How to Do Keyword Research on YouTube (Without Spending Half Your Day On It)
Most YouTube keyword research advice tells you to find high-volume, low-competition keywords.
Which is correct, and also completely unhelpful if it doesn't tell you how to actually find them without spending three hours in a spreadsheet.
This post covers how to do keyword research on YouTube using AI to get the analysis done in minutes, not a whole afternoon.
It's part of how I approach my AI marketing systems build for small business owners - letting the tools handle the repetitive work so the strategy part doesn't get buried.
Why YouTube keyword research is different from Google
When you think about keyword research, you probably think about Google.
But YouTube is a separate search engine, and the way people use it reflects that.
On Google, someone might search "best CRM for small business" because they're comparing options and close to a decision.
On YouTube, they're more likely to search "how to set up a CRM" or "best CRM walkthrough" because they want to learn by watching something.
The intent is different. The phrasing is different. And if you're pulling your YouTube strategy from Google keyword data alone, you're writing titles for the wrong platform.
YouTube's algorithm also works differently.
Your title and description feed the search results, but watch time, click-through rate, and engagement all play a role too.
Keyword research on YouTube isn't just about finding what people search for - it's about finding what they'll actually click on and watch all the way through.
Google keyword data is a starting point, but you need data from inside YouTube to see the full picture.
What you're actually looking for when you research YouTube keywords
Good YouTube keyword research isn't just about traffic volume.
A keyword with 100,000 monthly searches is useless if every video ranking for it comes from a channel with half a million subscribers.
What you're looking for is the combination of search demand and realistic ranking potential.
A few signals worth checking for each keyword:
Search volume - how many people are looking for that term each month on YouTube. Higher is better, but it's only part of the picture.
Competition level - how hard it will be to rank. High volume and low competition is the sweet spot. These gaps do exist, you just need to look for them systematically.
Top-10 analysis - who's already ranking. If the top results come from massive channels with millions of views, smaller channels will struggle to break in. If you see a mix of channel sizes, that's a signal that the gap is worth going after.
Search intent - what kind of video the person actually wants to watch. Tutorial, comparison, review? Knowing this shapes your title and your entire video concept.
When you're doing YouTube channel keyword research, you're building a picture of where you can show up and genuinely compete.
The manual way to do YouTube keyword research (and why it's slow)
The traditional approach involves a mix of tools and a lot of manual cross-referencing. It looks something like this:
1. Type a seed keyword into YouTube's search bar and note the autocomplete suggestions - these are real terms people are using.
2. Look at the top-ranking videos and check the channel sizes, view counts, and how old the videos are.
3. Use a browser extension like TubeBuddy or VidIQ to see estimated search volumes and competition scores.
4. Open a spreadsheet and log your keywords, volumes, competition levels, and notes on the current top results.
Repeat for every keyword variation you want to check.
For each keyword, you might spend 30 minutes doing this properly. If you're planning even 10 videos, that's several hours before you've written a single title.
Most of that time isn't analysis, it's data gathering.
Copy-pasting numbers into a spreadsheet, opening the same tabs repeatedly, cross-referencing the same metrics over and over.
It takes a lot of time but doesn't require much thinking.
Which makes it a perfect candidate for automation.
The best tool for YouTube keyword research right now isn't a keyword tool. It's AI.
How to use AI for YouTube keyword research
The way I use AI for YouTube keyword research is to let it handle the data-gathering - the part that eats up most of the time - so I can focus on the analysis and decision-making.
Want to see it in action? Here’s a video of how it works:
The process in practice is that I use a custom AI keyword research tool that pulls data directly from YouTube.
I give it a seed keyword or topic, it runs a search and pulls the key metrics from the top-ranking videos - views, channel size, upload date, engagement - then generates a ranked list of keyword opportunities based on search demand versus competition.
What would normally take an hour of manual searching takes a few minutes.
The output is a structured table showing the top 10 results for each keyword, with enough data to see at a glance whether there's a gap worth going after.
You're not just getting a list of keywords, you're also getting context on whether those keywords are actually winnable for a channel at your current size.
Keyword research with AI doesn't mean handing over the thinking. You still interpret the results and decide what fits your channel and audience.
But it removes the part that was slowing everything down. If you've been putting off building a YouTube content plan because the keyword research felt like too much work, this is the approach that makes it actually manageable.
If you're wondering how this fits into a broader YouTube strategy, this post on using AI to get clients from YouTube is worth reading alongside this one.
Reading the results - the top-10 table and gap analysis
When you run an AI keyword research tool against a topic, what comes back is more useful than a simple volume and difficulty score. The most valuable output is the top-10 analysis.
For each keyword, you can see the 10 videos currently ranking, along with view counts, subscriber counts, upload dates, and engagement levels relative to views.
This is where the gap analysis happens.
You're looking for keywords where the search demand is reasonable (even a few thousand searches per month is worth targeting if the competition is low), the top-ranking videos come from smaller or mid-sized channels, some of the ranking videos are old and haven't been updated, and the existing videos have decent views but low engagement (which often signals the audience is under-served).
A gap isn't always a keyword nobody's covered.
Sometimes it's a keyword covered badly, or by channels you can realistically compete with. The top-10 table shows you both.
Rather than building this analysis yourself from scratch, you're starting from a ranked shortlist of opportunities. Your job is to decide which ones to act on.
Filtering the recommendations through your brand
Once you have a list of keyword opportunities, the next filter is whether a topic actually makes sense for your channel and your audience.
A keyword can have low competition and decent search volume and still be the wrong choice because it attracts the wrong viewer, or because you don't have anything genuinely useful to add.
The questions to ask yourself
Does this keyword attract the right viewer? Is the person searching this term the kind of person who would benefit from your content and potentially become a client or customer? Or are they just browsing?
Can you add something real to this topic? A video is only worth making if you have a perspective or approach that's different or more useful than what's already ranking. If the top-10 results already cover it well, you need a clear reason for making another one.
Does it fit your content plan? YouTube keyword research works best when you're building clusters of related topics. A keyword that fits into a broader series is more valuable than a standalone topic, even if the volumes look similar.
AI can surface the opportunities, but you decide which ones are worth pursuing. That combination - fast data, human judgment - is what makes the whole process work.
Frequently Asked Questions
How do I do YouTube keyword research?
The most practical approach is to combine a starting keyword with a tool that shows you what's already ranking.
Look at who's in the top 10, how large those channels are, and how old the videos are. If you see smaller channels performing well, or older videos that haven't been refreshed, that's a gap worth considering.
AI tools can speed this up considerably by pulling the data and doing the initial analysis automatically.
What is YouTube keyword research?
YouTube keyword research is the process of identifying which search terms your target audience uses on YouTube so you can create videos that appear when they're looking.
Unlike Google keyword research, it focuses on video-specific intent - people on YouTube are generally looking to watch, learn, or be entertained rather than just find a link.
Good YouTube keyword research looks at search volume, competition, and ranking context together, not any single metric in isolation.
What are the best tools for YouTube keyword research?
TubeBuddy and VidIQ are the most widely used browser extensions, both showing search volume and competition scores directly inside YouTube.
For a more automated approach, AI keyword research tools can scrape top-ranking video data and generate gap analysis without the manual spreadsheet work. The right choice depends on how many keywords you're researching - for building out a full content plan, an AI-driven approach is considerably faster.
If you'd rather hand this off than figure it out yourself, I build AI-powered marketing systems for service businesses. Keyword research, content planning, the whole thing.