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🧠 Market Researcher CrewAI

A production-ready multi-agent AI system built with crewAI that autonomously conducts end-to-end market research, competitive intelligence, customer insights, product strategy, and business analysis — all in a single pipeline.


🚀 What It Does

Five specialized AI agents work sequentially, each producing a professional-grade report:

Agent Role Output
🔍 Market Research Specialist TAM/SAM/SOM sizing, trends, segmentation Market Research Report
🕵️ Competitive Intelligence Analyst Competitor profiles, feature matrix, threat heatmap Competitive Intelligence Briefing
👥 Customer Insights Researcher Personas, journey maps, unmet needs Customer Insights Report
🧭 Product Strategy Adviser Vision, strategic bets, roadmap Product Strategy Document
📊 Senior Business Analyst Unit economics, financial projections, ROI Business & Financial Analysis

📋 Output

When you run crewai run with the default inputs (AutoAgentX / Autonomous AI Agents), the crew produces five sequential reports covering:

1. Market Research Report

  • TAM projected at ~$13.4B by 2025, CAGR of 34.6%
  • 5 customer segments: automotive (40%), aerospace (20%), healthcare (15%), industrial automation (10%), consumer electronics (5%)
  • Top white-space: autonomous agents for industrial automation (~$4.2B opportunity)
  • Key risks: regulatory uncertainty, cybersecurity, technological disruption

2. Competitive Intelligence Briefing

  • Competitor tiers: Leaders (NVIDIA, Intel), Challengers (Microsoft, Google, Amazon), Niche (Siemens, Rockwell, ABB)
  • Feature comparison matrix across 7 capability dimensions
  • Recent signals: acquisitions, partnerships, and product launches (2020–present)
  • Strategic recommendation: differentiate via industrial automation focus

3. Customer Insights Report

  • 5 detailed personas across automotive, aerospace, healthcare, industrial, and consumer segments
  • End-to-end journey map: Awareness → Consideration → Evaluation → Purchase → Post-purchase
  • Top pain points: regulatory uncertainty, high dev costs, integration complexity, cybersecurity
  • Loyalty levers: reliability, customer support, continuous innovation

4. Product Strategy Document

  • Vision: become the leading autonomous agent provider for industrial automation
  • North star: 20% market share, $2.5B revenue by 2028
  • 3 strategic bets: industrial automation, healthcare, consumer autonomous vehicles
  • 6–12 month roadmap with milestones and resourcing asks

5. Business & Financial Analysis

  • Unit economics benchmarked against industry (CAC, LTV, gross margins)
  • 3 financial scenarios: base, upside, downside (3–5 year horizon)
  • ROI analysis for each strategic initiative
  • Prioritized recommendations to optimize margins and accelerate growth

🛠️ Installation

Prerequisites

  • Python >=3.10, <3.14
  • uv package manager

Install uv

pip install uv

Install dependencies

crewai install

⚙️ Configuration

1. Set up .env

OPENAI_API_BASE=https://api.groq.com/openai/v1   # Remove this line if using OpenAI directly
OPENAI_API_KEY=your_api_key_here
OPENAI_MODEL_NAME=llama-3.3-70b-versatile         # Or gpt-4o-mini for OpenAI
SERPER_API_KEY=your_serper_key_here

⚠️ Groq free tier has a 12,000 TPM limit. For full pipeline runs, upgrade to Groq Dev Tier or use OpenAI (gpt-4o-mini).

2. Customize inputs (main.py)

def get_inputs():
    return {
        'product_or_company_name':           'YourCompany',
        'target_market_or_industry':         'Your Industry',
        'your_company_or_product_name':      'YourCompany',
        'target_customer_segment_or_use_case': 'Your Target Segment',
        'industry_or_market_context':        'Your Market Context',
        'product_name_or_category':          'Your Product',
        'target_market_or_customer_segment': 'Your Target Customer',
        'industry_or_competitive_context':   'Your Competitive Context',
        'company_name_or_business_objectives': 'Your Business Goal',
    }

3. Customize agents & tasks

  • src/market_researcher_crew/config/agents.yaml — agent roles, goals, backstories
  • src/market_researcher_crew/config/tasks.yaml — task descriptions and expected outputs
  • src/market_researcher_crew/crew.py — tools, logic, agent-task wiring
  • src/market_researcher_crew/main.py — input variables

▶️ Running the Project

crewai run

Other commands

Command Description
crewai run Run the full 5-agent pipeline
crewai test -n 3 -m gpt-4o Test crew over 3 iterations
crewai train -n 5 -f training.json Train the crew
crewai replay -t <task_id> Replay from a specific task
crewai log-tasks-outputs View latest task outputs
crewai reset-memories -a Clear all agent memories

🗂️ Project Structure

market_researcher_crew/
├── src/market_researcher_crew/
│   ├── config/
│   │   ├── agents.yaml          # Agent definitions
│   │   └── tasks.yaml           # Task definitions
│   ├── tools/
│   │   └── custom_tool.py       # Custom tool implementations
│   ├── crew.py                  # Crew orchestration
│   └── main.py                  # Entry point & inputs
├── knowledge/
│   └── user_preference.txt      # User context for agents
├── .env                         # API keys (git-ignored)
├── .gitignore
├── pyproject.toml
└── uv.lock

🤝 Support

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An autonomous AI crew for deep market research, competitive intelligence, and product strategy. Powered by crewAI, Selenium, and Serper.

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