Social SEO
Make content findable when people search, not just visible when the feed happens to show it. In
2026 every social platform is a search engine, and search is the highest-intent, most evergreen
discovery there is.
Four truths shape everything:
- All social platforms are search engines (TikTok/IG/YouTube/Pinterest/LinkedIn) — and people
search different platforms for different intents. If you only optimize for the feed, you're
invisible to people actively looking.
- Keywords, not hashtags, are the lever. Write for the search bar first; hashtags are a minor
category signal → .
- Search optimization doubles as recommendation optimization — the keywords that get you found in
search are the same signals the algorithm uses to categorize you for the right feed/FYP audience.
- SEO turns posts into evergreen assets — a search-optimized post keeps getting found for months;
a feed post dies in ~48h.
(Full model + the AI-search/GEO boundary:
references/why-social-search.md
.)
Step 0 — Read the foundation + the goal
Load
and
(their exact search language matters). Get the
platform(s)
and what the user wants to be
found for.
Step 1 — Keyword research (real demand, never invented)
Find the terms people actually search via
platform autocomplete,
"others searched for",
related searches,
comments, audience language, and the user's
native search analytics (+ tools
like TikTok Creative Center / VidIQ).
The agent can't pull live search volumes — never fabricate
numbers; give the method and work from intent/specificity. Favor long-tail, intent-rich queries you
can genuinely answer. See
references/keyword-research-and-technique.md
.
Step 2 — Place keywords across the platform's SEO surface
Each platform indexes different things — optimize the right ones (full per-platform guide in
references/platform-seo-surfaces.md
):
- TikTok — spoken audio (transcribed) + on-screen text + caption (the triple mention).
- Instagram — caption + the searchable name/display field + bio + alt text + captioned Reels.
- YouTube — keyword-led title + ~200–300w description + transcript/captions + chapters.
- Pinterest — keyword title + description + board names + alt (hashtags deprecated there).
- LinkedIn — searchable headline/About + on-topic post keywords → .
- Cross-cutting — subtitles, alt text, descriptive file names, a consistent branded handle.
Step 3 — The on-content technique
Lead with keywords, support with hashtags. State the primary phrase in
natural language, early,
once or twice; align audio + on-screen + caption to
one search intent; add 3–5 niche hashtags.
Never keyword-stuff (spam dilutes your topical signal). Resolve the search-vs-feed tension (clarity
vs hook) deliberately. See
references/keyword-research-and-technique.md
.
Step 4 — Build topical clusters (evergreen authority)
One post rarely owns a query.
Cluster evergreen content around a pillar topic so you become the
answer/authority — which compounds
and sharpens recommendation categorization. Map a
pillar → a keyword cluster → many evergreen posts.
Step 5 — Optimize the profile as a search asset
The
name/display field, handle, headline/bio should carry the searchable keyword/category (not just
a clever brand line). This is the
searchability lens —
owns the
conversion
lens; both matter. Public profiles/content are increasingly
Google-indexable too.
Step 6 — Measure (honestly) + hand off GEO
Track
discoverability: impressions from search, the search terms that found you, profile visits
from non-followers, saves, evergreen-post growth — via
native platform search analytics (+ Search
Console/UTMs).
No WoopSocial analytics. For getting cited by
AI search/LLMs (GEO), hand off to
— related but separate.
Orchestration map
social-seo sets the discovery layer; it routes to / is routed from:
(hashtag
specifics) ·
(adds the keyword layer) ·
(conversion lens) ·
(clusters) ·
/
/
(search as a
growth pillar) ·
(GEO hand-off) ·
(publish).
Quality bar — self-check
- Did I do real keyword research (autocomplete/native analytics) and avoid inventing volumes?
- Did I optimize the platform-specific indexed surfaces (not one generic answer)?
- Did I use lead-with-keywords + the triple mention, in natural language (no stuffing)?
- Did I think in evergreen clusters / topical authority, and note the search = recommendation
payoff?
- Did I treat the profile as a search asset, route hashtags to , and hand GEO
to ?
- Native-search-insights measurement, no WoopSocial analytics, searchability not guaranteed
rankings?
Edge cases & pushback
- "Give me exact search volumes" → can't pull live volume; show the research method; don't
fabricate.
- "Stuff every keyword + 30 hashtags" → refuse; spam dilutes the signal; natural language + a few
niche tags.
- "I optimized one post, done" → build a cluster; one post rarely owns a query.
- "Just use trending hashtags" → hashtags categorize, keywords get found → .
- "Make ChatGPT/Google-AI cite me" → that's GEO → .
- "Which post ranks best?" → native platform search insights; no WoopSocial analytics.
- Clever-but-vague title → keep the searchable phrase; add intrigue after the keyword.
Related skills
- , — the search language and positioning.
- , — single-platform search depth (route platform-specific asks there).
- — the hashtag layer (a minor signal); — caption craft.
- — profile as conversion (this skill = profile as search).
- — pillars become keyword clusters; the growth skills lean on search.
- — the AI-search/LLM-citation (GEO) hand-off; — publish.
References
references/why-social-search.md
references/platform-seo-surfaces.md
references/keyword-research-and-technique.md
- — worked optimizations per platform + a cluster plan + honest scope.