Youtube seo keywords

YouTube Keyword & Topic Research (Advanced)

Process

1. Capture seed: keyword, channel URL, or niche description. If only a channel URL is provided, extract 5-10 seed topics from:
   • The channel's top 25 videos by views (title + description entities)
   • The channel's topic IDs from channels.list?part=topicDetails
2. Expand the seed set to 100-300 candidate keywords from first-party sources only (third-party tools like VidIQ, TubeBuddy, Ahrefs, and SocialBlade rate-limit and generate errors — avoid them):
   • YouTube suggest API (https://suggestqueries.google.com/complete/ search?client=firefox&ds=yt&q={seed}) — no key, returns JSON, iterate by appending a-z to the seed for long-tail expansion
   • YouTube Data API search.list?part=snippet&q={seed}&type=video — surface the top 50 ranking titles and mine their titles/tags for co-occurring terms
   • yt-dlp ytsearch50:{seed} as an API-less equivalent
   • Google autocomplete (suggestqueries.google.com/complete/search? client=firefox&q={seed}) for parent-topic discovery
   • User-provided seed list or topic outline
3. Classify intent for each keyword:
   • Informational ("what is ...", "how does ... work")
   • Tutorial ("how to ...", "... tutorial", "step by step")
   • Commercial / Review ("... review", "best ...", "... vs ...")
   • Entertainment (celebrity names, event names, memes)
   • News / Topical (breaking or time-sensitive)
   • Navigational (brand or channel names) → Each intent class maps to a different video format and surface.
4. Classify primary surface:
   • Search-dominant: "how to", "tutorial", long-tail specific queries
   • Browse-dominant: broad topics, personalities, trending
   • Suggested-dominant: sits adjacent to an existing popular video
5. Entity mapping: for each keyword, identify the Knowledge Graph entities involved (people, brands, products, concepts). Group keywords that share entities into topic clusters.
6. Competition analysis per keyword (top 10 SERP):
   • Median subscriber count of ranking channels
   • Median video age (weeks)
   • Median view count
   • Presence of mega channels (>1M subs) in top 3
   • Thumbnail/title quality median (estimate)
   • SERP features (Shorts shelf, mix shelf, promoted result)
7. Seasonality: pull Google Trends 5-year curve per keyword cluster. Classify:
   • Evergreen: flat or slowly rising
   • Seasonal: predictable annual peak (gift guides, tax season)
   • Trending: fast-rising, <6 months of data
   • Decaying: fast-dropping
8. Opportunity scoring (refined formula below)
9. Cluster keywords into 3-6 topic buckets with a pillar + satellites shape optimized for topical authority
10. Content calendar (optional) with pillar cadence and reactive slots

Refined Opportunity Formula

opportunity = (0.30 * log(volume + 1)) +
              (0.25 * (100 - difficulty)) +
              (0.15 * channel_fit) +
              (0.15 * entity_overlap_with_channel) +
              (0.10 * freshness_bonus) +
              (0.05 * session_chain_bonus)

• volume: YouTube monthly searches (estimated — YouTube doesn't expose this directly). Use one of these native-only proxies, in order: (a) YouTube suggest rank depth (keywords that appear at position 1-3 across a-z expansions = high demand); (b) total result count from search.list?q={kw}&type=video + median views of the top 10 as a demand proxy; (c) Google Trends relative interest via WebFetch on trends.google.com/trends/api/explore. Never fabricate a volume number — label it "low/med/high" when the only evidence is ordinal
• difficulty (0-100): derived from competition analysis —

  difficulty = (0.35 * normalize(median_subs)) +
               (0.25 * normalize(median_views)) +
               (0.20 * mega_channel_top3_flag) +
               (0.10 * thumbnail_title_quality) +
               (0.10 * (1 - median_age_weeks / 104))   # newer rankings = easier
  

• channel_fit (0-100): how well the keyword aligns with the channel's existing topical authority
• entity_overlap_with_channel: % of the keyword's entities already covered by the channel's existing content
• freshness_bonus: 10 if Trending, 5 if Seasonal peak within 60 days, 0 if Evergreen, -10 if Decaying
• session_chain_bonus: 5 if the keyword sits adjacent to existing high-performing channel content (suggested-video pathway)

Weights can be adjusted if the user explicitly wants low-competition or high-volume bias.

