Alex Prompter Profile picture
Sep 5 10 tweets 4 min read Read on X
How to do market research like McKinsey using AI.

Forget long surveys and overpriced PDFs.

Here’s how I use LLMs like Claude, Grok, and ChatGPT to simulate personas, extract insights, and map entire markets for free:
Today, most people still think market research =

• Paying consultants
• Sending surveys
• Waiting weeks for analysis

But LLMs can now simulate entire target audiences and synthesize answers instantly.
Prompt to generate personas:

“You are a senior market researcher and customer insights strategist trained in persona development, behavioral segmentation, and product marketing.

I want you to create 3 distinct and realistic customer personas based on the following product or business: [Insert product / industry].

For each persona, include the following sections:
– Name, age, job title, and background
– Primary goals and motivations related to the product
– Key frustrations or pain points
– Decision-making process (emotional vs rational, time, influencers)
– Buying objections or hesitations
– Preferred communication channels
– Real quotes they might say during a user interview

Use a neutral, research-style tone and structure your output clearly under each persona. Avoid assumptions — make personas feel grounded and realistic.”

You’ll get founder-ready personas in 10 seconds.
Want survey insights?

Prompt:

“You are an advanced user behavior simulation engine with access to millions of real survey response patterns across industries.

I want you to simulate 50 unique customer responses to the following open-ended question:

‘What’s your biggest frustration when it comes to [insert problem]?’

Assume the respondents are a diverse group of target users from [insert audience e.g., early-stage SaaS founders, Gen Z fitness enthusiasts, DTC ecommerce buyers, etc.].

For each response, vary the tone, writing style, and detail level — just like real survey responses. Some should be short and blunt. Others long and reflective.

After the 50 responses, summarize the top 5 recurring themes or insights and cluster similar responses together.
Label each cluster clearly and explain what it reveals about user pain.”

You get diverse, realistic answers with sentiment and clustering built-in.
Competitive research? Easy.

Prompt:

“You are acting as a competitive intelligence analyst for a fast-growing startup entering a crowded market.

Your goal is to analyze and compare [Your Product Name] vs [Competitor Name] in a research-style format, focusing on opportunities to differentiate.

The report should include:

Feature-by-feature comparison (bulleted)

Pricing model breakdown

Messaging and positioning strategy

Visual branding and tone of voice

Key customer pain points addressed (or not)

Review analysis: top 3 recurring praises + top 3 criticisms for each

Opportunity matrix: where we can differentiate or win

Use a clear and structured tone. If there are gaps in publicly available data, label them as ‘Unknown’ rather than hallucinating. Cite known sources when applicable.”

You’ll get a consulting-level teardown in seconds.
Example use cases:

• SaaS → Analyze churn reasons from user feedback
• DTC → Simulate buying triggers and objections
• B2B → Generate pitch angles for different ICPs
• Creators → Identify content gaps your audience wants

No survey tools required.
Market research firms are still selling PDFs.

LLMs give you living, flexible insight engines.

You can:

- Ask follow-up questions
- Reframe segments
- Update instantly
- Run "what if"s

This isn’t a static report. It’s dynamic intelligence.
If you know how to prompt, you can:

- Skip the consultants
- Build closer to your customer
- Move 10x faster

The new market research stack =

→ LLMs
→ Data
→ Clear questions

Prompt smarter. Build better.
10x your prompting skills with my prompt engineering guide

→ Mini-course
→ Free resources
→ Tips & tricks

Grab it while it's free ↓
godofprompt.ai/prompt-enginee…
I hope you've found this thread helpful.

Follow me @alex_prompter for more.

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More from @alex_prompter

Sep 4
This report might define the next 3 years of AI in business.

MIT calls it “The GenAI Divide.”

And the data is both brutal and clarifying.

Here's everything you need to know in 3 minutes: Image
MIT analyzed 300+ AI projects, interviewed 52 orgs, and surveyed 153 senior leaders.

The verdict?

→ 95% of enterprise AI implementations are failing.
→ Only ~5% of pilots reach production and deliver measurable P&L impact.

Adoption ≠ transformation. Image
The problem isn’t the models.

It isn’t regulation.

It’s learning.

Most tools don’t retain feedback.
They don’t adapt to workflows.
They don’t get better with use.

