Web Scraping Case Studies
Real results from real enterprise data projects. See how leading teams cut costs, accelerate pipelines, and unlock competitive intelligence with APISCRAPY.
All case studies
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How an Enterprise Replaced Five Vendors With One Data as a Service Pipeline
A global consumer electronics manufacturer consolidated five data vendors into one APISCRAPY DaaS pipeline, cut annual data acquisition spend by 41%, reduced weekly reconciliation from 60+ hours to under five, and expanded to three new Asia-Pacific markets in under two weeks each.
How a Marketplace Tracked Competitor Catalogs With Ecommerce Web Scraping
A US laboratory and medical equipment marketplace received 1.2 million competitor product records in its own template at 99%+ data quality, delivered in three weeks at around 80% savings on data collection costs.
How a PropTech Startup Built a Listings Feed From Real Estate Data Scraping
A seed-stage PropTech startup launched a multi-market listings feed covering 180,000+ active properties in 12 US metros in three weeks — versus a 6–9 month estimate for MLS access — with stale listing rate cut from 15% to under 2%.
How a SaaS Team Shipped Faster Using a Web Scraping API Instead of Building In-House
A Series A talent intelligence SaaS freed two engineers from scraper maintenance, shipped a feature that had slipped two quarters in-house, and improved source freshness from ~90% to 99%+ — seven weeks after switching to APISCRAPY's web scraping API.
How a Digital Shelf Analytics Firm Cut Weekly Data Collection Time by Outsourcing Web Scraping
A retail analytics firm cut data collection time by ~90% and delivered next-day shelf reports to brand clients by outsourcing web scraping to APISCRAPY.
From Manual Copy-Paste to Automated Web Data Extraction at Scale
A mid-market consumer insights agency reclaimed 100+ analyst hours per week and cut report turnaround from five days to under one day by replacing manual data entry with a managed web scraping service.
What enterprise teams say
We used to find out a job board had redesigned when a customer emailed us about missing salaries. Now the sites change and our data simply doesn't notice.
We used to spend the first week of every quarter arguing about whose numbers were right. Now there is one feed, one schema, and one team to call when a site changes.
We didn't need another folder of raw pages. We needed a competitor's entire catalog in our own format, and that is exactly what arrived.
Bring us your data challenge
Tell us the sources, the schema, and the cadence you need. We scope a pilot in days, not weeks — with published pricing and a sample dataset to compare.