📊 YouTube Creator Analytics

YouTube Creator Analytics is a YouTube channel analytics scraper that discovers channels by keyword or URL and attaches real performance and growth metrics to every result. It combines a YouTube channel finder with a creator intelligence layer: engagement rate, growth momentum, upload cadence, upload consistency, activity status, niche classification, contactability and a data-confidence score — all computed from public data the scraper actually fetches.

Use it as a YouTube influencer analytics tool, a creator research tool, a YouTube engagement rate calculator, or a lead-generation and outreach dataset builder for marketers, agencies, and analysts.

What it does

1. Discovers channels — via YouTube search keywords and/or direct channel/video URLs.
2. Scrapes each channel's public metadata — name, handle, subscriber count, description, location, join date, lifetime views, video count, and external links.
3. Samples recent videos — the most recent N videos' views, likes, comments and publish dates.
4. Computes analytics from that real data — engagement, momentum, cadence, consistency, activity, niche, contactability, confidence.
5. Filters and sorts — gate the output by subscribers, views, country, recency, or email presence; order by any metric.

Analytics fields (all derived from scraped data)

Field	Meaning	Derived from
subscribersCount	Subscribers as an integer	Scraped subscriber text
channelAgeMonths	Age of the channel in months	Join date
avgViewsPerVideo	Lifetime avg views/video	Lifetime views ÷ video count
avgRecentViews / medianRecentViews	Recent viewership	Recent videos' views
engagementRate	(likes + comments) ÷ views, %	Recent videos
viewsPerSubscriber / recentViewsPerSubscriber	Audience activation	Views + subscribers
momentumRatio / momentumLabel	Recent avg vs lifetime avg (rising/steady/cooling)	Recent + lifetime views
uploadsPerMonth	Upload cadence	Recent publish dates
consistencyScore	0–100 regularity of upload spacing	Recent publish dates
lastUploadDate / daysSinceLastUpload / activityStatus	Recency (active/slowing/dormant)	Recent publish dates
topRecentVideo	Best recent video by views	Recent videos
detectedNiche	Content category label	Keyword + description
contactabilityScore	0–100 outreach readiness	Email + links
analyticsConfidence	high/medium/low signal coverage	Available inputs

There are no estimated earnings, RPM, or sponsorship figures — YouTube does not expose revenue, so any such number would be a model, not data. Every field above is scraped-and-computed and independently verifiable.

Filters & sorting

• minSubscribers, maxSubscribers, minTotalViews — numeric gates.
• country — keep channels whose location contains the given text.
• uploadedWithinDays — keep only recently-active channels.
• requireEmail — keep only channels with a discovered contact email.
• sortBy — subscribers, views, recentViews, engagement, momentum, consistency, or contactability (descending).
• nicheOverride — force the niche label instead of auto-detecting it.

Optional AI enrichment

aiEnhancement (off by default) uses an LLM to refine the niche label and add an audience descriptor and a lead-quality read from the channel description. It is optional because the niche is already keyword-classified. Multi-provider: Anthropic, OpenAI, Google Gemini, xAI Grok, DeepSeek, Perplexity, Mistral (provider auto-detected from the model name). Provide aiApiKey or set the provider's environment variable.

Example input

{
  "keywords": ["python programming"],
  "channelCount": 10,
  "minSubscribers": 10000,
  "uploadedWithinDays": 60,
  "requireEmail": false,
  "sortBy": "engagement",
  "maxRecentVideos": 6
}

Output

One dataset row per channel: the base channel record (name, handle, subscribers, description, email, location, links, join date, lifetime views, video count, URL) plus the additive analytics block and an absolute scrapedAt timestamp. Export as JSON, CSV, or Excel.

How to use

1. Add search keywords and/or channel URLs.
2. Set filters and a sort metric.
3. (Optional) enable AI enrichment with an API key.
4. Run and read results from the dataset.

Compliance

Collect only publicly available data and use it responsibly. If you capture personal contact details (such as emails), follow GDPR and similar regulations and ensure a legitimate business purpose for outreach. Respect platform limits and do not attempt to access private data.