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Data & Analytics Workflows

Data processing and analytics

Demo Workflow - How to Use workflowStaticData()
This workflow demonstrates how to use the `workflowStaticData()` function to set any type of variable that will persist within workflow executions. [https://docs.n8n.io/code/cookbook/builtin/get-workflow-static-data/](https://docs.n8n.io/code/cookbook/builtin/get-workflow-static-data/) This can be useful, for example, when working with access tokens that expire after a certain time period. Using `staticData`, we can keep a record of that access token and the expiry time and build our workflow logic around it. ## Important Static Data only persists across **production** executions, i.e., triggered by Webhooks or Schedule triggers (not manual executions!). For this, the workflow will have to be activated. ## Setup - Configure HTTP Request node to fetch access token from your API (optional) - Activate workflow - Test the workflow with the webhook production link - You can check the population of the static data in the single executions ### Feedback If you found this useful or want to report some missing information - I'd be happy to hear from you at [ria@n8n.io](mailto:ria@n8n.io)
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Automate Website Funnel Analysis with AI and Google Sheets
This workflow automates the analysis of website conversion funnels using AI and data scraping tools, providing insights into optimization opportunities and user journey performance.
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Automate Startup Funding Data Extraction to Excel

This workflow automates the discovery and extraction of seed-funded startup data from RSS feeds, processes it with AI, and exports it to an Excel sheet on OneDrive, streamlining lead generation for sales teams.

Automate Business Data Enrichment for Company Domains with Perplexity AI and Google Sheets

This workflow automates the enrichment of company domain lists with detailed business information using Perplexity AI, storing results in Google Sheets for streamlined analysis.

Automate Business Data Collection from Google Maps to Sheets and Excel

Streamline the process of collecting business information from Google Maps and exporting it to Google Sheets or Excel for easy analysis and sharing.

Generate Interactive Quantity Reports from Revit and IFC Projects to HTML

## Revit to HTML Quantity Takeoff Generator Automates extraction of wall quantities from Revit models and creates a professional interactive HTML report. ### Key Features - Automated wall quantity analysis - Calculates volumes by wall type (Type Name) - Generates interactive HTML QTO report - Includes summary statistics: total elements, total and average volumes - Provides detailed breakdown by element type ### How it works 1. Upload a Revit file as input 2. Workflow extracts wall quantities and types 3. Creates and saves a ready-to-share HTML dashboard with QTO data --- - No API keys required - Runs offline - Output is a professional, ready-to-use HTML report ## 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)

Automate Construction Blueprint Processing to Google Sheets

Streamline the conversion of construction blueprints from Google Drive into structured Google Sheets entries using VLM Run for efficient data management.

Automate Resume Data Extraction from Gmail and Notifications via Slack

Streamline your recruitment process by automatically extracting data from resumes received in Gmail and sending notifications to Slack.

Enrich GoHighLevel Leads with Business Data from DataForSEO

Automatically enhance your GoHighLevel leads with detailed business information using DataForSEO API and Make. Access critical data such as business name, description, categories, and more to personalize outreach and optimize campaigns.

Scrape market data and send it to Slack

Overview Pipedream can leverage both Python and Node.js code in workflows, which can be used to scrape data from websites in real time. his workflow will read market data in real time from a website that publishes unusual asset class pricing, and ...

Bypass Cloudflare Turnstile for Web Scraping with 2captcha

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. ## Bypass Cloudflare Turnstile for Web Scraping with n8n ### How It Works This workflow automatically solves Cloudflare Turnstile CAPTCHAs for legitimate web scraping and automation tasks. It extracts the Turnstile sitekey from target webpages, submits solving requests to [2captcha](https://2captcha.com/?from=26496602), and returns bypass tokens that can be used in automated form submissions or data collection workflows. ### Set Up Steps 1. [Create a 2captcha Account](https://2captcha.com/?from=26496602): Sign up and get your API clientKey for CAPTCHA solving. 2. Import the Workflow into n8n: Add the workflow to your n8n instance. 3. Configure Authentication: Set up custom HTTP authentication with your clientKey in the credential settings. 4. Test the Workflow: Run with the demo URL to verify Turnstile detection and solving works correctly. 5. Replace the sample destination_url with your target website and start automating! Setup should take just a few minutes with your API credentials ready. ### Getting Started Once configured, the workflow can extract sitekeys from any Turnstile-protected webpage and return solved tokens for seamless automation. The [API documentation](https://2captcha.com/api-docs/cloudflare-turnstile?from=26496602) provides additional technical details for advanced use cases. ### Customizing the Workflow The workflow targets a demo page for testing. To adapt it, simply update the destination_url variable with your target website. You can also modify the sitekey extraction logic for sites that implement Turnstile differently, or integrate this as a subworkflow into larger scraping operations. ### API Reference Uses the TurnstileTaskProxyless task type with REST-based HTTPS communication. Each solve costs approximately $0.002 USD and typically completes within 30-90 seconds depending on queue load.

