This “Call Transcripts from Vapi into Google Sheets Beginner Friendly Guide” shows you how to grab call transcripts from Vapi and send them into Google Sheets or Airtable without technical headaches. You’ll meet a handy assistant called “Transcript Dude” that streamlines the process and makes automation approachable.
You’ll be guided through setting up Vapi and Make.com, linking Google Sheets, and activating a webhook so transcripts flow automatically into your sheet. The video by Henryk Brzozowski breaks the process into clear steps with timestamps and practical tips so you can get everything running quickly.
Overview and Goals
This guide walks you step-by-step through a practical automation: taking call transcripts from Vapi and storing them into Google Sheets. You’ll see how the whole flow fits together, from enabling transcription in Vapi, to receiving webhook payloads in Make.com, to mapping and writing clean, structured rows into Sheets. The walkthrough is end-to-end and focused on practical setup and testing.
What this guide will teach you: end-to-end flow from Vapi to Google Sheets
You’ll learn how to connect Vapi’s transcription output to Google Sheets using Make.com as the automation glue. The guide covers configuring Vapi to record and transcribe calls, creating a webhook in Make.com to receive the transcript payload, parsing and transforming the JSON data, and writing formatted rows into a spreadsheet. You’ll finish with a working, testable pipeline.
Who this guide is for: beginners with basic web and spreadsheet knowledge
This guide is intended for beginners who are comfortable with web tools and spreadsheets — you should know how to sign into online services, copy/paste API keys, and create a basic Google Sheet. You don’t need to be a developer; the steps use no-code tools and explain concepts like webhooks and mapping in plain language so you can follow along.
Expected outcomes: automated transcript capture, structured rows in Sheets
By following this guide, you’ll have an automated process that captures transcripts from Vapi and writes structured rows into Google Sheets. Each row can include metadata like call ID, date/time, caller info, duration, and the transcript text. That enables searchable logs, simple analytics, and downstream automation like notifications or QA review.
Typical use cases: call logs, QA, customer support analytics, meeting notes
Common uses include storing customer support call transcripts for quality reviews, compiling meeting notes for teams, logging call metadata for analytics, creating searchable call logs for compliance, or feeding transcripts into downstream tools for sentiment analysis or summarization.
Prerequisites and Accounts
This section lists the accounts and tools you’ll need and the basic setup items to have on hand before starting. Gather these items first so you can move through the steps without interruption.
Google account and access to Google Sheets
You’ll need a Google account with access to Google Sheets. Create a new spreadsheet for transcripts, or choose an existing one where you have editor access. If you plan to use connectors or a service account, ensure that account has editor permissions for the target spreadsheet.
Vapi account with transcription enabled
Make sure you have a Vapi account and that call recording and transcription features are enabled for your project. Confirm you can start calls or recordings and that transcriptions are produced — you’ll be sending webhooks from Vapi, so verify your project settings support callbacks.
Make.com (formerly Integromat) account for automation
Sign up for Make.com and familiarize yourself with scenarios, modules, and webhooks. You’ll build a scenario that starts with a webhook module to capture Vapi’s payload, then add modules to parse, transform, and write to Google Sheets. A free tier is often enough for small tests.
Optional: Airtable account if you prefer a database alternative
If you prefer structured databases to spreadsheets, you can swap Google Sheets for Airtable. Create an Airtable base and table matching the fields you want to capture. The steps in Make.com are similar — choose Airtable modules instead of Google Sheets modules when mapping fields.
Basic tools: modern web browser, text editor, ability to copy/paste API keys
You’ll need a modern browser, a text editor for viewing JSON payloads or keeping notes, and the ability to copy/paste API keys, webhook URLs, and spreadsheet IDs. Having a sample JSON payload or test call ready will speed up debugging.
Tools, Concepts and Terminology
Before you start connecting systems, it helps to understand the key tools and terms you’ll encounter. This keeps you from getting lost when you see webhooks, modules, or speaker segments.
