Avkash Kakdiya
Workflows by Avkash Kakdiya
Track employee performance KPIs from ClickUp with GPT-4.1 and Google Sheets
## How it works This workflow runs on a schedule to collect task data from ClickUp and evaluate employee performance using AI. Tasks are analyzed to generate structured summaries, productivity metrics, and KPI scores. JavaScript logic refines and standardizes the results. The final performance data is stored in Google Sheets as a live KPI dashboard. ## Step-by-step - **Step 1: Collect ClickUp task data** - **Schedule Trigger** – Starts the workflow automatically at defined intervals. - **Get many folders** – Fetches all folders from the selected ClickUp space. - **Loop Over Items** – Iterates through folders to process tasks sequentially. - **Get many tasks** – Retrieves tasks associated with each folder or list. - **Step 2: Analyze tasks and compute KPIs** - **Message a model** – Sends task details to an AI model to generate summaries and raw performance metrics. - **Code in JavaScript** – Parses AI output, recalculates KPI scores, and assigns standardized ratings. - **Step 3: Update employee KPI dashboard** - **Append or update row in sheet** – Writes or updates task and employee performance data in Google Sheets. ## Why use this? - Automates employee performance tracking without manual reporting. - Produces consistent KPI scores across all ClickUp tasks. - Helps managers quickly identify overdue or high-priority work. - Keeps Google Sheets dashboards continuously up to date. - Improves visibility into productivity and task execution trends.
Monitor HubSpot deal risk with OpenAI scoring and Slack alerts
## How it works This workflow runs on a daily schedule to analyze all active HubSpot deals and their latest engagement activity. It applies AI-driven behavioral scoring to predict conversion probability and deal health. High-risk or stalled deals automatically trigger Slack alerts. All insights are logged in Google Sheets for forecasting and performance tracking. ## Step-by-step - **Step 1 – Trigger and collect active deals** - **Schedule Trigger** – Runs the workflow automatically at a fixed time each day. - **Get Active Deals from HubSpot** – Retrieves all non-closed deals with key properties like value, stage, and activity dates. - **Formatting Data** – Cleans and normalizes deal data while calculating metrics such as deal age and inactivity duration. - **Step 2 – Enrich deals with engagement data** - **If** – Filters only active deals to ensure closed deals are excluded. - **Loop Over Items** – Processes each deal individually to handle enrichment safely. - **HTTP Request** – Fetches engagement associations linked to each deal. - **Get an engagement** – Retrieves detailed engagement records from HubSpot. - **Extracts Data** – Structures engagement content, timestamps, and internal notes for AI analysis. - **Step 3 – Analyze risk and notify the team** - **AI Agent** – Analyzes behavioral signals and predicts conversion probability, risk level, and next actions. - **Format Data** – Parses the AI output into structured fields and risk indicators. - **Filter Alerts Needed** – Identifies deals that require immediate attention. - **Send Slack Alert** – Sends a detailed alert with risks, signals, and recommended actions. - **Append or update row in sheet** – Stores analysis results in Google Sheets for tracking and forecasting. ## Why use this? - Detect deal risk early using consistent, AI-based analysis - Reduce manual pipeline reviews for sales managers - Provide clear, actionable next steps to sales reps - Keep a historical log of deal health and forecasts - Improve close rates through timely, data-driven intervention
Detect and score refund risk with Webhook, OpenAI and Google Sheets
## How it works This workflow automatically evaluates refund and chargeback risk for incoming e-commerce orders. Orders are received via a webhook, processed individually, and checked to avoid duplicate analysis. Each transaction is normalized and sent to OpenAI for structured risk scoring and classification. Results are logged for auditing, alerts are triggered for high-risk cases, and processed orders are marked to prevent reprocessing. ## Step-by-step - **Step 1 – Ingest incoming orders** - **Webhook** – Receives single or bulk order payloads from external systems. - **Split Out** – Breaks array-based payloads into individual order records. - **Split In Batches** – Iterates through each order in a controlled loop. - **Step 2 – Deduplication check** - **IF (DEDUPE CHECK)** – Verifies whether an order was already processed and skips duplicates. - **Step 3 – Normalize transaction data** - **Code (Normalize Data)** – Validates required fields and standardizes order, customer, and behavioral attributes. - **Step 4 – AI risk assessment** - **OpenAI (Message a model)** – Sends normalized transaction data to the AI model and requests a strict JSON risk evaluation. - **Step 5 – Parse AI output** - **Code (Parse AI Output)** – Cleans the AI response and extracts risk score, risk level, key drivers, and recommendations. - **Step 6 – Log results** - **Google Sheets (Append)** – Stores timestamps, order details, and AI risk outcomes for reporting and audits. - **Step 7 – Risk decision and alerts** - **IF (High Risk)** – Filters only transactions classified as HIGH risk. - **Discord** – Sends real-time alerts to operations or finance teams. - **Gmail** – Emails finance stakeholders with full risk context. - **Step 8 – Mark order as processed** - **Google Sheets (Update)** – Updates the source row to prevent duplicate processing. ## Why use this? - Automatically detects high refund or chargeback risk before losses occur. - Eliminates manual review with consistent, AI-driven risk scoring. - Sends instant alerts so teams can act quickly on high-risk orders. - Maintains a clear audit trail for compliance and reporting. - Scales easily to handle single or bulk order evaluations.
