As a digital marketer working on Indian real estate campaigns, I needed a reliable way to pull fresh property listing data from 99acres for targeting and competitive analysis. Here's the pipeline I built.
The core tool: Apify 99acres Scraper https://apify.com/canadesk/99acres-scraper
My automated workflow:
Schedule the Apify actor to run weekly
Input = 99acres search URL for my target localities (e.g. Hyderabad, Gachibowli, Kokapet)
Actor extracts all listings: price, BHK, sq.ft, builder, agent contact
Output CSV gets uploaded to Google Sheets via Apify webhook
BigQuery picks it up for trend analysis
Looker Studio dashboard auto-refreshes with new pricing data
What I use the data for:
Competitive pricing: Track how competitor projects price similar BHK configurations week-over-week
Ad audience building: Use locality + BHK data to build Custom Audiences in Google Ads and Meta
Inventory signals: Identify when competitor projects reduce listings (sold out) vs. add new ones (new phase launch)
Market reports: Auto-generate price-per-sqft trend charts for each micro-market
Why not build a custom scraper? 99acres has heavy bot detection. I tried Scrapy + rotating proxies and it broke within a week after their CDN update. The Apify actor is maintained and handles all that transparently.
Anyone else building data pipelines on top of Indian real estate portal data? Would love to see how others are structuring this.
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