Data Sources (priority order — first-party only)

1. YouTube suggest API (no key, no rate limits in practice): https://suggestqueries.google.com/complete/search?client=firefox&ds=yt&q={seed} — iterate {seed}{a..z} for long-tail expansion
2. YouTube Data API v3 (search.list, videos.list, channels.list) via YOUTUBE_API_KEY for ranked results, titles, tags, topicDetails
3. yt-dlp ytsearch50:{query} as an API-less equivalent when no key is set or quota is exhausted
4. Google Trends (public WebFetch on trends.google.com) for seasonality and relative interest
5. WebFetch on youtube.com/results?search_query=... for competition analysis when the API is unavailable
6. User-provided seed list or outline

Third-party analytics (VidIQ, TubeBuddy, Ahrefs, SocialBlade, NoxInfluencer) are intentionally excluded — they rate-limit or error. If the user volunteers a CSV from one of these, it is OK to read it, but never instruct the user to go acquire one.

Output

Keyword Sheet

Keyword	Intent	Surface	YT Vol	Difficulty	Fit	Entity%	Trend	Opportunity
how to ...	Tutorial	Search	12k	42	85	90%	Evergreen	78
... vs ...	Commercial	Search	4.2k	55	72	65%	Evergreen	64
... 2026	News	Browse	8k	68	80	50%	Trending	71

Sort by Opportunity descending. Limit to top 30-50.

Topic Clusters (3-6 clusters)

For each cluster, report:

• Theme: one-sentence description
• Shared entities: 5-10 Knowledge Graph entities
• Pillar video: title, format, length, target keyword (highest- opportunity broad keyword in the cluster)
• Satellite videos: 5-10 specific long-tail follow-ups, each with title + target keyword
• Suggested playlist: title + description
• Topical authority contribution: how this cluster strengthens the channel's classification

Intent Mix Chart

Report the intent distribution of the recommended keywords:

Tutorial:       40%  ████████
Commercial:     25%  █████
Informational:  20%  ████
Entertainment:  10%  ██
News:            5%  █

Flag if the mix is mismatched with the channel's current format strength.

Gap vs Channel (when channel URL provided)

• Keywords competitors cover that the channel does not
• Entities competitors own that the channel does not reference
• Format gaps (e.g., no reviews, no tutorials, no comparisons)

Content Calendar (optional, 8-12 weeks)

Alternates:

• Evergreen pillar (every 3-4 weeks): broad, high-opportunity keyword, long-form, binge-playlist anchor
• Topical/reactive slot (weekly): trending or news keyword
• Satellite fill (weekly): specific long-tail serving the pillar

Seasonality Calendar

Report any Seasonal-classified keywords with their peak windows so the user can plan 4-6 weeks ahead of each peak.

Integration

• Hand off top keywords to youtube-seo-optimize for metadata generation
• Hand off cluster plan to youtube-seo-channel for playlist structure
• Hand off competitor-entity gaps to youtube-seo-competitor for deeper analysis

Error Handling

Scenario	Action
No API key AND WebFetch blocked	Fall back to yt-dlp ytsearch50: + suggest API (both key-less); if still failing, ask the user for 5-10 seed keywords directly
API quota exhausted mid-run	Cache partial results, switch remaining expansion to yt-dlp + suggest API, continue
Niche too narrow (no volume data)	Pivot to broader parent topic, report the gap, score as "low demand, qualitative only"
Brand/product name with no search volume	Research category terms and comparison keywords instead
Trending keyword with <2 weeks of data	Flag as unstable; suggest pairing with an evergreen pillar
Google Trends returns empty	Skip seasonality classification for that keyword — do not guess the curve