This week, I want to pull back the curtain on one of our most important processes at Playstack, how we analyze YouTube video performance to improve and grow channels continually.
It's one thing to make videos, and that is an achievement in itself, but the next thing is to get results. The problem is, a lot of people give up on an idea, style or format because they get bad results after 1 or 2 videos.
Opposite, people fail to double down on any success they have, something like above-average hook retention or any parts of the video that get more attention because of editing or storytelling.
I'll share with you the parts of a video are worth looking at that determine success even tho you might not get a lot of views. As you know we work with a lot of businesses and views are not always the main indicator of success, but conversions or engagement are. This is where retention is very important, to build trust and authority.
Retention is also one of the main indicators of success for any video, resulting in more views. We noticed that videos above 40% retention usually get boosted more in views.
Part of what I do daily is consume a lot of content, and here are some of my favorites:
We created a full YouTube Idea Bank with all the previous outliers.
Format: Outlier score (multiple of average last 5 videos) \ Channel Name - Video name + link - My notes
Creating great content is just the beginning. The real magic happens when you systematically analyze what's working and why.
One thing I've been very obsessed with is capturing data, because now with AI it's a lot easier to create systems, conclusions and tools out of data.
Here's a look into our performance analysis workflow:
We don't just glance at view counts. We dig into the retention graphs to understand exactly where viewers are engaging and dropping off.
The YouTube retention dashboard now offers incredible insights, including:
Pro Tip: Look for those flat or upward spikes in your retention curve - these are golden moments where your content is truly resonating.
Your first 30 seconds make or break your video's success. We analyze hooks by:
One pattern we've noticed: Statistics combined with contrarian statements often perform exceptionally well with new viewers, while emotional hooks tend to work better with existing audiences.
We map your entire video structure with timestamps to identify:
Some examples are that generic stock footage tends to lose the attention of people but text graphics attracts them when done well.
Too much text makes people click off. A trick for this is having the text roll in word for word as someone is reading a book to keep attention so they are not overwhelmed with too much text at once.
Different content attracts different audiences. We analyze:
This helps determine if your video is serving your core audience or expanding to new viewers - both are valuable depending on your goals.
The biggest challenge? This process is time-consuming. We're actively working on ways to automate these insights using YouTube's API and AI tools.
In the meantime, we've created comprehensive templates that help streamline the analysis. Our AI prompt framework can take a video transcript and automatically identify:
Reply to this email and I'll share our Video deep-dive template for your AI.
The real value comes from implementing what you learn. For example:
Start small - pick your best-performing video and your worst-performing video. Compare:
The patterns you discover will likely reveal immediate opportunities to improve your content strategy.
Want help implementing a data-driven approach to your YouTube growth? That's exactly what we specialize in at Playstack.
What are some of your data insights you gathered?