Vapi: what it provides (call recording, transcription, webhooks)
Vapi provides call recording and automatic transcription services. It can record audio, generate transcript text, attach metadata like caller IDs and timestamps, and send that data to configured webhook endpoints when a call completes or when segments are available.
Make.com: scenarios, modules, webhooks, mapping and transformations
Make.com orchestrates automation flows called scenarios. Each scenario is composed of modules that perform actions (receive a webhook, parse JSON, write to Sheets, call an API). Webhook modules receive incoming requests, mapping lets you place data into fields, and transformation tools let you clean or manipulate values before writing them.
Google Sheets basics: spreadsheets, worksheets, row creation and updates
Google Sheets organizes data in spreadsheets containing one or more sheets (worksheets). You’ll typically create rows to append new transcript entries or update existing rows when more data arrives. Understand column headers and the difference between appending and updating rows to avoid duplicates.
Webhook fundamentals: payloads, URLs, POST requests and headers
A webhook is a URL that accepts POST requests. When Vapi sends a webhook, it posts JSON payloads to the URL you supply. The payload includes fields like call ID, transcript text, timestamps, and possibly URLs to audio files. You’ll want to ensure content-type headers are set to application/json and that your receiver accepts the payload format.
Transcript-related terms: transcript text, speaker labels, timestamps, metadata
Key transcript terms include transcript text (the raw or cleaned words), speaker labels (who spoke which segment), timestamps (time offsets for segments), and metadata (call duration, caller number, call ID). You’ll decide which of these to store as columns and how to flatten nested structures like arrays of segments.
Preparing Google Sheets
Getting your spreadsheet ready is an important early step. Thoughtful column design and access control avoid headaches later when mapping and testing.
Create a spreadsheet and sheet for transcripts
Create a new Google Sheet and name it clearly, for example “Call Transcripts.” Add a single worksheet where rows will be appended, or create separate tabs for different projects or years. Keep the sheet structure simple for initial testing.
Recommended column headers: Call ID, Date/Time, Caller, Transcript, Duration, Tags, Source URL
Set up clear column headers that match the data you’ll capture: Call ID (unique identifier), Date/Time (call start or end), Caller (caller number or name), Transcript (full text), Duration (seconds or hh:mm:ss), Tags (manual or automated labels), and Source URL (link to audio or Vapi resource). These headers make mapping straightforward in Make.com.
Sharing and permission settings: editor access for Make.com connector or service account
Share the sheet with the Google account or service account used by Make.com and grant editor permissions. If you’re using OAuth via Make.com, authorize the Google Sheets connection with your account. If using a service account, ensure the service account email is added as an editor on the sheet.
Optional: prebuilt templates and example rows for testing
Add a few example rows as templates to test mapping behavior and to ensure columns accept the values you expect (long text in Transcript, formatted dates in Date/Time). This helps you preview how data will look after automation runs.
Considerations for large volumes: split sheets, multiple tabs, or separate files
If you expect high call volume, consider partitioning data across multiple sheets, tabs, or files by date, region, or agent to keep individual files responsive. Large sheets can slow down Google Sheets operations and API calls; plan for archiving older rows or batching writes.
Setting up Vapi for Call Recording and Transcription
Now configure Vapi to produce the data you need and send it to Make.com. This part focuses on choosing the right options and ensuring webhooks are enabled and testable.
Enable or configure call recording and transcription in your Vapi project
In your Vapi project settings, enable call recording and transcription features. Choose whether to record all calls or only certain numbers, and verify that transcripts are being generated. Test a few calls manually to ensure the system is producing transcripts.
Set transcription options: language, speaker diarization, punctuation
Choose transcription options such as language, speaker diarization (separating speaker segments), and punctuation or formatting preferences. If diarization is available, it will produce segments with speaker labels and timestamps — useful for more granular analytics in Sheets.
Decide storage of audio/transcript: Vapi storage, external storage links in payload
Decide whether audio and transcript files will remain in Vapi storage or whether you want URLs to external storage returned in the webhook payload. If external storage is preferred, configure Vapi to include public or signed URLs in the payload so you can link back to the audio from the sheet.
