This article evaluates the applicability at the state and district level of web scraping--an automated data-extraction technique that regularly exports and refreshes data from the Internet--to provide a low-cost way to get a close-to-real-time snapshot of the demand side of the teacher labor market. Once set up, web scraping can quickly build and maintain updated and accurate data sets primed for analysis--and action. The teacher labor market is highly localized, and scraped job postings data can provide targeted and timely information for policymakers and education leaders. While states typically respond to teacher shortages with incentives to increase the overall supply of educators, ongoing analysis of job postings data can provide a detailed picture of demand and support precise strategies to shore up the teacher pipeline where and when it is needed.