Building the Agentic Foundatio...

AI-Powered Personas & Market Research: The Engineer's Guide

13min

﻿AI has completely changed the way we do market research. For the first time, you don't need guesswork and you don't have to make assumptions. The tools you already have can systematically gather all the intelligence you need.
Step 1: Mining Your Support Data
Your support inbox is a goldmine. Here's how to extract insights using AI.
The support analysis prompt:
AI Prompt
Analyze these support conversations and:
1. Identify common pain points
2. Group issues by user role/type
3. Extract feature requests
4. Note language patterns used
5. Flag satisfaction indicators

Support data:
[Paste 10-20 support conversations]
Analyze these support conversations and:
1. Identify common pain points
2. Group issues by user role/type
3. Extract feature requests
4. Note language patterns used
5. Flag satisfaction indicators

Support data:
[Paste 10-20 support conversations]
﻿
Use this with ChatGPT to analyze the customer support inbox exports. Look for patterns in:
Common complaints
Feature requests
User types
Language used
Bonus points: build a custom GPT.
﻿
Step 2: Sales Call Intelligence
Turn your sales calls into persona insights.
The sales call analysis prompt:
AI Prompt
Review these sales call transcripts and identify:
1. Common objections and how they vary by role
2. Key pain points mentioned
3. Feature requirements by segment
4. Decision criteria across roles
5. Budget discussions and patterns

Transcripts:
[Paste 3-5 call transcripts]
Review these sales call transcripts and identify:
1. Common objections and how they vary by role
2. Key pain points mentioned
3. Feature requirements by segment
4. Decision criteria across roles
5. Budget discussions and patterns

Transcripts:
[Paste 3-5 call transcripts]
﻿
😎  PRO TIP
Use tools like Zapier or Make to automate the transcripts export and feed them to AI for analysis.
Step 3: Review Mining
Leverage G2 and Capterra reviews systematically.
The review analysis prompt:
AI Prompt
Analyze these product reviews and:
1. Group feedback by user role
2. Identify primary use cases
3. Extract key benefits mentioned
4. List common complaints
5. Note competitive comparisons

Reviews:
[Paste 20-30 reviews]
Analyze these product reviews and:
1. Group feedback by user role
2. Identify primary use cases
3. Extract key benefits mentioned
4. List common complaints
5. Note competitive comparisons

Reviews:
[Paste 20-30 reviews]
﻿
Capterra.com review for Archbee
﻿
Step 4: Competitor Intelligence
Turn competitor reviews into strategic insights:
The competitive analysis prompt:
AI Prompt
Compare these competitor reviews and:
1. Map feature gaps vs. our product
2. Identify underserved needs
3. List common switch triggers
4. Extract pricing feedback
4. Note market positioning differences

Competitor reviews:
[Paste competitor reviews]
Compare these competitor reviews and:
1. Map feature gaps vs. our product
2. Identify underserved needs
3. List common switch triggers
4. Extract pricing feedback
4. Note market positioning differences

Competitor reviews:
[Paste competitor reviews]
﻿
Automatically Get Competitive Data and analyze it with AI
﻿
Step 5: Product Usage Patterns
Transform analytics into persona insights:
The usage pattern prompt:
AI Prompt
Analyze this product usage data and:
1. Identify user archetypes based on behavior
2. Map feature adoption patterns
3. Highlight engagement differences by role
4. Note common friction points
5. List success indicators

Usage data:
[Paste usage metrics]
Analyze this product usage data and:
1. Identify user archetypes based on behavior
2. Map feature adoption patterns
3. Highlight engagement differences by role
4. Note common friction points
5. List success indicators

Usage data:
[Paste usage metrics]
﻿
Step 6: Website Behavior Analysis
Turn web analytics into buyer journey insights:
The web behavior prompt:
AI Prompt
Review this website behavior data and:
1. Map common user journeys
2. Identify drop-off points
3. List high-engagement content
4. Note conversion patterns
5. Extract search intent signals

Analytics data:
[Paste analytics export]
Review this website behavior data and:
1. Map common user journeys
2. Identify drop-off points
3. List high-engagement content
4. Note conversion patterns
5. Extract search intent signals

Analytics data:
[Paste analytics export]
﻿
Step 7: Community Intelligence
Mine community discussions for deeper insights:
The community analysis prompt:
AI Prompt
Analyze these community discussions and:
1. List recurring questions
2. Identify expertise levels
3. Map common challenges
4. Note solution approaches
5. Extract terminology used

Discussion data:
[Paste community threads]
Analyze these community discussions and:
1. List recurring questions
2. Identify expertise levels
3. Map common challenges
4. Note solution approaches
5. Extract terminology used

Discussion data:
[Paste community threads]
﻿
﻿
Building Your Persona Framework
Now, synthesize all this data into clear personas:
The persona synthesis prompt:
AI Prompt
Using all the analyzed data, create detailed personas including:
1. Role and responsibilities
2. Key pain points and goals
3. Decision criteria
4. Common objections
5. Preferred channels
6. Language patterns
7. Success metrics

Previous analysis:
[Paste your AI analysis results]
Using all the analyzed data, create detailed personas including:
1. Role and responsibilities
2. Key pain points and goals
3. Decision criteria
4. Common objections
5. Preferred channels
6. Language patterns
7. Success metrics

Previous analysis:
[Paste your AI analysis results]
﻿
Creating Your Market Research Engine
Build this system:
Set up automatic data collection from all sources
Create regular AI analysis cycles
Update personas quarterly
Feed insights back to product and marketing
The research update prompt:
AI Prompt
Compare this new data with our existing insights and:
1. Identify emerging trends
2. Note changing preferences
3. Flag new opportunities
4. Highlight shifts in behavior
5. Suggest strategy adjustments

New data:
[Paste new data]
Previous insights:
[Paste previous analysis]
Compare this new data with our existing insights and:
1. Identify emerging trends
2. Note changing preferences
3. Flag new opportunities
4. Highlight shifts in behavior
5. Suggest strategy adjustments

New data:
[Paste new data]
Previous insights:
[Paste previous analysis]
﻿
Your AI research engine should grow smarter with each cycle. Feed it reliable data, ask thoughtful questions, and use its insights to refine and build for the next iteration.
That's how you engineer market understanding.

🤔

Have a question?

Our super-smart AI,knowledgeable support team and an awesome community will get you an answer in a flash.

To ask a question or participate in discussions, you'll need to authenticate first.

﻿

Reverse-Engineering Your ICP From The Data You Already Have

Engineering Your Competitive Intelligence System