AI doesn’t replace market research — it makes it faster and more accessible. This guide covers where AI adds the most value in the research workflow.

Where AI Adds Value in Market Research

High value:

  • Survey design and question writing
  • Qualitative data analysis (interview transcripts, open-ended responses)
  • Competitive landscape mapping
  • Secondary research synthesis
  • Report writing from collected data

Lower value (need real data):

  • Consumer opinion and preferences (AI can only reflect training data)
  • Market size numbers (verify with primary sources)
  • Real-time market trends (use Perplexity or news tools)

Survey Design

Question Writing

I'm designing a survey to research [topic] for [business purpose].

Target respondents: [describe who will take the survey]
Key research questions I need to answer:
1. [What you want to know]
2. [What you want to know]
3. [What you want to know]

Generate 15 survey questions that:
- Include a mix of question types (rating scales, multiple choice, open-ended)
- Avoid leading questions
- Are unambiguous and specific
- Flow logically
- End with 2-3 demographic questions

Include the question type for each (Likert scale, multiple choice, etc.)

Analyzing Open-Ended Survey Responses

I have 200 open-ended survey responses to the question: "[survey question]"

Here's a sample:
[paste 20-30 representative responses]

Analyze these responses:
1. Identify the top 5-7 themes
2. Estimate frequency of each theme (% of responses)
3. Note any surprising or unexpected responses
4. Identify positive and negative sentiment distribution
5. Surface 3-5 direct quotes that best represent key themes

Format as a structured report section with theme names and examples.

Competitive Analysis

Building a Competitive Landscape

Create a competitive analysis for [your company/product] in [market].

My product: [description]
My pricing: [price point]
My primary differentiator: [what makes you different]

Known competitors: [list]

For each competitor, analyze:
1. Core product and positioning
2. Target customer
3. Pricing model
4. Key strengths (where they're strong)
5. Key weaknesses (where they're vulnerable)
6. Recent moves (launches, funding, partnerships)

After the competitor-by-competitor analysis:
7. Identify 3 gaps in the market none of them are serving well
8. Identify where I should differentiate vs. compete head-on

SWOT Analysis

Create a SWOT analysis for [Company/Product]:

Internal information:
- Our product: [description]
- Team strengths: [list]
- Resources/assets: [describe]
- Known weaknesses: [list]

External information:
- Market trends: [describe]
- Competitive landscape: [describe]
- Regulatory environment: [if relevant]

Generate a detailed SWOT with 5-6 items per quadrant.
For each item, note the strategic implication.

After the SWOT, suggest 3 strategic priorities based on the analysis.

Customer Research

Persona Development

Create 3 detailed customer personas for [product/service].

Our product: [description]
Current customer data we have: [list any actual customer segments you know]
Industry: [your industry]

For each persona:
- Name and brief bio
- Demographics (age, role, company size/type)
- Goals and motivations (what are they trying to achieve?)
- Pain points (what frustrates them about current solutions?)
- Buying behavior (how do they research and decide?)
- Objections (why might they NOT buy?)
- Key message that would resonate with them

Mark which persona is highest priority for initial go-to-market.

Customer Interview Analysis

I've conducted 10 customer interviews. Here are my notes:

[paste transcript or notes]

Analyze these interviews for:
1. Common pain points (frequency and severity)
2. Current solutions they're using (and what they like/dislike)
3. What outcomes they're actually paying for (the job-to-be-done)
4. Pricing signals (what they've spent, what they'd consider)
5. Discovery channels (how they found/heard about solutions)
6. Decision factors (what made them choose or reject solutions)

Format as key findings with supporting quotes.

Market Sizing

AI can help structure your market size analysis, but verify numbers from primary sources:

Help me build a market size estimate for [product/service].

Target customer: [description]
Geography: [region]
Use case: [what problem you solve]

I want to calculate:
1. TAM (Total Addressable Market)
2. SAM (Serviceable Addressable Market)  
3. SOM (Serviceable Obtainable Market in year 3)

Walk me through:
1. The most credible assumptions I could use
2. How to calculate each layer
3. What industry research or databases I should verify numbers from
4. Common mistakes in sizing markets like this

I'll verify all numbers, this is just to structure the model.

Synthesizing Secondary Research

I've collected these market research excerpts from various reports:

[paste excerpts from industry reports, news articles, analyst notes]

Synthesize this into a market overview section:
1. Market size and growth rate (with caveats on source reliability)
2. Key market drivers
3. Key market challenges
4. Emerging trends
5. Competitive intensity
6. Market segmentation

Note: flag any contradictions between sources.
Maximum length: 500 words.

Market Research Report Writing

Write a market research report based on these findings:

Research conducted: [describe what you did — surveys, interviews, secondary research]
Sample size: [N]
Key findings: [paste your key data points]
Target audience for this report: [who will read it]

Report structure:
1. Executive Summary (200 words)
2. Research Methodology
3. Key Findings (5-7 findings with data)
4. Market Opportunities Identified
5. Recommendations
6. Appendix: Raw data summary

Write in objective, evidence-based language. Note confidence level on findings.

Questions AI Can’t Answer Reliably

These require real research — don’t rely on AI alone:

  • “What is the exact market size for X?” — AI can estimate, verify from Gartner, IBISWorld, etc.
  • “What do customers in X country prefer?” — survey them
  • “What is [Competitor]‘s revenue?” — check SEC filings, Crunchbase, press releases
  • “What trends are happening right now?” — use Perplexity, Google Trends, social listening tools

Use AI to structure these questions and analyze data once you have it — not to generate the data itself.