Lena Zhou
Growth & Integration Specialist
Lena Zhou is a Growth & Integration Specialist at Nstdata, focused on helping businesses leverage proxy technology for scalable data collection, automation, and global operations. With experience in product adoption, platform integrations, and growth strategies, she shares practical insights on proxy use cases, market intelligence, web scraping workflows, and digital expansion.
All Articles
Dun & Bradstreet Scraper and D&B API: A Business Data Guide
Compare public-page extraction with licensed D&B API access, follow the documented Direct+ token flow, and evaluate jurisdiction-specific registry alternatives.
Real Estate Scraping: A Guide to Public Property Data Collection
Build a property parser with bounded pagination, deduplication, unit normalization, and history. Distinguish listing identity, property identity, and source rights.
Dify SERP Scraping: How to Build a Search Data Workflow
Configure search retrieval, result normalization, optional page acquisition, and source-bearing answers in Dify. Includes a checked normalization function.
Firecrawl vs Nstdata: Features, Pricing, Performance & Migration Costs
Compare Firecrawl vs Nstdata Crawl on features, pricing, JavaScript rendering, scalability, and migration costs. Learn when and how to switch.
Crawl API for RAG: Turning Websites into LLM-Ready Data
Learn how to clean, validate, chunk, and index website content for a source-aware RAG pipeline.
Crawl4AI vs Nstdata Crawl: Self-Hosted and Managed Options
Compare self-hosted Crawl4AI, Crawl4AI Cloud, and Nstdata Crawl on control, operations, and RAG output.
How to Migrate from Firecrawl to Nstdata: A Developer Guide
Map crawl jobs, results, artifacts, and errors from Firecrawl to Nstdata with an adapter-first migration plan.
Firecrawl Too Expensive? A Cost Breakdown and Alternative
Model Firecrawl and Nstdata Crawl costs for one million pages, including credits, proxy traffic, and accepted-document rates.
How to Crawl Websites Responsibly and Reduce Avoidable Blocks
Responsible collection starts with fewer unnecessary requests and clear stopping conditions. Follow a bounded Python example, distinguish authorization from overload, and validate content before accepting records.
