Google Sheets Workflows
248 Ergebnisse — ausschließlich quellenverknüpfte n8n-Referenzen
Send portfolio risk reports from Google Sheets with OpenAI and Gmail
Quick overview This workflow collects a portfolio request via an n8n Form, loads holdings from Google Sheets, calculates portfolio risk and concentration metrics, generates an HTML risk narrative with OpenAI, then emails the full report via Gmail and appends an audit record back to Google Sheets. How it works Receives a portfolio analysis request from an n8n Form containing the investor details, base currency, and a Google Sheet ID. Reads all holdings from the provided Google Sheets document (Portfolio tab) and bundles the rows into a single portfolio dataset. Calculates market value, allocations, sector and asset-class breakdowns, P&L, concentration flags, and a 0–100 risk score. Sends the computed portfolio summary, breakdowns, risk flags, and holdings to OpenAI to generate a structured risk report in HTML. Builds a branded HTML email that includes the AI narrative plus sector and top-holdings tables and a concentration alert banner. Sends the HTML risk report to the investor via Gmail and appends a summary row to a Google Sheets “Analysis Log” audit sheet. Setup Create a Google Sheet with a tab named “Portfolio” and headers: ticker, company, sector, asset_class, quantity, avg_bu
Qualify inbound leads with OpenAI, Slack, and Google Sheets
Quick overview This workflow receives inbound leads via a webhook, normalizes common form fields, and uses OpenAI to score and tier each lead as HOT, WARM, or NURTURE. It logs the result to Google Sheets, sends a tier-specific email auto-reply, and alerts a Slack channel for HOT leads. How it works Receives an inbound lead submission via a POST webhook. Normalizes incoming fields (name, email, company, website, message, budget, timeline, and source) into a consistent structure. Sends the normalized lead details to OpenAI to generate JSON scores (fit, budget, urgency, overall), a tier, reasoning, next action, and red flags. Merges the AI qualification results back into the lead record and routes the lead based on the tier. For HOT leads, posts an alert to Slack, appends the lead to the “Hot Leads” tab in Google Sheets, and sends a HOT auto-reply email. For WARM and NURTURE leads, appends the lead to the matching Google Sheets tab and sends the corresponding tier-specific auto-reply email. Returns a JSON response to the webhook caller confirming success and the assigned tier. Setup Add an OpenAI credential and customize the system prompt ICP/scoring rules in the OpenAI step. Add Goog
Send weekly narrative client reports with Google Sheets, Claude, and Gmail
Quick overview This workflow runs every Friday at 9:00 AM, pulls active client status data from Google Sheets, uses Anthropic Claude to generate a narrative weekly report with structured HTML and plain text output, and sends the finished report to each client via Gmail. How it works Runs every Friday at 9:00 AM on a schedule trigger. Reads all client rows from a specified Google Sheets document. Filters out paused/inactive or incomplete rows, extracts any “Metric:” columns, and builds a reporting week label for each client. Sends each client’s normalized data to Anthropic Claude to write a 3–4 paragraph narrative report and return JSON containing an email subject plus HTML and plain-text bodies. Emails the generated HTML report to each client’s email address using Gmail. Setup Create a Google Sheet with the required columns (at minimum “Client Name” and “Client Email”) and optional “Status” plus any “Metric:” columns you want included. Add Google Sheets OAuth2 credentials in n8n and replace the placeholder Sheet ID in the Google Sheets read step. Add an Anthropic credential for the Claude chat model used to generate the structured report. Add Gmail OAuth2 credentials and confirm th
Recover overdue invoices with GPT-4o-mini, Gmail, Google Sheets and Slack
Quick overview This workflow runs every 24 hours to read overdue invoices from Google Sheets, uses OpenAI (GPT-4o-mini) to draft personalized recovery emails and determine escalation, sends emails via Gmail, logs outcomes back to Google Sheets, and posts status and error alerts to Slack. How it works Runs every 24 hours on a schedule trigger. Reads invoice rows from a Google Sheets “invoices” tab and checks whether there are any valid invoice entries to process. If no invoices are found, posts a “no overdue invoices” message to a Slack channel. For each invoice found, uses OpenAI (GPT-4o-mini) to assign an escalation level, draft a personalized HTML email (including payment plans when applicable), and recommend an escalation action. Parses the AI output into structured fields and sends the recovery email to the client via Gmail. If the AI recommends escalation, sends an internal escalation alert email to the legal team via Gmail. Updates the invoice row in Google Sheets with the new escalation level and AI summary, then appends a full audit log row to a “Recovery sheet” tab. If AI processing fails, posts an error alert to Slack and continues with the next invoice. Setup Add Google