Analyze contract risk from Google Drive with OpenAI and log to Gmail & Sheets
## How it works This workflow automates end-to-end contract analysis when a new file is uploaded to Google Drive. It downloads the contract, extracts its content, and uses AI to analyze legal terms, obligations, and risks. Based on the assessed risk level, it notifies stakeholders and logs structured results into Google Sheets for audit and compliance. ## Step-by-step - **Step 1: Contract ingestion and AI analysis** - **Google Drive Trigger** – Monitors a specific folder for newly uploaded contract files. - **Download file** – Downloads the uploaded contract from Google Drive. - **Extract Text From Downloaded File** – Extracts readable text or prepares raw content for complex files. - **AI Contract Analysis** – Analyzes legal, commercial, and financial clauses using AI. - **Format AI Output** – Parses and structures the AI response into clean, usable fields. - **Step 2: Risk alerts and audit logging** - **Alert Teams Automatically** – Evaluates risk level and checks for significant risks. - **Send a message (Risk Alert)** – Sends a detailed alert email for medium-risk contracts. - **Send a message (Info Only)** – Sends an informational email when no action is required. - **Get The Data To Save In Google Sheet (Alert Path)** – Prepares alert-related contract data. - **Get The Data To Save In Google Sheet (Info Path)** – Prepares non-alert contract data. - **Append row in sheet** – Stores contract details, risks, and timestamps in Google Sheets. ## Why use this? - Eliminates manual contract screening and repetitive reviews. - Detects explicit and inferred risks consistently using AI. - Automatically alerts teams only when attention is required. - Creates a centralized audit log for compliance and reporting. - Scales contract analysis without increasing legal workload.
Turn Gmail meeting summaries into HubSpot CRM records with OpenAI
## How it works This workflow listens for incoming meeting summary emails in Gmail and processes them automatically. The email content is cleaned and sent to an AI model that extracts CRM-ready sales data in a structured format. The parsed data is then used to create or update contacts, deals, and meeting engagements in HubSpot. This removes manual note-taking and ensures CRM data stays accurate and consistent after every call. ## Step-by-step - **Trigger on meeting summary email** - **Gmail Trigger** – Watches the inbox for new meeting summary emails from a specific sender. - **Prepare and normalize meeting notes** - **Prepare Meeting Summary** – Extracts the meeting text and stores it in a clean summary field for AI processing. - **Extract structured sales insights** - **AI Extraction** – Sends the meeting summary to an AI model to identify company details, problems, budget, decision makers, timing, competitors, and next steps. - **Parse AI response** - **Parse AI JSON Output** – Validates and converts the AI response into structured JSON fields usable by CRM nodes. - **Update HubSpot CRM** - **Create or Update Contact** – Creates a new contact or updates an existing one based on extracted details. - **Update Deal** – Updates the related deal with budget, description, stage, and pipeline information. - **Create Meeting Engagement** – Logs a meeting engagement in HubSpot with key discussion points and next actions. ## Why use this? - Eliminates manual CRM updates after sales or discovery calls. - Ensures meeting insights are captured consistently and accurately. - Reduces admin work for sales teams and improves data quality. - Works seamlessly with meeting recap tools that send summary emails. - Scales easily as meeting volume increases without extra effort.
Score HubSpot deal conversion risk with OpenAI and Slack alerts
## How it works This workflow runs daily to review all active deals and evaluate their likelihood of closing successfully. It enriches deal data with recent engagement activity and applies AI-based behavioral scoring to predict conversion probability. High-risk or stalled deals are flagged automatically. Actionable alerts are sent to the sales team, and all analysis is logged for forecasting and tracking. ## Step-by-step - **Trigger and fetch deals** - **Schedule Trigger** – Runs the workflow automatically at a fixed time each day. - **Get Active Deals from HubSpot** – Retrieves all open, non-closed deals with key properties. - **Formatting Data** – Normalizes deal fields such as value, stage, age, contacts, and activity dates. - **Enrich deals with engagement data** - **If** – Filters only active deals for further processing. - **Loop Over Items** – Processes each deal individually. - **HTTP Request** – Fetches engagement associations for the current deal. - **Get an engagement** – Retrieves detailed engagement records from HubSpot. - **Extracts Data** – Structures engagement content, timestamps, and metadata for analysis. - **Analyze risk, alert, and store results** - **OpenAI Chat Model** – Provides the language model used for analysis. - **AI Agent** – Evaluates behavioral signals, predicts conversion probability, and recommends actions. - **Format Data** – Parses AI output into structured, machine-readable fields. - **Filter Alerts Needed** – Identifies deals that need immediate attention. - **Send Slack Alert** – Sends detailed alerts for high-risk or stalled deals. - **Append or update row in sheet** – Logs analysis results into Google Sheets for reporting. ## Why use this? - Automatically identify high-risk deals before they stall or fail - Give sales teams clear, data-driven next actions instead of raw CRM data - Improve forecasting accuracy with AI-powered probability scoring - Maintain a historical deal health log for audits and performance reviews - Reduce manual pipeline reviews while increasing response speed
Analyze lost HubSpot deals and generate revival strategies with OpenAI
