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Seeking Advice on Sourcing Educational Data by Job Role and Region | Clay

Seeking Advice on Sourcing Educational Data by Job Role and Region

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Hi Clay Community, We're currently working on a project that involves sourcing educational data, and we’ve encountered a challenge we hope you can help with. While we’ve been able to access general teacher data, we’re struggling to narrow this down to specific job roles such as SENCO (Special Educational Needs Coordinator), Head of English, Deputy Head, and similar leadership or specialist positions. Additionally, we’re finding it difficult to filter this data by territory or region, which is crucial for our use case. We’re reaching out to ask:

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Has anyone successfully sourced or segmented educational data by job role and/or geography?
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Are there recommended tools, platforms, or data providers that offer more granular filtering capabilities?
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Would anyone be open to collaborating or sharing insights on how they’ve approached similar challenges?

We’re particularly interested in UK-based data but are open to broader strategies that could be adapted. Any advice, resources, or introductions would be greatly appreciated!

8 comments

Channeled
APP
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You can source UK educational data by job roles using Clay's Find People feature. Here's how: 1. Use the Find People source with these filters: • Job title: Filter for specific roles like "SENCO, " "Head of English, " "Deputy Head" • Location: Narrow to UK regions, cities, or specific areas • Company attributes: Filter for educational institutions 2. Layer your search by combining job title filters with location parameters to create highly targeted lists of educational professionals in specific UK regions. 3. For more granular data, you can import an initial list of educational institutions and then use enrichment to find people with specific roles at those institutions.
Sources: Find People [Clay 101] - Clay University Find People overview | Documentation | Clay University Find People [Clay 101] - Clay University Find Jobs Source + Enrichment [Clay 101] - Clay University
James G.
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Thanks we have done this but the data isn't as specific as we had hoped and still has random profiles listed
Channeled
APP
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To get more accurate UK educational data with specific roles like SENCO and Head of English, try these refined search strategies: 1. Use more specific job title filters by combining exact titles with education-specific terms (e.g., "SENCO education" or "Head of English school"). 2. Layer multiple filters together - combine job titles with UK location filters, education-specific company attributes, and relevant bio keywords that indicate educational specialties. 3. Create an initial list of UK educational institutions first, then use the "Companies" filter to find people specifically at those institutions. 4. Use the "Exclude people" feature to remove irrelevant profiles from your results.
Sources: Find People overview | Documentation | Clay University Find People [Clay 101] - Clay University
James G.
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Thanks will give that a go
James G.
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once we have searched via companies which agent is best to use within the waterfall to scrape the websites for the teacher's role?
Channeled
APP
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For scraping teacher roles from educational institution websites, Clay's native scraper is your best option. It's specifically designed to extract common data types like job titles from static webpages, which most school websites are. The "Scrape Website with Clay" action lets you extract content including body text and keywords from specified URLs, making it ideal for finding specific teacher roles like SENCO or Head of English.
Sources: Scrape Website with Clay Intro to Web Scraping [Limitless Research] - Clay University Deep Dive: Clay Scrapers [Limitless Research] - Clay University Intro to Web Scraping [Limitless Research] - Clay University
James G.
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and which one is best for linkedin?
Channeled
APP
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For scraping teacher roles from LinkedIn profiles, Claygent is your best option. This AI web scraper excels at LinkedIn profile enrichment and can extract specific job titles and work experience details. When using Claygent, choose the Neon model for optimal results. It's specially designed for data extraction and can format results into multiple columns, making it perfect for extracting specific teacher roles like SENCO or Head of English from LinkedIn profiles. While GPT-4 and Claude Opus are also available in Claygent, Neon is superior for structured data extraction from LinkedIn.
Sources: Claygent: AI Web Scraper [Limitless Research] - Clay University Claygent: AI Web Scraper [Limitless Research] - Clay University