YouTube Channel Statistics Scraper

📊 YouTube Channel Statistics Scraper – Subscriber Counts, Views & Channel Metadata

The YouTube channel statistics scraper extracts subscriber counts, total views, video counts and channel metadata from any public YouTube channel URL, without requiring a YouTube Data API key or a quota allocation. Pass this YouTube channel statistics scraper a list of channel URLs — handle format, /channel/ IDs, or custom URLs — and it returns one clean record per channel with the numbers already expanded from YouTube's abbreviated display format into real integers.

That last detail is the practical reason to use it. YouTube renders "1.2M subscribers" in its interface, which is useless for arithmetic. This actor returns totalSubscribers as an integer, along with totalViews and totalVideos, so ranking, filtering and averaging work directly on the output. Add channelId, publishedAt, country, description and a thumbnail URL, and each record is a complete profile snapshot ready for a creator database, an influencer shortlist, or a competitive tracking spreadsheet.

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📊 What Data Can You Extract with This YouTube Channel Scraper?

Each dataset item is one YouTube channel:

Category	Fields	What you get
🔗 Channel identity	youtubeChannelUrl, channelId, channelTitle	The URL you supplied, YouTube's canonical channel ID, and the channel's display name
📈 Audience metrics	totalSubscribers, totalViews	Subscriber count and lifetime view count, both as integers rather than abbreviated strings
🎬 Content volume	totalVideos	Number of public videos on the channel
🗓️ Channel history	publishedAt	When the channel was created, normalised to ISO format
🌍 Profile metadata	country, description, thumbnail	Country code, the channel's about-page description, and its avatar image URL

The most analytically useful combination is totalViews divided by totalVideos. Average views per video is a far better indicator of a channel's actual reach than subscriber count, because subscriber counts accumulate historically and never decay. A channel with 500,000 subscribers averaging 3,000 views per video and one with 50,000 subscribers averaging 40,000 views per video are very different partnership propositions, and only the derived metric reveals that.

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🌟 Key Features of the YouTube Channel Statistics Scraper

Feature	Description
🔑 No API key required	Works without a YouTube Data API key, so there is no quota to request, manage or exhaust
📋 Bulk channel processing	youtubeChannelUrls accepts an array, so an entire creator list is processed in one run
🔢 Expanded numeric counts	Abbreviated display values such as "1.2M" are converted to full integers for totalSubscribers, totalViews and totalVideos
🆔 Canonical channel IDs	Returns YouTube's stable channelId, which survives handle and display-name changes
🗓️ Normalised creation date	publishedAt is converted from YouTube's localised join-date text into an ISO format value
🌍 Country codes	country is returned as a code rather than a display name, ready for joins and filtering
🖼️ Avatar URL	thumbnail gives the channel avatar image, useful for dashboards and reports
🛡️ Managed proxy rotation	Proxy rotation is handled automatically; no proxy configuration is required from you
🧾 Flat output schema	Ten top-level fields with no nesting, so CSV and spreadsheet exports stay readable

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🚀 Why Choose This YouTube Channel Statistics Scraper?

No API key, no quota ceiling. The YouTube Data API requires a Google Cloud project, an API key and a daily quota that a moderately sized channel list will exhaust. This actor reads the public channel page directly, which removes that entire administrative layer and its limits.

Numbers you can actually compute with. totalSubscribers, totalViews and totalVideos are integers, expanded from YouTube's abbreviated display text. That means sorting, averaging, thresholding and ratio calculations work on the raw output with no string parsing step of your own.

A stable identifier for long-term tracking. Handles and display names change; channelId does not. Storing it as the key for a creator database means your records survive rebrands, which is exactly when a name-keyed dataset silently breaks.

Built for lists, not single lookups. The input is an array of channel URLs. Whether you are checking five competitors or a thousand candidate creators, the workflow is the same run, and the flat output schema means the export goes straight into a spreadsheet.

