seo-performance-review

name

seo-performance-review

description

Applies to Mini Diarium's marketing site (`website/`) and its SEO data under `docs/seo/`. Use this recurring, data-driven review when the user has fresh (or wants to pull) Google Search Console / Bing Webmaster performance exports and asks to turn them into ranked, actionable recommendations. Triggers include "SEO performance review," "GSC data," "Search Console export," "Bing keyword report," "how are we ranking now," "what should I write next," "SEO content briefs," "striking distance," "CTR gaps," "update the SEO action plan," or "run the SEO cycle." This is distinct from `seo-audit` (technical on-page auditing): this skill analyzes performance data over time and produces content briefs and an updated action plan. If the user wants a technical/on-page audit instead, use `seo-audit`.

SEO Performance Review

You convert each new Google Search Console + Bing Webmaster export into ranked, actionable recommendations for Mini Diarium. This is a performance-data skill, not an on-page audit. For technical/on-page issues use seo-audit. The two are complementary and share the docs/seo/product-marketing-context.md brand context.

Cadence: recommend bi-weekly at the current traffic (~455 Google clicks / quarter). Weekly is noise; GSC also lags 2-3 days. Do not run more often than the data can support.

Step 0 - Read context first

Read, in this order, before touching data:

1. docs/seo/product-marketing-context.md - brand, ICP, owned topic, the password/lock accuracy guardrail.
2. docs/seo/STRATEGY.md - the analysis framework, the keyword & topic-cluster map, the budget model (transfer/freeze/flip), and the measurement regime this skill executes. The cluster map in STRATEGY.md §3 is the scoring rubric for topical coverage.
3. docs/seo/action-plan.md - the live fix queue and the hypothesis log you will update.
4. The previous docs/seo/STATUS_REPORT_*.md (most recent by date) - the prior snapshot you compare against for movement.

Do not re-derive the strategy. Apply it.

Step 1 - Locate the latest exports (by pattern, never hardcoded names)

Exports live under docs/seo/performance/, one dated subfolder per cycle: docs/seo/performance/<YYYY-MM-DD>/, holding every file for that pull under its original downloaded filename. Match by filename pattern within the newest dated folder, never hardcode names — the pattern already changed once (Bing renamed the overview file), and zips are kept unextracted. Expect up to five files per cycle:

• GSC main export — *-Performance-on-Search-<date>.zip (not *Generative-AI*): contains Queries.csv, Pages.csv, Countries.csv, Devices.csv, Chart.csv, Filters.csv, Search appearance.csv. Extract to a temp dir to read; do not commit the extraction — the zip as downloaded is the tracked copy.
• GSC AI Overview export — *-Performance-on-Search-Generative-AI-Features-<date>.zip: same shape minus Queries.csv (Google does not break this report out by query). Impressions-only — no clicks/CTR/position. See Step 3.
• Bing overview CSV — *SearchPerformanceOverview*.csv (daily clicks/impressions/CTR).
• Bing query-level CSV — *KeywordReport*.csv (per-keyword impressions/clicks/CTR/position).
• Bing AI/Copilot citations CSV — *AIPerformanceOverviewStats*.csv (daily Citations / Cited Pages counts). See Step 3.

A folder may also hold stray non-export files (e.g. leftover placeholder text files from manual reorganization) — ignore anything that doesn't match these patterns rather than erroring, but flag unrecognized files to the user instead of silently treating them as data.

Older cycles (pre-2026-08) may still use the legacy layout: GSC CSVs extracted into a nested google-search-console_<date>/ folder, Bing CSVs loose directly under docs/seo/performance/ with no dated wrapper, and no AI-performance exports at all. Treat those as historical — read them for the prior-cycle comparison in Step 2/3, but do not rewrite them into the new layout.

Find the newest dated folder and the immediately prior one (the last STATUS_REPORT names which cycle it came from). If the newest export is older than ~3 weeks, it is stale: guide the user to pull fresh data before analyzing (Step 1a). Do not analyze stale data silently.

Step 1a - Guide a fresh pull when stale

If exports are stale or missing, walk the user through it (this is manual; the skill cannot authenticate). Save everything under one new docs/seo/performance/<today>/ folder, original filenames, zips left unextracted:

• Google Search Console (search.google.com/search-console): Performance > Search results > set date range to Last 3 months > Export > download the zip. Then repeat with the AI Overview filter applied (Search appearance > AI Overview, or the "Generative AI Features" report if offered directly) > Export > download that second zip.
• Bing Webmaster Tools (bing.com/webmasters): Search Performance > export the overview CSV; then the Keyword report > export the query-level CSV; then the AI / Copilot performance view > export the citations CSV.

Step 2 - Run the analysis framework, per engine

Execute the measurement regime from STRATEGY.md §5 for both engines. Respect the GSC caveats: position is an average, data is sampled (low-impression rows dropped), reporting lags 2-3 days. Aggregate low-impression rows before drawing conclusions; single-digit-impression rows are statistically fragile.

