Deep Research

When you activate Deep Research, ChatGPT does not just run a single web search. It performs multi-step research across multiple sources, following leads the way a human researcher would:

1. You submit your research question -- a topic, a comparison, a market question, anything that requires depth.

2. ChatGPT generates a research plan -- an outline of what it intends to investigate, which angles it will cover, and what sources it will look for.

3. You review and edit the plan -- you can add focus areas, remove irrelevant sections, or redirect the investigation before it begins.

4. The agent browses and reads -- it visits dozens of web pages, extracts relevant information, and takes notes. You can watch its progress in real time.

5. It synthesizes and delivers -- the final output is a structured report with inline citations linking back to every source it used.

Deep Research can take anywhere from a few minutes to over 30 minutes depending on the complexity of the question. It is designed for quality, not speed.

One of the most powerful aspects of Deep Research is that you control the plan before it runs. This is where most people miss an opportunity. Instead of accepting the default plan, take a moment to shape it:

Add specificity. If you are researching a market, tell it to focus on your specific segment. "Focus on B2B SaaS companies with 50-200 employees" is far more useful than "research the SaaS market."

Remove noise. If the plan includes sections you do not care about, remove them. Fewer sections means deeper coverage on what matters.

Specify source types. You can tell Deep Research to prioritize certain kinds of sources: "Focus on peer-reviewed studies and government reports" or "Prioritize recent articles from the last 6 months."

Direct to specific sites. You can instruct Deep Research to look at particular websites or connected apps like Google Drive and OneDrive. For example: "Check our company's Google Drive for last quarter's sales data and compare it with public market reports."

While Deep Research is running, you can watch its progress in real time. ChatGPT shows you:

- Which sources it is currently reading

- What information it has gathered so far

- How far along it is in the research plan

You can also redirect the research mid-run. If you notice it is going down an unproductive path, you can step in and say "skip this section and focus more on competitor pricing" or "I need more data on the European market specifically." The agent will adjust its approach accordingly.

This makes Deep Research feel less like a black box and more like a collaborative process. You are the director; ChatGPT is the researcher doing the legwork.

Deep Research shines when you need depth, breadth, and citations. Here are the use cases where it delivers the most value:

Strategy reports. Competitive landscape analysis, market entry research, technology evaluations. Deep Research can compare multiple companies, products, or approaches across dozens of sources.

Literature reviews. Academic and professional literature surveys. It can find and summarize relevant papers, articles, and reports on any topic.

Market analysis. Pricing comparisons, feature matrices, customer sentiment analysis. It pulls data from review sites, pricing pages, and industry reports.

Due diligence. Investigating companies, technologies, or partnerships. It digs into public information, news coverage, and expert commentary.

Travel and event planning. Detailed itineraries with pricing, reviews, and logistics pulled from multiple travel sources.

Learning new domains. When you need to quickly get up to speed on an unfamiliar field, Deep Research gives you a structured overview with pointers to the best sources.

The common thread: any time a simple answer is not enough and you need a well-researched, well-cited document, Deep Research is the right tool.