https://buff.ly/4bKXoyM // Finding and comparing similar companies is a tedious task that gets regularly performed by a range of professionals such as investors and founders mapping competitive landscapes or salesmen growing their lead funnel. Thankfully, we can automate this process with modern tools.
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In this video, we'll take you through the process of automatically extracting valuable information from your emails, including subject lines, message bodies, attachments, and email URLs, and adding it into Google Sheets for easy analysis and storage. By using Google Apps Script, we'll demonstrate how to set up a trigger that will pull all of this data from your emails and store it in a centralized Google Sheet. This will provide you with a powerful tool for managing your email data and optimizing your workflows, freeing up your time and energy for more important tasks. https://bit.ly/3A2BusQ #GoogleAppsScript,#GoogleSheets,#AutomatedEmailManagement,#EmailDataExtraction,#EmailOrganization,#EmailPrioritization,#GmailAutomation,#GmailDataIntegration,
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Google Map Scraper – Get this Extension for 🦊 Firefox (en-US)
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Customer Data Can Be Fragmented, but HubSpot Makes It Digestible If you want to understand your customers better, there are some simple strategies to pursue. Read more here: https://lnkd.in/dv9He92f . . Like 💝 Comment below ⏬ Share ✅ For More Such Updates Follow Us @qnewshub @qnewscrunch . . #qnewshub #qnewscrunch #StartupFunding
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🚀 Google Update Alert! 🚀 Google 's new Tag Diagnostics tool is here to ensure accurate data collection. Accessible via Google tag settings and the Tag Manager landing page, this tool helps identify and fix tag issues effortlessly. Say goodbye to data inaccuracies! 🚀🔧 https://lnkd.in/gM7pWjpb #GoogleUpdate #TagDiagnostics #GoogleTagManager #DataAccuracy #WebsiteOptimization #DigitalMarketing #TagDiagnostics #DataAccuracy #WebsiteOptimization #ga4
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Like many of you, we've faced the challenge of storing large text and querying it efficiently. After trying various solutions, we ended up using our current ClickHouse implementation. We’ve written a blog post detailing how we did it, focusing on: Optimizing Query Performance 🚀 Benchmarking Solutions 🔍 If you've been wrestling with massive texts, check the article we've written with Nathan Ostgard. https://lnkd.in/dYRvJe5C
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