Produce these tables (Google from Queries.csv/Pages.csv, Bing from KeywordReport):

1. Branded vs non-branded split. Branded = "mini diarium" and close variants. Report the clicks share and whether generic demand is being captured.
2. Striking distance (position ~8-20 with real impressions). These are the near-term rank wins. Rank them by impressions.
3. CTR gap (high-impression / low-CTR relative to position). These are the title/meta levers. A page at position ~7 with sub-2% CTR is a flag.
4. Topical-coverage score against the cluster map (STRATEGY.md §3). For each cluster, note the owning page, its position, and whether a gap exists (demand with no strong owning page). Prioritize procedural/comparison gaps (highest LLM absorption).
5. Movement vs the previous snapshot. For the tracked queries/pages, note direction of change. This validates the prior cycle's hypotheses (see the hypothesis log).
6. Google-vs-Bing divergence check. Bing is Windows/PC-first and surfaces predecessor ("mini diary" successor) and feature-intent ("does diarium have a password", "offline encrypted diary") demand that Google under-reports. Every recommendation must account for both engines: Google = topic/positioning terms; Bing = platform + successor + feature intent.

Step 3 - GEO citation check

Since 2026-08, two real measured data sources exist per cycle (Step 1) and are the primary signal for the engines they cover — prefer them over the manual spot-check where they overlap:

• Google AI Overviews — the AI-Overview zip's Pages.csv (which URLs surfaced in an AI Overview and how often, impressions-only) and Chart.csv (daily trend). No query breakdown and no clicks/CTR/position — Google does not expose that for this surface. Compare a page's AI-Overview impressions against its total impressions in the main export's Pages.csv to see what share of its visibility is AI-Overview-driven.
• Bing / Copilot — the *AIPerformanceOverviewStats*.csv's daily Citations and Cited Pages counts. A direct, comparable-cycle-over-cycle citation-volume KPI.

Still run the fixed ~30-query set in references/geo-citation-queries.md for ChatGPT and Perplexity, which publish no exportable performance data:

• Attempt automation with the available web/browser tools where possible (e.g. Perplexity via the browser tool). Record, per engine and per query: (a) whether mini-diarium.com is cited, and (b) whether the answer language was absorbed (the answer reflects the site's framing).
• Fall back to a manual checklist when a platform cannot be automated (most chat UIs). Present the query set as a checklist for the user to run and paste back.
• Also use the spot-check to sanity-check which queries are plausibly driving the Google/Bing AI numbers, since neither export breaks out by query.

Report all four engines together. This is a separate KPI from GSC ranking (STRATEGY.md §5). Do not overstate: the Google/Bing counts are real but still small-sample at this traffic volume, and the ChatGPT/Perplexity spot-check stays a directional baseline, not a precise metric.

Step 4 - Output prioritized content briefs (do not auto-draft)

For each recommended new or refreshed post, output a content brief using references/content-brief-template.md. Rank briefs by expected leverage (impressions x CTR-gap or striking-distance proximity). Each brief:

• Target query + cluster placement (from STRATEGY.md §3).
• Current position / impressions / engine.
• Working title (<=60 chars, click-worthy, not a feature list).
• BLUF (50-80 words, self-contained, names products/trade-off/constraint) for BLUF_MAP.
• H2 outline (each section a distinct purpose; include H2/H3 Q&A for question intent).
• Required internal links (>=2 of /encrypted-journal/, /compare/, related posts).
• Any accuracy guardrails that apply (e.g. the password/lock rule for that cluster).

Do not write the post. Hand the brief to the blog workflow (website/CLAUDE.md) so the human/author controls voice per WRITING_STYLE.md and the AI-writing rules. Also decide, for existing pages, refresh vs new: if a page already owns the cluster (e.g. mini-diary-alternative for predecessor demand), recommend strengthening it rather than a new post.

Step 5 - Update the action plan and hypothesis log

1. Write a new dated status report if the user wants a full snapshot: docs/seo/STATUS_REPORT_<YYYY-MM>.md (follow the structure of the existing one). Otherwise update the existing snapshot's "movement" notes.
2. Update docs/seo/action-plan.md: mark completed items, re-rank open items against the new data, add new items (with file/location, exact change, expected effect, verification command).
3. Append to the hypothesis log in action-plan.md: validate last cycle's hypotheses by directional movement (we cannot prove causation at this traffic scale), and record this cycle's changes as new hypotheses with expected direction. Append, never rewrite history.
4. If the cluster map's positions have shifted materially, note it so STRATEGY.md §3 can be refreshed (positions there are a point-in-time snapshot).

Guardrails

• Never auto-draft blog posts. Produce briefs; the author writes.
• Respect the password/lock accuracy guardrail (docs/seo/product-marketing-context.md, read in Step 0) in any brief for the secure/password cluster: whole-journal AES-256-GCM + per-entry edit-lock, never per-entry encryption.
• Honest about scale. ~455 clicks/quarter is far below the ~500k monthly visitors needed for valid split testing. Report directional signals and hypotheses, not causal claims.
• Freeze non-transferring signals. Do not recommend keyword-density, anchor-text, paid-link velocity, or SERP-feature chasing work (STRATEGY.md §4).
• This skill reads and writes docs/seo/; it does not touch website/ HTML directly. On-site changes go through the blog/docs generators and the action plan.

References

• references/geo-citation-queries.md - the fixed ~30-query GEO citation spot-check set, grouped by cluster.
• references/content-brief-template.md - the content brief hand-off template.