--- name: rampstackco/seo-traffic-diagnosis source: https://app.decimal.ai/s/rampstackco-seo-traffic-diagnosis@2/SKILL.md source_sha256: 591aa3de89c6 --- # SEO Traffic Diagnosis Diagnose why organic traffic moved (down, flat, or unexpectedly up) using Ahrefs MCP combined with Search Console and analytics data. Stack-agnostic. Produces a root-cause diagnosis and an action plan. --- ## When to use - Organic traffic dropped sharply - Organic traffic has been flat for months despite content investment - After a known Google algorithm update - After a migration, replatform, or domain change - After a deploy that touched routing, redirects, or rendering - When a competitor is visibly taking organic share - When a single page dropped from a ranked position - When stakeholders need an explanation, fast ## When NOT to use - Routine performance reporting (use `analytics-strategy`) - Pre-emptive content planning (use `seo-content-gap-audit`) - Backlink-only investigations (use `seo-backlink-audit`) - Technical issue triage outside of traffic concerns (use `seo-site-health-audit`) --- ## Required inputs - Description of the symptom (what changed, when, magnitude) - Date the change started (best estimate) - Recent SEO history: deploys, migrations, content changes, link campaigns - Access to Ahrefs MCP, Search Console, and analytics - Confirmation the change is real (not a tracking artifact) --- ## The framework: 5 layers of diagnosis A traffic change has one or more root causes. Move through the layers in order. Stop when you have enough evidence. ### Layer 1: Confirm the change is real Before diagnosing, rule out: - Tracking gaps (analytics outages, tag manager issues) - Bot traffic changes - Reporting comparison errors (different date ranges, wrong segment) - Seasonality (compare year-over-year, not just month-over-month) - Holiday or weekday effects Cross-check Search Console clicks against analytics organic sessions. Significant divergence often points to a tracking issue, not a real traffic change. ### Layer 2: Localize the change Where is the change happening? Segment by: - Country and language - Device (mobile, desktop, tablet) - Page or section (homepage, blog, product, category) - Query type (branded vs non-branded) - Landing page A change in one segment requires different diagnosis than a change everywhere. | Pattern | Likely cause | | --- | --- | | One country dropped | Local algorithm update, hreflang issue, geo redirect issue | | Mobile dropped, desktop flat | Mobile usability or page speed regression | | One section dropped | Topical algorithm update or section-specific quality issue | | Branded queries dropped | Brand-level issue: site outage, reputation, manual action | | Non-branded dropped | Algorithmic ranking issue | | Single page dropped | Page-level issue: content, technical, or competitive | | Sitewide dropped | Sitewide issue: penalty, technical, migration, or algorithm | ### Layer 3: Page-level analysis For affected pages, audit: - Position changes per ranked keyword (Ahrefs Rank Tracker history) - SERP composition changes (more ads, AI overviews, featured snippets, video) - Click-through rate changes - Index status (Search Console coverage) - Crawl errors and accessibility - Recent content changes - Internal link changes - Backlink changes (lost links, redirect chains) A page can lose traffic without losing rank if SERP composition changed. ### Layer 4: Technical analysis Did anything break technically? Check: - Robots.txt changes - Canonical tag changes - Meta robots changes (accidental noindex) - Redirect chains and loops - Render issues (especially for JS-heavy frameworks) - Site speed regressions - Hreflang errors - Sitemap freshness - HTTP status codes (4xx, 5xx spikes) - Server log evidence of crawl behavior changes Recent deploys are the prime suspect. Compare deploy dates to traffic change dates. ### Layer 5: External analysis If layers 1-4 do not explain the change, look outward. - Algorithm update calendar (cross-reference timing) - Competitor moves (new content, new SERP features they captured) - Industry trend (declining search demand for the topic) - Manual action (Search Console security and manual actions) - Negative SEO (sudden link velocity changes) External-factor diagnosis benefits from competitive context: did your traffic drop while competitors held steady (suggests an algorithm-specific issue), or did the entire vertical lose ground (suggests a user-behavior shift)? Similarweb shows competitor traffic trends; Ahrefs shows competitor SERP movement; pairing both surfaces whether the issue is yours alone or the category's. --- ## Workflow 1. **Confirm the symptom.** Get exact dates, magnitude, segment if known. 2. **Validate the data.** Layer 1 checks. Rule out tracking and seasonality. 3. **Localize.** Layer 2. Segment until the pattern is clear. 4. **Page-level dive.** Layer 3 on the most affected pages. 5. **Technical check.** Layer 4. Recent deploys, robots, canonicals, redirects. 6. **External check.** Layer 5. Algorithm updates, competitors, industry. 7. **Build the hypothesis.** State the cause as a single sentence. 8. **Validate the hypothesis.** Find the evidence that confirms or refutes it. See [`references/diagnosis-checklist.md`](references/diagnosis-checklist.md). 9. **Action plan.** Specific fixes mapped to specific evidence. 10. **Communicate.** Write up the diagnosis. Stakeholders want clarity, not exhaustive analysis. --- ## Failure patterns - **Jumping to algorithm update.** "It must be the algorithm" is the lazy answer. Eliminate technical and page-level causes first. - **Solving the wrong problem.** A drop diagnosed as "content quality" when the real cause was an accidental noindex on a deploy. Validate the hypothesis before fixing. - **No baseline for "normal."** Without a baseline, every fluctuation looks alarming. Establish what normal noise looks like before reacting. - **Treating one page as the site.** Site-wide and page-level diagnoses are different. Confirm scope first. - **Ignoring branded vs non-branded.** A drop in branded queries means a brand-level problem. A drop in non-branded means an SEO problem. Different teams own them. - **Comparing wrong date ranges.** Comparing 28 days to the previous 28 days during a holiday distorts the picture. Use year-over-year for seasonal businesses. - **Stopping at correlation.** A deploy and a drop on the same day is a strong correlation, not proof. Find the mechanism. - **Single-source diagnosis.** Ahrefs sees position. Search Console sees clicks and queries. Analytics sees behavior. Logs see crawl. Use them together. - **Premature reassurance.** Telling stakeholders "it is just an algorithm update, will recover" without evidence sets up a worse conversation later. --- ## Output format A diagnosis document with: 1. **Summary.** What changed, when, magnitude, root cause in one paragraph. 2. **The symptom.** Charts and segment breakdowns. 3. **Layer-by-layer findings.** What each layer ruled in or out. 4. **Root cause hypothesis.** Single statement with evidence. 5. **Action plan.** Ordered fixes with owners and timelines. 6. **Recovery forecast.** Realistic expectations on timeline and ceiling. 7. **Monitoring plan.** What to watch for confirmation of recovery. Length: 4-10 pages. Stakeholders read this fast. --- ## If required data is unavailable This skill's output depends on data, measurements, or tool results it cannot generate on its own. When a required input, tool, or data source is unavailable or unverifiable, the sanctioned output is the deliverable with the gap stated: what was needed, what was actually obtained or verified, and which parts of the output are affected. Fabricating, estimating, or interpolating a required number to complete the deliverable is never sanctioned. A stated gap is a complete answer. --- ## Reference files - [`references/diagnosis-checklist.md`](references/diagnosis-checklist.md) - Layer-by-layer diagnostic checklist with the specific data to pull at each layer and how to interpret each signal.