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Tag Extractor

Tag Extractor

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Extracts metadata tags and key post details from social media URLs. Get a clean keyword list plus structured fields for research and SEO planning.

Want to scrape data in bulk? Try Thunderbit for free.

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Extract Tags and Post Data FastUse Thunderbit to scrape pages and extract structured fields in a few clicks. Automate collection across posts, subpages, and files, then export to Sheets.
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Extract Tags and Post Data Fast

Collect tags, titles, URLs, views, dates, descriptions, likes, and comments from social media using Thunderbit’s AI Web Scraper Chrome Extension. Click AI Suggest Fields, scrape the page, and get a structured table that’s ready for analysis. Scrape across subpages and pagination, and extract data from PDFs, docs, and images when sources include them. Summarize, categorize, and format fields as you scrape, then export to Google Sheets, Airtable, or Notion.

How to Extract Tags Using Thunderbit

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STEP 1Download and InstallDownload and install the Thunderbit Chrome Extension from the Thunderbit Chrome Extension Download Page. Once installed, log in or create a free account to get started.
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STEP 2Open ExtensionOpen the video page or post or reel you want to analyze, then open the Thunderbit Chrome Extension. In the Tag Extractor, paste the public link into the field labeled "Enter a URL" so Thunderbit can read the content and prepare a structured output table.
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STEP 3Click the Extract tags ButtonClick the "Extract tags" button to run the Tag Extractor. Thunderbit will return a table that includes Title, URL, Views Count, Upload Date, Description, Tags, Number of Likes, and Number of Comments. After the table is generated, export the results to Excel, Google Sheets, Airtable, or Notion, or download as CSV or JSON.

Learn how to extract tags and post metadata from public URLs

Extract tags and metadata from a single URL

Thunderbit’s Tag Extractor pulls key metadata from a public video or post or reel URL and returns it as a structured table. It captures the content Title, URL, Views Count, Upload Date, Description, Tags, Number of Likes, and Number of Comments. This helps marketers, creators, and analysts avoid manual copy and paste while building a consistent dataset for review and reporting.
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Standardize keyword tags for research and indexing checks

Tags are often buried in page metadata or mixed into noisy descriptions. The Tag Extractor isolates the tag list so you can compare keyword strategies across posts, creators, and campaigns. Use it to validate how content is categorized, spot missing topics, and understand what terms may influence discovery. It is useful for competitive research, content planning, and teams responsible for search visibility.
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Build competitor and creator benchmarks

Use the output table to benchmark performance and positioning across multiple URLs. Collect Views Count, Likes, and Comments alongside Tags and Descriptions to see which topics correlate with engagement. This supports influencer research, channel audits, and campaign retrospectives where you need evidence for what worked. The structured format also makes it easier to share findings with stakeholders and keep comparisons consistent.
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Export results to spreadsheets and databases for workflows

After extraction, export the table to Excel, Google Sheets, Airtable, or Notion, or download as CSV or JSON for analysis and archiving. This makes it practical to create tag libraries, track content performance over time, and feed cleaned metadata into dashboards or internal tools. Teams can maintain a repeatable process for content audits without rebuilding templates for each new URL.
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What users say about Thunderbit

Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.

Frequently Asked Questions

Extract Data using AI
Easily transfer data to Google Sheets, Airtable, or Notion
Chrome Store Rating
PRODUCT HUNT#1 Product of the Week
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