u/Dondongy

This question came to my mind out of curiosity, so I wanted to share it with you. I’ve been an active browser here for a while, and I’ve noticed some Redditors sharing their political opinions without fear, unlike on Facebook. Is it because we’re behind usernames and random PFPs, or is it simply because our government hasn’t acknowledged the existence of Reddit in general yet? 😂

Honestly, I hope it stays that way so this sub can remain a chill place for everyone.

Hello my account is two years old , when i first created it back i had 4 posts and got from them 10 to 20 karma (I dont remember exactly) but these days i logged in and found that the posts still exists but the old karma points are gone why is that ?

I landed my first paid automation project last week. Client sells football jerseys wholesale and needed qualified retailer contacts across the UK, France, and Italy. He was doing it manually — scrolling Google Maps for hours, missing most opportunities, and had no way to score which shops were actually worth a cold call.

I built him a full qualification pipeline. Here's what shipped:

https://preview.redd.it/2sfatu3g31jh1.png?width=1528&format=png&auto=webp&s=1a96b7b50c3e094c5da1bdb651f9af2764368d40

The stack:

• Apify (Google Maps Scraper) for raw data pull
• n8n for orchestration — 3 parallel branches (GB/FR/IT), Loop Over Items for batching
• OpenRouter +DeepSeek for qualification — reads page_title, meta_description, meta_keywords
• Google Sheets as the destination

The filtering logic:
I call it "Smart Wide." It only blocks the obvious junk — chains, club megastores, pubs, schools, stadiums, malls. Everything else passes to DeepSeek. The AI returns DEFINITELY, LIKELY, MAYBE, or NO with a one-sentence reason.

The result: 23 qualified independent jersey shops in the first 2 days. Client went from manual scrolling to a filtered Sheet he can call down in an afternoon.

One painful lesson: I started with keyword-only filtering. Thought I could catch everything with "vintage football shirts" and "retro jerseys." It was a disaster. Caught printing shops, souvenir stands, and club megastores that happened to mention the right words. I had to rebuild the whole scoring layer with DeepSeek reading the actual page content — title, description, keywords — and returning a real qualification score with reasoning. Night and day difference. Keywords catch mentions. AI catches intent.

I just got a question for the community how do you handle the transition from keyword filtering to AI qualification without burning through API costs on obvious junk? I used a "Smart Wide" pre-filter to block the worst categories before sending anything to DeepSeek, but I'm curious if there's a cleaner way to tier filtering without losing nuance.