Noise vs Signal 101 on YouTube Analytics (in practice) Here, I...

@wono_strategy
wono@wono_strategy
16 views Mar 01, 2025 ~3 min read
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Noise vs Signal 101 on YouTube Analytics (in practice)

Here, I guide you through a concrete example of how I work on analytics for my channels/clients to extract signal from noise.

I go step by step so you can easily follow 👇
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This thread is a practical case using this mega thread I've made on Noise vs Signal in YouTube metrics.


x.com/wono_strategy/…
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In the 1st tweet pic, CTR doesn't make sense without context, the signal is hidden behind an average.

There's nothing you can get out of it (too much noise).

If "signal hidden behind an average" is fuzzy to you, here's a simple example to understand using views graph 👇
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Alright, let's proceed meticulously:

1. Remove the noise (ciao CTR 👋)

2. Follow the signal (views graph)

We can see 3 spikes.

The first is too diffuse and is likely just an organic market shift (based on experience).

The two others are interesting (as they are bumpier).
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Let's start with the biggest spike (November).

When we zoom in, there is indeed a clear spike.

Something unusual happened, and we're lucky:

👉 88.6% of these views are from the "Suggested videos" tab.

Lucky, because "Suggested videos" provide more details.

Let's see...
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For context, this channel has ~80k subs.

When a video gets more than 160k views, I consider it viral (outreaching 2x my subs).

The top 5 videos that brought views (pic tweet below) are from my channel as well.

Great!

There's something we can learn about my audience!
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Purple (see pic) is the video that brought in the highest number of views.

In red, viral videos 👉 noise 🔊.

Why?

Because from experience, viral videos bring attention to your library, that's a normal phenomenon (noise 🔊).

But purple is not viral! (look at the views)
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There we go!

All the noise is gone, the signal is now clear 📶.

👉 It's this similar video with a similar title from November 12th.
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Now let's investigate the second bump from August. 🔎
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This time, it is trickier.

The big spike is not from "Suggested videos" but from "Browse features".

As you can see, in that period the views from "Suggested videos" only accounted for 45.6%.

Not enough to find the signal.
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Especially because I know the context behind the big spike.

The videos uploaded during that specific period had more views than usual, the attention demand increased because a big update was released for the game.

Same supply + higher demand = more views.

Market law basics.
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The big spike was noise 🔊 -> ciao 👋

Now if we pay close attention, we can see something is happening here.

Let's investigate 🔎
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There we go! We found our culprit.

We can see another video uploaded that day with a similar title contributed to the spike as well.

The blue video has a different title, but is a similar video.
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And when we zoom out the timeline a bit, it's more clear:
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I upload daily on that channel (mostly to train my title/thumbnail skills and experiment with stuff).

The channel has over 510 videos.

Videos help other similar videos' views compound over time, which is why I make a lot of series to increase the chances of that happening.
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So:

• The first video definitely played a role in the November bump

• The second video helped the video get a bit of traction, but wasn't behind August's bump.

Conclusion:

👉 The more similar videos you have, the faster you will grow your audience.
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The title can help, but the main factor is the similarity of content.

Here, one similar video can bring up to 2.5k views to other similar ones.

Say I upload a video that has 20 similar ones, with a conservative 1k views boost /video, I can get an extra 20k views for free!
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That's it for this one!

See you soon for another thread. 🫡
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