The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
I analysed customer data covering purchase history, customer behaviour and engagement to identify key customer segments and performance trends.
I cleaned and standardised the underlying data, created calculated fields and used Excel formulas and PivotTables to analyse customer value, purchase frequency, revenue and regional performance.
I then developed a clear dashboard bringing the findings together, including customer segmentation, key performance metrics, charts and insights to support commercial analysis and decision-making.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Everyone thinks a data dashboard should look complicated.
I think that is exactly why most of them fail.
I just finished Helios, a tool that tracks solar energy assets in real time. Dozens of sites, live output, verification records, a wall of numbers. The kind of screen people drown in.
Most designers would make it feel technical. More lines, more glow, more charts. I did the opposite. Every number had to answer one question in half a second, is this good or is this a problem. If it could not, it lost its place.
Because design is not decoration, it is closer to math. It is deciding what to remove until only the truth is left.
Complexity was never the enemy. Confusion is.
Get that right, and people trust you before you have said a word.
These components are perfectly executed, and the background is perfect for them.
Excel PivotTable — Sales Summary
Client had raw sales data (14 rows across UK/USA, split by quarter) and needed it turned into something actually usable. I cleaned it up and built a PivotTable that breaks total sales down by rep and country, with grand totals for both.
What I did:
Structured the raw data into a proper table (consistent headers, currency formatting)
Built a PivotTable summarizing Sum of Sales by Last Name and Country
Used SUMIFS so the totals update automatically if the source data changes — nothing hardcoded
Checked every formula for errors before delivery
Delivered as a working .xlsx file, ready to plug into a bigger report or dashboard.
If you've got messy sales/ops data sitting in a spreadsheet and need it turned into something you can actually read at a glance, this is exactly the kind of thing I can help with.
Built a pricing trend and variance analysis using synthetic business data to demonstrate my approach to data validation, trend analysis, anomaly review, and KPI reporting.
I analyzed month-over-month pricing changes, flagged unusual movements, compared performance across industries, and summarized the results in a clear Excel dashboard designed to support business review and decision-making.
Tools used: Excel, data validation, variance analysis, KPI reporting, and data visualization.
This is a self-directed portfolio project created to demonstrate an end-to-end analytical workflow.