Configure webhook callback settings and allowed endpoints
In Vapi’s webhook configuration, add the endpoint URL you’ll get from Make.com and set allowed methods and content types. If Vapi supports specifying event types (call ended, segment ready), select the events that will trigger the webhook. Ensure the callback endpoint is reachable from Vapi.
Test configuration with a sample call to generate a payload
Make a test call and let Vapi generate a webhook. Capture that payload and inspect it so you know what fields are present. A sample payload helps you build and map the correct fields in Make.com without guessing where values live.
Creating the Webhook Receiver in Make.com
Set up the webhook listener in Make.com so Vapi can send JSON payloads. You’ll capture the incoming data and use it to drive the rest of the scenario.
Start a new scenario and add a Webhook module as the first step
Create a new Make.com scenario and add the custom webhook module as the first module. The webhook module will generate a unique URL that acts as your endpoint for Vapi’s callbacks. Scenarios are visual and you can add modules after the webhook to parse and process the data.
Generate a custom webhook URL and copy it into Vapi webhook config
Generate the custom webhook URL in Make.com and copy that URL into Vapi’s webhook configuration. Ensure you paste the entire URL exactly and that Vapi is set to send JSON POST requests to that endpoint when transcripts are ready.
Configure the webhook to accept JSON and sample payload format
In Make.com, configure the webhook to accept application/json and, if possible, paste a sample payload so the platform can parse fields automatically. This snapshot helps Make.com create output bundles with visible keys you can map to downstream modules.
Run the webhook module to capture a test request and inspect incoming data
Set the webhook module to “run” or put the scenario into listening mode, then trigger a test call in Vapi. When the request arrives, Make.com will show the captured data. Inspect the JSON to find call_id, transcript_text, segments, and any metadata fields.
Set scenario to ‘On’ or schedule it after testing
Once testing is successful, switch the scenario to On or schedule it according to your needs. Leaving it on will let Make.com accept webhooks in real time and process them automatically, so transcripts flow into Sheets without manual intervention.
Inspecting and Parsing the Vapi Webhook Payload
Webhook payloads can be nested and contain arrays. This section helps you find the values you need and flatten them for spreadsheets.
Identify key fields in the payload: call_id, transcript_text, segments, timestamps, caller metadata
Look for essential fields like call_id (unique), transcript_text (full transcript), segments (array of speaker or time-sliced items), timestamps (start/end or offsets), and caller metadata (caller number, callee, call start time). Knowing field names makes mapping easier.
Handle nested JSON structures like segments or speaker arrays
If segments come as nested arrays, decide whether to join them into a single transcript or create separate rows per segment. In Make.com you can iterate over arrays or use functions to join text. For sheet-friendly rows, flatten nested structures into a single string or extract the parts you need.
Dealing with text encoding, special characters, and line breaks
Transcripts may include special characters, emojis, or unexpected line breaks. Normalize text using Make.com functions: replace or strip control characters, transform newlines into spaces if needed, and ensure the sheet column can contain long text. Verify encoding is UTF-8 to avoid corrupted characters.
Extract speaker labels and timestamps if present for granular rows
If diarization provides speaker labels and timestamps, extract those fields to either include them in the same row (e.g., Speaker A: text) or to create multiple rows — one per speaker segment. Including timestamps lets you show where in the call a statement was made.
Transform payload fields into flat values suitable for spreadsheet columns
Use mapping and transformation tools to convert nested payload fields into flat values: format date/time strings, convert duration into a readable format, join segments into a single transcript field, and create tags or status fields. Flattening ensures each spreadsheet column contains atomic, easy-to-query values.
Mapping and Integrating with Google Sheets in Make.com
Once your data is parsed and cleaned, map it to your Google Sheet columns and decide on insert or update logic to avoid duplicates.
Choose the appropriate Google Sheets module: Add a Row, Update Row, or Create Worksheet
In Make.com, pick the right Google Sheets action: Add a Row is for appending new entries, Update Row modifies an existing row (requires a row ID), and Create Worksheet makes a new tab. For most transcript logs, Add a Row is the simplest start.
