Data & Analytics Automation Workflows — Page 3 | Neura Market

Neura Market/Categories

Home/Categories/Data & Analytics

Data & Analytics Workflows

Data processing and analytics

Automate News Scraping and Storage with AI and Google Sheets
Streamline the process of collecting and storing news articles using AI-powered scraping and Google Sheets integration for efficient analysis and tracking.
n8n$4.99
Authenticate and Search Reddit Subreddits with OAuth2 in n8n
This workflow reliably searches Reddit subreddits using OAuth2 authentication to bypass request blocks, ensuring accurate data retrieval.
n8n$4.99
Automate Website Change Monitoring with OpenAI and Firecrawl
This workflow automates the monitoring of competitor websites for changes using OpenAI and Firecrawl. Receive email alerts for specific changes, helping you stay informed and competitive.
n8n$9.99

Marketplace

Prompts
Workflows
Agents Store
Workflow Packs
Categories
Marketplace

Directories

AI Tools Directory
ChatGPT
Claude
Gemini
Cursor
Grok
DeepSeek
Perplexity
CoPilot
Midjourney
Stable Diffusion
MCP Servers
.md Directory
All Directories

Free Tools

AI Text Humanizer
AI Content Detector
Workflow Generator
Model Comparison
AI Pricing Calculator
AI Benchmarks
ROI Calculator
All Free Tools

Resources

AI News
Blog
AI Answers
Error Solutions
AI Tutorials
AI Models
Integrations
Alternatives
n8n vs Zapier
Make vs Zapier
n8n vs Make
Resource Library
Documentation
API Access to Our Data

Community

AI Newsletter
AI Jobs
AI Events
AI Companies
Start Selling
Sell n8n Workflows
Sell AI Agents
Sell Prompts
Creator Guide
Advertise
Affiliates

Company

About
Contact
Help
Careers
Pricing
Terms
Privacy
License
DMCA

The #1 Newsletter in AI

Weekly updates, news, and content that matter.

© 2026 Neura Market. All rights reserved.

Automate Web Scraping with Selenium and AI in n8n

Leverage Selenium and AI to automate data extraction from web pages, including those requiring login, using n8n. This workflow integrates session cookies and AI for advanced scraping capabilities.

Scrape Public Email Addresses from Any Website Using Firecrawl

## Who's it for This template is perfect for sales professionals, marketers, and business developers who need to quickly gather contact information from company websites. Whether you're building prospect lists, researching potential partners, or collecting leads for outreach campaigns, this automation saves hours of manual email hunting. ## What it does This workflow automatically discovers and extracts email addresses from any website by: - Taking a website URL as input through a simple form - Using Firecrawl's mapping API to find relevant pages (about, contact, team pages) - Batch scraping those pages to extract email addresses - Intelligently handling common email obfuscations like (at) and (dot) - Returning a clean, deduplicated list of valid email addresses The automation handles rate limiting, retries failed requests, and filters out invalid or hidden email addresses to ensure you get quality results. ## How to set up 1. **Get Firecrawl API access**: Sign up at [firecrawl.dev](https://firecrawl.dev) and obtain your API key. 2. **Configure credentials**: In n8n, create a new HTTP Header Auth credential named Firecrawl with: - Header Name: `Authorization` - Header Value: `Bearer YOUR_API_KEY` 3. **Import the workflow**: Copy the workflow JSON into your n8n instance. 4. **Test the form**: Activate the workflow and test with a sample website URL. ## How to customize the workflow **Search parameters**: Modify the `search` parameter in the map_website node to target different page types (currently searches for about, contact, company, authors, team). **Extraction limits**: Adjust the `limit` parameter to scrape more or fewer pages per website. **Retry logic**: The workflow includes retry logic with a 12-attempt limit - modify the `check_retry_count` node to change this. **Output format**: The `set_result` node formats the final output - customize this to match your preferred data structure. **Email validation**: The JSON schema in `start_batch_scrape` defines how emails are extracted - modify the prompt or schema for different extraction rules. The workflow is designed to be reliable and handle common edge cases like rate limiting and failed requests, making it production-ready for regular use.

Automate Brazilian Company Data Enrichment with CNPJ API and Google Sheets

Enhance your Brazilian business databases by automatically fetching and updating CNPJ information from the MinhaReceita.org API into Google Sheets. Ideal for data analysts and sales teams needing comprehensive company data at scale.

Automate Financial Data Visualization from Yahoo Finance to Telegram

This n8n workflow automates the process of scraping financial data from Yahoo Finance using Bright Data, visualizing market cap information, and delivering insights to Telegram. It streamlines financial analysis by integrating data collection, processing, and notification.

