Turn CoStar properties search results into a structured dataset with address, building name, SF available, asking rent and rent/SF, sale price and status, class, RBA/GLA, year built/renovated, % leased, parking ratio, market/city/state/ZIP, land acres, last sale date/price, and true owner. Built for U.S. commercial real estate brokers, acquisitions analysts, and tenant-rep teams to build market surveys, comp sets, and deal pipelines—then enrich, analyze, and export to Google Sheets, Airtable, Notion, or your CRM.
This template is designed for U.S. commercial real estate professionals—leasing and investment sales brokers, acquisitions analysts, site selectors, and research teams—who rely on CoStar’s list view to evaluate markets, source deals, and benchmark comps. It captures high-value fields like Asking Rent, Rent/SF, SF Avail, Sale Price, Price/SF, Class, RBA/GLA, % Leased, Year Built/Renov, Land (AC), Last Sale details, Market/City/State/ZIP, and True Owner, turning CoStar search results into a clean, analysis-ready table.
Use it to rapidly assemble market surveys, comp sets, and acquisition shortlists. With Bardeen, you can filter by submarket or asset class, compute derived metrics (e.g., total availability, weighted average rent), summarize inventory by market, and enrich ownership with firmographics or contacts. Then push data where you work—Google Sheets for modeling, Airtable/Notion for tracking, or a CRM like Salesforce/HubSpot for deal pipeline—while keeping everything deduplicated and up to date.
Maintained by Bardeen: this scraper template is actively monitored and updated to reflect changes to CoStar’s interface, delivering reliable, high-quality data for your workflows.
With Bardeen, you can do much more than just web scraping. After extracting data from any website, use Bardeen’s powerful automation tools to validate and enrich your data, run additional scrapers on linked pages, or leverage AI to qualify leads and generate content automatically. Once your data is ready, you can easily export it to CSV, Google Sheets, Airtable, or Notion for further analysis and reporting.
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