Log clinic chatbot inquiries from a website widget with OpenAI and Google Sheets
Quick overview This workflow receives website chatbot messages via a webhook, uses OpenAI to generate an AI receptionist reply with session-based context, extracts structured inquiry details, and appends or updates a single visitor row in Google Sheets before returning a clean JSON reply to the widget. How it works Receives a POST request from the website chat widget containing the visitor message, sessionId, and timestamp. Uses an OpenAI-powered receptionist agent with per-session memory to generate a contextual reply and a hidden JSON block of extracted inquiry details. Strips the hidden data block from the reply, parses the JSON into fields (name, contact, intent, appointment details, summary, status), and flags whether any meaningful data was captured. If collectible data exists, appends or updates a Google Sheets row matched on Session ID with the latest extracted details and a Last Updated timestamp. Returns the cleaned reply to the chat widget as a JSON response with CORS headers. Setup Add an OpenAI API credential for the OpenAI chat model used by the receptionist agent. Add a Google Sheets OAuth2 credential and set the target spreadsheet document ID and sheet/tab name used
Evaluate vendor proposal PDFs with OpenAI, Gmail, and Google Sheets
Quick overview This workflow collects vendor proposal PDFs via an n8n Form, extracts text from the PDF, uses an OpenAI ChatGPT model to summarize and flag risks, logs the evaluation to Google Sheets, and sends an approval or review-needed notification through Gmail. How it works Receives a submission from an n8n Form with the submitter’s details, optional notes, and a vendor proposal PDF upload. Extracts text from the uploaded PDF and cleans/limits it to a safe length for AI evaluation. Sends the cleaned proposal text and submitter notes to an OpenAI ChatGPT model to return structured JSON with vendor details, summary, key points, and risks. Parses the AI response, formats key points and risks for readability, and flags the submission as “REVIEW NEEDED” when any risks are present. Appends the evaluation results to an “Evaluations” tab in Google Sheets with the decision, summary, and risk metadata. Sends a Gmail alert to the review team when risks are found, otherwise emails an auto-approval notification to the approver. Setup Add an OpenAI API credential and select the model for the OpenAI Chat Model used by the evaluator. Connect Google Sheets OAuth2 and replace YOUR_PROPOSAL_LOG_
Categorize emails and draft Gmail replies with Groq and Google Sheets
Quick overview This workflow monitors Gmail for new emails, uses Groq (via the LangChain Agent node) to categorize and summarize each message and draft a reply, sends an alert email for high-priority items, and logs the analysis and draft details to Google Sheets. How it works Checks Gmail every minute for new incoming emails. Skips processing if the email has no body content or snippet. Extracts the sender, subject, received date, message ID, and a truncated body (up to 3000 characters) for analysis. Sends the email content to Groq to return a JSON analysis with category, priority, summary, key asks, action items, suggested labels, and a draft reply. Parses and validates the AI JSON output, stopping if it cannot be parsed. Sends a Gmail alert to your chosen address when the email is marked HIGH priority, then continues. Appends the parsed analysis fields to a Google Sheets “Email Log” sheet and creates a Gmail draft reply only when the analysis indicates a response is required. Setup Connect a Gmail OAuth2 credential with permission to read emails and create drafts, and select it in the Gmail Trigger, Alert email, and Create Draft nodes. Add a Groq API credential and select it in
Repurpose content into 5-platform posts with Groq Llama 3.3 and Upload-Post
Quick overview This workflow receives a webhook with either a URL or raw text, uses Groq (Llama 3.3 70B) to analyze and repurpose the content into Instagram, X, LinkedIn, email, and video formats, optionally logs results to Google Sheets, and posts the LinkedIn text to multiple platforms via Upload-Post.com. How it works Receives a POST webhook request containing a single content value that is either a URL or plain text. If the input starts with http, it fetches the page content over HTTP and packages it as cleaned source text; otherwise it uses the provided text as-is. Sends the prepared content to Groq (Llama 3.3 70B) to generate a structured analysis of the core message, key points, audience, tone, and hook angles. Uses Groq again to generate platform-specific outputs (Instagram caption/hashtags, X thread, LinkedIn post, email newsletter, and a short video script) as JSON. Parses the AI JSON, validates character limits for Instagram, LinkedIn, and X, and returns an error response if the output cannot be parsed. On success, appends the generated content and validation warnings to Google Sheets, posts the LinkedIn text to selected social platforms via the Upload-Post.com API, and