Automate Google Maps Business Data Extraction and Enrichment with AI

This workflow automates the process of extracting, enriching, and storing business information from Google Maps using AI tools and Google Sheets. Ideal for lead generation, market research, and digital marketing.

Automate Glassdoor Job Searches with Bright Data and Google Sheets Integration

Streamline your job search process by automatically scraping Glassdoor job listings using Bright Data and storing the results in Google Sheets for easy analysis.

Automate YouTube Creator Email Extraction for Outreach

Streamline your influencer outreach by automating the extraction of YouTube creator emails using Apify and OpenAI in n8n. This workflow efficiently scrapes channel descriptions and formats contact emails for easy access.

Indeed Job Scraper with AI Filtering & Company Research Using Apify and Avily

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow **scrapes job listings** on Indeed via Apify, **automatically gets that dataset**, extracts information about the listing, **filters jobs for relevance**, finds a decision maker at the company, and updates a database (Google Sheets) with that info for outreach. **All you need to do is run the Apify actor** then the database will update with the processed data. #### Benefits: - Complete Job Search Automation - A webhook monitors the Apify actor which sends an integration and starts the process. - AI-Powered Filter - Uses ChatGPT to analyze content/context, identify company goals, and filters based on job description. - Smart Duplicate Prevention - Automatically tracks processed job listings in a database to avoid redundancy. - Multi-Platform Intelligence - Combines Indeed scraping, web research via Avily, and enriches each listing. - Niche Focus - Processes content from multiple niches, currently 6 (hardcoded) but can be changed to fit other niches (just prompt the job filter node). #### How It Works: 1. **Indeed Job Discovery:** - Search and apply filter for relevant job listings, copy and use URL in Apify. - Uses Apify's Indeed job scraper to scrape job listings from the URL of interest. - Automatically scrapes the information, stores it in a dataset, and initiates an integration. 2. **Oncoming Data Processing:** - Loops over 500 items (can be changed) with a batch size of 55 items (can be changed) to avoid running into API timeouts. - Multiple filters to ensure all fields are scrapped with our required metrics (website must exist and number of employees < 250). - Duplicate job listings are removed from the oncoming batch to be processed. 3. **Job Analysis & Filter:** - An additional filter to remove any job listing from the oncoming batch if it already exists in the Google Sheets database. - Then all new job listings get passed to ChatGPT which uses information about the job post/description to determine if it is relevant to us. - All relevant jobs get a new field verdict which is either true or false and we keep the ones where verdict is true. 4. **Enrich & Update Database:** - Uses Avily to search for a decision maker (doesn't always find one) and populate a row in Google Sheet with information about the job listing, the company, and a decision maker at that company. - Waits for 1 minute and 30 seconds to avoid Google Sheets and ChatGPT API timeouts then loops back to the next batch to start filtering again until all job listings are processed. ### Required Google Sheets Database Setup: Before running this workflow, create a Google Sheets database with these exact column headers: **Essential Columns:** - jobUrl - Unique identifier for job listings - title - Position title - descriptionText - Description of job listing - hiringDemand/isHighVolumeHiring - Are they hiring at high volume? - hiringDemand/isUrgentHire - Are they hiring with urgency? - isRemote - Is this job remote? - jobType/0 - Job type: In person, Remote, Part-time, etc. - companyCeo/name - CEO name collected from Avily's search - icebreaker - Column for holding custom icebreakers for each job listing (Not completed in the workflow. I will upload another that does this called Personalized IJSFE) - scrapedCeo - CEO name collected from Apify Scraper - email - Email listed for job listing - companyName - Name of company that posted the job - companyDescription - Description of the company that posted the job - companyLinks/corporateWebsite - Website of the company that posted the job - companyNumEmployees - Number of employees the company listed that they have - location/country - Location of where the job is to take place - salary/salaryText - Salary on job listing **Setup Instructions:** - Create a new Google Sheet with these column headers in the first row. - Name the sheet whatever you please. - Connect your Google Sheets OAuth credentials in n8n. - Update the document ID in the workflow nodes. The merge logic relies on the id column to prevent duplicate processing, so this structure is essential for the workflow to function correctly. Feel free to reach out for additional help or clarification at my Gmail: terflix45@gmail.com, and I'll get back to you as soon as I can. ### Set Up Steps: 1. **Configure Apify Integration:** - Sign up for an Apify account and obtain an API key. - Get the Indeed job scraper actor and use Apify's integration to send an HTTP request to your n8n webhook (if the test URL doesn't work, use the production URL). - Use the Apify node with Resource: Dataset, Operation: Get items, and use your API key as your credentials. 2. **Set Up AI Services:** - Add OpenAI API credentials for job filtering. - Add Avily API credentials for company research. - Set up appropriate rate limiting for cost control. 3. **Database Configuration:** - Create a Google Sheets database with the provided column structure. - Connect Google Sheets OAuth credentials. - Configure the merge logic for duplicate detection. 4. **Content Filtering**

