Optimize Amazon Sales with a Dynamic Excel Dashboard

Optimize Amazon Sales with a Dynamic Excel DashboardOptimize Amazon Sales with a Dynamic Excel Dashboard

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Samuel Maina

• 20h

Amazon Sales Performance Dashboard

Developed a fully interactive, dynamic e-commerce dashboard inside Microsoft Excel to analyze sales trends, operational fulfillment metrics, and distribution performance for Amazon sales data.

Key Features & Analytical Breakdown:

Executive Revenue Tracking: Analyzes over $78.5M in Total Revenue, tracking 128K+ Total Orders and keeping a precise gauge on an Average Order Value of $609.36.

Product & Demand Analysis: Features localized bar charts breaking down performance by product categories and a comprehensive 'Size Demand Analysis' to track high-volume inventory movement.

Logistics & Fulfillment Operations: Built pie charts detailing Fulfillment & Shipping Speed alongside dynamic status trackers (Cancelled, Shipped, Unshipped) to spot supply chain bottlenecks.

Dynamic Slicers & State Filters: Programmed fully interactive Excel slicers to filter performance seamlessly by individual state markets.

Data Analysis Data Visualization Microsoft Excel

Uto Justine Terzulum

• Jun 22

I built a comprehensive sales tracking spreadsheet for an engine oil business that automatically tracks daily sales, calculates profit per transaction and labels each sales. The client can instantly see their most profitable product, total revenue, total costs and net profit for any period without any manual calculations.

Accounting Data Analysis Data Visualization Clean Spreadsheets Microsoft Excel

Geethasree Naguboina

pro

• Jun 25

This is exactly the kind of clarity every small business owner needs — being able to see profit per transaction and top products at a glance without manual calculations is a game changer. Great work on the performance labelling too! 🙌

Dmytro Zelinskyi

pro

• Jun 23

Sentra — AI Decision Intelligence Platform

AI platforms have a credibility problem. Everyone claims intelligence. Most websites look the same: gradient blobs, generic dashboard screenshots, vague promises. Sentra needed to feel like the product already works before you've even signed up.

The 3D wireframe spheres do the heavy lifting here. They visualize the pipeline (Raw Signals → Decision Engine → Actionable Output) without a single flowchart arrow. You read the data journey through the visuals, not despite them. The dark UI isn't an aesthetic choice, it's a trust signal. When your product processes unstructured multi-source data into confident decisions, the interface should feel like a control room, not a marketing page.

Mobile keeps the same weight. No compromises, no "lite" version. Same conviction, smaller screen.

"Clarity. Signal. Control." Three words in the footer. The design already said it.

#WebDesign #UIDesign #SaaS #AI #DataVisualization #DarkUI #ProductDesign #LandingPage #3DDesign #TechDesign

UI Design UX Design Web Design Figma

Liudmila Davydiuk

• Jun 24

Designed and built a full data pipeline — pulling from multiple sources, resolving inconsistencies, enriching with external variables, and delivering clean outputs through interactive Power BI dashboards stakeholders can actually act on. Designed and built a full data pipeline — pulling from multiple sources, resolving inconsistencies, enriching with external variables, and delivering clean outputs through interactive Power BI dashboards stakeholders can actually act on.

The starting point was a large, structurally complex dataset with inconsistent formats, missing values, and misaligned fields. The goal was a repeatable pipeline that transformed it into something reliable enough to drive real decisions.

The enrichment layer was the differentiator: layering in demographic and contextual variables from external sources to add depth that the raw data alone couldn't provide. The final output was a Power BI dashboard built for non-technical audiences — clear enough to act on, rigorous enough to hold up to scrutiny.

AI-assisted validation (Claude Enterprise) was used throughout to cross-check outputs and flag inconsistencies before delivery