Publish science newsletter posts from YouTube using Ghost and Google Sheets
Quick overview This workflow turns science keywords from Google Sheets into researched Ghost newsletter posts by discovering and screening YouTube videos with Apify, validating claims using Brave Search, storing sources in Qdrant with Cohere embeddings, drafting content with LLMs, and publishing via a custom Ghost HTTP endpoint. How it works Runs either manually to qualify “FAIR GAME” keywords from Google Sheets or on a schedule to start the automated publishing pipeline. Uses Brave Search with an LLM agent to research each keyword’s current context and writes a structured relevance, domain, and angle assessment back to the Keywords sheet. On schedule, randomly selects an eligible keyword, uses Apify’s YouTube Scraper to fetch recent videos with English transcripts, and appends normalized candidates to the Candidate Videos sheet. Scores each candidate’s virality from views, engagement, channel size, and publish age, marks rows as VIRAL or NOT VIRAL, and archives NOT VIRAL items to an Archive sheet. Reviews VIRAL candidates with an editorial LLM agent to select exactly one evidence-worthy video (or reject all), updates statuses and reasoning in Google Sheets, and archives rejected v
Monitor warehouse receiving performance with Google Sheets, Gemini, and Gmail
Quick overview This workflow runs hourly to analyze warehouse receiving logs from Google Sheets, calculates per-user performance and compliance metrics, enriches results with department data, uses Google Gemini to generate recommendations for flagged users, emails managers via Gmail when escalation is needed, and appends results to an analytics dashboard sheet. How it works Runs every hour on a schedule trigger. Reads receiving log rows from Google Sheets and normalizes key fields like duration, errors, and compliance. Aggregates the log data by user_id and computes performance status, severity score, and alert tier based on time, errors, and compliance rate. Looks up each user’s department and manager email in a Google Sheets “Departments” tab and attaches this context to the analysis. For users not rated “good,” sends the metrics to Google Gemini to generate structured root-cause and action-step recommendations. If the alert tier is not “none,” sends an info/warning or critical escalation email via Gmail (using manager_email when available). Appends the final per-user analysis (metrics, issues, recommendations, and whether an email was sent) to a Google Sheets “AnalyticsDashboard
Detect maverick spend and alert reviewers via Slack, Gmail, Sheets and Gemini
Quick Overview This workflow runs daily to compare procurement transactions in Google Sheets against an approved supplier list, flags unapproved (maverick) spend, uses Google Gemini to generate compliant alternatives, alerts reviewers via Slack and Gmail, logs violations back to Google Sheets, and escalates unresolved cases after two hours. How it works Runs every day at 11:00 AM on a schedule. Loads the approved supplier list and the latest transactions from Google Sheets and normalizes supplier names for consistent matching. Compares each transaction’s supplier against the approved list and flags transactions from unapproved suppliers as maverick spend. For approved suppliers, marks the transaction as processed in Google Sheets and ends. For maverick spend, sends the transaction details and the approved supplier list to Google Gemini to generate corrective recommendations and alternative suppliers. Formats the AI output with a timestamp, posts a Slack alert, and sends a detailed violation email through Gmail. Appends the violation details to a Google Sheets log, marks the transaction as processed, waits two hours, and then posts an escalation message to Slack. Setup Connect Googl
Monitor budget variance with Google Sheets, Gemini, Slack, and Gmail
Quick overview This workflow runs daily to compare department budgets and actual spend from Google Sheets, calculates variance, uses Google Gemini to generate root-cause insights, sends Slack alerts when variance breaches a threshold, logs results back to Google Sheets, and emails a daily report via Gmail. How it works Runs every day at 9:00 AM on a schedule. Reads budget and actual spend data from two Google Sheets tabs and matches records by Department. Calculates spend variance and variance percentage, then assigns a status label (Healthy/Warning/Critical) and run context like date and summary. Sends the variance details to Google Gemini to generate a JSON response with root cause, risk level, and recommendations. Checks whether the variance percentage is greater than 10% and sends a Slack alert with the AI insights when the threshold is exceeded. Appends the final analysis (including whether an alert was sent) to a Google Sheets log and sends the same report via Gmail. Setup Connect Google Sheets OAuth credentials and set the correct spreadsheet and sheet tabs for Budget Data, Actual spend, and the Final report log. Add a Google Gemini (PaLM) API credential for the Gemini model
