Helping founders automate their messy data collection tasks
Hey everyone,
I’ve been building and refining my custom backend data pipelines in public for over 3 years now. One major thing I’ve noticed in the startup community is how much time solo founders waste on manual data entry and lead scraping when validating their ideas.
My current focus is helping indie hackers completely automate these bottlenecks. I build tailored Python scraping scripts that run in the background, extract real-time data from any directory, and push it straight to your spreadsheets.
If you are currently stuck doing repetitive data mining or manual outreach tracking, let me automate it for you.
My expert Python scripting and web scraping services are now live on Fiverr:
🔗 https://www.fiverr.com/s/qDWRm8X
Drop your most time-consuming manual data task below, and let’s talk about how to automate it!
Good timing to bring this up. One thing I see founders overlook when automating data collection: the scraping itself is usually the easy part — the hard part is what happens downstream. Data lands in a spreadsheet or flat file, and then 3 months later someone needs to query across 90 days of it, and now you're rebuilding the pipeline from scratch with actual structure.
If you're helping founders who eventually want to do analytics (not just collection), it's worth nudging them early toward a simple schema — even a basic staging table in SQLite or Postgres beats a folder of CSVs when you're trying to answer questions like 'which lead source converted best last quarter.' The scraping layer and the query layer need to be designed together, not sequentially. Worth flagging to clients before they scale.
Spot on, Shehroz! Couldn't agree more. A folder full of messy CSVs quickly becomes a nightmare for any founder trying to scale analytics downstream. I always push for a clean, relational schema (even a lightweight SQLite setup) right from the start. Designing the scraping layer with the final query structure in mind saves months of refactoring later. Appreciate you flagging this critical point!