials, picture materials, etc.

[0024] As a preferred technical solution of the present invention, the marked content includes the theme, style, applicable scenarios, duration, key elements, etc. of the material.

[0025] As a preferred technical solution of the present invention, the script template includes basic elements such as the structural framework of the video, the order of shots, the description of the pictures, the content of the lines, the music and sound effects, etc.

[0026] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0027] 1. The present invention can generate personalized marketing videos according to different marketing scenarios and user needs, improve the pertinence and attractiveness of the videos, and enhance the marketing effect.

[0028] 2. The present invention can quickly modify and update the video content according to market feedback and the adjustment of marketing goals, and realize the dynamic optimization and iteration of marketing videos.

[0029] 3. The present invention can reduce the dependence on professional video production teams, reduce labor costs and production costs, and is especially suitable for small and medium-sized enterprises and marketing activities with limited budgets. Specific Embodiments

[0030] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0031] The present invention provides a method for automatically generating videos based on marketing scenarios, including the following steps;

[0032] S1: Marketing scenario recognition and classification;

[0033] (1) Data collection: Collect the data of the enterprise's past marketing activities, and at the same time collect various marketing video cases in the market, and analyze their scenario characteristics and elements.

[0034] (2) Construction of a scenario classification model: Use machine learning algorithms to classify marketing scenarios into multiple categories such as new product launches, festival promotions, brand stories, user cases, etc., and set corresponding feature tags for each category.

[0035] (3) Real-time scenario recognition: When a new marketing requirement is input, extract key information through natural language processing technology, and use the constructed scenario classification model for real-time recognition to determine the category of the marketing scenario to which it belongs.

[0036] Scenario data collection and collation: Collect at least 1000 pieces of data on marketing campaign cases of different types, including campaign planning documents, execution reports, video materials, etc. Clean and label the data to establish a marketing scenario dataset.

[0037] Material collection and annotation: Collect no less than 5000 video materials of various types, no less than 10000 image materials, no less than 2000 music materials, and no less than 3000 copywriting materials. Use professional annotation tools to annotate the materials in detail, and store the annotation information in a relational database (such as MySQL).

[0038] S2: Material library construction and management;

[0039] (1) Material collection: Widely collect various video materials, and at the same time collect copywriting materials related to different marketing scenarios, such as promotional slogans, product introduction copywriting, etc.

[0040] (2) Material annotation and classification: Annotate the collected materials in detail. According to the annotation information, classify and store the materials in different databases to establish a structured material library.

[0041] (3) Material update and maintenance: Regularly update the material library, add new materials, eliminate outdated or low-quality materials. At the same time, according to user feedback and usage data, optimize the annotation and classification of materials to improve the retrieval efficiency and accuracy of materials.

[0042] Scenario classification model training: Use machine learning libraries in Python (such as Scikit-learn), based on the marketing scenario dataset, train support vector machine (SVM) and random forest models, compare indicators such as accuracy and recall of the two, and select the model with the best performance as the marketing scenario classification model.

[0043] Script template design and optimization: Invite professional video script writers and marketing experts to jointly design more than 10 script templates for different marketing scenarios. Continuously optimize the structure and content of the script templates according to actual application feedback and data analysis.

[0044] S3: Automatic script generation;

[0045] (1) Script template design: Design corresponding script templates for different marketing scenarios.

[0046] (2) Parameterized generation: According to the identified marketing scenario category, select the corresponding template from the script template library. Then, combine the input marketing requirements and relevant materials in the material library to generate specific script content in a parameterized manner.

[0047] (3) Script optimization and review: Utilize natural language processing and image recognition technologies to initially optimize the generated script, check for grammar errors, logical coherence of the scenes, etc., and provide an interface for manual review, allowing marketers to conduct the final review and modification of the script to ensure that the script meets the marketing objectives and brand image.

[0048] S4: Video synthesis and special effect addition;

[0049] (1) Video synthesis: According to the generated script, extract corresponding video, picture, audio and other materials from the material library, and perform video synthesis in accordance with the order and requirements of the script. Utilize the automated interface of video editing software to achieve rapid splicing, editing and synthesis of the video.

[0050] (2) Special effect addition: Automatically add corresponding special effects according to the needs of the marketing scenario and video style, such as transition effects, animation effects, subtitle effects, etc.

[0051] (3) Video rendering and output: After completing video synthesis and special effect addition, perform rendering processing on the video, select appropriate video formats, resolutions and frame rates, output high-quality marketing videos, and provide a video preview function to facilitate users to conduct the final inspection and adjustment before output.

