GEO + content audit · Sept 29, 2026 · GSC data: Sept 29, 2025 – Sept 29, 2026
Six prioritized moves for organic and AI search growth. Technical hygiene addressed separately below.
Complete core municipal-workflow pillar pages first, then organize supporting content around them through deliberate internal linking. Focus authority around a small number of commercially relevant subjects rather than disconnected blog production. Content should not just be landing pages or blogs, but also include free lead-gen tools.
Pillar pages are live and cluster pages link to them. GSC shows impressions consolidating around pillar URLs. At least one lead-gen tool is scoped or shipped.
Use GSC to prioritize high-impression pages and queries with suppressed CTR or rankings within striking distance of stronger first-page visibility. Exclude anomalous/bot-driven impression patterns from prioritization.
CTR improves on targeted pages in GSC. Clicks increase on shortlisted queries without proportional impression growth.
Create jurisdiction-specific pages around open-meeting requirements, meeting-minutes workflows and municipal clerk needs. Prioritize states using customer concentration, regulatory specificity and population rather than blindly creating all 50.
Pilot state pages are indexed. GSC shows impressions on jurisdiction-specific queries. At least one page earns first-page ranking within the quarter.
Improve commercially and informationally important pages with concise answer-first passages, descriptive headings, self-contained factual sections, relevant FAQs and appropriate structured data. Do not mechanically turn every heading into a question.
Priority pages contain answer-first passages and FAQs. Schema validates cleanly. Manual LLM testing shows ClerkMinutes appearing in answers for target queries where it currently returns nothing.
Standardize product positioning, features, integrations, pricing, HeyGov relationship and target audience across authoritative pages. Reinforce these facts with appropriate structured data, named expertise, citations and proprietary evidence where available.
Product description is consistent on-site and off-site. Organization schema is live and validates. LLM responses about municipal meeting-minutes software include accurate ClerkMinutes descriptions.
Use repeatable ChatGPT/Claude/Gemini/Perplexity testing as a diagnostic baseline, not the primary KPI. Measure impact through branded GSC activity, qualified organic visibility, self-reported signup attribution and trial volume.
Branded GSC query volume trends up from Sept 2025 baseline. Self-reported organic attribution is trackable. Trial volume correlates with organic click growth.
All traffic is the product's target audience (US municipal government) plus organic international. Non-US clicks are almost all informational, not commercial.
| Country | Clicks | Impressions | CTR | Position |
|---|
UK (97 clicks), Canada (90), Philippines (71): Not buyers. Philippines and UK traffic is likely people in local government admin roles looking for general meeting minutes tooling. They will not convert on a US municipal product.
Serbia (68 clicks, 17% CTR): HeyGov is based in Serbia. This is team/internal traffic.
Netherlands + Germany (18k impressions, near-zero clicks): Part of the bot query traffic. Automated searches triggering impressions with no real intent.
Action: No content changes needed for international traffic. The GEO work targets US government search and LLM queries specifically.
84% of all clicks come from the US. The product is US municipal-only. This ratio is healthy. Non-US impressions are inflating the total impression count without contributing to pipeline.
Run each query in ChatGPT (GPT-4o), Claude (Sonnet), Gemini, and Perplexity. Document whether ClerkMinutes appears and whether the description is accurate. This is the before-state for the Q4 GEO plan.
Status column: ✓ Appears accurately · ~ Appears inaccurately · ✗ Not mentioned · ? Not yet checked
Most LLM-influenced traffic arrives as direct, not referral. GA4 undercounts LLM impact. Prompt-based tools (Profound, Peec, etc.) automate the same flawed methodology. Use the query table below for diagnostic audits — not as a KPI.
Export from GSC: Performance → filter Queries "containing" → clerkminutes → Date range: Aug 1 – today → Export CSV. Drop the file below.
| Query | ChatGPT (GPT-4o) | Claude (Sonnet) | Gemini | Perplexity | Notes / accuracy issues |
|---|
Same 8 queries, same 4 tools, December 2026. Use as directional context alongside GSC brand search volume and trial signup attribution data — not as standalone proof of impact.
Each hub needs a live, well-structured pillar page before spokes can properly reference it.
Priority states for programmatic SEO and LLM citation. Selection criteria: customer concentration + open meeting law specificity + population weight.
| State | Status | Open meeting law | Notes |
|---|
Posts that need review for generic/non-specific content. LLMs deprioritize vague content. So do clerks.
| Page | Impressions | Pos | Quality flag | Action |
|---|