Convert Revit Projects to Database with Drawings & Specifications Using DDC

Turn a **.rvt** project into open, analysis-ready data (XLSX + optional DAE/PDF) using the **RvtExporter.exe** from the DDC Revit toolkit. This n8n template provides a **Form UI** to set paths and flags, then runs the exporter with safe defaults. Converts CAD/BIM files with customizable export modes (basic: 309 categories, standard: 724 categories, complete: all 1209 categories) and optional outputs like bounding box, Revit schedules, or PDF drawings. ## What it does - Launches `RvtExporter.exe` with your chosen **Revit file** and **export mode** - Optional feature flags: **bbox**, **schedule**, **sheets2pdf**, **-no-xlsx**, **-no-collada** - (Optional) Output folder auto-generates `*_rvt.xlsx` and `*_rvt.dae` names ## Prerequisites - Windows host (the exporter is a Windows executable) - DDC Revit toolkit installed (path like: `C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe`) - A local `.rvt` file you can read ## How to use 1. **Import** this json workflow into n8n. 2. Open the **Form UI** trigger (ensure pop-ups are allowed). 3. Fill in: - **Path to Revit Converter**: `C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe` - **Revit File Path**: e.g. `C:\\Sample_Projects\\your_project.rvt` - **Export Mode**: `basic | standard | complete | custom` - **Conversion Options**: multi-select flags (optional) - **(optional) Output Folder**: e.g. `C:\\DDC_Output` 4. Click **Submit** — the workflow runs **Run Revit Exporter**. ## Consulting and Training We work with leading construction, engineering, consulting agencies, and technology firms around the world to help them implement open data principles, automate CAD/BIM processing, and build robust ETL pipelines. If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us. ## Author [DataDrivenConstruction.io](https://DataDrivenConstruction.io) [info@datadrivenconstruction.io](mailto:info@datadrivenconstruction.io) **Docs & Issues:** [Full Readme on GitHub](https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto)

Decode and Clean Google News RSS URLs for Direct Article Links

This workflow extracts and decodes URLs from Google News RSS feeds, providing clean and direct links to articles. It's ideal for developers, journalists, and content aggregators who need to streamline the processing of news URLs.

Track CVE Vulnerability Details & History with NVD API and Google Sheets

## Who is this for? NVD (National Vulnerability Database) data is essential for security analysts, vulnerability managers, and DevSecOps professionals who need to perform both CVE lookups and monitor historical change logs. This workflow helps streamline those efforts by providing structured outputs for audit, triage, or compliance tracking purposes. **Note:** While this example uses Google Sheets as the destination, you can easily modify the final destination node (e.g., send to Slack, email, database, etc.) based on your specific automation needs. ## What problem is this solving? Security teams often manually look up CVE data and track changes across multiple tools. This process is inefficient and error-prone. This workflow automates the CVE lookup and historical change tracking by logging enriched vulnerability data into Google Sheets in real-time. ## What this workflow does This workflow is designed for CVE API lookup and change history tracking. In many vulnerability automation pipelines, it is essential to determine not only the metadata of a CVE but also how it has evolved over time. Based on the operational need—whether it's enrichment, risk scoring, or remediation validation—this workflow becomes particularly handy in surfacing both current and historical CVE data. This template performs the following actions: - Accepts incoming webhook requests containing a CVE ID - Queries the NVD CVE Lookup API to fetch vulnerability metadata - Queries the NVD CVE History API to retrieve all historical changes - Flattens both datasets into a sheet-compatible structure - Appends vulnerability metadata to one sheet and change history to another within the same Google Spreadsheet ## Setup **Request an NVD API Key** To request an NVD API Key, please provide your organization name, a valid email address, and indicate your organization type at [NVD API Key Request](https://nvd.nist.gov/developers/request-an-api-key). You must scroll to the end of the Terms of Use Agreement and check "I agree to the Terms of Use" to obtain an API Key. After submission, you will receive a single-use hyperlink via email to activate and view your API Key. If not activated within seven days, a new request must be submitted. **API Rate Limits** Without an API key, you're limited to 5 requests per 30-second window. With an API key, you're allowed up to 50 requests in the same period. To prevent request throttling, it's recommended to introduce slight delays between consecutive API calls in production setups. 1. Clone or import this workflow into your n8n instance. 2. Set up the following credentials: - Google Sheets OAuth2 - NVD API Key (via HTTP Header Auth) 3. The workflow logs data to a Google Sheet titled **NVD Database**, with Sheet 1 named **CVE Lookup** and Sheet 2 named **CVE History**. 4. Trigger each workflow using the respective webhook URL, appending `?cveId=CVE-XXXX-XXXX` as a query parameter. ### **Example Webhook Request (CVE Change History)** You can test this workflow with the following example: ``` GET https://your-domain.com/webhook/cve-history?cveId=CVE-2023-34362 ``` ## How to customize this workflow - Use the `Edit Fields` node (optional) to centralize configuration like sheet name or query input - Extend the CVE flattening logic to include more nested metadata if needed - Integrate notification systems (e.g., Slack or email) by branching from the processing nodes - Modify webhook paths for better endpoint organization ## **Production Security Tips** - Use **HTTP Header Auth** on the webhook for secure access > **This template uses webhooks and NVD API access with authentication headers.** --- This template uses two flows: - **Webhook 1:** `NVD CVE Lookup` - Lookup CVE vulnerability metadata from NVD and sync to Google Sheet - **Webhook 2:** `NVD CVE Change History` - Track change history for CVEs via NVD and log each update Each flow: - Hits NVD's respective endpoint - Uses custom JS Code node to flatten the nested JSON - Syncs data to dedicated Google Sheet tabs - Consists of 4 nodes: Webhook → API Call → Parse → Sheet Sync Make sure both flows are activated and webhooks exposed for external access. Based on your needs, ensure you have a secure setup—whether hosted internally or in a cloud environment—when running n8n in production.