Automate AI Access to Transportation Laws and Incentives

Transform the Transportation Laws and Incentives API into a Machine Communication Protocol (MCP) server, enabling seamless AI agent integration for querying laws and incentives.

Automate Web Data Search, Summarization, and Delivery via Webhooks

This workflow automates the process of searching web data using Perplexity, cleaning and summarizing the results with Gemini AI, and delivering structured insights to a webhook.

Automate Line Chart Creation and Upload to Google Drive

This workflow generates a dynamic line chart from JSON data using QuickChart and uploads the resulting image to Google Drive, streamlining your data visualization process.

AI Marketing Team: Multi-Agent Content Automation with OpenAI

Simulates a full marketing team using OpenAI O3 CMO agent that delegates chat inputs to specialist GPT-4.1-mini agents for copywriting, SEO, ads, and more.

Pull Square Sales Summary Reports for Automated Reporting and Analysis

## Programmatically Pull Square Report Data Into N8N ## What It Does This sub-workflow connects to the Square API and generates a daily sales summary report for all of your Square locations. The report matches the figures displayed in the Square Dashboard > Reports > Sales Summary. It's designed to be reused in other workflows, ideal for reporting, data storage, accounting, or automation. ## Prerequisites To use this workflow, you'll need: - Square API credentials (configured as a Header Auth credential) ## How to Set Up Square Credentials: - Go to Credentials > Create New - Choose Header Auth - Set the Name to Authorization - Set the Value to your Square Access Token (e.g., Bearer <your-api-key>) ## How It Works 1. Trigger: The workflow is triggered as a sub-workflow, requiring a report_date input. 2. Fetch Locations: An HTTP request gets all Square locations linked to your account. 3. Fetch Orders: For each location, an HTTP request pulls completed orders for the specified report_date. 4. Filter Empty Locations: Locations with no sales are ignored. 5. Aggregate Sales Data: A Code node processes the order data and produces a summary identical to Square's built-in Sales Summary report. 6. Output: A cleaned, consistent summary that can be consumed by parent workflows or other nodes. ## Example Use Cases - Automatically store daily sales data in Google Sheets, MySQL, or PostgreSQL for analysis and historical tracking - Automatically send daily email or Slack reports to managers or finance teams - Build weekly/monthly reports by looping over multiple dates - Push sales data into accounting software like QuickBooks or Xero for automated bookkeeping - Calculate commissions or rent payments based on sales volume ## How to Use - Configure both HTTP Request nodes to use your Square API credential. - If you are not in the Toronto/New York timezone, please change the start_at and end_at parameters in the second HTTP node from -05:00 to your local timezone - Use as a sub-workflow inside a main workflow. - Pass a report_date (formatted as YYYY-MM-DD) to the sub-workflow when you call it. ## Customization Options - Add pagination to handle locations with more than 1,000 orders per day. - Expand the workflow to save or send the report output via additional integrations (email, database, webhook, etc.). ## Why It's Useful This workflow saves time, reduces manual report pulling from Square, and enables smarter automation around sales data—whether for operations, finance, or performance monitoring.

Generate Data Pipeline Blueprints with Claude 3.5, Slack, and Avily Search

## Architecture Agent ## Overview The Architect Agent listens to Slack messages and generates full data architecture blueprints in response. Powered by Claude 3.5 (Anthropic) for reasoning and design, and heavily for real-time web search, this agent creates production-ready data pipeline scaffolds on-demand - transforming natural language prompts into structured data engineering solutions. ## Capabilities - Understands and interprets user requests from Slack - Designs end-to-end data pipeline architectures using industry best practices. - Outputs include high-level architecture diagrams ## Required Connections To operate correctly, the following integrations must be in place: - Slack API token with permission to read messages and post responses - Heavily API Key for external search functionality - Claude 3.5 API Access via Anthropic Detailed configuration instructions are provided in the workflow. ## Setup time <15 minutes ## Example input: Create a data pipeline orchestrated by Airflow, running on a Docker image. It should connect to a MySQL database, load the data into a PostgreSQL DB (incremental load), and then transform the data into business-oriented tables also in the PostgreSQL database. Create an example setup with raw sales data. ## Customizing this workflow Try saving outputs to Google Drive to store all your architecture blueprints.

