Data & Analytics Automation Workflows — Page 15 | Neura Market
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    Data & Analytics Workflows

    Data processing and analytics

    • Automate Startup Analysis with Crunchbase, Bright Data, Gemini AI, and Google Sheets

      This n8n workflow automates the process of discovering, enriching, and analyzing startups from Crunchbase using Bright Data and Gemini AI, with results exported to Google Sheets for easy tracking.

      n8n$9.99

    • Automate Data Processing from Apify to Google Sheets via ChatGPT

      Streamline your workflow by fetching dataset items from Apify, generating completions with ChatGPT, and updating Google Sheets with the results.

      Make$4.99

    • Connect Pipedrive Deal Outcomes to GA4 & Google Ads via Measurement Protocol

      ## Who's it for **Problem:** Your ads and GA4 often optimize to shallow web events (form fills), while the *real* value sits in Pipedrive (Qualified, Closed Won). That gap means bidding chases cheap leads instead of revenue. **Solution:** This template turns Pipedrive deal milestones into **server-side GA4 events** (via Measurement Protocol), matched to the original visitor by `client_id`—no external database. You mark them as **Key events** in GA4 and, when ready, import them into Google Ads. **Business value:** Ads can optimize on **actual CRM outcomes with value** (and currency), improving CAC/ROAS and reducing lead spam. Everything stays GA4-centric, consent-aware, and deduped with deterministic `event_id`, so you get reliable attribution without building a custom Ads integration. If you're serious about scaling paid spend toward **high-quality, high-value deals**, this is the missing link. This is **not plug-and-play**. Expect **~2 hours of developer work** to integrate: ## What it does On **Deal Updated**, the workflow checks for target stages (e.g., Qualified, Closed Won), fetches the linked Person's **client_id**, builds a GA4 **Measurement Protocol** event (with `value`, `currency`, deterministic `event_id`), and posts it server-side. Success updates deal-level dedupe flags; failures are logged to a Pipedrive Note. Credentials use n8n **Credentials**—no hardcoded secrets. ## How it works (high level) A Pipedrive trigger listens for stage changes — an eligibility check gates sends — a payload builder composes the GA4 event — an HTTP call posts to GA4. Sticky notes in the canvas explain the whole setup and what to edit. ## Requirements GA4 installed on your site; GA4 **Measurement ID** + **API Secret** (same data stream); Pipedrive Person field for `client_id`, optional `consent_granted`; Pipedrive Deal booleans for dedupe; n8n credentials configured (no secrets in nodes). ## How to customize the workflow - Change which stages send events and the event names. - Adjust `value` logic (e.g., margin- or probability-weighted). - Choose skip-on-no-consent vs. `non_personalized_ads: true`. - Add extra params (`deal_id`, `pipeline_stage`, etc.) to GA4 as custom dimensions (event-scoped). ## Troubleshooting & debugging - If `client_id` is null: GA4 not initialized yet, consent denied, GM var not firing, or adblockers—fix site capture first. - If GA4 shows events in DebugView but Ads import is empty: events not marked as Key events, GA4—Ads not linked/imported, or wrong stream/secret pairing. - Use `https://www.google-analytics.com/debug/mp/collect` only for payload validation; it won't verify your API secret. Final sends go to `/mp/collect`.