Enrich B2B leads with Tavily search, Groq Llama 3.3, and Google Sheets
Quick overview This workflow receives a company name via webhook, runs three Tavily web searches (company info, recent news, and key people), uses Groq (Llama 3.3 70B) to synthesize a structured lead profile, optionally appends the results to Google Sheets, and returns the enriched profile in the webhook response. How it works Receives a POST webhook request containing a company name and an optional domain. Queries the Tavily Search API for company overview details, then searches Tavily again for recent news and key executives/leadership. Sends the combined search results to a Groq LLM agent to generate a sales-ready lead enrichment profile as strict JSON (company details, products, signals, news, pain points, and outreach angles). Parses the AI output, extracts valid JSON if possible, and flattens key fields into a single row-friendly structure. If parsing succeeds, appends the enriched lead data to a Google Sheets spreadsheet and returns the full profile in the webhook response. If parsing fails, returns an HTTP 422 error response with the raw AI output for troubleshooting. Setup Create a Groq API key, add it as an n8n Groq credential, and select it in the Groq LLM node. Create a
Transcribe and analyze sales meetings with Deepgram, Gemini, GHL, Slack & Gmail
Quick overview Youtube Video: https://youtu.be/GNAplBWdCDE?si=TjojVTZX7ViiRUiG This workflow receives meeting voice recording via webhook, transcribes it with Deepgram, and uses Gemini to extract client details and next-step tasks. It then updates GoHighLevel, posts a task summary to Slack, emails the client their action items via Gmail, and logs the meeting to Sheets. How it works Receives a POST webhook request containing a meeting ID, attendee email, meeting date/time, and an audio file. Looks up the contact in GoHighLevel by email and creates/updates the contact if it does not already exist. Checks Google Sheets for the meeting ID and only continues if no existing row is found. Sends the audio binary to Deepgram to transcribe the recording with speaker diarization and utterances enabled. Formats the transcript and sends it to a Google Gemini–powered agent that returns structured JSON with client identification and task lists. Creates a GoHighLevel task with the extracted service-provider tasks, posts the task summary to Slack, and emails the client their tasks via Gmail. Appends the meeting details, extracted company name, and action items to Google Sheets and returns a webhook
Generate personalized financial plans with Google Gemini, Sheets, Drive and Gmail
Quick overview This workflow receives income and financial-goal data via webhook, stores enriched metrics in Google Sheets, generates a tailored plan with Google Gemini, converts it to a PDF via PDFShift, uploads it to Google Drive, and emails the result using Gmail. How it works Receives a POST webhook request containing an Income value and a Goal string. Normalizes the incoming fields and validates that income is non-negative and the goal is not empty, returning a webhook error response if validation fails. Calculates a timestamp, a recommended monthly saving amount (20% of income), and an income category (Low/Mid/High), then appends the record to Google Sheets. Routes the request by income category and uses Google Gemini (PaLM) to generate a personalized financial plan with category-specific guidance. Builds an HTML report that includes the user’s inputs and the Gemini-generated plan, then converts the HTML to a PDF using the PDFShift API and fetches the generated file. If the PDF is created successfully, uploads it to Google Drive, emails the PDF and Drive link via Gmail, and returns the HTML report in the webhook response. If PDF generation fails, returns a JSON error response
Score job listings and generate tailored cover letters with Apify, OpenAI and Google Sheets
Quick overview This workflow runs on a schedule to scrape job listings via Apify (Google Jobs and Career Site API), scores each role against your base resume using OpenAI, generates tailored cover letter and optionally a tailored resume in Google Docs, and logs the results to Google Sheets with Gmail error alerts. How it works Runs on a schedule (with an optional manual test trigger) and loads your search query and Google IDs from the configured variables. Uses Apify actors to scrape jobs from Google Jobs and the Career Site API, then normalizes and merges both result sets into a single list. Processes jobs in batches and skips listings that already exist in Google Sheets (matched by Apply URL), have no apply link, have short descriptions, or don’t meet the seniority criteria. Fetches your base resume from Google Docs and sends the resume plus job details to OpenAI to score relevance from 1–10 with a one-sentence rationale. For jobs scoring 7+, uses OpenAI to generate a personalized cover letter from the job description and your resume. For jobs scoring 8+, uses OpenAI to tailor your resume, saves it as a new Google Doc in your Drive folder, and makes the document publicly readable
