5 AI Use Cases for GTM Market Research

With 7 simple prompt examples

Dear GTM Strategist,

Abraham Lincoln said, “If I had eight hours to chop down a tree, I'd spend six hours sharpening my axe.”

Good preparation is a key to success. The preparation for the go-to-market strategy starts with market research - collecting good intelligence for decision making (competitors, market, customers). And market research should not be limited to the preparation stage. It should be a regular activity and something that you regularly block time to do.

I devoted a whole chapter to knowing your market in my book Go-To-Market Strategist.

Another military strategy comes into play. The OODA Loop is a mental model created by the U.S. Air Force Colonel John Boyd. It’s a practical concept and the basis for logical thinking in complex or chaotic circumstances. It consists of four stages: Observe, Orient, Decide, and Act, collectively known as the OODA loop.

And then came AI and changed everything.

• Both ChatGPT and Gemini now have “deep research” mode, which can do in-depth analysis with lots of variables.

• You can upload complete documents to AI tools to analyze large amounts of unstructured data.

• AI is becoming more integrated with other software we regularly use. Emerging standards like MCP will make that even more powerful.

The basic principles remain the same, but tools and workflows are changing and access to intelligence is easier than ever. Having unique insights is still a massive advantage, but the grunt research work can be beautifully optimized.

In this newsletter, I am sharing my best practices and use cases that will help you gain intelligence faster. We will cover:

• Best practices, prompts, and tools for market research in GTM

• How AI can make you 10x more productive

• 5 hands-on use cases

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Best practices of market research for GTM

Most GTM teams make one of two mistakes:

• They skip research altogether because “they know better”.

• They go down a rabbit hole of competitor analysis and never ship anything. There’s a term for that: analysis paralysis.

They might think that you need a large budget to do market research.

But all you need is intellectual curiosity, structured thinking - and now a bit of AI assistance. With smart workflows, you can now do more insightful, more iterative, and faster research than ever before.

First, let’s tackle the key information you should gather in the initial stages.

The first question should be: Is this a market worth winning?

One effective method is analyzing the Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM).

• TAM represents the total demand for a product or service.

• SAM is the segment targeted by your products and services within geographical reach.

• SOM is the portion of the market that your company can realistically capture, considering the existing competition and market entry barriers.

But you don’t need to bother with definitions. Just ask your AI assistant to perform the research and give you the estimates. You will find the prompt example in the next section.

Next question: Who are your competitors? They are playing to win, so you better analyze what they're doing.

Here’s another trap that often leads to wasting precious time: in-depth analysis of every potential competitor in a crowded market. Up to 10 will be more than enough. If your target market has only 2-3 competitors, that is enough to start with. Rather, think of indirect competitors - what are your potential customers currently doing instead of using your solution? Sometimes, the answer will be “Excel sheet” or “nothing”.

Here are my proven steps for competitor analysis:

1. DIY customer research:

Talk to your customers or prospects. Find out which competitors they considered before choosing you, what the actual problems are they have, and how they are currently solving them.

2. Analyze the online presence of your competitors:

Do a teardown of their websites. Look at messaging, pricing, and sales funnels. Tools like SimilarWeb and BuiltWith provide insights into their tech stack and traffic on the website.

3. Marketing & sales activities:

Create a swipe file with their examples. This file will later come in handy for AI analysis of the key patterns and trends. Use SEO tools (Ahrefs, Semrush), social media monitoring (Brand24, BuzzSumo), and ad spy tools (SpyFu, Google Ads library). Tools like Brand24 enable alerts that can keep you updated.

4. Hands-on experience:

Engage with competitors directly. Make a purchase, a sales call, or hire a mystery shopper. Stay ethical while you are doing this, but it can be eye-opening to get the first-hand experience.

5. Netnography:

Look at online groups and review sites. See if there is some recurring feedback. You can check G2, TrustRadius, and others in B2B, or Amazon and forums in B2C. Then upload this to your AI tool to get insights much faster. You will find another prompt in the final section of this post.

This type of research will enable you to go beyond basic metrics like employee count or social media followers and focus on aspects that truly impact your buyer's decision.

Identify what truly matters to your customers - "free trial," "sustainability," or "quality of customer care" can all be crucial factors. These insights will guide your differentiation, positioning, and messaging, which are all essential elements of your GTM strategy. (I wrote more about positioning in this article).

Now that we have covered the initial market research questions, let’s see how we can achieve even more with the latest tools.

How AI can make you 10x more productive

Market research might not cost you dollars, but it’s still expensive in terms of the time you can devote to it. It requires not only gathering lots of data, but also analysing and structuring it into meaningful insights.

Here is where AI tools and assistants can help most. It’s actually one of my best use cases for using AI. Think of it as having a junior research assistant at your disposal.

“10x more productive” is not an exaggeration in this case. You can easily lose 10 hours of information gathering if you are comparing several competitors and are diving into customer reviews. With smart use of AI, you can get powerful insights in less than an hour.

Here are my best practices for using AI for market research:

1. Combine AI tools with source uploads

When you have specific sources (PDFs, Excel, review dumps, strategy docs), upload them and ask:

“Analyze this document and extract key insights about GTM motions, ICP targeting, and feature priorities.”

You can upload G2 reviews, internal sales notes, even product pages. Let ChatGPT, Claude, or your tool of preference synthesize it all. This will turn unstructured input into structured intelligence.

For larger projects, I open a new Project in ChatGPT, upload all relevant files, and then work there.

2. Use AI assistants that can browse the web

Perplexity is one of my top choices. It has a powerful combination of web search and AI tools that is just natural for research. Now it also enables “deep research” mode.

