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Barry Eichhorn - BE Digital

Written by

Owner & AI Advisor

Updated on 23 April 2025

When do you use deep research in ChatGPT?

Within ChatGPT you'll find more and more functions that go beyond asking a simple question. One of them is deep research. This function is designed specifically for those who really want to go in depth: when preparing strategic choices, analysing complex topics or structuring substantively strong content. In this article you'll read when to use deep research, what exactly it does and how to use it to reach better insights faster as a professional.

What is the deep research function in ChatGPT?

Deep research is a function within ChatGPT (available from GPT-4o and higher) that makes it possible to get longer, structured and well-substantiated answers to complex questions. The model stays within one topic for longer, recognises connections better and can switch more quickly between different angles.
Where a standard prompt often leads to a short and general answer, deep research is intended for users who:
  • Want to form a strategy
  • Need to substantiate choices
  • Want insight into trends, market movements or subject matter
  • Or want to create content that doesn't stop at the first paragraph

When do you use deep research in ChatGPT?

The deep research function is particularly suited to situations where you want to think beyond the first Google page or superficial answers. Think of:
  • Strategic exploration For example: “What are emerging revenue models in the AI software market?”
  • Competitor or market analyses Have ChatGPT compare marketplaces, structure strengths and weaknesses or summarise customer needs.
  • Preparing for positioning or a relaunch “Which brands are positioning themselves in Europe as sustainable SaaS players?”
  • Substantive briefing for a campaign or article “What trends are there in e-learning for the healthcare sector and how do target audiences respond to them?”
So you mainly use deep research when you need substance to make decisions or develop persuasive communication.

What makes deep research different from ‘just looking something up’?

The difference lies not in the searching, but in the processing of information. You can see it like this:
  1. The model approaches a topic more broadly, giving an overview and diving into the detail.
  2. You can ask follow-up questions, have scenarios worked out and have summaries generated.
  3. It works with a longer context, which makes answers more consistent.
  4. The output is easier to structure into formats such as SWOT analyses, plans, tables or positioning maps.
In short: you don't just get information, but also structure and coherence.

How to use deep research in practice

If you work with deep research, you get the most out of this function by using it in steps:

1. Ask a focused main question

For example:
“What are the key considerations for an SME to implement generative AI within its marketing department?”

2. Provide context

Briefly tell it something about your situation, target audience or role. This increases the relevance of the answer.

3. Ask for structure

For example:
“Can you structure this into opportunities, risks and practical steps for implementation?”

4. Work in iterations

Have ChatGPT go deeper per sub-topic. Ask follow-up questions. Have it develop a chapter, piece of advice or segment.

5. Have it summarise and convert

Ask the model to summarise everything in a format you can use, such as a presentation outline, content plan or policy memo.

Best practices for using deep research effectively

  • Work from scenarios or hypotheses Have the model work out different routes (“What if we follow option A versus option B?”).
  • Use it as preparation, not as an end product Deep research helps you think, but you remain responsible for interpretation.
  • Combine it with a trained GPT Have you had a GPT trained on your tone of voice, market information or customer knowledge? Then the output becomes even more useful.

What BE Digital can do for you

At BE Digital we help companies implement AI smartly in their work processes. Deep research is a powerful part of that. We build GPTs that don't just write, but really think along with you, based on your specific context and goals.
With the BE Digital scan we look at:
  • Which departments can use deep research straight away
  • Where you can train AI assistants for recurring analyses
  • How to set up work processes in which AI and strategy reinforce each other
Request the free BE Digital scan and discover where deep research makes your work smarter, faster and stronger in substance.

Frequently asked questions

What is deep research in ChatGPT?

Deep research is a feature in ChatGPT (available from GPT-4o and higher) that gives you longer, structured and well-founded answers to complex questions. The model stays within one topic for longer, recognises connections better and switches more quickly between angles.

When should you use deep research in ChatGPT?

Use it when you want to think beyond the first Google page, for example for strategic exploration, competitor or market analyses, preparing a positioning or relaunch, and substantive briefings for a campaign or article. It suits you best when you need content to make decisions or develop persuasive communication.

How do I use deep research in practice?

Work in steps: ask a focused main question, give context about your situation, target group or role and ask for structure. Then work in iterations with follow-up questions per sub-topic. Finally, have the model summarise everything in a usable format, such as a presentation outline, content plan or policy memo.

How does deep research differ from simply looking something up?

The difference lies in how information is processed, not in the searching. The model tackles a topic more broadly, works with a longer context and lets you ask follow-up questions and develop scenarios. The output is easy to structure in formats such as SWOT analyses, plans and tables.

Barry Eichhorn - BE Digital

About the author

Owner & AI Advisor

Barry Eichhorn is the owner of BE Digital and advises organisations on digital strategy, AI and online growth. With more than 10 years of experience, he helps business owners and teams put technology to practical use and make digital choices that contribute to sustainable growth.