## How it works This workflow runs on a daily schedule to analyze all Closed–Lost deals from your CRM and uncover the true reason behind each loss. It uses AI to classify the primary loss category, generate a confidence-backed explanation, and then create a realistic re-engagement strategy for every deal. All insights are consolidated into leadership-ready email and Slack summaries. Every analyzed deal and revival plan is logged for long-term tracking and audits. ## Step-by-step - **Trigger and fetch lost deals** - **Schedule Trigger** – Runs the workflow automatically at a defined time. - **Get many deals** – Fetches all deal records from the CRM. - **If** – Filters only deals marked as Closed–Lost. - **Edit Fields** – Standardizes key deal attributes like amount, industry, owner, and loss reason. - **Analyze loss reasons and generate revival strategies** - **Brief Explanation Creator** – Uses AI to identify the primary loss category with confidence. - **Code in JavaScript** – Parses and normalizes AI loss analysis output. - **Merge** – Combines deal data with loss insights. - **Feedback Creator** – Generates a practical re-engagement strategy for each lost deal. - **Code in JavaScript7** – Parses and safeguards revival strategy outputs. - **Merge4** – Merges deal details, loss analysis, and revival strategy into one final dataset. - **Report, notify, and store results** - **Code in JavaScript11** – Builds a consolidated HTML summary email. - **Send a message4** – Sends the summary to stakeholders via email. - **Code in JavaScript12** – Creates a structured Slack summary. - **Send a message1** – Delivers insights to a Slack channel. - **Code in JavaScript10** – Reconstructs final data with delivery status. - **Append or update row in sheet** – Logs all results into Google Sheets for audit and tracking. ## Why use this? - Turns lost deals into actionable learning instead of static CRM records - Gives sales teams clear, realistic re-engagement plans without manual analysis - Provides leadership with concise, decision-ready summaries - Creates a historical database of loss reasons and revival outcomes - Improves pipeline recovery while enforcing consistent sales intelligence
Generate social content pillars, calendars and posts using Google Sheets and OpenAI
## How it works This workflow turns a single planning row in Google Sheets into a fully structured content engine. It generates weighted content pillars, builds a rule-based posting calendar, and then creates publish-ready social posts using AI. The workflow strictly controls format routing, CTA rules, and execution order. All outputs are written back to Google Sheets for easy review and execution. ## Step-by-step - **Step 1: Input capture & pillar generation** - **Google Sheets Trigger** – Detects new or updated planning rows. - **Get row(s) in sheet** – Fetches brand, platform, scheduling, and promotion inputs. - **Message a model** – Calculates calendar metrics and generates platform-specific content pillars. - **Code in JavaScript** – Validates AI output and enforces 100% weight distribution. - **Append row in sheet** – Stores finalized content pillars in the pillars sheet. - **Step 2: Calendar generation & routing** - **Message a model7** – Generates a full day-by-day content calendar from the pillars. - **Code in JavaScript7** – Normalizes calendar data into a sheet-compatible structure. - **Append row in sheet6** – Saves calendar entries with dates, formats, CTAs, and status. - **Switch By Format** – Routes items based on Video vs Non-Video formats. - **Step 3: Post creation & final storage** - **Loop Over Items** – Processes each calendar entry one at a time. - **Message a model6** – Creates complete hooks, captions, CTAs, and hashtags. - **Code in JavaScript6** – Formats AI output for final storage. - **Append row in sheet7** – Stores publish-ready posts in the final sheet. - **Wait** – Controls pacing to avoid API rate limits. ## Why use this? - Eliminates manual content planning and ideation. - Enforces strategic content mix and CTA discipline. - Produces platform-ready posts automatically. - Keeps all planning, calendars, and content in Google Sheets. - Scales content operations without extra overhead.
Review and approve employee expenses with forms, OpenAI and Google Workspace
## How it works This workflow automates employee expense reimbursements from submission to final resolution. Expenses are captured via a form, reviewed by an AI agent for justification, and routed to managers for approval or clarification. Approved expenses notify employees instantly, while rejected or unclear cases automatically schedule a follow-up discussion. All actions are logged to keep finance records clean and auditable. ## Step-by-step - **Step 1: Capture, summarize, and request approval** - **On Expense Form Submission** – Captures structured expense details submitted by employees. - **Append row in sheet** – Stores each expense entry in Google Sheets for tracking. - **AI Agent** – Reviews the expense description and validates whether the full amount is justified. - **OpenAI Chat Model** – Powers the AI reasoning used to analyze the expense. - **Output Parser** – Converts the AI response into a structured decision format. - **If** – Routes the flow based on whether the expense is appropriate or not. - **Step 2: Manager reviews and responds** - **Send Email to Manager for Approval** – Sends an approval email when the expense is justified. - **Send Email to Manager for Approval1** – Sends a clarification-required email when justification is unclear. - **If1** – Checks the manager’s approve or reject response from the email. - **Step 3: Notify employee or schedule discussion** - **Send a message** – Notifies the employee when the expense is approved. - **Booking Agent** – Automatically finds the next available business-day time slot if the expense is rejected. - **OpenAI** – Interprets availability rules and slot selection logic. - **Get Events** – Fetches existing calendar events for the selected day. - **Check Availability** – Identifies free time slots within working hours. - **Output Parser1** – Structures the selected meeting time. - **Send a message2** – Emails the employee with discussion details when clarification is required. ## Why use this? - Enforce consistent expense validation before manager review. - Reduce manual back-and-forth between employees, managers, and finance. - Keep a centralized, auditable record of all expense submissions. - Speed up reimbursements with automated approvals and notifications. - Handle rejected expenses professionally with automatic discussion scheduling.