Here is the prompt I use:

"Act as a market analyst. Provide a detailed overview of the [industry or product category] market, including: (1) the estimated Total Addressable Market (TAM) globally and by region, (2) key growth trends and forecasts, (3) major customer segments, and (4) a competitive landscape analysis identifying leading players, their market share, value propositions, pricing models, and go-to-market strategies. Include data sources and mention any recent developments or disruptive startups in this space."

3. Ask AI to follow specific frameworks and models

Again, think of AI as a junior assistant. It can process large amounts of information, but the results are as good as the instructions you give. So, one of the best ways is to instruct them to follow proven frameworks and mental models.

SWOT, for example, is a timeless, always useful framework to identify the strengths and weaknesses of your product (internal capabilities) and threats and opportunities on the market (external factors). For example, after feeding your AI tool documents with your product descriptions and getting initial market research, ask it to perform a SWOT analysis.

Example of some questions to guide your SWOT analysis

4. Use built-in AI tools

Chat was the first “killer app” and interface of the generative AI tools. But now that they are getting more capable, make use of advanced integrations that are purpose-built for specific workflows.

If you use Google Workspace and have access to Gemini, it has become powerful to summarize long documents and give you actionable insights. So you can even skip document upload.

Even more specific examples are built-in AI features in tools like Miro. Miro recently launched AI sidekicks which were developed with partners such as Product Marketing Alliance. They are based on specific knowledge that makes them act like an actual person would review your plans.

Example of AI sidekicks in Miro that give you actionable ideas for further research. See it in action.

5 Hands-On Use Cases

To make this quick guide even more actionable, here are five examples of how to rock your market research with AI to uncover new insights and stay ahead of the game.

1) Market Landscape Scan

When I’m entering a new space, I ask my AI assistant to:

• Summarize the current competitive landscape

• Identify top players

• Highlight recent shifts in customer behavior or regulation

• List common buying criteria

It gives me a high-level map that I then cross-check with tools like SimilarWeb, G2 reviews, or market reports.

Prompt example:

“Act like a GTM strategist. I’m building a [category] product for [ICP]. What are the top 5 trends, key competitors, and customer frustrations in this market?”

2) Validate assumptions with AI-simulated customer interviews

You don’t need 20 interviews to test your initial assumptions. You need 3-5 smart hypotheses and quick directional feedback.

I feed ChatGPT the profile of my ECP and ask it to simulate interview responses - based on public data, common objections, and review mining.

It’s not a replacement for real interviews. But it’s a great tool for pre-validating your assumptions and writing better interview scripts.

Prompt example:

“My early adopters are [describe persona]. Pretend you are one of them. What would you say in a customer discovery interview about your current solutions and frustrations?” [alternatively, conduct an example of a customer interview with consecutive questions - and your AI assistant acting as an early adopter.”

3) Automate competitive analysis teardown

Analyzing competitors used to take days. Now, I feed my AI assistant transcripts from websites, landing pages, even LinkedIn content - and ask for:

• Pricing models

• Feature gaps

• UVP breakdowns

• Go-to-market strategies

This is gold when you’re defining your own differentiation and choosing which “battle to win.”

Simple prompt example:

“Analyze this landing page and summarize its target audience, positioning, CTA, and offer hierarchy.”

4) Source qualitative insights at scale

Netnography - aka structured research on forums, social media, and reviews - is a dream when combined with AI.

You can scrape reviews from G2 or similar websites, then feed them to AI to cluster user sentiment and identify unmet needs.

Sometimes, a goldmine can be Reddit. Subreddits can reveal lots of customer sentiment you didn’t know existed and new perceptions of the product.

Prompt example:

“Summarize 100 G2 reviews of [competitor] into themes: top likes, dislikes, and feature requests. Prioritize by frequency.”

5) Deep research

Deep research is an excellent new feature in ChatGPT, Gemini, and Perplexity. Take some more time to write a prompt, outline your goals and expectations, preferably also the structure you want for the report. Your AI tool will research the web and synthesise the analysis for you. If your instructions are unclear, it will guide you with subquestions before finalizing the research.

Select “Deep research” mode in ChatGPT to guide you with your research

Prompt example:

"Act as a senior market research analyst. I want to evaluate the market opportunity for [PRODUCT / INDUSTRY]. Please conduct a deep analysis and return a structured report with the following sections:

1. Market Overview

   • Define the industry

   • Key trends and growth drivers

   • Size of the market (TAM, SAM, SOM if available)

2. Target Customer Segments

   • Main personas or buyer profiles

   • Key pain points

   • Current alternatives / existing behavior

3. Competitive Landscape

   • Top 5-10 direct competitors (brief descriptions)

   • Pricing models

   • Unique value propositions (UVPs)

   • Strengths and weaknesses

4. Emerging Opportunities or Gaps

   • Under-served niches

   • Innovation whitespace

   • Regulatory or technological tailwinds

5. Sources

   • List all used sources with URLs if available

Format the answer as a structured market research report. Use bullet points, bolded section titles, and include estimates with dates wherever possible. Focus on strategic insights for a go-to-market decision."

6) Build a living swipe file or moodboard

Save all insights in Notion, Google Drive, Miro board, or similar. Return to them each quarter and upload them to your AI assistant to uncover more insights. Market signals change fast, so you should always stay on top of your research and monitoring game.

This is an example of how I save the best-performing posts from top content creators to my moodboard

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You can get proven templates, examples, and more detailed prompts, including how to do market research, in my 100+ Step GTM Checklist.