So they stall. Image
Read 12 tweets
Sep 1
If you want to learn n8n, read this.

It’s the fastest way to understand what it is, why it matters, and how to use it to build your first AI-powered automation ↓
What is n8n?

n8n is an open-source automation tool that connects your apps, builds agentic workflows, and lets you host everything yourself.

Think Zapier, but with more power and zero vendor lock-in.

Ideal for devs, indie hackers, & AI builders.

n8n.ioImage
What's so special about it.. you ask:

- AI-native workflows
- Fully customizable
- No-code UI, low-code freedom
- 1,000+ integrations
- You can self-host (keep your data!)
- Agents that think, not just trigger → act

It’s built for the AI era.
Read 14 tweets
Aug 31
This one concept explains why LLMs “forget” mid-conversation.

It’s called 'context length' and it defines how much an AI can “remember” at once.

Here’s the concept explained in plain English: Image
Every Large Language Model (LLM) has a token limit.

A token = a chunk of text (≈ 3–4 characters of English).

Think of it as the AI’s working memory.

If you exceed it, the model starts dropping information.

Example:

- GPT-4o has ~128k tokens (~300 pages of text).
- Claude 3.5 Sonnet has 200k tokens (~500 pages).
- Gemini 1.5 Pro: 1M+ tokens (~3,000 pages).

But no model has “infinite memory.”Image
Why it matters:

Context length defines how much history you can pass in:

- A long chat log
- A book or research paper
- Multiple files or codebases

If your prompt + conversation > token limit → earlier parts get truncated.
Read 10 tweets
Aug 30
GPT-5 is insanely powerful.

Stop listening to people who say GPT-5 gives you the same boring outputs as every other AI.

I've been using it for 3 weeks and it has automated 90% of my work.

Here are 5 ways I use it daily to automate my boring tasks:
1. Research + summarization

I don’t waste hours skimming reports anymore. gpt-5 turns 50 pages into a 2-minute actionable summary.

Helps me move fast without missing key details.

Prompt I use:

"you are my research assistant. read the following document or url and give me:
1. a 10-sentence executive summary
2. 5 key insights i should act on
3. the top 3 risks or blindspots most people might miss
4. rewrite the insights in simple, no-jargon language i can share with my team "

here you've to add the document link or the document itself (i prefer the file)
2. Content Ideation

Instead of staring at a blank page, I use GPT-5 to generate structured ideas for posts, newsletters, and scripts. What used to take me 2 hours is now a 15-minute draft.

Prompt I use:

"You are a professional ghostwriter. Generate 15 high-signal content ideas on [topic].

For each idea:
- Give me a hook line (<= 15 words, curiosity-driven)
- Outline the structure in 3 parts (hook, point, action)
- Include an example or analogy that will resonate with [audience type]

Make them practical, non-generic, and designed to spark discussion."
Read 8 tweets
Aug 29
AI is getting scarily good at app development.

I asked 3 models to code a timer app from scratch:

🇺🇸 ChatGPT
🇨🇳 Qwen
🇨🇳 Kimi

Here's the result (prompt + demos 👇) Image
Prompt I used:

"Create a simple timer app using only HTML, CSS, and JavaScript. It should have Start, Pause, and Reset buttons and display the elapsed time in mm:ss format."
1. ChatGPT

✅ Fully functional
✅ Clean, modern design
✅ Smooth UX

It nailed both functionality and presentation.

chatgpt.com/canvas/shared/…
Read 9 tweets
Aug 28
America is quietly entering its 4th major reinvention.

The last 3 times this happened, it triggered 25 years of explosive growth.

We’re at that point again... right now.

Here’s what most people don’t see yet 🧵: Image
1/ Every 80 years, America hits a breaking point.

And from that breakdown, it reinvents everything - tech, economy, politics.

It happened in:
• 1787 (Post-Enlightenment)
• 1865 (Post-Civil War)
• 1945 (Post-WWII)

Each one sparked a 25-year boom. Image
2/ We’re now in the 2025 version.

And 3 tipping points are hitting at once:
• Artificial Intelligence
• Clean Energy
• Bioengineering

They’re not “emerging.”
They’ve arrived - and they’re scaling. Image
Read 12 tweets

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