Automate Shopify Store Data Extraction and Logging to Google Sheets

This workflow automates the extraction of Shopify store and product data using RapidAPI's Shopify Scraper API and logs the information into Google Sheets for streamlined analysis.

Automate JotForm Submissions Without API Keys Using n8n

This workflow enables automatic data submission to JotForm from various sources using n8n, bypassing the need for API keys by leveraging the HTTP Request node.

Automate Product Data Extraction from Google Sheets URLs with Dumpling AI

This workflow automates the extraction of product information from URLs listed in a Google Sheet, using Dumpling AI to gather details like product name, price, and description, and stores the data in another sheet.

Automate Google Maps Business Phone Scraping to Google Sheets

This n8n workflow automates the extraction of business phone numbers and other details from Google Maps using the Bright Data API, and stores the information in Google Sheets for easy access and management.

Beginner's Guide to Using SerpAPI for Lead Finding

This n8n workflow finds experts on **any topic**, scrapes their websites, and pulls out contact emails automatically. Core services used: **SerpAPI (google search)**, **Apify (website crawler)**, **OpenAI (GPT-4 email extraction)**. --- ## Step-by-Step Setup & Execution ### 1. Run Workflow (Manual Trigger) | Node | Type | Purpose | |------|------|---------| | `Run Workflow` | Manual Trigger | Start the workflow on demand while you test. | --- ### 2. Set Your Topic | Node | Type | How to configure | |------|------|------------------| | `Set Topic` | **Set** | Add a string field **Topic** - e.g. `n8n`. This keyword drives every subsequent step. | --- ### 3. Search Google (Results 1-10) | Node | Type | API Credential | |------|------|----------------| | `Search Google (top 10)` | **SerpAPI** | **Create SerpAPI credential**<br>1. Sign up → copy API key → n8n → **Credentials → New → SerpAPI** → paste.<br>2. Select the credential in this node. | | **Key Params** | | | | `q` | | `={{ $json.Topic }} Expert` | | `location` | | Region code (ex `585069efee19ad271e9c9b36`) | | `additionalFields.start` | | `10` (Google position 1-10)| --- ### 4. Search Google (Results 11-20) | Node | Type | Notes | |------|------|-------| | `Search Google (11-20)` | **SerpAPI** (same credential) | Remove `start` or set to 20+ to fetch next page. | --- ### 5. Extract URL Lists | Node | Type | Script Purpose | |------|------|----------------| | `Extract Url` & `Extract Url 2` | **Code** | Loop `data.organic_results` → output `{ title, link, displayed_link }` for each result. | --- ### 6. Combine Both Result Sets | Node | Type | Details | |------|------|---------| | `Append Results` | **Merge (combineAll)** | Merges arrays from steps 3 & 4 into a single list for processing. | --- ### 7. Loop Over Every URL | Node | Type | Configuration | |------|------|---------------| | `Loop Over Items1` | **Split In Batches** | Default batch = 1 (process one page at a time).<br>`onError = continueRegularOutput` keeps loop alive on failures. | --- ### 8. Scrape Webpage Content (Apify) | Node | Type | API Credential | |------|------|----------------| | `Scrape URL with Apify` | **HTTP Request** | **Create Apify credential**<br>1. Sign up at https://console.apify.com<br>2. Account → **API tokens** → copy.<br>3. n8n → **Credentials → New → HTTP Query Auth** → set query param `token=YOUR_TOKEN`. | | **Request Details** | | | | Method | POST | | URL | `https://api.apify.com/v2/acts/6sigmag~fast-website-content-crawler/run-sync-get-dataset-items` | | JSON Body | ```json { startUrls: [{{ $json.link }}] } ``` | --- ### 9. Extract Email with OpenAI | Node | Type | API Credential | |------|------|----------------| | `Extract Email from webpage` | **LangChain Agent** | **Create OpenAI credential**<br>1. Generate key at https://platform.openai.com/account/api-keys<br>2. n8n → **Credentials → New → OpenAI API** → paste key. | | Prompt (system) | ```extract the email address from the text. if there is no email address, output null.