Monitor customer risk and AI feedback using PostgreSQL, Gmail and Discord
## How it works This workflow monitors customer health by combining payment behavior, complaint signals, and AI-driven feedback analysis. It runs on daily and weekly schedules to evaluate risk levels, escalate high-risk customers, and generate structured product insights. High-risk cases are notified instantly, while detailed feedback and audit logs are stored for long-term analysis. ## Step-by-step - **Step 1: Triggers & mode selection** - **Daily Risk Check Trigger** – Starts the workflow on a daily schedule. - **Weekly schedule1** – Triggers the workflow for weekly summary runs. - **Edit Fields3** – Sets flags for daily execution. - **Edit Fields2** – Sets flags for weekly execution. - **Switch1** – Routes execution based on daily or weekly mode. - **Step 2: Risk evaluation & escalation** - **Fetch Customer Risk Data** – Pulls customer, payment, product, and complaint data from PostgreSQL. - **Is High Risk Customer?** – Evaluates payment status and complaint count. - **Prepare Escalation Summary For Low Risk User** – Assigns low-risk status and no-action details. - **Prepare Escalation Summary For High Risk User** – Assigns high-risk status and escalation actions. - **Merge Risk Result** – Combines low-risk and high-risk customer records. - **Send a message4** – Sends the customer risk summary via Gmail. - **Send a message5** – Sends the same risk summary to Discord. - **Code in JavaScript3** – Appends notification status and timestamps. - **Append or update row in sheet3** – Logs risk evaluations and notification status in Google Sheets. - **Step 3: AI feedback & reporting** - **Get row(s) in sheet1** – Fetches customer records for feedback analysis. - **Loop Over Items1** – Processes customers one by one. - **Prompt For Model1** – Builds a structured prompt for product feedback analysis. - **HTTP Request1** – Sends data to the AI model for insight generation. - **Code in JavaScript** – Merges AI feedback with original customer data. - **Append or update row in sheet** – Stores AI-generated feedback in Google Sheets. - **Wait1** – Controls execution pacing between records. - **Merge1** – Prepares consolidated feedback data. - **Send a message1** – Emails the final AI-powered feedback report. ## Why use this? - Detect customer churn risk early using payment and complaint signals - Automatically escalate high-risk customers without manual monitoring - Convert raw customer issues into executive-ready product insights - Keep a complete audit trail of risk, feedback, and notifications - Align support, product, and leadership teams with shared visibility
Automate unified marketing reports with Google Analytics, Google Ads, Meta Ads & HubSpot
## How it works This workflow runs on scheduled weekly and monthly triggers to generate unified marketing performance reports. It processes multiple websites by collecting analytics data, paid ads performance, and CRM leads, then calculates KPIs and insights automatically. The workflow sends structured reports via email and stores historical data in Google Sheets. It ensures consistent reporting without manual effort. ## Step-by-step - **Step 1: Trigger & report type detection** - **Schedule Trigger2** – Triggers the workflow weekly at a predefined time. - **Schedule Trigger3** – Triggers the workflow monthly at a predefined time. - **check month and week1** – Identifies whether the run is weekly or monthly and sets flags. - **Set Websites and Campaings1** – Defines websites, GA4 property IDs, and mapped ad campaigns. - **Expand Websites1** – Expands the website array into individual website items. - **Attach Run Flags1** – Attaches weekly or monthly flags to each website record. - **Step 2: Website & ads data processing** - **Loop Websites1** – Iterates through each website independently. - **Get a report** – Fetches website traffic and engagement metrics from analytics. - **Get many campaigns** – Retrieves Google Ads campaign data. - **Fetch Meta Ads** – Fetches Meta Ads performance data via API. - **Filter Google Ads By Website1** – Filters Google Ads campaigns by website. - **Filter Meta Ads By Website1** – Filters Meta Ads campaigns by website. - **Merge1** – Merges analytics, Google Ads, and Meta Ads datasets. - **Build Website Dataset1** – Builds a unified dataset per website. - **Calculate KPIs & Campaign Insights1** – Calculates spend, CTR, CPA, CPL, conversions, and performance insights. - **Append or update row in sheet2** – Stores website-level marketing metrics in Google Sheets. - **Step 2.1: Marketing report generation** - **Prepare Report Data2** – Combines all website datasets into a unified report object. - **Switch** – Routes execution based on weekly or monthly report type. - **Send Weekly Marketing report2** – Sends the weekly marketing performance email. - **Send Monthly Marketing Report2** – Sends the monthly marketing performance email. - **Step 3: HubSpot lead analysis** - **Fetch1** – Fetches leads from HubSpot CRM. - **Filter Hubspot Leads** – Filters leads based on weekly or monthly time range. - **Summarize Hubspot Leads** – Aggregates lead status and lifecycle metrics. - **Prepare Report Data3** – Prepares CRM summary data for reporting. - **Step 3.1: CRM reporting & storage** - **Switch3** – Routes CRM reporting by report type. - **Send Weekly Marketing report3** – Sends the weekly CRM summary email. - **Send Monthly Marketing Report3** – Sends the monthly CRM summary email. - **Code in JavaScript1** – Transforms CRM data for storage. - **Append or update row in sheet3** – Stores CRM lead performance data in Google Sheets. - **Switch3** – Routes CRM reporting by report type. - **Send Weekly Marketing report3** – Sends the weekly CRM summary email. - **Send Monthly Marketing Report3** – Sends the monthly CRM summary email. - **Code in JavaScript1** – Transforms CRM data for storage. - **Append or update row in sheet3** – Stores CRM lead performance data in Google Sheets. ## Why use this? - Automates complex weekly and monthly marketing reporting. - Unifies website analytics, ad platforms, and CRM data in one flow. - Delivers consistent KPI calculations and insights every run. - Maintains historical performance logs in Google Sheets. - Scales easily across multiple websites and campaigns.
Real-time lead response across social channels with Llama AI & Google Sheets
## How it works This workflow acts as an instant SDR that replies to new inbound leads across multiple channels in real time. It first captures and normalizes all incoming lead data into a unified structure. The workflow then evaluates IST working days and hours, generates a context-aware AI response, and routes the reply to the correct channel. Finally, it logs the full interaction, response status, and timing into Google Sheets. ## Step-by-step - **Step 1: Lead intake & normalization** - **Incomming Lead whatsapp1** – Receives new WhatsApp lead messages via webhook. - **Incomming Lead facebook1** – Captures incoming Facebook lead messages. - **Incomming Lead instagram1** – Listens for Instagram lead messages. - **Incomming Lead linkdin1** – Captures LinkedIn lead messages. - **Incomming Lead Website1** – Receives website form submissions. - **Normalize Lead Data6** – Normalizes WhatsApp lead fields. - **Normalize Lead Data7** – Normalizes Facebook lead fields. - **Normalize Lead Data8** – Normalizes Instagram lead fields. - **Normalize Lead Data9** – Normalizes LinkedIn lead fields. - **Normalize Lead Data5** – Normalizes website lead data. - **Switch2** – Merges all normalized leads into a single processing path. - **Step 2: Working hours & AI response** - **Extract Day and Hours1** – Converts timestamps to IST and extracts day