[0052] The present invention aims to provide a method for automatically generating marketing videos based on marketing scenarios. By integrating multi-source data and applying intelligent algorithms, it can quickly, efficiently and accurately generate personalized marketing videos according to different marketing scenarios, reduce the video production cost, and improve the marketing effect.

[0053] Among them, the marketing activity data includes activity themes, target audiences, marketing effects, etc.

[0054] Among them, the video materials include enterprise product display videos, brand promotion clips, animation materials, music materials, picture materials, etc.

[0055] Among them, the annotation content includes the theme, style, applicable scenario, duration, key elements, etc. of the materials.

[0056] Among them, the script template includes basic elements such as the structural framework of the video, the order of shots, scene descriptions, line content, music and sound effects.

[0057] The working principle and usage process of the present invention: It can generate personalized marketing videos according to different marketing scenarios and user needs, improve the pertinence and attractiveness of the videos, enhance the marketing effect, can quickly modify and update the video content according to market feedback and adjustments of marketing objectives, realize the dynamic optimization and iteration of marketing videos, can reduce the dependence on professional video production teams, lower the labor cost and production cost, and is especially suitable for small and medium-sized enterprises and marketing activities with limited budgets.

[0058] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0059] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for automatically generating videos based on marketing scenarios, characterized in that: The steps include: S1: Marketing scenario identification and classification; (1) Data collection: Collect the company’s past marketing activity data, as well as various marketing video cases on the market, and analyze their scene characteristics and elements. (2) Scenario classification model construction: Using machine learning algorithms, marketing scenarios are divided into multiple categories such as new product launches, holiday promotions, brand stories, user cases, etc., and corresponding feature labels are set for each category. (3) Real-time scenario recognition: When a new marketing demand is input, key information is extracted through natural language processing technology, and the constructed scenario classification model is used for real-time recognition to determine the marketing scenario category to which it belongs. S2: Material library construction and management; (1) Material collection: Collect a wide range of video materials, as well as copywriting materials related to different marketing scenarios, such as slogans, product introductions, etc. (2) Material labeling and classification: Detailed labeling of the collected materials is performed, and according to the labeling information, the materials are classified and stored in different databases to establish a structured material library. (3) Material update and maintenance: Regularly update the material library, add new materials, and eliminate outdated or low-quality materials. At the same time, optimize the labeling and classification of materials based on user feedback and usage data to improve the efficiency and accuracy of material retrieval. S3: script automatic generation; (1) Script template design: Design corresponding script templates for different marketing scenarios. (2) Parametric generation: Based on the identified marketing scenario category, the corresponding template is selected from the script template library. Then, the specific script content is generated in a parametric manner by combining the input marketing needs and the relevant materials in the material library. (3) Script optimization and review: Use natural language processing and image recognition technology to perform preliminary optimization on the generated scripts, check for grammatical errors, screen logic coherence, etc., and provide a manual review interface to allow marketers to conduct a final review and modification of the scripts to ensure that the scripts meet marketing goals and brand image. S4: video synthesis and special effects addition; (1) Video synthesis: According to the generated script, extract the corresponding video, picture, audio and other materials from the material library, perform video synthesis according to the order and requirements of the script, and use the automated interface of the video editing software to achieve rapid splicing, editing and synthesis of the video. (2) Adding special effects: Automatically add corresponding special effects according to the needs of marketing scenarios and video styles, such as transition effects, animation effects, subtitle effects, etc. (3) Video rendering and output: After completing video synthesis and adding special effects, the video is rendered and processed, and the appropriate video format, resolution, and frame rate are selected to output high-quality marketing videos. A video preview function is provided to facilitate users to make final checks and adjustments before output.

2. The video automatic generation method based on a marketing scenario according to claim 1, wherein: The marketing activity data includes activity theme, target audience, marketing effect, etc.

3. A method for automatically generating a video based on a marketing scenario according to claim 1, wherein: The video materials include corporate product display videos, brand promotion clips, animation materials, music materials, picture materials, etc.

4. A method for automatically generating videos based on a marketing scenario according to claim 1, characterized in that: The annotation content includes the theme, style, applicable scenarios, duration, key elements, etc. of the material.

5. The video automatic generation method based on a marketing scenario according to claim 1, wherein: The script template includes basic elements such as the structural framework of the video, the order of shots, the description of the scenes, the content of the lines, the music and sound effects, etc.