Map parsed webhook fields to your sheet columns using Make’s mapping UI
Use Make.com’s mapping UI to assign parsed fields to the correct columns: call_id to Call ID, start_time to Date/Time, caller to Caller, combined segments to Transcript, and so on. Preview the values from your sample payload to confirm alignment.
Decide whether to append new rows or update existing rows based on unique identifiers
Decide how you’ll avoid duplicates: append new rows for each unique call_id, or search the sheet for an existing call_id and update that row if multiple payloads arrive for the same call. Use a search module in Make.com to find rows by Call ID before deciding to add or update.
Handle batching vs single-row inserts to respect rate limits and quotas
If you expect high throughput, consider batching multiple entries into single requests or using delays to respect Google API quotas. Make.com can loop through arrays to insert rows one-by-one; if volume is large, use strategies like grouping by time window or using multiple spreadsheets to distribute load.
Test by sending real webhook data and confirm rows are created correctly
Run live tests with real Vapi webhook data. Inspect the Google Sheet to confirm rows contain the right values, date formats are correct, long transcripts are fully captured, and special characters render as expected. Iterate on mapping until the results match your expectations.
Building the “Transcript Dude” Workflow
Now you’ll create the assistant-style workflow — “Transcript Dude” — that cleans and enriches transcripts before sending them to Sheets or other destinations.
Concept of the assistant: an intermediary that cleans, enriches, and routes transcripts
Think of Transcript Dude as a middleware assistant that receives raw transcript payloads, performs cleaning and enrichment, and routes the final output to Google Sheets, notifications, or storage. This modular approach keeps your pipeline maintainable and lets you add features later.
Add transformation steps: trimming, punctuation fixes, speaker join logic
Add modules to trim whitespace, normalize punctuation, merge duplicate speaker segments, and reformat timestamps. You can join segment arrays into readable paragraphs or label each speaker inline. These transformations make transcripts more useful for downstream review.
Optional enrichment: generate summaries, extract keywords, or sentiment (using AI modules)
Optionally add AI-powered steps to summarize long transcripts, extract keywords or action items, or run sentiment analysis. These outputs can be added as extra columns in the sheet — for example, a short summary column or a sentiment score to flag calls for review.
Attach metadata: tag calls by source, priority, or agent
Attach tags and metadata such as the source system, call priority, region, or agent handling the call. These tags help filter and segment transcripts in Google Sheets and enable automated workflows like routing high-priority calls to a review queue.
Final routing: write to Google Sheets, send notification, or save raw transcript to storage
Finally, route the processed transcript to Google Sheets, optionally send notifications (email, chat) for important calls, and save raw transcript files to cloud storage for archival. Keep both raw and cleaned versions if you might need the original for compliance or reprocessing.
Conclusion
Wrap up with practical next steps and encouragement to iterate. You’ll be set to start capturing transcripts and building useful automations.
Next steps: set up accounts, create webhook, test and iterate
Start by creating the needed accounts, setting up Vapi to produce transcripts, generating a webhook URL in Make.com, and configuring your Google Sheet. Run test calls, validate the incoming payloads, and iterate your mappings and transformations until the output matches your needs.
Resources: video tutorial references, Make.com and Vapi docs, template downloads
Refer to tutorial videos and vendor documentation for step-specific screenshots and troubleshooting tips. If you’ve prepared templates for Google Sheets or sample payloads, use those as starting points to speed up setup and testing.
Encouragement to start small, validate, and expand automation progressively
Begin with a minimal working flow — capture a few fields and append rows — then gradually add enrichment like summaries, tags, or error handling. Starting small lets you validate assumptions, reduce errors, and scale automation confidently.
Where to get help: community forums, vendor support, or consultancies
If you get stuck, seek help from product support, community forums, or consultants experienced with Vapi and Make.com automations. Share sample payloads and screenshots (with any sensitive data removed) to get faster, more accurate assistance.
Enjoy building your Transcript Dude workflow — once set up, it can save you hours of manual work and turn raw call transcripts into structured, actionable data in Google Sheets.
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