Detect the revenue your store never realized.
Revenue Leak Detection System is a Shopify-focused intelligence platform designed to surface hidden losses from discounts, cancellations, chargebacks, abandoned checkout, shipping mismatch, inventory issues, and app spend. The current MVP includes discount-related leak detection and a working Shopify webhook export pipeline that sends order event data to AWS S3 for cloud-based storage and future processing.
Discount rule implemented to flag suspiciously high discount percentages in Shopify orders.
Order-related Shopify webhook events are successfully exported into S3 for external cloud storage.
Webhook subscriptions were corrected so order creation and fulfillment-related events can be captured properly.
Additional leak modules are planned, but the portfolio presents the current system honestly as an MVP with real integration work completed.
Revenue is only half the story.
Shopify merchants often track sales, but a lot less attention goes to revenue that leaks out through discounts, cancellations, refunds, operational cost mismatch, technical issues, and disconnected data. This project reframes store analytics around realized revenue, not just top-line activity.
Revenue loss is fragmented.
Discounts, returns, chargebacks, stockouts, and shipping losses are usually scattered across reports and tools instead of being surfaced in one clear system.
A single leak detection layer.
This platform groups multiple revenue-loss patterns into one product vision so merchants can identify where money is disappearing and prioritize action.
Discount detection + S3 export pipeline.
The current MVP detects discount-related revenue leakage and captures Shopify order webhook data into AWS S3, building a real cloud-based data pipeline for future processing and reporting.
Ten ways a Shopify store can leak revenue.
This system is designed as a multi-module product, not just a single dashboard screen. The categories below define the full product vision and long-term roadmap.
High Discount Leakage
Detect orders where aggressive or abnormal discounting erodes expected revenue.
Order Cancellations & Returns
Track post-purchase losses that reduce realized revenue after the order was initially booked.
Chargebacks
Surface losses from disputes, payment reversals, and fraud-related transactions.
Abandoned Checkout
Highlight missed revenue where customers reached checkout but did not complete the purchase.
Store / Domain Issues
Store outages or broken domain setups can silently reduce conversion and revenue.
Traffic Without Revenue
Visitors are arriving, but the store fails to convert them into sales.
Staff Orders with Credit / Gift Cards
Review internal order creation patterns involving store credit or high-percentage gift card usage.
Shipping Cost Mismatch
Compare what the customer paid for shipping versus what the merchant actually spent on the shipping label.
Inventory Loss
Out-of-stock products create missed revenue opportunities and conversion drop-off.
High App Charges
Identify recurring Shopify app costs that may not be producing meaningful store value.
How the system works.
The architecture is intentionally simple and cloud-friendly: connect to Shopify, capture webhook events, export raw data to AWS S3, evaluate revenue-leak logic, and surface readable findings for merchants.
Shopify App Integration
The app connects to Shopify and receives order-related activity through app routes and webhook subscriptions.
Webhook Data Export to AWS S3
Incoming Shopify order events are exported to Amazon S3 for durable cloud storage and future external processing.
Revenue Leak Processing
The MVP evaluates order pricing and discount behavior to detect suspicious discount-related revenue leakage.
Dashboard Findings
The merchant sees readable findings instead of manually piecing together revenue issues across disconnected reports.
Potential revenue leakage
Illustrative dashboard concept
What is built now vs. what comes next.
This project is presented honestly as a strong MVP with real Shopify and AWS integration already working, plus a clear roadmap for deeper revenue intelligence.
Discount leakage detection + S3 export pipeline
- Analyzes Shopify order-level pricing data
- Flags discount-related revenue leak scenarios
- Displays findings in a dashboard
- Exports Shopify order webhook data to AWS S3
- Creates a cloud-ready data pipeline for future processing and third-party integrations
Shipping loss module
Compare charged shipping fee versus actual shipping label cost.
Refunds, cancellations, and chargebacks
Quantify post-purchase erosion of realized revenue.
Traffic and conversion leakage
Show when visitors arrive but meaningful revenue does not follow.
Inventory and app-cost intelligence
Detect missed sales from stock issues and recurring app costs with low value contribution.
Technical highlights.
This project is not just a UI concept. It includes embedded Shopify app work, real webhook handling, AWS S3 export, and debugging through actual integration issues.
Shopify embedded app foundation
Built as a Shopify app with backend routes, admin authentication flow, and dashboard-oriented product thinking.
AWS S3 export pipeline
Webhook payloads are exported into S3 so store activity can be stored externally and used later for processing, analysis, or integrations.
Revenue intelligence direction
The project is designed around business value: turning raw commerce events into actionable revenue-loss signals.
Issues faced and troubleshooting done.
One of the strongest parts of this project was the debugging journey. The finished MVP came from working through real integration problems across Shopify routes, webhook subscriptions, TypeScript imports, app configuration, and AWS export behavior.
1. Route and file naming issues
During development, route and model imports caused TypeScript errors because of file-name casing mismatches. One import referenced leakFinding.server while the file was actually named LeakFinding.server.
2. Dashboard initially showed zero findings
Even after creating real test orders with different discount values, the dashboard initially showed no findings. That created uncertainty around order access, Admin API connectivity, and logic correctness.
3. Webhook subscriptions were incomplete
In Shopify app setup, the developer dashboard initially showed only limited webhook subscriptions. Order creation was present, but fulfillment-related subscriptions were missing until the webhook configuration was corrected and redeployed.
4. Wrong webhook route path
A webhook URI path issue prevented correct handling. The path needed to include the proper application route pattern instead of the earlier incorrect webhook path configuration.
5. S3 export uncertainty
After creating orders from the online store, the exported data did not initially appear in S3, which required checking whether the webhook was firing, whether the subscription existed, and whether the handler route matched the config.
6. Portfolio-related 404 and deployment issues
While documenting the project publicly, the portfolio site also had deployment friction, including broken case-study routing and missing page assets, which required fixing file placement and hosted path consistency.
Consistent file casing and imports
The model file naming and imports were corrected so TypeScript could resolve the proper server module without duplicate-file casing conflicts.
Tested with real Shopify orders
Real orders were created using multiple discount scenarios such as 10%, 30%, and 50% to verify that the logic was using actual store data instead of mock assumptions.
Reviewed Shopify app configuration
The app configuration and webhook registration were checked and updated so order-related subscriptions were properly registered after deployment.
Corrected webhook endpoint routing
The webhook URI path was fixed to the correct application route structure so Shopify events could hit the intended backend handler.
Verified new entries in AWS S3
After correction and redeployment, new order-related entries were successfully confirmed in S3, proving the webhook export pipeline was functioning.
Improved credibility through honest scope
Instead of presenting the system as fully complete, the project was repositioned accurately as a real MVP with one working leak rule and a functioning Shopify-to-S3 integration pipeline.
Why recruiters should care.
This project demonstrates full-stack product thinking across Shopify app development, webhook integration, AWS S3 data export, backend logic, dashboard presentation, and debugging under ambiguity. It shows the ability to turn raw commerce events into a structured system for business problem solving.
Full-stack product thinking
Combines Shopify app integration, backend logic, cloud export, and frontend presentation in one cohesive workflow.
Solves a measurable problem
This project is tied directly to margin, realized revenue, and operational efficiency rather than being just a visual dashboard concept.
Built through real troubleshooting
The implementation required solving actual route, config, webhook, TypeScript, and cloud export issues instead of following a tutorial-only path.
A revenue intelligence platform for Shopify.
Built to help merchants find hidden losses, validate discount behavior, and create a foundation for broader revenue leak detection using Shopify events and AWS cloud storage.