Build an AI-Powered SEO Analyzer with OpenAI and Next.js — Proven to Boost Google Search Console Performance
In this hands-on course, you’ll build your own AI-powered SEO Analyzer using Next.js, OpenAI (GPT), and the Google Search Console API. This is more than theory — it’s a working tool I used on my own site to 10x Impressions and 50+ Clicks in 45 Days.
🎯 Goal: 10x Impressions and 50+ Clicks in 45 Days 🔓 The course will unlock after 45 days, once the tool proves it works — and you'll be able to use it in your own projects.
What makes this course unique:
- We’re not just building — we’re proving it works
- This tool is working on a live site and track results in real-time
- When the tool hits our 50-click goal, the course will be launched to the public.
Whether you're a developer, marketer, or SEO enthusiast, you'll walk away with:
- A fully working SEO Analyzer app (Next.js + GPT + GSC API)
- Prompt templates to generate SEO insights
- Actionable strategies to increase impressions, clicks, and CTR
Daily Performance Report
About the Course
Welcome to the Build Google Search Console Performance Analyzer with OpenAI and Next.js course — a hands-on journey designed to empower you with the skills to create an AI-driven SEO tool that can transform your website’s organic traffic.
In this course, you will learn how to harness the power of Google Search Console (GSC) data combined with advanced large language models (LLMs) like OpenAI’s GPT to generate actionable SEO insights. Starting from scratch, we guide you through setting up a modern Next.js application, integrating with Google’s Search Console API to fetch vital performance metrics such as clicks, impressions, CTR, and average position.
You’ll discover how to process and display this data effectively in a clean, interactive dashboard using React components and Tailwind CSS with DaisyUI. But this course goes beyond just data visualization — you’ll learn how to leverage prompt engineering techniques to feed your GSC metrics into an LLM, enabling the AI to analyze keyword performance, diagnose SEO issues, and suggest targeted optimization strategies.
The course also covers building a conversational chatbot interface powered by Vercel’s useChat hook, allowing you to interact with the AI in real-time and receive personalized SEO recommendations. This practical approach gives you a deep understanding of how AI can augment traditional SEO workflows, making your optimization efforts smarter and more efficient.
Whether you’re an SEO specialist, developer, or digital marketer, this course equips you with the knowledge to build a cutting-edge SEO analyzer that blends data-driven insights with AI intelligence. By the end, you’ll not only have a working tool but also the skills to customize and expand it — including ideas like adding persistent chat messages and correlating page content with keyword data for even richer analysis.
Join this course to unlock the future of SEO optimization by combining the best of Google Search Console and AI technology in a seamless, user-friendly application. 🚀
Requirements
Highly recommended to have basic knowledge of Next.js and React, and read the following resources
Course Instructors
Learn from real-world instructors with extensive experience who actively work in the roles they teach. They are committed to helping you succeed by sharing practical insights.
Amir is a full-stack developer with a strong focus on building modern, AI-powered educational platforms. Since 2013, he has worked extensively with Open edX, gaining deep experience in scalable learning management systems. He is the creator of Cubite.io, and publishes AI-focused learning content at The Learning Algorithm and Testdriven. His recent work centers on integrating artificial intelligence with learning tools to create more personalized and effective educational experiences.
📚 Syllabus
- 📌An AI tool that helped to increase organic traffic by 40%
- 📌What Are Google Search Console Metrics?
- 📌Why use LLM with GSC
- 📌Role of GSC in Modern SEO Strategies
- 📌Summary
- 📌Installing Next.js
- 📌Install Libraries and Dependencies
- 📌Install DaisyUI
- 📌Adding UI components
- 📌Enable GSC API in Google Cloud Project
- 📌Import Service Account Key
- 📌Fetch Data from Google Search Console API
- 📌Show Data in the Metrics Table
- 📌AI API Endpoint
- 📌Picking the Model
- 📌Prompt Engineering
- 📌Implement Chatbot
- 📌Show LLM Insights
- 📌Key Takeaways and Next Steps