``` | | **Output Parser** | `Structured Output Parser2` expects → `{ email: address OR null }` | --- ### Loop Continues & Final Data - The extracted result returns to **Loop Over Items1** until every URL is processed. - **Typical final item JSON**: ```json { title: "How to Build n8n Workflows", link: "https://example.com", email: "info@example.com" } ``` Optional Enhancements - **Save Leads**: Add a Google Sheets or Airtable node after the loop. - **Validate Emails**: Chain a ZeroBounce / Hunter.io verification API before saving. - **Parallel Crawling**: Increase SplitInBatches size (watch Apify rate limits). Need More Help? - Robert Breen - Automation Consultant & n8n Expert - Email: robert.j.breen@gmail.com - LinkedIn: https://www.linkedin.com/in/robert-breen-29429625/ - Website: https://ynteractive.com

Conversational AI for Snowflake Database Interaction

This workflow enables conversational querying of a Snowflake database using AI, automating SQL generation, secure execution, and dynamic report generation with rich visualizations.

Automate SQL Queries on Google Sheets Data Using AI and PostgreSQL

This n8n workflow enables you to query structured data from Google Sheets or CSV files using AI-generated SQL, storing and processing it efficiently in PostgreSQL.

Create a Google Analytics Data Report with AI and Send It to Email and Telegram

## What this workflow does This workflow retrieves Google Analytics data from the last 7 days and the same period in the previous year. The data is then prepared by AI as a table, analyzed, and provided with a small summary. The summary is then sent by email to a desired address and, shortened and summarized again, sent to a Telegram account. This workflow has the following sequence: 1. Time trigger (e.g., every Monday at 7 a.m.) 2. Retrieval of Google Analytics data from the last 7 days 3. Assignment and summary of the data 4. Retrieval of Google Analytics data from the last 7 days of the previous year 5. Allocation and summary of the data 6. Preparation in tabular form and brief analysis by AI. 7. Sending the report as an email 8. Preparation in short form by AI for Telegram (optional) 9. Sending as a Telegram message. ## Requirements The following accesses are required for the workflow: - Google Analytics (via Google Analytics API): [Documentation](https://docs.n8n.io/integrations/builtin/credentials/google/) - AI API access (e.g., via OpenAI, Anthropic, Google, or Ollama) - SMTP access data (for sending the mail) - Telegram access data (optional for sending as a Telegram message): [Documentation](https://docs.n8n.io/integrations/builtin/credentials/telegram/) Feel free to [contact me via LinkedIn](https://www.linkedin.com/in/friedemann-schuetz), if you have any questions!

Interactive Recipe Search Using API Ninjas in n8n

Effortlessly search for recipes by entering keywords into a form, which retrieves detailed recipes using the API Ninjas Recipe API and displays them instantly.

Automate GitHub Trending Data Collection to Supabase

Streamline the process of collecting and storing GitHub trending repository data in Supabase for easy access and analysis.

← PreviousPage 3 of 42Next →

Related categories

Communication (2,463)AI (1,930)Business Operations & ERPs (1,540)Other (1,425)Productivity (1,202)Marketing (1,145)File & Document Management (802)CRM - Sales (604)Notifications (580)Social Media (562)

Need a custom data & analytics workflow?

Our automation experts build tailored workflows for your exact stack and process.

Request a Custom Workflow