and time. - **Is Working Day and Working Hour?1** – Determines whether the lead arrived during business hours. - **Code in JavaScript3** – Builds the AI prompt using lead details and timing context. - **Get Ai Response1** – Generates a short, human-like response. - **Step 3: Send reply & log data** - **Code in JavaScript4** – Combines AI output with normalized lead data. - **Switch3** – Routes the response based on the source channel. - **Send message** – Sends WhatsApp replies. - **Send Instagram Message1** – Sends Instagram responses. - **Send Facebook Messages1** – Sends Facebook replies. - **Send Linkdin Messages1** – Sends LinkedIn responses. - **Send a message1** – Sends email replies for website leads. - **Code in JavaScript5** – Finalizes response status and metadata. - **google-sheet-name** – Appends or updates lead and response data in Google Sheets. ## Why use this? - Replies instantly to leads across all major inbound channels - Keeps all lead data standardized and easy to manage - Automatically respects IST working days and hours - Reduces manual SDR workload without losing response quality - Maintains a complete response log for reporting and follow-up
Monitor ad performance drops with Meta & Google Ads + multi-channel alerts
## How it works This workflow monitors Meta Ads and Google Ads campaigns on a daily schedule to detect performance drops. It fetches yesterday’s campaign data, standardizes metrics, and calculates CTR and ROAS against fixed benchmarks. Campaigns that fall below thresholds are flagged automatically. Alerts are then sent across multiple channels and all results are logged in Google Sheets for tracking. ## Step-by-step - **Step 1: Fetch ad performance data** - **Schedule Trigger (Daily Ad Check2)** – Runs the Meta Ads performance check at the scheduled time. - **HTTP Request (Fetch Meta Ads Data)** – Retrieves campaign metrics from the Meta Ads API. - **Set (Set Benchmarks)** – Normalizes Meta Ads data and assigns platform details. - **Schedule Trigger (Daily Ad Check3)** – Runs the Google Ads performance check at a separate scheduled time. - **Google Ads (Get many campaigns)** – Fetches campaign performance data from Google Ads. - **Set (Set Benchmarks4)** – Normalizes Google Ads data and assigns platform details. - **Step 2: Detect performance drops** - **Code (Detect Performance Drop)** – Calculates CTR and ROAS, compares them with predefined benchmarks, and flags drops. - **If** – Filters only campaigns where a performance drop is detected. - **Split In Batches (Loop Over Items)** – Processes each affected campaign individually. - **Step 3: Alert and log results** - **WhatsApp (Send message1)** – Sends instant WhatsApp alerts for critical visibility. - **Slack (Send a message)** – Posts detailed alerts to a Slack channel. - **Gmail (Send a message4)** – Sends email notifications with full campaign metrics. - **Code (Code in JavaScript)** – Recombines campaign data after notifications. - **Wait (Wait1)** – Ensures alert delivery before logging. - **Google Sheets (your-google-sheets-name)** – Appends or updates campaign records for reporting and audit history. ## Why use this? - Catch CTR and ROAS drops before ad spend is wasted. - Monitor Meta Ads and Google Ads in a single automated flow. - Notify teams instantly via WhatsApp, Slack, and Email. - Keep a centralized performance log for analysis and reporting. - Reduce manual checks with consistent daily monitoring.
Automate employee leave approvals with GPT, Gmail & Calendar integration
## How it works This workflow automates the complete employee leave approval process from submission to final resolution. Employees submit leave requests through a form, which are summarized professionally using AI and sent for approval via email. The workflow waits for the approver’s response and then either sends an approval confirmation or schedules a clarification discussion automatically. All communication is handled consistently with no manual follow-ups required. ## Step-by-step - **Step 1: Capture leave request, generate summary, and request approval** - **On form submission** – Captures employee details, leave dates, reason, and task handover information. - **AI Agent** – Generates a professional, manager-ready summary of the leave request. - **OpenAI Chat Model** – Provides the language model used to generate the summary. - **Structured Output Parser** – Extracts the email subject and HTML body from the AI response. - **Send message and wait for response** – Emails the summary to the approver and pauses the workflow until approval or rejection. - **If** – Routes the workflow based on the approval decision. - **Step 2: Notify employee or schedule discussion automatically** - **Approved path** - **Send a message** – Sends an official leave approval email to the employee. - **Clarification or rejection path** - **Booking Agent** – Determines the next business day and finds the first available 10-minute slot. - **OpenAI** – Applies scheduling logic to select the earliest valid slot. - **Get Events** – Fetches existing calendar events to avoid conflicts. - **Check Availability** – Confirms free time within working hours. - **Output Parser** – Extracts the final meeting start time. - **Send a message1** – Emails the employee with the scheduled discussion details. ## Why use this? - Eliminate manual approval follow-ups and email back-and-forth - Ensure consistent, professional communication for every leave request - Automatically handle both approvals and clarification scenarios - Reduce manager effort with AI-generated summaries - Schedule discussions without manual calendar coordination
Recover abandoned onboarding users with personalized emails via Postgres, Gmail & Slack
## How it works This workflow automatically identifies users who started but did not complete the signup process. It runs on a fixed schedule, checks your database for inactive and incomplete users, and validates the results before proceeding. Each user is then processed individually to send a personalized recovery email and enroll them in a follow-up sequence. Finally, the workflow updates the database to avoid duplicate outreach and notifies the sales team in Slack. ## Step-by-step - **Step 1: Run scheduled check and identify abandoned users** - **Schedule Trigger** – Executes the workflow automatically every 24 hours. - **Find Abandoned Users** – Queries Postgres for users marked as incomplete and inactive for over 24 hours. - **If** – Confirms that valid user records exist before continuing. - **Step 2: Process users and send recovery emails** - **Loop Over Items** – Processes users one at a time to avoid rate limits and execution errors. - **PrepareEmail email** – Generates a personalized recovery email using a predefined template. - **Send a message** – Sends the recovery email through Gmail. - **Get a message** – Retrieves the sent email details for tracking and thread reference. - **StartSequence email** – Adds the email to a follow-up sequence for engagement tracking. - **Step 3: Update records and notify the team** - **Update rows in a table** – Marks the user as contacted to prevent duplicate recovery emails. - **Alert Sales Team** – Sends a Slack notification with user details and recovery status. ## Why use this? - Recover users who abandon onboarding without manual follow-ups - Ensure each user receives only one recovery email - Keep your Postgres user data accurate and up to date - Provide sales teams with real-time visibility via Slack alerts - Improve signup completion and activation rates automatically
Automate event registration and reminder emails with Forms, Sheets & Gmail
