Self-initiated fictional concept. The e-commerce business and dataset are fictional and were created for portfolio demonstration. No real company data or real-world business results are represented.
For an e-commerce team, “How are sales doing?” needs more than a revenue total. What period are we looking at? Which orders count? What should we investigate next?
In my BI dashboard concept, I kept the executive view focused on four core measures: revenue, completed orders, purchasing customers and average order value.
The important decisions sit behind those cards:
• Revenue uses completed order lines after discounts; cancellations and full refunds are excluded.
• Orders and purchasers are distinct counts. AOV is revenue divided by completed orders—not an average of monthly averages.
• Filters use a shared scope, and year-over-year comparisons use the same dates and dimension filters.
• Findings lead to investigation prompts, not promises. A strong category is a reason to examine product mix and costs before increasing inventory.
My starting point when scoping a dashboard: agree on the decision, define the measures, then choose the visuals. That helps a small team understand what the numbers can—and cannot—tell them.
Which is harder in your sales reporting: agreeing on the numbers or deciding what to investigate next?
🚀 Turning Manual E-commerce Order Processing into an Automated Workflow with n8n
Manual order management may seem simple, but copying customer details, checking information, preventing duplicate orders, and sending confirmation emails can quickly become repetitive and error-prone.
I recently built an end-to-end order processing automation using n8n to solve these challenges for a handmade products store.
Here's what I implemented:
🔹 Automated Order Capture: Receive new orders through a webhook.
🔹 Data Validation & Cleaning: Validate required fields, email formats, quantities, and prices before processing.
🔹 Duplicate Prevention: Detect existing Order IDs to prevent duplicate records.
🔹 Google Sheets Integration: Automatically store valid orders and calculate order totals.
🔹 Email Notifications: Send order updates to the store owner and confirmation emails to customers.
🔹 Error Monitoring: Capture failed executions, log error details in a dedicated Google Sheets tab, and send email alerts.
The goal was simple: reduce repetitive administrative work, improve data accuracy, and make order operations more reliable.
This is what I enjoy about building with n8n — turning complex, repetitive business processes into practical automation systems.
Have a repetitive workflow in your business that could be automated? Let's connect!
What should a beekeeping website explain before asking someone to choose a hive?
For Bee Girl, I designed and built a complete Shopify website around a clear journey: meet the colony, understand what’s inside a nucleus hive, compare the options, and connect with the beekeeper.
Honey yellow, hive black, warm cream, and bold typography bring the same visual language across desktop and mobile layouts.
One design decision that ties it together: the page explains the colony and its five frames before introducing the hive-quantity choices. Education gives the product selection context.
I handled the complete website project for the client through Fiverr, using Shopify. This video walks through the homepage.
Which would you explore first—the hive options, field classes, or the beekeeper’s story?
I'd open the hive options first, but only because the colony section already told me what I'm buying. Explaining the five frames before the quantity choice is a smart order. Teaching before asking someone to choose is so underrated in Shopify stores.