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    n8n$14.99

  1. Calculate the Centroid of a Set of Vectors

    # n8n Workflow: Calculate the Centroid of a Set of Vectors ## Overview This workflow receives an array of vectors in JSON format, validates that all vectors have the same dimensions, and computes the centroid. It is designed to be reusable across different projects. ## Workflow Structure ### Nodes and Their Functions: 1. **Receive Vectors (Webhook)**: Accepts a GET request containing an array of vectors in the `vectors` parameter. - **Expected Input:** `vectors` parameter in JSON format. - **Example Request:** `/webhook/centroid?vectors=[[2,3,4],[4,5,6],[6,7,8]]` - **Output:** Passes the received data to the next node. 2. **Extract & Parse Vectors (Set Node)**: Converts the input string into a proper JSON array for processing. - **Ensures `vectors` is a valid array.** - **If the parameter is missing, it may generate an error.** - **Expected Output Example:** ```json { "vectors": [[2,3,4],[4,5,6],[6,7,8]] } ``` 3. **Validate & Compute Centroid (Code Node)**: Validates vector dimensions and calculates the centroid. - **Validation:** Ensures all vectors have the same number of dimensions. - **Computation:** Averages each dimension to determine the centroid. - **If validation fails:** Returns an error message indicating inconsistent dimensions. - **Successful Output Example:** ```json { "centroid": [4,5,6] } ``` - **Error Output Example:** ```json { "error": "Vectors have inconsistent dimensions." } ``` 4. **Return Centroid Response (Respond to Webhook Node)**: Sends the final response back to the client. - **If the computation is successful**, it returns the centroid. - **If an error occurs**, it returns a descriptive error message. - **Example Response:** ```json { "centroid": [4, 5, 6] } ``` ## Inputs - JSON array of vectors, where each vector is an array of numerical values. ### Example Input ```json { "vectors": [ [1, 2, 3], [4, 5, 6], [7, 8, 9] ] } ``` ## Setup Guide 1. **Create a new workflow in n8n**. 2. **Add a Webhook node** (`Receive Vectors`) to receive JSON input. 3. **Add a Set node** (`Extract & Parse Vectors`) to extract and convert the data. 4. **Add a Code node** (`Validate & Compute Centroid`) to: - Validate dimensions. - Compute the centroid. 5. **Add a Respond to Webhook node** (`Return Centroid Response`) to return the result. ### Function Node Script Example ```javascript const input = items[0].json; const vectors = input.vectors; if (!Array.isArray(vectors) || vectors.length === 0) { return [{ json: { error: "Invalid input: Expected an array of vectors." } }]; } const dimension = vectors[0].length; if (!vectors.every(v => v.length === dimension)) { return [{ json: { error: "Vectors have inconsistent dimensions." } }]; } const centroid = new Array(dimension).fill(0); vectors.forEach(vector => { vector.forEach((val, index) => { centroid[index] += val; }); }); for (let i = 0; i < dimension; i++) { centroid[i] /= vectors.length; } return [{ json: { centroid } }]; ``` ## Testing - Use a tool like Postman or the n8n UI to send sample inputs and verify the responses. - Modify the input vectors to test different scenarios. This workflow provides a simple yet flexible solution for vector centroid computation, ensuring validation and reliability.

    n8n$4.99

  2. Fetch and Store Company Branding Data in Airtable

    Automatically retrieve a company's logo, icon, and other information using Brandfetch and store it in Airtable for easy access and management.

    n8n$4.99

  3. Automate LinkedIn Profile Discovery and Verification with Airtop

    Streamline the process of finding and verifying LinkedIn profiles using Airtop for enhanced accuracy in prospecting, recruiting, and contact enrichment.

    n8n$9.99

  4. Automatically Update Cyfe Widgets with New Google Sheets Data

    Streamline your data management by automatically pushing new Google Sheets entries to Cyfe widgets, ensuring real-time data visualization.

    MakeFree

  5. Automate Data Insertion and Retrieval in Stackby

    This workflow automates the process of inserting new data into a Stackby table and retrieving all existing data from it, streamlining your data management tasks.

    n8n$4.99

  6. Preconfigured Nodes for Systeme.io API Requests

    Using the Systeme API can be challenging due to its pagination settings and low rate limit. This requires a bit more knowledge about API requests than a beginner might have. This template provides preconfigured HTTP Request nodes to help you work more efficiently. Pagination settings, item limits, and rate limits are all configured for you, making it easier to get started. ### How to configure Systeme.io credentials The Systeme API uses the Header Auth method. So, create a Header Auth credential in your n8n with the name X-API-Key. ![image.png](fileId:825) ### Check out my other templates ☀️🌊 [**https://n8n.io/creators/solomon/**](https://n8n.io/creators/solomon/)

    n8n$9.99

  7. Automate Duplicate Record Removal in Airtable Using ChatGPT

    Streamline your Airtable database by automatically identifying and removing duplicate records using ChatGPT's AI capabilities, ensuring cleaner and more efficient data management.

    Make$4.99

  8. Automate ISS Position Tracking and Storage in TimescaleDB

    This workflow automates the process of fetching the International Space Station's (ISS) position and storing it in a TimescaleDB table every minute.

