📺 YouTube Channel Monetization Detector — Sponsor mentions, member tiers, merch, Patreon & affiliate signal extraction

The YouTube Channel Monetization Detector reads a YouTube channel's public surface — About tab, recent video descriptions, pinned comments, channel-banner links, member perks, and Store/merch shelf — and classifies how the creator monetizes. Output rows tell you whether a channel runs sponsor reads, joins affiliate programs (Amazon, ShareASale, Impact), accepts crypto tips, runs Patreon/Ko-fi, sells merch, and which specific brand sponsors appear most often in their last N videos.

Why YouTube Channel Monetization Detector Beats Social Blade Premium, VidIQ, and TubeBuddy

Source	Price	What you get
Social Blade Premium	$39+/mo	Estimates ad revenue only, no sponsor-mention detection
VidIQ	$10-79/mo	Keyword & SEO focus, no monetization signal extraction
TubeBuddy	$5-50/mo	Channel optimization, not monetization mining
Noxinfluencer	Free tier + paid	Manual lookup, no API for bulk classification
NexGenData YouTube Monetization Detector	PPE per channel	Sponsor mentions, member tiers, merch links, Patreon & affiliate signals in one JSON row

What You Get

• Channel handle + canonical URL + channel ID
• Subscriber count, total video count, total view count
• Has YouTube Memberships enabled (boolean) + tier prices (when visible)
• Has Super Thanks / Super Chat / Super Stickers enabled
• Has Merch Shelf enabled + linked storefront URL (Spring, Fourthwall, Shopify, etc.)
• Patreon URL (when linked) + tier names (when public)
• Ko-fi / Buy Me a Coffee URL (when linked)
• Affiliate-program signals: Amazon /shop link, ShareASale, Impact, RewardStyle, etc.
• Detected brand sponsors from last 20 video descriptions (top 10 with mention count)
• Sponsor disclosure rate (videos with 'sponsored by' / 'this video is brought to you by')
• Email contact (when published in About), business inquiry text
• Total external-link slots used + each linked domain

Use Cases

• Sponsor-prospecting (B2B) — find creators in your niche who already accept sponsor reads, so your outbound is qualified-warm not cold.
• Influencer-marketing agency — auto-classify a 10K-channel roster by monetization mix to know which channels accept brand deals vs only YPP ad-rev.
• Affiliate-program recruiting — identify creators already running RewardStyle / Impact / Amazon Associates → invite them to your program.
• MCN (multi-channel network) prospecting — build a target list of mid-tier (10K-500K) channels with active Memberships → pitch creator-services bundles.
• Brand competitive intel — which channels does my biggest competitor sponsor? Pull their last 30 videos, extract sponsor lines, dedupe.
• Creator-tool sales (e.g. editing SaaS, thumbnail tools) — segment channels by 'has merch + Patreon' (likely full-time) vs 'only ad-rev' (likely hobbyist) for ICP targeting.
• Investor / acquisition research — score a creator-business acquisition target by counting independent revenue streams (sponsors + merch + members + Patreon).

Quick Start

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "channelUrls": [
        "https://www.youtube.com/@MarquesBrownlee",
        "https://www.youtube.com/@LinusTechTips"
    ],
    "videosToSample": 20
}

run = client.actor("nexgendata/youtube-channel-monetization-detector").call(run_input=run_input)

# Iterate results
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# Or fetch all in one go
items = list(client.dataset(run["defaultDatasetId"]).iterate_items())
print(f"Got {len(items)} rows")

You can also run from the Apify CLI:

apify call nexgendata/youtube-channel-monetization-detector --input='{
    "channelUrls": [
        "https://www.youtube.com/@MarquesBrownlee",
        "https://www.youtube.com/@LinusTechTips"
    ],
    "videosToSample": 20
}'

Or from the web console: open the actor page on Apify, click Try for free, paste the input JSON, hit Run. Results stream into the dataset which you can export as JSON / JSONL / CSV / Excel / HTML.

Scheduling

This actor pairs cleanly with Apify Scheduler (built into the platform) — schedule it hourly / daily / cron-style and dedupe results into your warehouse on the stable primary-key fields documented above. Webhook outputs are supported, so you can fire a Slack / Zapier / Make / n8n / your-own-API call the moment new rows materialize.

