Workflow Templates

Workflow JSON TO CSVWorkflow JSON TO CSVWorkflow JSON TO CSVWorkflow JSON TO CSV

This workflow exports the contents of a JSON file to Google Sheets.

This n8n workflow converts invoices in PDF format into a structured, ready-to-use JSON, using AI and XML transformation — without writing any code. 🚀 How it works Upload form → The user uploads a PDF file. Text extraction → The PDF content is extracted as plain text. XML schema definition → A standard invoice structure is defined with fields such as: Invoice number Customer and issuer details Items with description, quantity, and price Totals and taxes Bank account details AI (Gemini) → The model rewrites the PDF text into a valid XML following the predefined schema. XML cleanup → Removes extra tags, line breaks, and unnecessary formatting. JSON conversion → The XML is transformed into a clean, structured JSON object, ready for integrations, APIs, or storage. ✨ Benefits Transforms unstructured PDFs into normalized JSON data. No coding required, only n8n nodes. Scalable to different invoice formats with minimal adjustments. Leverages AI to interpret complex textual content. 🛠️ Use cases Automating invoice data capture. Integration with ERPs, CRMs, or databases. Generating financial reports from PDFs.

Who's it for This template is perfect for sales teams, marketing professionals, recruiters, and business development specialists who need to efficiently collect targeted lead data from multiple sources. Whether you're building prospect lists, conducting market research, or expanding your contact database, this automated solution saves hours of manual data collection. How it works The workflow uses an n8n built-in form to collect search parameters, then automatically scrapes targeted leads from Google Maps and/or LinkedIn within Apify Actors based on your criteria. All collected data is cleaned, structured using Edit field nodes, and stored in your Supabase database for easy access and analysis. Key features: Interactive form for easy lead targeting Dual-source scraping (Google Maps + LinkedIn), you choose one or Both. Automatic data collection and cleaning, and structuring from Apify actors. Direct database storage in Supabase Flexible result limits and location targeting. How to set up Step 1: Set Up Apify Account Create account at apify.com Navigate to Settings > Integrations > API tokens Create new API token and copy it Ensure you have access to these actors: LinkedIn Profile Search Scraper (harvestapi/linkedin-profile-search) Google Maps Scraper (compass/crawler-google-places) Step 2: Configure Supabase Database Create new project at supabase.com Go to SQL Editor in your Supabase dashboard Run the SQL scripts from the Requirements section to create tables Navigate to Settings > API to copy: Project URL (starts with https://...) Service role key (secret key, not anon public) Step 3: Import and Configure Workflow Download the workflow JSON file In n8n Cloud, go to Workflows > Import from File Select the downloaded JSON file Configure credentials by clicking on each node that shows a warning: For Apify nodes (linkedin_dataset & googlemaps_dataset): Click "Create New Credential" Name: "Apify account" API Token: [Paste your Apify token from Step 1] Save credential For Supabase nodes (save_linkedin & save_googlemaps): Click "Create New Credential" Name: "Supabase account" Host: [Your Supabase project URL from Step 2] Service Role Secret: [Your service role key from Step 2] Save credential Step 4: Test the Workflow Click on the "On form submission" node Copy the Production URL (webhook link) Open this URL in a new browser tab Fill out the test form: Title/Industry: "restaurants" Location: "San Francisco, CA" Source: "Google Maps" Number of results: "3" Click Submit and wait for processing Check your Supabase tables to verify data was saved Step 5: Verify Setup Success In Supabase, go to Table Editor Check the googlemaps table for new entries Verify all fields are populated correctly Test with LinkedIn source to confirm both paths work The workflow is designed to be plug-and-play once credentials are configured. Simply share the form URL with your team or bookmark it for regular lead generation tasks. How to customize the workflow Search Parameters: Modify Apify actor configurations in the dataset nodes Adjust search query formats for better targeting Change result limits based on your needs Data Processing: Edit the Set nodes to extract additional fields Add data validation steps Implement duplicate detection logic Storage Options: Replace Supabase with other databases (Airtable, PostgreSQL) Add data export to CSV/Excel Implement real-time notifications Support: Check n8n community forum for help Review Apify actor documentation The workflow is designed to be plug-and-play once credentials are configured. Simply fill out the form with your target criteria and let the automation handle the rest. Requirements External Services: Apify account with credits (for web scraping) Supabase account (for data storage) Supabase Table Schemas: LinkedIn Table (LinkedIn): publicidentifier (text) linkedinurl (text) name (text) headline (text) about (text) premium (boolean) verified (boolean) openprofile (boolean) topskills (text) connectionscount (integer) followercount (integer) latest_experience (text) education (text) Google Maps Table (googlemaps): title (text) category_name (text) address (text) neighborhood (text) street (text) city (text) postal_code (text) state (text) country_code (text) website (text) phone (text) phone_unformatted (text) location (text) total_score (numeric) Node Requirements: Form Trigger (built-in), you may use others, or a webhook. Switch (built-in) Set (built-in) Supabase (built-in) Apify (community node), you'll have to install it first. How to customize the workflow Form Customisation: Modify form fields in the "On form submission" node to add additional search criteria if you want more. You may adjust dropdown options for different lead sources. Add validation rules for better data quality Search Parameters: Customize Apify actor configurations for different scraping behaviours. Modify the number of results per search. Add additional location targeting options Data Processing: Enhance the Set nodes to extract additional LinkedIn profile data Add data validation and cleaning steps Implement duplicate detection logic Storage Options: You may replace Supabase with other databases (Airtable, Google Sheets, etc.) Add data enrichment steps before storage Implement data export functionality Advanced Features: Add email notifications when scraping completes Implement error handling and retry logic Create data quality scoring mechanisms Let's connect: TUMUSIME David

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