AI-Powered Business Analysis & Strategy Development
Session Summary: Mini-Project Overview
Session Overview
This session focused on a mini project where students will analyze a struggling startup using AI tools, data analysis, and strategic planning. The objective is to identify root causes of customer retention issues and develop an AI-driven business strategy to improve performance.
Key Topics Covered
Introduction to AI-Driven Business Analysis
- Overview of how AI tools can be leveraged for data-driven decision-making.
- Discussion on customer retention issues in startups, particularly in the health tech sector.
Introduction to Notion for Project Management & Collaboration
Demonstration of how to use Notion AI for:
- Task management (creating project timelines, setting deadlines).
- Collaboration (teamwork and assigning responsibilities).
- Documenting insights and findings for structured analysis.
Overview of AI Tools for Data Analysis & Visualization
- Miro – For customer journey mapping and strategic planning.
- Perplexity AI – For industry research and competitive analysis.
- Infogram – For data visualization (charts, graphs, reports).
- ChatGPT / Claude – For generating customer datasets and insights.
Mini-Project Breakdown: Steps & Execution
Students will follow a structured approach to analyze a struggling startup’s challenges and propose a data-backed turnaround strategy.
Step 1: Data Collection
Objective: Generate realistic datasets using AI tools.
Key Actions:
- Use ChatGPT or Claude to create synthetic customer data for a health tech startup.
- Include:
- Customer complaints & support tickets (recurring issues).
- Product usage data (features frequently used vs. ignored).
- Subscription details (trial vs. paid users).
- Churn patterns (why customers leave).
Step 2: Customer Feedback & Complaint Analysis
Objective: Identify trends and patterns in customer dissatisfaction.
Key Actions:
- Use AI-powered sentiment analysis to classify feedback as positive, neutral, or negative.
- Categorize most frequent complaints (e.g., long response times, app crashes, unclear pricing).
- Use Infogram to visualize common pain points and customer frustration patterns.
Deliverable: A report highlighting key issues impacting customer retention.
Step 3: Industry Research & Benchmarking
Objective: Compare the startup’s performance with industry standards.
Key Actions:
- Use Perplexity AI to research:
- Customer retention benchmarks in health tech.
- Competitor strategies for reducing churn.
- Case studies of successful startups tackling similar issues.
- Identify at least 3 competitors and analyze their growth strategies.
Deliverable: A comparative industry analysis highlighting gaps and opportunities.
Step 4: Hypothesis Development
Objective: Use data insights to identify possible causes of churn.
Key Actions:
- Formulate 3-4 hypotheses about why customers are leaving.
- Example hypotheses:
- Poor onboarding process → Higher churn.
- Long response times → Low customer satisfaction.
- Unclear pricing → Billing disputes.
- Document findings in Notion AI.
Deliverable: A list of data-backed hypotheses explaining the startup’s retention issues.
Step 5: Data Insights & Visualization
Objective: Present findings using AI-generated reports & charts.
Key Actions:
- Use Infogram to create:
- Correlation charts (e.g., response time vs. churn rate).
- Churn distribution graphs (which customer segments are leaving?).
- Use ChatGPT to refine data insights and generate additional reports.
Deliverable: A comprehensive report with visual insights.
Step 6: Action Plan Development
Objective: Propose an AI-powered retention strategy.
Key Actions:
- Use Notion AI to structure a step-by-step action plan.
- Use Miro to create a strategy map, focusing on:
- Improving onboarding (tutorials, AI-powered support).
- Enhancing customer support (chatbots, faster response times).
- Pricing adjustments (clearer plans, discounts for renewals).
Deliverable: A strategic plan to enhance customer retention.
Step 7: Final Presentation & Submission
Objective: Present findings in a professional, data-backed format.
Key Actions:
- Create a structured presentation covering:
- Startup’s problem statement.
- Data-driven insights.
- Competitive benchmarking findings.
- Recommended AI-powered solutions.
- Be prepared to present in the next live session (Top 3 teams selected).
Deliverable: A polished, well-researched presentation with actionable insights.
Team Formation & Project Submission
- Students will work in teams of 3-4 to complete the project.
- Submission Deadline: Before the next session.
- Top 3 teams will be selected to present their analysis and win prizes.
Key Takeaways
- Hands-on experience using AI for business analysis.
- Practical application of data visualization tools (Infogram, Miro, Notion AI).
- Exposure to real-world business problem-solving using AI.
- Development of analytical, strategic thinking, and teamwork skills.
This mini-project is an opportunity to apply AI tools and strategic planning in a real-world business scenario. Best of luck to all teams!
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