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📥 Input

{
  "youtubeChannelUrls": [
    "https://www.youtube.com/@BoysPlaytime"
  ]
}

🔧 YouTube Channel Scraper Input Fields

Field	Type	Required	Default	Description
youtubeChannelUrls	array	Yes	prefilled ["https://www.youtube.com/@BoysPlaytime"]	List of YouTube channel URLs to scrape, for example https://www.youtube.com/@BoysPlaytime

💡 Input Examples

A single channel:

{
  "youtubeChannelUrls": ["https://www.youtube.com/@BoysPlaytime"]
}

A competitive set, using handle URLs:

{
  "youtubeChannelUrls": [
    "https://www.youtube.com/@channelone",
    "https://www.youtube.com/@channeltwo",
    "https://www.youtube.com/@channelthree"
  ]
}

A mixed batch using both handle and channel ID URL formats:

{
  "youtubeChannelUrls": [
    "https://www.youtube.com/@examplecreator",
    "https://www.youtube.com/channel/UCexampleChannelIdHere",
    "https://www.youtube.com/@anothercreator"
  ]
}

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📤 Output

{
  "youtubeChannelUrl": "https://www.youtube.com/@BoysPlaytime",
  "channelId": "UCexampleChannelIdHere",
  "channelTitle": "Boys Playtime",
  "thumbnail": "https://yt3.googleusercontent.com/example=s88-c-k-c0x00ffffff-no-rj",
  "publishedAt": "2019-03-14",
  "totalSubscribers": 1240000,
  "totalViews": 385000000,
  "totalVideos": 742,
  "country": "US",
  "description": "Family-friendly toy reviews and playtime videos uploaded every week."
}

🧾 YouTube Channel Statistics Output Fields

Field	Type	Description
youtubeChannelUrl	string | null	The channel URL, as supplied in your input
thumbnail	string | null	Channel avatar image URL
channelTitle	string | null	Channel display title
channelId	string | null	YouTube's canonical channel identifier
publishedAt	string | null	When the channel was created, normalised to ISO format
totalViews	integer | null	Lifetime total view count for the channel
totalSubscribers	integer | null	Subscriber count
totalVideos	integer | null	Number of public videos
country	string | null	Country code for the channel
description	string | null	Channel description from the about page

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💻 How to Use the YouTube Channel Statistics Scraper (Step by Step)

Step 1: Collect the channel URLs you want to track

youtubeChannelUrls is the only input, and it accepts an array. Handle-style URLs (https://www.youtube.com/@creatorname) are the most common modern format and work well. Channel ID URLs (https://www.youtube.com/channel/UC...) are the most robust because they never change. Both are accepted, and mixing formats within a single array is fine.

Step 2: Verify the URLs are channel pages, not video pages

The single most common input mistake is passing a video URL, a playlist URL or a shorts URL instead of a channel URL. Those point at content, not at a channel profile, and will not yield channel statistics. If you are working from a list of videos, resolve each to its channel page first — the fastest way is to open one video and click through to the channel.

Step 3: Build your batch

Paste the full list into the input array. There is no per-run limit in the input schema, so batch size is governed by practical runtime. For very large creator databases, splitting into batches of a few hundred keeps runs responsive and means partial results are available sooner if something goes wrong mid-way.

Step 4: Run the actor

Start the run from the Apify Console, the API, or a schedule. There is no proxy configuration to complete — proxy rotation is handled automatically — and no API key to supply, so the run begins immediately. Watch the log for channels that produce errors; those are almost always URL format problems or channels that have been removed.

Step 5: Verify the parsed numbers

Before building anything on the output, spot-check two or three records against the live channel pages. Confirm that totalSubscribers matches what YouTube displays once expanded, and that totalVideos looks right. This takes a minute and catches the occasional channel whose about page is configured unusually — for example, channels that hide their subscriber count entirely, which will return null.

Step 6: Derive the metrics that matter

Raw counts are the input to analysis, not the analysis. Compute average views per video from totalViews and totalVideos. Compute channel age from publishedAt and derive an upload cadence. Compute a views-to-subscribers ratio as a rough engagement proxy. These derived figures are what actually differentiate channels in a shortlist.

Step 7: Export, store by channelId, and re-run on a schedule

Export as JSON, CSV or Excel, or pull the dataset via the API. Store records keyed on channelId rather than channelTitle, because titles change and IDs do not. Scheduling repeated runs turns a static snapshot into a growth time series — and growth rate is almost always more informative than any single-point measurement.

