[Project] E-commerce Sales Analysis (Power BI)

Why I worked on this project

E-commerce data gets messy very quickly. Orders, products, customers, countries - everything piles up fast.

I worked on this project to step back and answer a more fundamental question: What actually drives revenue in an online business - and how concentrated is it?

Rather than focusing on individual transactions, I wanted to understand the bigger picture behind sales performance.

The question behind the data

From a business perspective, e-commerce performance is rarely evenly distributed.

Typical questions that come up are:

• Which products really drive revenue?

• How much does the business rely on a small group of customers?

• Are sales stable over time, or heavily seasonal?

• Which markets matter most?

Without this context, it’s difficult to make informed decisions about inventory, marketing priorities, or growth strategy.

How I approached the analysis

I used Power BI to explore sales performance across multiple dimensions:

• revenue and order volume,

• customer and product contribution,

• time-based trends,

• geographic distribution.

The focus was not on building a complex model, but on structuring the data in a way that reveals concentration, patterns, and seasonality.

Clear KPIs and simple comparisons made it easier to see where revenue was actually coming from.

What patterns emerged

Several patterns became clear during the analysis.

Revenue was heavily concentrated:

• a small number of products generated a large share of total sales,

• a limited group of customers accounted for a disproportionate amount of revenue.

Sales also showed strong seasonality, with noticeable peaks during specific periods of the year.

Geographically, performance varied significantly, with one market dominating overall revenue while others played a much smaller role.

Looking at these patterns together helped explain why headline revenue numbers alone can be misleading.

Why this matters for business decisions

Understanding revenue concentration and seasonality has direct business implications.

Insights from this analysis could support decisions around:

• inventory planning and stock prioritisation,

• marketing focus during high-impact periods,

• customer value management,

• risk awareness related to over-reliance on a narrow customer or product base.

It shifts the conversation from “How much did we sell?” to “Where does our revenue really come from - and how fragile is it?”

Tools used

• Power BI for data preparation, modelling, and visual analysis

The emphasis was on business insight and interpretability rather than technical complexity.

Want to see the technical details?

The full project, including the Power BI report and supporting materials, is available on GitHub

Final thought

This project made it very clear how fragile e-commerce revenue can be when it relies too heavily on a small group of products or customer.

Without understanding who and what drives sales, growth strategies risk being built on assumptions rather than evidence.