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AI & UX Research, BEST PRACTICES, UX QUALITY

Deep Research AI | How to use ChatGPT effectively for UX work

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4

MIN

Nov 25, 2025

Why does ChatGPT sometimes deliver brilliant analyses – and sometimes hot air?

Perhaps it's not just the model, but also your mode. Anyone who works with AI knows that sometimes it takes more than just a prompt. It takes depth, structure and context – especially when it comes to complex UX questions. This is exactly where Deep Research Mode comes in handy.

In this article, I'll show you:

  • what Deep Research Mode is (and what it isn't),

  • how it differs from other GPT versions,

  • and where it can help you in your everyday UX work – from stakeholder briefings to AI implementation.


I've been working in UX for over 20 years, leading international research projects and developing content strategies for AI-supported UX teams. For me, Deep Research Mode isn't a trick – it's an attitude.


📌 The most important points in brief:

• Deep Research Mode is not a feature, but a methodical way of working with ChatGPT.

• Particularly helpful for strategic, argumentative and ambiguous UX questions.

• GPT-4o is fast and versatile – o3 is stable and text-strong. The mode works with both.

• Ideal for user research, risk assessment, AI classification and thought leadership.

• Works in a structured, iterative way, with sources and theories (e.g. COM-B, SDT).

• UX thrives on thinking in alternatives – which is exactly what Deep Research supports.

• The mode can be activated with a simple prompt: ‘Please respond in Deep Research Mode.’


What exactly is Deep Research Mode?

In short, it is not a tool, but a way of working. Deep Research Mode describes an approach to working with LLMs such as ChatGPT:

  • structured reasoning,

  • reflective source criticism,

  • iterative analysis processes,

  • and clear methodological classification.

It is triggered by prompts in which you say, for example:

‘Please answer this in Deep Research Mode. Work with sources and structure.’

This mode is particularly valuable when you need not just an answer, but a comprehensible thought structure. And that's quite often the case in the UX world.


Which GPT version is suitable for what?

Many people ask themselves: Should I use GPT-4o or GPT-4 (o3)? And what does this have to do with Deep Research Mode? Here is an overview:

Version/Mode

Features

Suitable for

GPT-3.5 (o1)

Fast, inexpensive, rather superficial


Standard prompts, small tasks, no depth required

GPT-4 (o3)

Stable, analytically strong, very clean text

Strategy texts, reports, well-founded UX arguments

GPT-4o

Multimodal, very fast, web/tool access

Prompt development, image/audio integration, creative use

Deep Research Mode

Methodical working style, independent of the model

Strategic UX questions, qualitative analysis, AI classification

Tip: GPT-4o in Deep Research Mode is the best of both worlds – fast and well-founded. If you work purely in writing (e.g. for white papers or customer presentations), o3 is often the more stable partner.


When does Deep Research Mode help you in your everyday UX work?


1. Answer strategic UX questions more clearly

Example: ‘Why is UX investment worthwhile in the early stages?’

Instead of buzzwords, you get: ROI data, risks of missing UX, argumentation structure for stakeholders.


2. Prepare and evaluate research

Example: ‘What psychographic patterns can I recognise in 15 interviews?’

This mode helps you with coding, theory formation (e.g. COM-B = Capability, Opportunity, Motivation – Behaviour or SDT = Self-Determination Theory) and evidence-based derivation.


3. Evaluate and defend methods

Example: ‘Is a remote test just as valid as an on-site test?’

Deep Research provides you with: criteria comparisons, study status, advantages and disadvantages for your setting.


4. Classify and help shape AI in UX

Example: ‘What role does RAG play in AI-supported UX tools?’

Instead of speculation: architecture explanation, opportunities, risks, recommendations for AI implementation.


5. Building bridges between UX, product & data

Example: ‘How do I formulate a research statement that everyone understands?’

Deep Research helps you integrate different perspectives – from management to backend.


6. Developing positioning & thought leadership

Example: ‘How do I write an article about UX risks in MedTech platforms?’

The mode provides you with: structure, sources, style recommendations, differentiation from the competition.


FAQ: Frequently asked questions about Deep Research Mode

What distinguishes Deep Research from a normal ChatGPT prompt?

→ Depth, structure and methodical approach. No list – just comprehensible reasoning.

Can I also use the mode with Claude, Gemini or Perplexity?

→ Yes, in part. But the combination of GPT-4o + tool access + Deep Research Prompt is currently the most flexible.

Do I need to learn how to write special prompts for this?

→ No. But being precise helps: ask for structure, source criticism, derivation – then you're good to go.


Conclusion: AI is only as smart as your mode

UX is complex. And good UX work needs depth – especially when AI comes into play. Deep Research Mode is an easy way to get more out of ChatGPT:

  • better thought-out arguments,

  • well-founded analyses,

  • better decisions.


👉 Try it for yourself. For example:

‘Please use Deep Research Mode to develop an argument for why UX should be part of risk management.’

💌 Not enough? Then read on – in our newsletter. It comes four times a year. Sticks in your mind longer. To subscribe: https://www.uintent.com/newsletter

As of November 2025

Author: Tara Maria Bosenick, UX consultant, content strategist & AI sparring partner.


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AUTHOR

Tara Bosenick

Tara has been active as a UX specialist since 1999 and has helped to establish and shape the industry in Germany on the agency side. She specialises in the development of new UX methods, the quantification of UX and the introduction of UX in companies.


At the same time, she has always been interested in developing a corporate culture in her companies that is as ‘cool’ as possible, in which fun, performance, team spirit and customer success are interlinked. She has therefore been supporting managers and companies on the path to more New Work / agility and a better employee experience for several years.


She is one of the leading voices in the UX, CX and Employee Experience industry.

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