Amazon Keyboard Product Scraper with AI and Google Sheets Integration 🎯 Target Audience E-commerce analysts and researchers Product managers tracking competitor keyboards Data analysts monitoring Amazon keyboard market trends Business owners conducting market research Developers building product comparison tools 🚀 Problem Statement Manual monitoring of Amazon keyboard products is time-consuming and error-prone. This template solves the challenge of automatically collecting, structuring, and storing keyboard product data for analysis, enabling data-driven decision making in the competitive keyboard market. 🔧 How it Works This workflow automatically scrapes Amazon keyboard products using AI-powered web scraping and stores them in Google Sheets for comprehensive analysis and tracking.
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Enrich contact emails and phone numbers with Tomba and Google Sheets
Quick overview This workflow runs on a schedule to read “Pending” contacts from Google Sheets, uses Tomba to find email addresses and (when available) phone numbers, then writes the enriched results back to the same spreadsheet. How it works Runs on a scheduled trigger. Reads rows from a Google Sheets worksheet where the Status column equals “Pending”. Processes the contacts in batches and sends each contact’s name, company, and domain to Tomba to find an email address. If Tomba indicates phone data is available, looks up the phone number in Tomba using the found email address. Normalizes the output (email, phone, score, and enrichment status) and updates the matching row in Google Sheets with the results and Status set to “Done”. Setup Connect your Google Sheets OAuth credentials and set the target spreadsheet and worksheet that contains your contacts. Add a Tomba API credential. Ensure your Google Sheet includes the expected columns (First Name, Last Name, Company, Domain, Status) and output columns (Email, Phone, Score), with Status set to “Pending” for rows you want to enrich.
Extract business card contacts with LDX hub Gemini AnalyzeDoc and Google Sheets
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