Built on my own dataset — AAA Reviews and Invoices — this dashboard was designed for a Sales & Marketing VP who needs fast, authoritative answers without switching tools, digging through reports, or losing the narrative.

To power the analysis, I built a suite of custom calculations covering sales performance, year-over-year comparisons, targets, review metrics, and customer sentiment — transforming a flat dataset into a rich analytical engine.

The experience begins with a single choice. A drop-down filter labeled "Dashboard" with two values — Review and Sales — acts as a navigation control unlike anything you've seen before. One selection silently reshapes the entire canvas into a completely different analytical world. The end user never needs to know what's happening behind the scenes. They just choose and go.

Select Review and the dashboard comes alive with customer intelligence — sentiment-coded review trends with forecast, the top 10 most positively and negatively reviewed products, and KPIs tracking review volume, average rating, and reviewer count. The story isn't just what sold — it's what customers felt.

Select Sales and the canvas transforms — revenue by channel, sales trends with forecast, top products, and a side-by-side channel comparison that puts Amazon, Camp & Compass, and eBay in direct conversation with each other.

Anchoring both views is something you won't find in any documentation, any community post, or any other dashboard — a first-of-its-kind KPI Banner, independently discovered and built from scratch:

🎯 YTD Sales $4.08M | 95.4% of Goal ◆ 📣 Reviews TY: 1,065 PY: 3,104 | 👥 2,298 Customers | 💻 55% Direct 🏆🔥

Six live metrics. One bold, scannable line. Completely independent of any workbook dataset — drop it onto any dashboard across the organization and it instantly delivers the same live corporate metrics everywhere it lands. One banner. Every dashboard. One source of truth.

And the backdrop? A dramatic ai-generated, outdoor wilderness scene — dark skies, towering pines, a glowing campfire — created deliberately to reflect the world of the products being sold.

One Oracle Analytics AI feature was used — Forecast — applied to both the review trend and sales trend charts to project future performance. Every other element was designed, calculated, and built by hand.