Thunderbit

Thunderbit now offers a managed scraping service😀 For teams that need public web data but don’t want to build or debug scrapers themselves, our team can help turn URLs into clean datasets—one-time or recurring. Use it for price monitoring, lead generation, AI training data, market research, and more. Send us your data requirements. Get a custom quote in 1 business day. thunderbit.com/web-scraping-s…

Your Coworkers Are Hiding This AI Web Scraper...

🐶🐱 Dog vs Cat Podcast: Why Do Humans Smell Our Paws?

Wait... this whole thing can be automated? #webscraping #thunderbit #NoCode #ai

🧵 2/4 No single tool fits every corporate niche. Choose your stack wisely: 🔹 For website discovery: Thunderbit 🔹 For name + domain pattern matching: Hunter or Tomba 🔹 For all-in-one prospecting & sequencing: Apollo or Snov 🔹 For Europe-focused outreach: Kaspr

🧵 1/4 Finding a CEO’s direct email in 2026 is tough, but it’s the ultimate shortcut to bypass gatekeepers & compress deal cycles. I tested 9 major email finder tools across 50 companies to see what actually works. Here is the honest breakdown 👇

🧵 4/4 Finding the email is only half the battle—deliverability is key. ⚠️ Bounces over 2% trigger spam filters. Google requires spam rates under 0.3%. Never send to an unverified address. Keep pitches under 5 sentences, focus on CEO-level priorities, and always include an opt-out.

🧵 3/4 Starting with just a list of company names? Use this 5-step pipeline: 1️⃣ Find domains via Google/LinkedIn 2️⃣ Scrape About/Team pages with AI tools to grab CEO names 3️⃣ Run Name + Domain 4️⃣ Verify 5️⃣ Segment & personalize

🚀 Meet the new Thunderbit CLI! Transform any web page into LLM-ready Markdown, extract structured data with AI schemas, and handle up to 100 URLs in bulk—right from your terminal. Build faster. Happy coding! 💻🔥 thunderbit.com/docs/cli

🚀 Big news! We’re officially launching our Model Context Protocol (MCP) server! 🤖✨ Now you can seamlessly search, scrape, and extract structured data from any webpage directly within your favorite MCP-ready AI hosts like Cursor & Claude. Try it out: thunderbit.com/docs/mcp

What's that??

Try disco!

@JustWillAitken Statistically speaking, the loudest in the room are usually the quietest on the leaderboard😂

Asked ten outbound reps to score themselves from 1-5 on ten sales skills (cold calling, buyer knowledge, time management, etc) Added up the totals combined into percentage and compared against quota attainment and activity What do you think the trend was?

@MuskieMcKay @systematicls Agreed. Mindset is the engine. Without it, even the best plans stall out.

@systematicls I definitely think mindset matters when you are voluntarily doing something long and hard.

Learn to love the journey. If you genuinely feel like shit all the time, you are not going to last. If you want to last in doing anything hard, you need to learn to love it. It just means learning to have fun chewing glass. And if you’re not going to last, don’t even start.

That’s why AI search readiness is becoming a real issue for DTC brands. Thunderbit helps teams uncover structured data gaps across their own sites and competitors’ sites — no code required.

The bigger gap is structured product data. Product schema appeared on only: 0.9% of homepages 39.2% of product pages AI shopping assistants need facts like price, reviews, availability, variants, and product details to compare and recommend products effectively.

One thing is becoming more common: llms.txt. We found it across 629 domains. But most were platform-generated, which means they often don’t provide the deeper product-level context AI systems actually need. Visibility is not the same as understanding.

The average AI readiness score was just 36.4 / 100. Only 11 domains reached the “AI ready” tier. That means fewer than 1% of the DTC brands we analyzed are truly prepared for AI search and AI shopping assistants.

AI can find your DTC brand. But can it actually understand your products? 🤯 We analyzed 1,238 DTC websites and found a major gap between basic AI discoverability and true product-level readiness. Here’s what the data shows ↓

AI market research is a superpower... until your agent hallucinates because of bad data. 📉 The truth is: Your AI is only as smart as your data. If your source data is a mess, your insights will be too. Thunderbit bridges the gap between chaotic web signals and brilliant AI execution. ❌ Before: Messy, unstructured web noise. ✅ After: Clean, workflow-ready datasets. Give your AI agents the infrastructure they deserve to deliver sharper market insights. 👉 Try Thunderbit for free: thunderbit.com