Send GitHub release audio newsletters with OpenAI, Google Drive, Gmail and Sheets
Quick overview This workflow triggers on a published GitHub Release, uses OpenAI to turn the release notes into a short spoken script and MP3, stores the audio on Google Drive, pulls subscribers from Google Sheets, and sends an HTML “listen” newsletter to them via Gmail. How it works Triggers when a GitHub Release is published for the configured repository. Parses and cleans the release changelog, extracting key items into features, fixes, improvements, and other notes. Uses an OpenAI chat model to rewrite the release details into a 60–90 second spoken script. Calls the OpenAI text-to-speech API to generate an MP3 audio file from the script. Uploads the MP3 to Google Drive and sets the file permissions to “anyone with the link can view.” Loads subscriber email addresses from Google Sheets, builds an HTML newsletter with the public audio link and release highlights, and sends it via Gmail using BCC. Setup Connect a GitHub credential with access to the target repo and replace YOUR_GITHUB_USERNAME and YOUR_REPO_NAME in the GitHub trigger. Add an OpenAI API credential for both the chat model step and the OpenAI TTS HTTP request. Connect Google Drive OAuth2 and replace YOUR_AUDIO_FOLDER
Track expenses from phone notifications with Google Gemini and Google Sheets
Quick overview This workflow receives phone push notification through FlowTrigger mobile app, extracts the transaction amount and date, uses Google Gemini to categorize the expense and adds it to a Google Sheets transactions log. How it works Receives a POST webhook request containing a captured notification payload from FlowTrigger mobile app. Parses the notification data and skips the flow if no amount is detected in the notification payload. Sends the notification title and body to Google Gemini and parses a structured response with cleaned merchant name, expense category, reasoning, and ISO currency code. Appends the date, amount, category, currency, and merchant to a selected Google Sheets tab. Returns a success response with the saved fields, or an error response if the AI categorization or Google Sheets write fails. Setup Create and connect a Google Gemini API key credential for the Google Gemini Chat Model. Create and connect a Google Sheets OAuth2 credential, then set the Google Sheets Document ID and Sheet Tab Name in the Google Sheets append step. Activate the workflow, copy the Webhook production URL from the Webhook trigger, and paste it into FlowTrigger’s Notification
Qualify Product Hunt leads with Google Gemini, Apify, and Google Sheets
Quick overview Youtube Video: https://youtu.be/h47YeiivZvs?si=V-S1X-ME5V24Tuch This workflow runs daily to pull the latest Product Hunt posts, qualifies them with Google Gemini, scrapes ICP-matching product websites with Apify to find emails, then writes the lead data to Google Sheets and creates contacts in GoHighLevel. How it works Runs every day on a schedule trigger. Queries the Product Hunt GraphQL API for the latest posts and iterates through each result. Resolves each product’s website redirect target, extracts a clean domain, and filters out blocked domains like app stores, social networks, and link aggregators. Sends the product name, tagline, and description to a Google Gemini–powered agent to score ICP fit and keeps only matches. Uses Apify to crawl each matched website and extract email addresses from the site content. Groups scraped results by domain, keeps only products with at least one email, and appends or updates a matching row in Google Sheets. Creates a GoHighLevel contact using the first email and stores any additional emails in a custom field. Setup Add Product Hunt OAuth2 credentials and ensure the GraphQL query in the Product Hunt request returns the fields
Extract meeting insights from transcripts with OpenAI, Google Sheets and ClickUp
Quick Overview This workflow collects a meeting transcript via an n8n Form, uses OpenAI (ChatGPT) to extract structured meeting intelligence, logs the results to Google Sheets, creates one ClickUp task per action item, and emails an HTML meeting brief via Gmail. How it works Receives a form submission containing the meeting title, date, participants, duration, and full transcript. Validates the input (including a minimum transcript length), calculates counts, and generates a unique meeting ID. Sends the meeting context and transcript to an OpenAI ChatGPT model to extract a strict JSON payload with summary, topics, decisions, action items, risks, follow-up date, and sentiment. Parses and normalizes the AI JSON output, then formats readable strings and metrics for reporting. Appends the full meeting record to a Google Sheets “Meetings” tab. Splits the extracted action items and creates a ClickUp task for each valid item, including owner, priority, and due date when provided. Sends a formatted HTML meeting brief to the configured team email address using Gmail. Setup Add an OpenAI credential in the OpenAI Chat Model node and select the model to use. Connect Google Sheets OAuth2, repla