    n8n$4.99

  9. Parse Email Body Message

    # Who we are We are **Aprende n8n**, the first n8n Spanish course for all n8n lovers. If you want to learn more, you can find out more at [Aprende n8n](https://aprenden8n.com). # Our goal This task allows extracting data from any email body with a NoCode snippet. # A small explanation You receive an email when a user submits a form from your website. All those emails usually have the same structure as the next one: ``` Name: Miquel Email: miquel@aprenden8n.com Subject: Welcome aboard Message: Hi Miquel! Thank you for your signup! ``` This task allows parsing any email body and assigning all values to the defined labels, getting an output like this: ``` { Name: Miquel, Email: miquel@aprenden8n.com, Subject: Welcome aboard, Message: Hi Miquel! Thank you for your signup! } ``` # After importing it When you import the import, you get the next task in your n8n: ![aprenden8n.com_email_parser_task.jpeg](fileId:613) We recommend importing this workflow into your current task and adapting it. You define a couple of variables in the Set values SE: - body: the email body you want to parse. You can add this as an expression from previous variables. - labels: the keywords you want to detect and parse. Labels are case insensitive. We define the next values: Body ``` Name: Miquel Email: miquel@aprenden8n.com Subject: Welcome aboard Message: Hi Miquel! Thank you for your signup! ``` Labels ``` Name,Email,Subject,Message ``` A screenshot of the Set output is the next one ![aprenden8n.com_email_parser_set.jpeg](fileId:611) If we check the Function item Node, we get the next content after executing the task: ![aprenden8n.com_email_parser_output.jpeg](fileId:612) # Capabilities The task has the next features: - You can detect as many labels as you want. - Label detection is case insensitive. - You can use the snippet as an independent workflow to call it generically, adding the Function item to the workflow and passing body and labels as parameters. # Limitations This task has limitations: - The parser only accepts multiline values at the end of the email. # Help and comments If you have any doubt about this snippet, please, contact us at miquel@aprenden8n.com. You can contact us at [Aprende n8n](https://aprenden8n.com) or in the [Spanish n8n community](https://t.me/comunidadn8n)

    n8n$3.99

  10. Weekly Data Transfer from Google Sheets to MySQL

    Automate the weekly import of data from Google Sheets into a MySQL database, ensuring your database is consistently updated.

    n8n$3.99

  11. Automate DNB Company Data Extraction with Bright Data and OpenAI

    Streamline the process of gathering structured business intelligence from Dun & Bradstreet by automating search, scraping, and data extraction using Bright Data and OpenAI.

    n8n$14.99

  12. Monitor eBay API Rate Limits for AI Integration

    This workflow transforms eBay's Analytics API into an MCP-compatible server for AI agents, enabling seamless monitoring of application and user rate limits.

    n8n$4.99

  13. Automatically Store LinkedIn Scraper Results in Airtable

    This workflow automates the process of storing LinkedIn Profile Scraper results from Phantombuster into Airtable, streamlining data management.

    n8n$4.99

  14. Automate Customer Insights from Trustpilot Reviews Using Qdrant and OpenAI

    This workflow automates the extraction and analysis of Trustpilot reviews to generate actionable customer insights. It leverages Qdrant for vector storage and OpenAI for sentiment analysis, saving marketers significant time in review analysis.

    n8n$24.99

  15. Real-Time Processing of Icypeas Search Results with n8n

    This workflow enables real-time listening and processing of search results from Icypeas using n8n. It integrates with a webhook to capture search data and a set node to extract relevant information, such as email and names.

    n8n$4.99

  16. Automate Email Validation and Update in Google Sheets Using Email Validator AI

    This workflow automates the validation of email addresses in a Google Sheet using Email Validator AI via RapidAPI, updating the sheet with the validation results.

    n8n$9.99

  17. Automate LinkedIn Profile Discovery for Key Roles Using Google Search

    This workflow automates the discovery of LinkedIn profiles for roles like CISO and CEO using Google Programmable Search. It extracts profile links, names, and timestamps, logging them into a structured Google Sheet for analysis.

    n8n$4.99

  18. Weekly Data Transfer from MySQL to Google Sheets

    This workflow automates the weekly transfer of data from a MySQL table to Google Sheets, ensuring your spreadsheet is always up-to-date.

    n8n$3.99

  19. Export SQL Data to XML with XSL Formatting via Webhook

    This workflow exports SQL data to XML and formats it using an XSL template, ensuring compatibility with modern browser CORS policies.

    n8n$9.99

  20. Comparing Data with the Compare Datasets Node

    This workflow is designed to compare two datasets (Dataset 1 and Dataset 2) based on a common field, fruit, and provide insights into the differences. Here are the steps: 1. **Manual Trigger**: The workflow begins when a user clicks "Execute Workflow." 2. **Dataset 1**: This node generates the first dataset containing information about fruits, such as apple, orange, grape, strawberry, and banana, along with their colors. 3. **Dataset 2**: This node generates the second dataset, also containing information about fruits, but with some variations in color. For example, it includes a kiwi with the color mostly green. 4. **Compare Datasets**: The "Compare Datasets" node takes both datasets and compares them based on the fruit field. It identifies any differences or matches between the two datasets. In summary, this workflow is used to compare two datasets of fruits and their colors, identify differences, and provide guidance on how to explore the comparison results.

    n8n$4.99

  21. WhatsApp AI Recipe Suggestions from Pantry via Gemini & FatSecret

    Transforms WhatsApp pantry item lists into personalized recipes using Gemini AI for intent analysis and FatSecret API for nutritional data. Enables conversational cooking assistance with context memory.

    n8n$24.99
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