Q. Final Year student: Sohaan Sureshkumar
Q. Course: BSc Hons Computing (Software Engineering)
Q. Project title: Virality-to-Profit Dashboard: A Business Intelligence Tool for Organic E-Commerce Sellers
Q. Motivation for choosing the project: I run an organic e-commerce Brand called WaxAwayCo alongside my studies, selling products through Shopify with all marketing done organically on Instagram no paid ads, just content creation. I kept hitting the same wall where I could see my Instagram views in one app and my Shopify profit in another, but there was no way to connect them.
Paid advertisers have metrics like CPA (Cost Per Acquisition) and ROAS (Return on Ad Spend) built into their platforms. Organic sellers have nothing. After a viral post, I’d spend hours on spreadsheets trying to answer: “How much profit did that video actually make me?”. My literature review with over 50 academic sources confirmed this wasn’t just my problem it’s a genuine gap across the entire organic social commerce industry. I decided to build the tool I wished existed.
Q. Overview of the practical implementation:
The dashboard is a web application built with PHP 8.3, MySQL, and Chart.js. Users upload two CSV files: Instagram Insights and Shopify Orders and the system processes them through an ETL pipeline:
- Data Extraction: Parse both CSV files, handling different date formats and currency symbols automatically.
- Transformation: Aggregate Instagram metrics by day, clean Shopify data, calculate derived metrics including two novel measures I developed.
- Loading: Store processed data in a normalised MySQL database with four tables, powering all dashboard visualisations.
The core innovation is two new metrics I created specifically for organic e-commerce:
- V2O (Views to Orders): Orders generated per million views. If V2O is 200, every million views produces ~200 orders.
- NPV (Net Profit Value per Million Views): Actual profit per million views after all costs (COGS, shipping, fees, refunds).
The main dashboard is where users upload their Instagram Insights and Shopify Orders CSV files. Once processed, the page displays six KPI cards summarising total views, orders, revenue, net profit, and the two novel metrics, V2O and NPV. Below the cards, a dual-axis line chart plots views against orders over time, revealing how content performance correlates with sales. A daily profit bar chart uses conditional colouring to show profitable days in green and loss-making days in red.
This page provides a deeper breakdown of profitability. The waterfall chart visualises how gross sales reduce to net profit step-by-step, showing exactly how much is lost to cost of goods sold, shipping, payment fees, and refunds. A doughnut chart displays cost proportions at a glance.
The best and worst performing days are ranked by net profit, the day with the highest net profit appears as the best performer, while the day with the lowest (or most negative) net profit is flagged as the worst. This helps sellers quickly identify what’s working and what isn’t.
The automated insights analyse the actual data and generate contextual recommendations. If cost of goods sold exceeds 50% of revenue, it suggests reviewing supplier pricing. If the refund rate exceeds 5%, it flags a potential product quality issue. If shipping costs are disproportionately high, it recommends exploring alternative fulfilment options. These thresholds are based on standard e-commerce benchmarks, giving sellers actionable guidance without needing to interpret the numbers themselves.
Q. Overview of the outcome/conclusion:
The system was tested with 28 test cases achieving 100% pass rate, with calculations verified against manual spreadsheet checks. User evaluation with five organic e-commerce sellers from my target audience produced strong results:
- Overall Rating: 4.6/5
- Visual Design: 4.68/5 (highest category)
- 80% said they would “definitely” use the tool regularly
User feedback was particularly encouraging. One participant called V2O:
“Genius, I can finally see how many views I need to generate sales.”
Another said the waterfall chart “makes accounting simple to understand.”
The project demonstrates that standardised efficiency metrics for organic social commerce equivalent to what paid advertisers have had for years are both achievable and genuinely valued by sellers.
Q. Advice for students who are interested in completing a University Degree & Final Year project?
- 1. Develop resilience by seeking challenges early. The skills that feel most difficult at the start like independent research, technical problem-solving, presenting your work, become significantly easier with practice. Students who push themselves outside their comfort zone in earlier years tend to find the demands of final year far more manageable.
- 2. Solve a problem you actually have. My project worked because I built something I genuinely needed for my own business. When you’re solving your own problem, you understand the user deeply, you stay motivated when things get hard, and you can test with real data from day one. Don’t pick a project because it sounds impressive, pick something you’ll still care about when the code isn’t working.
- 3. Start your literature review early. I reviewed more than 50 sources, and that foundation shaped everything else. When I found papers confirming organic ROI measurement was an unsolved problem, it validated my entire approach. The literature review isn’t a box to tick, it’s where you discover whether your idea has real merit.
- 4. Scope ruthlessly. I could have added TikTok support, API integration, user accounts, and a dozen other features. But a polished tool that does three things excellently beats a sprawling mess that does ten things poorly. Define your minimum viable project, build that well, and put everything else in “Future Work.”
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UWTSD Applied Computing Blog 
Written by jameswilliams
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