## How it works This workflow automates event registrations and attendee communication from initial signup to event day. It captures form submissions, prevents duplicate entries, and stores registrations in Google Sheets. Confirmed attendees receive immediate confirmation emails, while failures trigger admin alerts. A scheduled process then sends pre-event and event-day reminders, with all communication tracked to ensure emails are sent only once. ## Step-by-step - **Step 1: Capture and process registration** - **Event Registration Form** – Collects attendee details through a public registration form. - **Edit Fields** – Normalizes and prepares form data for processing. - **Read Existing Registrations** – Fetches existing attendee records from Google Sheets. - **Check for Duplicate Email** – Compares the submitted email against stored records. - **If Not Duplicate** – Stops the workflow when a duplicate email is detected and continues only for new registrations. - **Store Registration (Google Sheets)** – Appends the new registration only when no duplicate is found. - **Step 2: Confirm registration and send notifications** - **Add Status & Event Date** – Assigns confirmed status and event date to the registration. - **Check Registration Success** – Verifies whether the registration is confirmed. - **Send Welcome Email** – Sends a confirmation email to the attendee. - **Send Admin Alert** – Sends an alert email to the admin if registration fails. - **Code in JavaScript** – Confirms email delivery and prepares tracking data. - **Update Welcome Email Status** – Updates the welcome email status in Google Sheets. - **Step 3: Scheduled trigger and reminder routing** - **Schedule Trigger** – Runs daily to initiate reminder processing. - **Edit Fields** – Marks the execution source as a scheduled run. - **Switch** – Ensures the workflow runs only for scheduled executions. - **Get Confirmed Aptitude Candidates** – Retrieves confirmed event registrations from Google Sheets. - **Filter Reminder Candidates** – Calculates remaining days until the event. - **Switch Reminder Type** – Routes attendees to 3-day or event-day reminder flows. - **Step 4: Send reminders and update event communication status** - **Loop 3-Day** – Iterates through attendees eligible for the 3-day reminder. - **Send 3-Day Reminder** – Sends a personalized pre-event reminder email. - **Prepare 3-Day Update** – Prepares reminder status data. - **Wait** – Adds delay to control email sending rate. - **Update 3-Day Status** – Updates the 3-day reminder status in Google Sheets. - **Loop Event-Day** – Iterates through attendees eligible for the event-day reminder. - **Send Event-Day Reminder** – Sends final event-day instructions and check-in details. - **Prepare Event-Day Update** – Prepares event-day reminder tracking data. - **Wait** – Adds delay between event-day emails. - **Update Event-Day Status** – Updates the event-day reminder status in Google Sheets. ## Why use this? - Blocks duplicate registrations automatically at submission time. - Sends instant confirmation emails to attendees. - Alerts admins immediately when a registration fails. - Delivers perfectly timed reminders without manual follow-ups. - Keeps a complete communication log inside Google Sheets.
Bulk WhatsApp & Gmail messenger with Google Sheets status tracking via InboxPlus
## How it works This workflow sends WhatsApp messages and emails in bulk using contact data stored in Google Sheets. Contacts are processed in small batches to control throughput and avoid API rate limits. WhatsApp and email are treated as independent channels and are sent only when their status is marked as pending. All success and failure results are written back to Google Sheets to enable tracking, retries, and safe re-runs. ## Step-by-step - **Step 1: Fetch contacts & batch processing** - **Manual Trigger** – Starts the workflow manually. - **Get Contacts** – Reads contact data from Google Sheets. - **Split In Batches** – Processes contacts in controlled batch sizes. - **Step 2: Email preparation & sending** - **Has Email Address** – Checks whether the contact has an email address. - **IF Mail Pending** – Ensures the email is still marked as pending. - **PrepareEmail email** – Loads the selected InboxPlus email template. - **Build HTML Email** – Builds the final HTML email body. - **Fetch Email Image** – Downloads images for inline or attachment usage. - **Send Gmail** – Sends the email via Gmail. - **Delivered** – Confirms successful email delivery. - **Step 3: WhatsApp message sending** - **Has Phone Number** – Checks whether the contact has a phone number. - **IF WhatsApp Pending** – Ensures the WhatsApp message is still pending. - **Send template** – Sends the approved WhatsApp template message. - **Sent** – Confirms message acceptance by WhatsApp. - **Step 4: Delivery status updates** - **Update Sheet** – Writes successful delivery results back to Google Sheets. - **Mail Failure** – Updates Google Sheets if email delivery fails. - **Whatsapp Failure** – Updates Google Sheets if WhatsApp delivery fails. ## Why use this? - Prevents duplicate messages with channel-level pending checks - Handles WhatsApp and email independently in one workflow - Supports safe retries without resending completed messages - Keeps Google Sheets as the single source of truth - Scales bulk outreach safely using batch-based execution
Automated resume screening & interview scheduling with Gmail, GPT & Airtable
## How it works The workflow detects incoming job-application emails, extracts resumes, and parses them for AI analysis. It evaluates each candidate against three open roles and assigns a fit score with structured reasoning. Low-scoring applicants are stored for review, while strong candidates move into an automated scheduling flow. The system checks availability on the next business day, books the slot, sends a confirmation email, and records all details in Airtable. --- ## Step-by-step ### Detect and collect job-application data - **Gmail Trigger1** – Monitors inbox for all new emails. - **Message a model2** – Classifies whether the email is a job application. - **If2** – Continues only when the AI result is YES. - **Get a message1** – Fetches the full message and attachments. - **Upload file1** – Uploads the resume to Google Drive. - **Extract from File1** – Converts the PDF resume into text. ### Analyze the resume and evaluate fit - **Available Positions1** – Defines the three open roles. - **Message a model3** – Produces recommended role, fit score, strengths, gaps, skills, and reasoning. - **If3** – Routes candidates based on `fit_score ≥ 8`. - **Create a record3** – Stores lower-scoring applicants in Airtable. - **Get Next Business Day1** – Calculates the schedule window for qualified candidates. ### Check availability on the next business day - **AI Agent1** – Orchestrates availability search using calendar nodes. - **Get Events1** – Retrieves events for the target day. - **Check Availability1** – Evaluates free 1-hour slots. - **OpenAI Chat Model2** – Reasoning engine for the agent. - **Structured Output Parser1** – Returns clean JSON with `start_time` and `end_time`. - **OpenAI Chat Model3** – Supports structured parsing. ### Schedule the interview and notify the candidate - **Create an event1** – Books the interview in Google Calendar. - **Send a message1** – Sends an HTML confirmation email to the candidate. - **Create a record2** – Saves shortlisted candidate and interview data in Airtable. --- ## Why use this? - Removes manual screening by automating email intake and resume parsing. - Ensures consistent AI-based role matching and scoring. - Books interviews automatically using real calendar availability. - Keeps all applicant and scheduling data organized in Airtable. - Provides a fully hands-off, end-to-end hiring pipeline.
