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Competitor Media Strategy & Content Value Analysis
Ad Info provides insights into market volume, content, and interactive effectiveness of various brands within the industry. It utilizes real consumer sample data, allowing advertisers to stay informed about the market share, advertising performance, and creative effectiveness of the overall market, industry peers, and competitors.
Why Ad Info?
Reliable Data Sources
Real consumer sample data with over 10,000 active samples collected.
Advanced Technological Capabilities
Continuously optimizing algorithms to provide more precise insights
Enhanced AI Model Capabilities
Combines the power of large-scale models to support applications such as label expansion, creative generation, and media guidance.
01
Utilizing Miaozhen’s unique real consumer behavioral sample data, which is collected across various industries, media types, and data categories, providing broader insights.
Collection of Real Consumer Data: 1-to-1 privacy agreements, mature recruitment processes, and sophisticated user selection/refinement algorithms.
Comprehensive Coverage: Monitoring of 260+ apps, comprehensive IN-APP data collection, and long-term continuous behavior tracking.
Multi-dimensional Data Collection Empowering Data-driven Decision-making: Advertising monitoring, social media content monitoring, media consumption habits tracking, e-commerce behavior monitoring, and more, covering the entire industry and media landscape.
02
Utilizing Big Data, Artificial Intelligence, and Machine Learning to Continuously Optimize Algorithms for More Precision
Identification of Advertising Data Elements: Applying NLP (Natural Language Processing), OCR (Optical Character Recognition), ASR (Automatic Speech Recognition), ACR (Automatic Content Recognition), and other technologies to accurately identify elements within the captured advertising data.
Iterative Algorithm Optimization: Iteratively optimizing machine learning and parameter training for large-scale data models through tens of thousands of iterations.
03
Leveraging the latest advancements in LLM and AIGC to enhance data capabilities, applied in areas such as label expansion, creative generation, and media guidance.
Label Expansion for Content: Expanding content labels such as spokesperson, scene, selling points, audience labels, and more.
Automated Creative Content Generation: Combining AIGC capabilities to analyze historical high-quality advertising content and extract key elements for automated creative content generation.
Automated Media Strategy Generation: Leveraging large language models to support automatic generation of media strategies (such as budget allocation recommendations for media channels and targeted audience features) based on user input requirements, providing guidance for advertising campaigns.
It currently covers hard advertising media touchpoints, which refer to advertisements that comply with advertising regulations and are labeled as “advertisements.” This includes splash screens, information feeds, video overlays, banners, and more.
It supports querying based on dimensions such as terminals, media, advertising formats, industries, brands, regions, and more. The metrics supported include exposure ratio, cost, effective interaction rate, clicks, and more.
The data is updated on a monthly basis.
Yes, it not only allows users to view complete creative content but also supports AI analysis of the content, providing strategic guidance for content delivery.