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🔌 API Access & Integrations

Run the YouTube channel statistics scraper and get the dataset back in one call:

curl -X POST "https://api.apify.com/v2/acts/scrapers-hub~youtube-channel-statistics-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "youtubeChannelUrls": [
      "https://www.youtube.com/@BoysPlaytime"
    ]
  }'

Python, using the official client:

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")

run = client.actor("scrapers-hub/youtube-channel-statistics-scraper").call(
    run_input={
        "youtubeChannelUrls": [
            "https://www.youtube.com/@channelone",
            "https://www.youtube.com/@channeltwo",
        ]
    }
)

for channel in client.dataset(run["defaultDatasetId"]).iterate_items():
    views = channel.get("totalViews") or 0
    videos = channel.get("totalVideos") or 1
    print(channel["channelTitle"], channel["totalSubscribers"], round(views / videos))

Results can be sent to Zapier, Make, Google Sheets or Slack, or delivered to your own service with an Apify webhook fired when the run completes.

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💡 Best Use Cases for YouTube Channel Statistics Data

🤝 Influencer discovery and vetting

Before committing budget to a creator partnership, you need the numbers behind the pitch deck. totalSubscribers sets the headline scale, but dividing totalViews by totalVideos reveals actual per-video reach, and publishedAt shows whether that audience was built over a decade or in the last eighteen months. Channels with a high subscriber count and low average views are the ones worth questioning.

📈 Competitive channel benchmarking

Track your own channel alongside your competitive set in a single run. Comparing totalVideos against totalViews shows who is getting more from less, and repeating the run on a schedule turns the comparison into growth curves. country adds the geographic dimension when your competitors publish from different markets.

🗄️ Creator database building

Media agencies and influencer platforms need structured creator records, not browser bookmarks. The ten flat fields here map directly to a database table, with channelId as the primary key, thumbnail for the UI, description for search, and the three count fields for filtering and ranking.

📊 Campaign reporting and measurement

Capture channel statistics before a campaign launches and again after it ends. The change in totalSubscribers and totalViews over the period gives an attributable delta for partner channels, which is a far more concrete reporting artefact than platform-supplied impressions alone.

🌍 Market and language expansion research

The country field lets you segment a creator list geographically, and description reveals content language and positioning. Together they support decisions about which markets already have strong creator coverage in your category and which are underserved.

📉 Channel growth and cadence analysis

publishedAt and totalVideos together give upload cadence — total videos divided by channel age. A channel publishing weekly for five years is a different operational proposition from one that published two hundred videos in six months. Combined with average views per video, this separates sustainable creators from short bursts.

🔬 Content strategy research

Studying the top channels in your niche starts with knowing which they are. Rank a candidate list by totalViews rather than totalSubscribers to find who genuinely commands attention, then read their description fields for how they position themselves. The ranking difference between the two metrics is itself informative.

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⚙️ Tips for Better YouTube Channel Scraping Results

• Use channel URLs, not video or playlist URLs. This is the single most common cause of empty results. A /watch?v= or /shorts/ URL is not a channel page.
• Prefer /channel/UC... URLs for long-term lists. Handles can be changed by their owners; channel ID URLs cannot, so a stored list built on them will not rot.
• Key your storage on channelId. Display titles change with rebrands. Using the ID as your primary key means a rebrand updates a record rather than creating a duplicate.
• Batch large lists. Splitting a thousand channels into runs of a few hundred keeps runtime manageable and gives you usable partial results sooner.
• Re-run on a schedule to build a time series. A single snapshot tells you size; repeated snapshots tell you trajectory, which is what most decisions actually depend on.
• Treat nulls as "not published" rather than zero. Channels can hide their subscriber count. A null in totalSubscribers is a configuration choice by the creator, not an audience of zero, and averaging it as zero will skew your analysis.

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🛠️ Troubleshooting

A channel returned null values for the statistics. The most likely cause is that the channel has hidden its subscriber count, which YouTube allows. It can also happen when the about-page data is not present in the page response. Verify by opening the channel page and checking whether the counts are publicly displayed.

The run returned nothing for a URL I supplied. Check the URL format. Video, playlist and shorts URLs will not produce channel statistics. Also confirm the channel still exists — deleted, terminated and renamed channels will not resolve.