AI-powered webinar feedback replies with GPT-4, Google Sheets, and Gmail
## How it works This workflow captures webinar feedback through a webhook and normalizes the submitted data for processing. It stores raw feedback in Google Sheets, uses an AI model to understand sentiment and intent, and generates a personalized response. A professional HTML thank-you email is sent automatically to each attendee. All replies and delivery details are logged back into the spreadsheet for tracking. ## Step-by-step - **Receive webinar feedback** - **Feedback Webhook** – Accepts feedback submissions from a webinar form in real time. - **ID Generation** – Creates a human-readable, unique feedback ID for tracking. - **Normalize Feedback** – Cleans and standardizes incoming fields like name, email, rating, and comments. - **Store and enrich feedback** - **Store Partial** – Saves the raw feedback data into Google Sheets. - **Common Resources** – Attaches shared webinar resources such as recordings and slides. - **Analyze feedback with AI** - **Message a model** – Evaluates sentiment, engagement level, and intent using an AI model. - **Parse AI Response** – Extracts structured insights like segment, reply text, and next steps. - **Generate and send follow-up** - **Merge** – Combines feedback data, AI response, and resources. - **Build Email HTML** – Creates a clean, professional HTML email tailored to each attendee. - **Send AI Thank You Email** – Sends the personalized follow-up via Gmail. - **Log final outcome** - **Store Feedback** – Updates Google Sheets with the sent email content, timestamp, and status. ## Why use this? - Save time by automating webinar feedback follow-ups end to end. - Ensure every attendee receives a thoughtful, personalized response. - Maintain a complete feedback and communication log in one place. - Improve engagement without sounding promotional or generic. - Scale post-webinar communication without manual effort.
Automate outbound lead follow-up & qualification
## How it works This workflow pulls pending leads from Google Sheets on a scheduled trigger and processes each record individually. For every lead, an AI agent generates a structured subject and HTML body based on predefined rules. A tracking ID is then created and injected into the outgoing email before sending via Gmail. Once sent, Gmail metadata is retrieved and forwarded to your tracking API to initiate a follow-up sequence, and the corresponding lead entry in Google Sheets is updated. ## Step-by-step - **Lead intake** - **Schedule Trigger** – Runs daily and initiates lead retrieval. - **Get row(s) in sheet** – Fetches only rows marked with “Pending”. - **Loop Over Items** – Iterates through each lead entry. - **Email generation** - **AI Agent** – Generates subject and HTML body using provided lead fields. - **OpenAI Chat Model** – Executes the LLM instructions powering the email creation. - **Structured Output Parser** – Validates that the AI returns compliant JSON. - **Tracking setup** - **Generates Tracking ID** – Calls your tracking API and receives a unique tracking identifier. - The tracking ID is embedded into the email through a tracking pixel. - **Email dispatch** - **Send a message** – Sends the personalized email from Gmail using the AI-generated subject and body. - **Metadata retrieval** - **Fetches Email Data** – Retrieves the sent email’s messageId, threadId, and related metadata. - **Sequence initiation** - **Starts Sequence** – Posts metadata and tracking ID to your tracking API to activate the automated follow-up sequence. - **Lead status update** - **Append or update row in sheet** – Marks the processed lead as “Done” and updates Google Sheets. ## Why use this? - Automates outbound lead processing without manual input or oversight. - Delivers consistent, structured, AI-generated email outreach. - Ensures every email is tracked with unique identifiers for engagement analytics. - Pushes metadata to your tracking system for reliable follow-up sequences. - Updates your Google Sheets lead pipeline automatically to prevent duplicate outreach.
Recover Abandoned Shopify Carts with Email Follow-ups, HubSpot CRM & Google Sheets Tracking
## How it works The workflow triggers on a new checkout event from Shopify and extracts all relevant cart data. It filters carts based on value and age to isolate qualified abandoned checkouts. For each qualified cart, it sends a follow-up email, updates or creates the corresponding HubSpot contact, and generates a CRM note linked to that contact. Finally, it logs the processed cart into Google Sheets for tracking and review. ## Step-by-step - **Trigger on new Shopify checkout** - **Shopify Trigger** – Starts the workflow when a new checkout is created. - **Normalize and structure cart data** - **Parse Cart Data** – Extracts email, customer name, items, cart totals, timestamps, and hours since creation. - **Filter carts that meet follow-up criteria** - **Filter Qualified Carts** – Passes only carts older than 12 hours and valued above 50. - **Send follow-up message** - **Send a message** – Delivers a reminder email to the customer about the pending checkout. - **Create or update CRM contact** - **Create or update a contact** – Ensures the shopper exists as a HubSpot contact. - **Prepare CRM note details** - **Generates Note Data** – Builds a structured note containing timing, cart details, and follow-up context. - **Create the HubSpot note** - **Create HubSpot Note** – Submits the prepared note to HubSpot’s CRM. - **Associate note with the contact** - **Associate Note with Contact in HubSpot** – Links the generated note to the correct HubSpot contact. - **Record activity in tracker sheet** - **Log to Google Sheets** – Appends processed cart fields including items, totals, timestamps, and customer info. ## Why use this? - Identifies high-value or long-abandoned carts automatically and follows up without manual effort. - Keeps CRM records updated and adds contextual notes sales teams can act on. - Maintains a structured audit trail of every abandoned cart interaction. - Improves recovery chances by combining email outreach with CRM enrichment and logging. - Enables analysis of abandoned checkout patterns directly from Google Sheets.