Convert CSV to JSON with Error Handling and Slack Alerts

This workflow converts CSV data into JSON format via a webhook, with robust error handling and Slack notifications for any issues encountered.

Automate Business Lead Scraping and Data Cleaning to Google Sheets

Streamline your lead generation process by automatically scraping business leads from Scrapeless, cleaning the data, and exporting it to Google Sheets for easy access and analysis.

Automate Event Data Collection from 10times Using AI and Google Sheets

Streamline your event data collection process by automatically scraping and organizing event information from 10times into Google Sheets using AI and Bright Data.

Extract & Summarize B2B Leads from Crunchbase with Bright Data, GP-4O & Google Sheets

### Who this is for The Crunchbase B2B Lead Discovery Pipeline is designed for sales teams, B2B marketers, business analysts, and data operations teams who need a reliable way to extract, structure, and summarize company information from Crunchbase to fuel lead generation and market intelligence. This workflow is ideal for: 1. **Sales Development Reps (SDRs)** - Needing structured leads from Crunchbase 2. **Marketing Analysts** - Generating segmented outreach lists 3. **Growth Teams** - Identifying trending B2B startups 4. **RevOps Teams** - Automating company research pipelines 5. **Data Teams** - Consolidating insights into Google Sheets for dashboards ### What problem is this workflow solving? Manual extraction of company data from Crunchbase is time-consuming, inconsistent, and often lacks the contextual summary required for sales enablement or growth targeting. This workflow automates the extraction, transformation, summarization, and delivery of Crunchbase company data into structured formats, making it instantly usable for B2B targeting and analysis. It solves: - The difficulty of scaling lead discovery from Crunchbase - The need to summarize raw textual content for quick insights - The lack of integration between web scraping, LLM processing, and storage ### What this workflow does - **Markdown to Textual Data Extractor**: Takes raw scraped markdown from Crunchbase and converts it into readable plain text using a basic LLM chain - **Structured Data Extraction**: Applies a parsing model (OpenAI) to extract structured fields such as company name, funding rounds, industry tags, location, and founding year - **Summarization Chain**: Generates an executive summary from the raw Crunchbase text using a summarization prompt template - **Send to Google Sheets**: Adds the structured data and summary into a Google Sheet for team access and further processing - **Persist to Disk**: Saves both raw and structured data files locally for archiving or further use - **Webhook Notification**: Sends a structured payload to a webhook endpoint (e.g., Slack, CRM, internal tools) with lead insights ### Pre-conditions 1. You need to have a [Bright Data](https://brightdata.com/) account and do the necessary setup as mentioned in the Setup section below. 2. You need to have an OpenAI Account. ### Setup - Sign up at [Bright Data](https://brightdata.com/). - Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. - In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). ![Header Authentication.png](fileId:1345) The Value field should be set with the **Bearer XXXXXXXXXXXXXX**. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker token. - In n8n, Configure the Google Sheet Credentials with your own account. Follow this documentation - [Set Google Sheet Credential](https://docs.n8n.io/integrations/builtin/credentials/google/) - In n8n, configure the OpenAi account credentials. - Ensure the URL and Bright Data zone name are correctly set in the **Set URL, Filename and Bright Data Zone** node. - Set the desired local path in the **Write a file** to disk node to save the responses. ### How to customize this workflow to your needs **LLM Prompt Customization**: - Modify the extraction prompt to include additional fields like revenue, social links, leadership team - Adjust summarization tone (e.g., executive summary, sales-focused snapshot or marketing digest) **File Persistence** - Store raw markdown, extracted JSON, and summary text separately for audit/debug **Webhook Notification** - Connect to CRM (e.g., HubSpot, Salesforce) via webhook to automatically create leads - Send Slack notifications to alert sales reps when a new high-potential company is discovered

Send Google Analytics Data to AI to Analyze, Then Save Results in Baserow

## Who's this for? - If you own a website and need to analyze your Google Analytics data - If you need to create an SEO report on which pages are getting the most traffic or how your Google search terms are performing - If you want to grow your site based on suggestions from data ![Screenshot 20241101 at 11.07.21PM.png](fileId:858) ![Screenshot 20241101 at 11.07.31PM.png](fileId:857) ## Use case Instead of hiring an SEO expert, I run this report weekly. It checks and compares the data from this week to the week before: - Views based on countries - The top performing pages - Google Search Console performance [Watch YouTube tutorial here](https://www.youtube.com/watch?v=KlWFhz9M9g) [Get my SEO A.I. agent system here](https://2828633406999.gumroad.com/l/rumjahn) ## How it works - The workflow gathers Google Analytics data for the past 7 days, then it gathers the data for the week before for comparison. - It does this 3 times to get: views per country, engagement per page, and Google Search Console results for organic search results. - The Google Analytics nodes have already chosen the correct dimensions and metrics. - At the end, it passes the data to openrouter.ai for A.I. analysis. - Finally, it saves to Baserow. ## How to use this - Input your Google Analytics credentials - Input your property ID - Input your Openrouter.ai credentials - Input your Baserow credentials - You will need to create a Baserow database with columns: Name, Country Views, Page Views, Search Report, Blog (name of your blog). Created by [Rumjahn](https://rumjahn.com/)

