How I built an "AI-Research Assistant" that saves 10+ hours a week (and tracks every competitor)

Let’s be real—manually tracking YouTube competitors is a massive time-sink.

I see so many creators and agency owners spending hours every week jumping between tabs, checking view counts, and trying to "guess" what content is actually trending.

That’s a waste of high-level talent.

I decided to solve this with a 2-part n8n automation engine. Now, the data comes to me.

Here’s the breakdown of the system:

1️⃣ The Data Harvester: It monitors a list of target channels in Google Sheets. Every time a new video drops, it automatically pulls the views, likes, comments, and tags. No more manual data entry.

2️⃣ The Outlier Detector: This is where the ROI happens. The system calculates the average performance of a channel and only alerts me when a video is an "outlier" (performing way above average).

3️⃣ The Intel Report: It generates a professional HTML newsletter and drops it in my inbox. I can see the "viral signals" while I’m drinking my morning coffee. ☕

The ROI?

Time: 10+ hours/week saved (that's 40+ hours a month to focus on high-ticket sales).

Money: Replaces the need for a $1,500/month research assistant.

Strategy: You stop guessing and start creating content that is backed by real-time competitor data.

I’m curious—how many of you are still tracking your market research manually?

If you want to see a walkthrough of how the nodes are set up or want this built for your business, drop a "TRENDS" in the comments below! 👇

0:41

2 comments

Wifi Life

skool.com/wifi-life

A community of developers & entrepreneurs that provides exclusive material to develop coding based side hustles, land high paying tech jobs, and more.

Leaderboard (30-day)