Why is country empty for some channels? Country is an optional field on a YouTube channel's about page. Many creators leave it unset, in which case the scraper returns null rather than guessing.

Subscriber counts look rounded. YouTube itself rounds publicly displayed subscriber counts above a certain threshold. The scraper expands the abbreviated display value into a full integer, but it cannot recover precision YouTube does not publish. Treat large counts as approximate by design.

A run failed partway through a large batch. Apify writes items to the dataset as they are produced, so results collected before the failure are still available in the run's dataset. Export what completed, then re-run the remaining URLs in a smaller batch.

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❓ Frequently Asked Questions About YouTube Channel Statistics Scraping

What does the YouTube channel statistics scraper collect? Subscriber count, total views, video count, channel ID, title, creation date, country code, description and avatar URL for each public YouTube channel URL you supply.

Do I need a YouTube Data API key? No. The actor reads public channel pages directly, so there is no API key, Google Cloud project or quota to manage.

What URL formats are accepted? Channel URLs in handle format (https://www.youtube.com/@name) and channel ID format (https://www.youtube.com/channel/UC...). Custom channel URLs generally work too. Video and playlist URLs do not.

How many channels can I scrape in one run? There is no fixed limit in the input schema. Runtime is the practical constraint, so batches of a few hundred keep runs responsive.

Are the subscriber counts exact? They are as exact as YouTube publishes. YouTube rounds large subscriber counts in its public display, and the scraper expands that rounded value into an integer. It cannot recover precision that YouTube does not show.

Why does the scraper return integers when YouTube shows "1.2M"? Because abbreviated strings cannot be sorted, averaged or compared. The actor expands them so totalSubscribers, totalViews and totalVideos are ready for computation.

Can I get individual video statistics? No. This actor returns channel-level statistics only. The output fields are limited to the ten listed above.

What is channelId and why should I store it? It is YouTube's canonical, permanent identifier for the channel. Unlike handles and display titles, it never changes, which makes it the correct primary key for any stored creator dataset.

Do I need to configure proxies? No. Proxy rotation is handled automatically by the actor. There is no proxy input in the schema.

Can I track channel growth over time? Yes, by scheduling repeated runs and storing each snapshot keyed on channelId. The actor returns point-in-time values; the time series is something you build by running it regularly.

Why is description sometimes empty? Because the creator has not written one. The field reflects what is published on the channel's about page.

What format is publishedAt in? It is normalised from YouTube's localised join-date text into an ISO-style date value, so it can be parsed and sorted without locale-specific handling.

Can I export the results to Google Sheets? Yes. Apify datasets export to CSV, Excel, JSON, XML and HTML, and can be pushed to Google Sheets through the API, Zapier or Make.

How do I calculate engagement from this data? The most useful derived metric is totalViews divided by totalVideos — average views per video. A views-to-subscribers ratio is a further rough proxy. Neither is a true engagement rate, which would require per-video interaction data.

Is scraping YouTube channel statistics allowed? The actor collects only information that YouTube displays publicly without login. You remain responsible for complying with YouTube's terms of service and with applicable data protection law in how you store and use the results.

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🆘 Support & Feedback

If a channel is not resolving, statistics look wrong, or a run fails, please open a report on the Issues tab with the channel URLs involved and the run ID.

For custom work — additional channel fields, video-level data, scheduled monitoring pipelines, or a private build for your team — email scraperhubapi@gmail.com with your requirements.

If this YouTube channel statistics scraper is useful, please leave a review on the actor page. Feedback directly shapes which features get added next.

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⚖️ Disclaimer

This YouTube channel statistics scraper collects only publicly available channel information that YouTube displays without authentication. It does not log into YouTube, use account credentials or session cookies, or access private analytics, unlisted content or creator dashboards.

Channel descriptions and profile data may contain personal information about identifiable individuals, particularly for independent creators. Where that applies, GDPR, UK GDPR, CCPA and comparable privacy regimes govern your processing, and you are responsible for establishing a lawful basis, providing any required notices, and honouring erasure requests. You are also responsible for complying with YouTube's terms of service, including any restrictions on the storage, redistribution or commercial reuse of platform data and thumbnail imagery.

To request removal of specific data collected by this actor, email scraperhubapi@gmail.com with the details.