Quick overview This scheduled workflow pulls last week’s Salesforce opportunities, tasks, and events for a specific rep, computes activity and pipeline health metrics, uses Groq (LLM) to generate coaching insights, creates a QuickChart performance chart URL, and emails a weekly behavioral report via Gmail. How it works Runs weekly on a schedule. Retrieves a target Salesforce user and queries that user’s opportunities with activity in the last week. Builds an Opportunity ID list, then pulls related Salesforce Tasks and Events and merges them into a single activity stream alongside the opportunities. Calculates per-opportunity engagement metrics (touches, calls, emails, follow-ups, meetings) and the days since last activity based on activity subjects and dates. Aggregates the opportunity metrics into per-rep totals including revenue, won/lost deals, and a stale-deal count based on activity gaps. Generates a QuickChart URL visualizing weekly activity versus outcomes and sends the rep metrics to Groq to produce structured coaching insights. Combines the chart and AI insights and sends an HTML weekly coaching email through Gmail.
Tags
Gmail
Groq Chat Model
Salesforce
Structured Output ParserRelated workflows
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Audit landing page CRO and log results with OpenAI and Data Tables
Quick overview This workflow collects a landing page URL, scrapes its HTML, and uses OpenAI to generate a structured conversion-rate-optimization (CRO) audit with scores and prioritized tips, then renders a styled report in the browser and logs each audit to an n8n Data Table. How it works Presents an n8n Form where the user submits a landing page URL. Fetches the landing page HTML via an HTTP request with retries, and routes to an error page if the URL can’t be retrieved. Sends the scraped HTML and URL to OpenAI to produce a CRO audit including an overall score, category scores, a written roast, and a ranked list of optimization tips. Uses a structured output parser with an OpenAI “fixer” model to validate and auto-correct the AI response into the required JSON schema. Builds a styled HTML report from the structured audit results. Logs the audit metadata (URL, score, verdict, summary, language, timestamp) to an n8n Data Table and displays the report back in the user’s browser. Setup Add an OpenAI API credential and select it for both the main OpenAI model and the output-fixer model. Create or select an n8n Data Table (for example, “CRO Audit Log”) and map the columns used for url,
Analyze YouTube comments with OpenAI, Google Sheets, and Gmail
Quick overview This workflow monitors a Google Sheets list of YouTube video IDs, fetches video details and top comments from the YouTube Data API, analyzes the comments with OpenAI into structured sentiment and themes, emails an HTML report via Gmail, and writes the results back to Google Sheets. How it works Triggers every minute when a row in Google Sheets is added or updated. Reads the video ID and status from the row and continues only if the status is set to “Pending”. Calls the YouTube Data API to fetch the video’s metadata and the top comment threads for that video. Flattens the comment threads, calculates basic stats (comment count and average likes), and compiles a limited comment text block for analysis. If comments exist, sends the compiled comments and video title to OpenAI to generate a structured analysis (sentiment score, sentiment breakdown, themes, questions, feedback, insights, and summary). Builds an HTML email report from the structured results, sends it to the configured recipient with Gmail, and updates the Google Sheet row with the analysis fields; if no comments exist, marks the row as “No comments”. Setup Create or duplicate a Google Sheet with at least “Vi
Detect early payment invoice opportunities with Groq and Google Sheets
Quick Overview This workflow runs daily to fetch invoice data from an HTTP endpoint, calculate early-payment savings and annualized ROI, and use Groq (Llama 3.3) to prioritize eligible discounts. It logs eligible and expired invoices to Google Sheets and emails a digest of HIGH-priority recommendations via Gmail. How it works Runs every day at 9:00 to start an invoice scan. Fetches invoice records from an external HTTP API endpoint. Calculates potential savings, days saved by paying early, annualized ROI, and whether each invoice is still eligible before the discount deadline. Routes eligible invoices to Groq (Llama 3.3) to return a JSON decision with a YES/NO recommendation, HIGH/MEDIUM/LOW priority, and a short reason, then normalizes the AI response. Appends eligible invoice evaluations (including ROI, savings, priority, recommendation, and reason) to a Google Sheets log. Filters for invoices marked YES and HIGH priority, aggregates them into a daily batch, and emails a plain-text digest to the finance team via Gmail. Marks ineligible invoices as expired with a skip reason and appends them to a separate Google Sheets audit log. Setup Add a Groq API credential and ensure the sele