Track Slack EOD updates and post executive summaries with Google Sheets and Gemini
Quick overview Youtube Video: https://youtu.be/AbkX2splTTg?si=LTHqLFIWQD4hAYsO This workflow collects end-of-day updates from team members in Slack, stores them in Google Sheets, and posts a concise executive summary back to Slack using Google Gemini. How it works Runs daily at 3pm, reads the team roster from Google Sheets, filters out people marked as on leave, and sends each active member an EOD update form in Slack. Receives Slack button/form submissions via a webhook, parses the interactive payload, and replaces the original message with a confirmation. Checks whether the submitted EOD date matches today’s date, and sends a private Slack alert to the owner if someone submits late. For on-time submissions, reads today’s entries from the EOD submissions Google Sheet, deduplicates by user and date, and appends the new submission to Google Sheets. Runs daily at 5pm, reads today’s submissions and yesterday’s “tomorrow plan” entries from Google Sheets and merges them per user. Aggregates the merged data, calculates attendance and expected submission counts from the team roster, and sends the dataset to Google Gemini to generate an executive summary. Posts the generated Slack-formatte
Grade system prompts in Google Sheets with a Gemini LLM judge
Quick overview This workflow manually grades a system prompt by running it against a sample user task with Google Gemini, then has a second Gemini judge score the prompt (1–10) and write the grade and reason back to Google Sheets. How it works Starts when you run the workflow manually. Reads the prompt list from a Google Sheets spreadsheet and keeps only the last row as the system prompt under test. Sets a fixed sample customer-support task and sends it to a Google Gemini-powered agent using the sheet prompt as its system instructions. Sends the original prompt, the sample task, and the agent’s response to a second Google Gemini judge that returns a structured grade and short justification. Updates the same Google Sheets row with the returned grade and reason. Setup Connect a Google Sheets OAuth2 credential with access to the target spreadsheet. Connect a Google AI Studio (Gemini) credential for the candidate model, grader model, and parser-fixer model. Ensure your sheet has columns for at least prompt, grade, and reason, and that the workflow can match rows using the row_number field. Update the spreadsheet ID/sheet and edit the sample task text if you want to test prompts against
Detect competitor launch signals from ads with OpenAI and Google Sheets
Quick Overview This workflow runs weekly to scan competitor ad copy from Meta, Google Ads, and LinkedIn via Adyntel, detects newly emerging terms, uses OpenAI to assess launch signals, and records results in Google Sheets while sending a Slack alert when a launch signal is detected. How it works Runs every week on a schedule (Monday) to start the competitor monitoring cycle. Reads competitors marked as Pending from Google Sheets and processes them one by one. For each competitor domain, pulls current ads from Meta, Google Ads, and LinkedIn using Adyntel and combines the results. Extracts and deduplicates ad titles and body copy, then loads the competitor’s previously known terms from Google Sheets. Extracts candidate new terms from this week’s ad copy, filters for terms that recur across multiple ads, and decides whether there are meaningful new terms to analyze. If meaningful new terms exist, sends the context to OpenAI to classify the terms and determine whether a product launch signal is present, then appends the signal record and the newly classified terms to Google Sheets. If no meaningful new terms exist, appends baseline terms from this week’s ad titles to Google Sheets to p
Extract ecommerce product data with Google Sheets, ScrapingBee and Gemini
Quick Overview This workflow manually runs to read a list of webpage URLs from Google Sheets, scrape each page with ScrapingBee, and use Google Gemini to extract structured product data from screenshots with an HTML fallback, then append the results back into a Google Sheets sheet. How it works Runs when you manually trigger the workflow. Reads the list of URLs to scrape from a Google Sheets spreadsheet. Fetches a full-page screenshot for each URL using the ScrapingBee API. Sends the screenshot (and the URL for context) to a Google Gemini model to extract product details into a structured JSON format, calling a ScrapingBee HTML fetch tool when screenshot extraction is incomplete. Converts any fetched HTML to Markdown and returns it to the Gemini agent to complete the extraction. Splits the extracted product array into individual items and appends them as new rows in the Google Sheets “Results” sheet. Setup Create a Google Sheets service account connection in n8n and set the target spreadsheet and the “List of URLs” and “Results” sheet selections. Add a Google Gemini (PaLM) API credential in n8n and ensure the selected model (gemini-1.5-pro-latest) is available for your account. Add