Automate Shopify Product Posting to Social Media with GPT-4.1-Mini & Data Tracking
## How it works This workflow listens for new products in Shopify and transforms the product data into polished social media content. It generates captions and hashtags using an AI model, then posts the product to Instagram and Facebook using the Facebook Graph API. It logs every post to Google Sheets and sends a confirmation message to Discord. The flow ensures consistent publishing across all platforms with automated formatting and tracking. ## Step-by-step - **Trigger on Shopify product creation** - **Shopify Trigger** – Activates when a new product is added to the store. - **Prepare product data** - **parse product data** – Extracts product name, price, description, URL, image, and timestamp. - **Generate caption and hashtags** - **Generate caption and hashtags** – Uses an AI model to craft a caption and produce 10 relevant hashtags. - **Configure posting parameters** - **Set Configuration** – Stores access tokens, platform IDs, caption text, hashtags, and image URL. - **Publish to Instagram** - **Create Instagram Media Container** – Sends the image and caption to create a media container. - **Wait for Processing** – Waits for the container to finish processing. - **Publish Instagram Media** – Publishes the processed container to the Instagram feed. - **Publish to Facebook** - **Download Image for Facebook** – Downloads the product image from Shopify. - **Post to Facebook Page** – Uploads the image with the caption and hashtags to the Facebook Page. - **Merge publishing results** - **Merge** – Combines responses from Instagram and Facebook for unified logging. - **Log post to Google Sheets** - **Log Product Post Data** – Appends product info, caption, and hashtags to a spreadsheet. - **Notify via Discord** - **Notify Discord About Post** – Sends a message summarizing the published product. ## Why use this? - Ensures every new Shopify product is promoted instantly across major social platforms. - Eliminates manual posting and caption creation with reliable automation. - Maintains centralized logging for auditing, tracking, or analytics. - Provides real-time team notifications to confirm successful posts. - Reduces errors and keeps brand messaging consistent across channels.
Automate blog publishing from PostgreSQL to WordPress with OpenAI GPT
## How it works This workflow automatically generates and publishes marketing blog posts to WordPress using AI. It begins by checking your PostgreSQL database for unprocessed records, then uses OpenAI to create SEO-friendly, structured blog content. The content is formatted for WordPress, including categories, tags, and meta descriptions, before being published. After publishing, the workflow updates the original database record to track processing status and WordPress post details. ## Step-by-step - **Trigger workflow** - **Schedule Trigger** – Runs the workflow at defined intervals. - **Fetch unprocessed record** - **PostgreSQL Trigger** – Retrieves the latest unprocessed record from the database. - **Check Record Exists** – Confirms the record is valid and ready for processing. - **Generate AI blog content** - **OpenAI Chat Model** – Processes the record to generate blog content based on the title. - **Blog Post Agent** – Structures AI output into JSON with title, content, excerpt, and meta description. - **Format and safeguard content** - **Code Node** – Prepares structured data for WordPress, ensuring categories, tags, and error handling. - **Publish content and update database** - **WordPress Publisher** – Publishes content to WordPress with proper categories, tags, and meta. - **Update Database** – Marks the record as processed and stores WordPress post ID, URL, and processing timestamp. ## Why use this? - Automates end-to-end blog content generation and publishing. - Ensures SEO-friendly and marketing-optimized posts. - Maintains database integrity by tracking published content. - Reduces manual effort and accelerates content workflow. - Integrates PostgreSQL, OpenAI, and WordPress seamlessly for scalable marketing automation.
Automatically close cold HubSpot deals with Gmail feedback & Slack notifications
## How it works This workflow identifies HubSpot deals that have gone untouched for 21+ days and automatically updates their status to Closed Lost. It fetches associated contacts, retrieves their details, and sends personalized follow-up emails requesting feedback. Finally, it notifies your team via Slack about the deals moved to Closed Lost. The workflow runs on a scheduled interval, ensuring consistent lead management without manual intervention. ## Step-by-step **1. Trigger the workflow** - **Schedule Trigger** – Runs the workflow at a defined interval (daily, weekly, etc.). - **Get HubSpot Deals** – Retrieves all deals with key properties from HubSpot. - **Extract Deal Fields** – Normalizes deal data for consistent processing. **2. Identify and update cold deals** - **Filter Cold Leads (21+ days)** – Keeps only deals not updated in the past 21 days. - **Update Deal to Closed Lost** – Marks stale deals as Closed Lost in HubSpot. **3. Map deals to contacts** - **Fetch Deal Associations** – Retrieves contacts linked to filtered deals. - **Extract Contact IDs** – Parses associations to get contactId, dealId, and dealName. - **Get Contact Details** – Fetches enriched contact information. - **Extract Contact Email** – Simplifies data, keeping only the email field. **4. Follow-up & team notification** - **Send Gmail Feedback Request** – Sends a personalized thank-you email requesting feedback. - **Send Slack Notification** – Alerts the team about deals updated to Closed Lost. ## Why use this? - Ensures timely closure of stale HubSpot deals, keeping your pipeline clean. - Automates follow-up emails to gather valuable feedback from disengaged leads. - Reduces manual effort in deal management and contact outreach. - Keeps your team informed in real-time with Slack notifications. - Improves sales process efficiency and lead data hygiene.