Auto Find YouTube Subscriber Emails | n8n

This is where your automation begins. The Daily Trigger node uses n8n's built-in Cron functionality to automatically kick off the workflow at the same time every day — no manual intervention required. Once you publish this workflow, it runs on autopilot.

Setting this to midnight means your subscriber list gets processed while you sleep. By the time you wake up, new subscribers have been checked, emails have been scraped, and welcome messages have been sent. That's the power of automation working around the clock.

💡 Tip: If you'd prefer the workflow to run at a different time (say, 9 AM when you start work), simply change the "Trigger at Hour" dropdown. You can also set it to run multiple times per day by adding additional trigger rules.

This HTTP Request node connects directly to YouTube's Data API v3 to retrieve your channel's subscription data. It's the foundation of the entire workflow — without this, you'd have no subscriber information to process.

The node uses OAuth2 authentication, which means you'll need to set up YouTube API credentials in your Google Cloud Console and connect them to n8n. Once configured, this node pulls subscriber information including their channel IDs, display names, and subscription timestamps.

💡 Tip: Make sure your OAuth2 scope includes youtube.readonly at minimum. The full API URL should look something like: https://www.googleapis.com/youtube/v3/subscriptions?part=snippet&myRecentSubscribers=true&maxResults=50

The YouTube API returns all subscribers bundled together in an items array. This Split Out node breaks that array apart so each subscriber becomes a separate item in the workflow. This is essential because we need to process each subscriber individually — checking duplicates, scraping emails, and sending personalized messages.

Without this step, you'd be trying to process an entire array as a single unit, which would break the subsequent logic. Think of it as unpacking a box of items so you can examine each one separately.

💡 Tip: If you're ever unsure what field name to use, execute the previous node first and examine its output. The array you want to split will be visible in the JSON structure.

This node is crucial for controlling the flow of your automation. By setting the batch size to 1, you ensure that each subscriber is processed completely — duplicate check, email scrape, welcome email — before moving on to the next one.

This prevents rate limiting issues with APIs (especially Apify), keeps your workflow organized, and makes debugging much easier if something goes wrong. You'll always know exactly which subscriber was being processed when an issue occurred.

💡 Tip: If you have many subscribers and want to speed things up, you could increase the batch size. However, keep it low (3-5 maximum) to avoid hitting API rate limits with Apify or Gmail.

Before scraping emails or sending welcome messages, we need to check if we've already processed this subscriber. This Google Sheets node queries your database to see if the subscriber's channel ID already exists. If it does, we skip them — no wasted API calls, no duplicate emails.

This is what makes the workflow intelligent. Run it every day for a year, and you'll never accidentally welcome the same person twice or waste Apify credits on subscribers you've already checked.

💡 Tip: Create your Google Sheet before running the workflow with three columns: "Subscriber name", "Subscriber id", and "Email". The column headers must match exactly what you configure in later nodes.

This conditional node examines the result of the Google Sheets lookup. If a row_number exists in the response, that means we found a matching record — the subscriber has already been processed. If row_number doesn't exist, this is a new subscriber who needs the full treatment.

The workflow splits into two paths here: existing subscribers loop back to process the next person, while new subscribers continue forward to have their email scraped.

💡 Tip: The "true" output of this node goes to subscribers who already exist (skip them). The "false" output goes to new subscribers (process them). Make sure your connections are wired correctly!

This is where the magic happens. The Apify node runs the YouTube Email Scraper actor, which visits the subscriber's YouTube channel page and extracts any publicly available email address from their "About" section or channel description.

The actor runs in Apify's cloud, handles all the scraping complexity, and returns structured data including any email addresses found. This is far more reliable than trying to scrape YouTube yourself — plus it respects YouTube's structure even when they update their frontend.

💡 Tip: You'll need an Apify account with API access. The YouTube Email Scraper consumes compute units, so monitor your usage. Each run typically costs a fraction of a cent, but it adds up with many subscribers.

Not every YouTube channel has a public email address. This conditional node checks whether the Apify scraper actually found an email. If yes, we proceed to save the full record and send a welcome email. If no, we still save the subscriber (so we don't check them again) but skip the email outreach.

This branching logic ensures your workflow handles both scenarios gracefully without errors.

💡 Tip: Apify returns emails as an array because some channels list multiple contact emails. We're using email[0] to grab the first one, which is typically the primary contact.

When an email is found, this node appends a complete row to your Google Sheet including the subscriber's name, channel ID, and email address. This builds your contact database automatically, giving you a growing list of engaged YouTube fans you can reach directly.

The expressions pull data from earlier nodes in the workflow, combining subscriber information from YouTube with the scraped email from Apify.