Analyze Hacker News for Business Insights Using AI and Google Sheets

This n8n workflow monitors top Hacker News posts to identify business-related pain points using AI, and logs results into Google Sheets for further analysis.

Extract, Summarize & Analyze Amazon Price Drops with Bright Data & Google Sheets

### Notice Community nodes can only be installed on self-hosted instances of n8n. ### Who this is for This n8n-powered automation uses Bright Data's MCP Client to extract real-time data from a price drop site listing Amazon products, including price changes and related product details. The extracted data is enriched with structured data transformation, content summarization, and sentiment analysis using Google Gemini LLM. The Amazon Price Drop Intelligence Engine is designed for: - **Ecommerce Analysts** who need timely updates on competitor pricing trends - **Brand Managers** seeking to understand consumer sentiment around pricing - **Data Scientists** building pricing models or enrichment pipelines - **Affiliate Marketers** looking to optimize campaigns based on dynamic pricing - **AI Developers** automating product intelligence pipelines ### What problem is this workflow solving? This workflow solves several key pain points: **Reliable Scraping**: Uses Bright Data MCP, a managed crawling platform that handles proxies, captchas, and site structure changes automatically. **Insight Generation**: Transforms unstructured HTML into structured data and then into human-readable summaries using Google Gemini LLM. **Sentiment Context**: Goes beyond raw pricing data to reveal how customers feel about the price change, helping businesses and researchers measure consumer reaction. **Automated Reporting**: Aggregates and stores data for easy access and downstream automation (e.g., dashboards, notifications, pricing models). ### What this workflow does **Scrape price drop site with Bright Data MCP** The workflow begins by scraping targeted price drop site for Amazon listings using Bright Data's Model Context Protocol (MCP). You can configure this to target: **Structured Data Extraction** Once the HTML content is retrieved, Google Gemini is employed to: - Parse and structure the product information (title, price, discount, brand, ratings) **Summarization & Sentiment Analysis** The extracted data is passed through an LLM chain to: - Generate a concise summary of the product and its recent price movement - Perform sentiment analysis on user reviews and public perception **Store the Results** - Save to disk for archiving or bulk processing - Updated in a Google Sheet, making it instantly shareable with your team or integrated into a BI dashboard ### Pre-conditions 1. Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - [model-context-protocol](https://www.anthropic.com/news/model-context-protocol) 2. You need to have the [Bright Data](https://brightdata.com/) account and do the necessary setup as mentioned in the **Setup** section below. 3. You need to have the Google Gemini API Key. Visit [Google AI Studio](https://aistudio.google.com/) 4. You need to install the Bright Data MCP Server [@brightdata/mcp](https://www.npmjs.com/package/@brightdata/mcp) 5. You need to install the [n8n-nodes-mcp](https://github.com/nerding-io/n8n-nodes-mcp) ### Setup 1. Please make sure to set up n8n locally with MCP Servers by navigating to [n8n-nodes-mcp](https://www.youtube.com/watch?v=NUb73ErUCsA) 2. Please make sure to install the Bright Data MCP Server [@brightdata/mcp](https://www.npmjs.com/package/@brightdata/mcp) on your local machine. 3. Sign up at [Bright Data](https://brightdata.com/). 4. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel. 5. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. 6. In n8n, configure the Google Gemini (PaLM) API account with the Google Gemini API key (or access through Vertex AI or proxy). 7. In n8n, configure the credentials to connect with MCP Client (SDIO) account with the Bright Data MCP Server as shown below. ![MCPClientAccount.png](fileId:1434) Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token> ### How to customize this workflow to your needs - **Target different platforms**: Switch Amazon for Walmart, eBay, or any e-commerce source using Bright Data's flexible scraping infrastructure. - **Enrich with more LLM tasks**: Add brand tone analysis, category classification, or competitive benchmarking using Gemini prompts. - **Visualize output**: Pipe the Google Sheet to Looker Studio, Tableau, or Power BI. - **Notification integrations**: Add Slack, Discord, or email notifications for price drop alerts.

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