New Learning Series: Achieving Product-Market Fit for Generative AI-Powered Data Analytics Products!

Are you a professional eager to build groundbreaking generative AI solutions in the data analytics space? Join me for a quick learning series (part-1 and part-2) coming soon! Where I delve into the journey of taking OpenAI Codex, a generative AI-powered data analytics product, from 0 to 1.

Throughout the series, I’ll cover:

1. Understanding the Market and Identifying the Problem
2. Designing the Solution and Creating a Prototype
3. Building and Testing the MVP
4. Launching and Marketing the Product
5. Measuring Success and Iterating

Get ready to explore real-life examples, actionable insights, and practical steps to achieve product-market fit for your AI-powered data analytics products. Stay tuned for my part-1, part-2 posts

Series Outline

PART-1

Understanding the Market and Identifying the Problem

• Market Research
• Identifying Gaps
• Developing User Personas
• Crafting a Problem Statement

Designing the Solution and Creating a Prototype

• Solution Ideation
• Prototype Development
• Gathering User Feedback
• Iterative Design

Building and Testing the MVP

• Defining MVP Core Features
• Development Sprint
• User Testing
• Establishing Feedback Loop

PART-2

Launching and Marketing the Product

• Developing a Launch Plan
• Identifying Marketing Channels
• Articulating Value Proposition
• Implementing Engagement Tactics

Measuring Success and Iterating

• Identifying Key Metrics
• Gathering Continuous Feedback
• Prioritizing Improvements
• Developing a Future Roadmap

Future content subscribe to https://linktr.ee/madhumitamantri