Deep Research Function in Generative AI: Its Structure and Impact on SEO

Target Audience

• Web Developers and Digital Marketers: Those who want to understand the latest AI features and leverage them for website management
• Corporate Web Administrators: Those seeking to update their SEO strategies to align with the latest AI technologies
• AI Enthusiasts: Those interested in the details and working principles of the Deep Research function

1. What Is the Deep Research Function?

Deep Research is the latest research agent feature added to ChatGPT by OpenAI. This feature aims to automatically gather and analyze data from multiple sources to generate comprehensive research reports in a short time.

2. How Deep Research Works

① Automating Multi-Step Research

Deep Research automates the research process through the following steps:

1. Web Search and Information Collection: AI autonomously crawls relevant websites to obtain the latest information and necessary data.
2. File Analysis and Text Summarization: It analyzes various data formats such as PDFs, images, and spreadsheets, summarizing key information.
3. Advanced Data Analysis Using Python Code: Using its built-in Python tools, AI quickly performs statistical analysis of numerical data and generates graphs.

② Crawling Timing and Frequency

Deep Research collects relevant information from the web in real-time when receiving a prompt (question or instruction) from the user. While the specific timing and frequency of crawling are not disclosed, it is designed to dynamically retrieve the necessary information according to the user’s request.

3. Impact on SEO and Countermeasures

① Providing High-Quality Content

Generative AI like Deep Research generates responses by summarizing key points from multiple sources. Therefore, offering high-quality content that effectively answers user questions is essential to gain better recognition from AI.

② Optimizing Headings and Structure

AI prefers clear headings and paragraph structures for efficient information analysis. Use Q&A formats and headings for each paragraph to make the content easily understandable at a glance.

③ Using a Conclusion-First Structure

Present the main topic that users want to know at the beginning, followed by detailed explanations. This “conclusion-first” structure helps AI quickly grasp the key points.

④ Addressing Related Questions

Since users often ask follow-up questions, placing a “Frequently Asked Questions (FAQ)” section at the end of articles to answer related additional questions can improve AI response accuracy.

⑤ Enhancing E-E-A-T

AI prioritizes reliable sources. Provide content that demonstrates Expertise, Authoritativeness, Trustworthiness, and Experience (E-E-A-T) to gain better recognition from AI.

4. Conclusion

With the advent of Deep Research, the process by which AI collects and analyzes information from the web has become more advanced. As a result, website operators and digital marketers must provide content that benefits both AI and users. Focus on delivering high-quality information, maintaining a clear structure, and ensuring reliability to keep up with the latest AI technologies and optimize your website for better performance.