Marketplace Value Pipeline
Running a resale business means juggling listings, buyers, shipping, and financials all at once. It’s easy to lose track of what’s really driving or draining profit.
I built a dashboard that takes the guesswork out. Instead of piecing things together from spreadsheets or gut feelings, this automated pipeline pulls data directly from eBay and Craigslist, cleans it, and updates a Power BI dashboard in real time.
You can track your inventory lifecycle, spot flip opportunities, and keep tabs on shipping costs and profit margins. All in one place.
With automation and AI built into the process, the system keeps working in the background so you can focus on the human side of the business.
Finding great products and serving customers.
Marketplace Resale Business | eBay & Craigslist
Industry: E-commerce / Resale
Annual Revenue: <$1K (side business, scaling phase)
Tools:
Python (Pandas, NumPy, BeautifulSoup, OpenAI) – Data scraping, cleaning, automation, AI-assisted labeling
Supabase (Postgres) – Cloud storage & data modeling
Power BI – Interactive dashboards & KPI visualization
Render / cron (launchd) – Automated job scheduling
BI Maturity: Early – Data siloed across spreadsheets and marketplace accounts, limited visibility into profitability and operations
Problem
Running a resale business means balancing inventory, shipping, sourcing, and profit tracking. I was relying on manual spreadsheets and inconsistent tracking, which left me blind to where money was actually being made or lost. The business was running negative profit, and I needed clarity on shipping costs, overspending on products, and rushing deals instead of waiting for the right customer.
Project Goals
Automate data collection from eBay and Craigslist
Centralize inventory, sales, and costs into a single cloud database
Build a Power BI dashboard to track pipeline, lifecycle, and profitability
Surface insights on flip opportunities and market trends
Lay the foundation for AI-powered agents to handle alerts and marketing
Process Pipeline Dashboard
High-level view of the resale business pipeline, tracking unlisted, active, and sold inventory. Includes flip opportunities, profit summary, and average profit per opportunity.
Flip Opportunities Dashboard (Craigslist & eBay)
Detailed marketplace insights highlighting estimated profit by listing, pricing trends, and sell-through rates. Bubble charts and tables surface the best flip opportunities across themes like Nintendo, PlayStation, and LEGO.
Star Schema Data Model
Data model connecting dimension tables (Date, Search Terms, Item/Inventory) with fact tables for eBay and Craigslist (cleaned and summary levels). This schema supports efficient querying, trend analysis, and scalable BI reporting.
Results
Clarity Over the Pipeline
Created a real-time pipeline dashboard showing items from Bought → Listed → Sold, surfacing where inventory was stuck and how long items had been aging.
Opportunities at a Glance
Built a Flip Opportunities view with eBay and Craigslist tabs, including pricing trends, margins, and GenAI-generated opportunity labels. Reducing the need to manually sift through listings.
Profitability Insights
Developed a profit summary that broke down acquisition cost, shipping, fees, revenue, and margins. Early insights showed negative profits tied to shipping costs, rushed sales, and overspending on products.
Foundation for AI & Automation
Automated scraping and scheduled refreshes keep data current without manual effort. With GenAI already assisting in labeling, the project sets the stage for future AI agents to handle marketing alerts and pricing strategy.
Marketplace Data Pipeline Architecture
End-to-end workflow from marketplace listings through automated scraping, Python processing, data cleaning/modeling, cloud storage in Supabase/Postgres, and visualization in Power BI. Automated with cron jobs to ensure fresh insights daily.