CampaignWave - Marketing Analytics Dashboard

CampaignWave was built to solve a common frustration: making sense of marketing campaign performance data without drowning in spreadsheets or paying for expensive enterprise analytics tools. But honestly? This project has a deeper story. I built CampaignWave as a test application for a workflow I've been developing, one where Claude can see and fix its own visual mistakes. You can read about that in my Claude God Tip #12 blog post. I needed a clean, contained project to experiment with, and a marketing dashboard seemed perfect. Then my Dell XPS 13 decided November 30th was a great day to take its last breath. Three years and four months old. I had just gotten back from hanging out with a friend, sat down to work, pressed the power button... and nothing. Over an hour of Reddit troubleshooting later, it was officially dead. So I had to postpone working on the app until I received my new laptop. The timeline says November 29 to December 6, but really? Two actual working days: the 29th and the 6th. One good thing about this delay was that I learned a lot about tokens and context engineering while waiting for the arrival of my new laptop, and that knowledge had some impact on the case study. The design philosophy centers on neumorphism, my second favourite design trend. Every card, button, and input has that characteristic "pushed" or "raised" look that makes the interface feel tactile and modern. In many ways, this app is similar to the ones I built when working at Outlier training AI models, but with one major difference: unlike those single-file solutions, CampaignWave is built properly with modular components, clean separation of concerns, and a scalable folder structure. The dashboard tracks six key marketing metrics: Engagement Rate, Follower Growth, Conversion Rate, Click-Through Rate, Bounce Rate, and Session Duration. Each metric displays with animated count-up effects when the page loads. Campaign comparison lets users select any two campaigns and compare them side-by-side using six different chart types, with a range slider controlling how many months of data to display. Users can import their own JSON files or download one of six sample industry datasets covering different data patterns: E-commerce, SaaS, Healthcare, Restaurant, Nonprofit, and even a "Struggling Brand" dataset for testing downward trends. The whole thing is wrapped in smooth Framer Motion transitions that make navigating between pages feel polished.