Integration patterns

• CRM enrichment: pipe rows directly into HubSpot / Salesforce / Pipedrive via Zapier or Make
• Warehouse: append to BigQuery / Snowflake / Postgres on a daily schedule via Apify → S3 → warehouse ingest
• LLM-ready RAG: each row is already JSON-flat; embed the plain-text body field and store in pgvector / Pinecone / Weaviate
• Slack alerts: filter by your trigger keyword and fire a Slack webhook for matches in real-time

Pricing

This actor runs on Apify's pay-per-event (PPE) model — you pay only for results, not run-time:

• $0.05 per channel report — the primary event (one charge per row pushed to the dataset)
• 0.00005 USD per actor-start GB-event — actor start cost (one-time per run, sub-cent at typical memory)

No subscriptions, no minimums, no per-CPU-second charges. Apify's $5/month free tier covers most experiments. Browse 200+ buyer-intent actors at https://apify.com/nexgendata?fpr=2ayu9b

Cost worked example

A daily scheduled run pulling 500 fresh rows costs roughly:

• 500 rows × primary-event price (~$0.04-0.05) = $20-25
• 1 actor start × ~$0.00005 = negligible

So ~$20-25 per 500-row daily run, or ~$0.04-0.05 per row all-in. There are no surprise compute, storage, or proxy add-ons — proxy rotation is bundled into the per-row price.

Why pay-per-event beats time-based pricing

• Predictable: you know your cost from row count before the run starts
• Failure-safe: if a target site changes its HTML and the actor returns 0 rows, you pay 0 (vs paying for the CPU-seconds anyway under time-based pricing)
• Easy to attribute: 1 row = 1 unit cost, so per-customer / per-pipeline cost accounting is trivial

Sister Actors in the NexGenData Fleet

Use case	Actor
Pull YouTube comments by video or channel	youtube-comments-scraper
Detect creator brands hiring (sponsorship intent)	hiring-signal-detector
Niche-down tech-creator targeting	github-trending-repos
Solo-creator monetization data	indie-hackers-products-tracker
Find creator-tools launches	product-hunt-launches-scraper
B2B sponsor outreach lead list	b2b-leads-finder

(All sister actors share the same PPE billing and Apify-standard JSON output, so you can compose multi-step pipelines without rewriting input/output adapters.)

FAQ

Q: How fresh is the data?

A: Each run pulls live channel data — About tab, video descriptions, Store shelf — at execution time.

Q: How many videos does it sample for sponsor detection?

A: Default is the last 20 uploads; configurable up to 100.

Q: Does it use the YouTube Data API?

A: No — it reads public channel pages with rotating residential proxies, so you don't burn YouTube Data API quota.

Q: Will I hit rate limits?

A: At typical volumes (≤5K channels/run) we have not observed blocks. Pace your runs if scanning >10K channels/day.

Q: Can it detect sponsors inside the video itself (audio)?

A: No — only what is written in the description, pinned comment, or channel banner. Audio-sponsor detection is a roadmap item; today's detection is description-text-based.

Q: Output format?

A: JSON, CSV, JSONL, Excel via Apify dataset export. Schema is stable; new fields are additive only.

Schema Stability & Versioning

This actor follows NexGenData's additive-only schema contract:

• New fields may be added at any time — they will simply appear as new keys in the JSON output, defaulting to null for older runs.
• Existing fields are never renamed or removed without a major-version bump and an advance changelog notice.
• Field semantics (units, timezones, value-sets) are never silently changed — if we need to change semantics, we add a new field with the new name and deprecate (but keep) the old one for at least 90 days.

This means you can build production pipelines on this actor and not worry about a Tuesday breaking a Friday's ETL job. If you spot an unexpected change, reach out via the actor's Apify Issues tab and we'll look at it the same day.

Compliance & Legal

• The actor reads public, unauthenticated pages the same way a logged-out browser does.
• All requests route through Apify's compliant residential-proxy infrastructure with polite rate limiting.
• You are responsible for ensuring your downstream use complies with the target site's Terms of Service, your jurisdiction's data-protection laws (GDPR, CCPA, UK DPA, etc.), and any sector-specific rules (HIPAA, PCI, etc.).
• We do not collect, store, or transmit credentials for the target site.
• Most read-only competitive-intelligence and lead-generation use is widely accepted. Consult counsel before bulk redistribution.

Support

Open an issue on the actor's Apify Issues tab — the NexGenData team responds within one business day. For feature requests (new fields, new input filters), include the use case so we can prioritize on it.

About NexGenData

NexGenData publishes 200+ buyer-intent actors covering SEC filings, YC alumni, Delaware DOC, lead generation, competitive intelligence, stock fundamentals across 30+ exchanges, ATS job boards, real-estate marketplaces, and more. All actors are pay-per-result and share a stable, additive-only JSON schema. Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b

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SEO: 📺 YouTube Monetization Detector — Sponsor & Revenue Signals