CapstonAI is an AI visibility platform that helps brands track, audit, and optimize their presence in AI-generated answers. It monitors how your brand is mentioned across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews, then provides actionable fixes to improve your share of voice in AI search results.

How does CapstonAI track AI visibility?

CapstonAI sends structured brand queries to multiple large language models (LLMs) on a recurring basis and records whether your brand is mentioned, cited, or recommended. It aggregates these results into a GEO score, a share-of-voice metric, and a citation report.

Which AI models does CapstonAI monitor?

CapstonAI currently monitors ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Perplexity, and Google AI Overviews. Coverage is continuously expanded as new AI search surfaces emerge.

CapstonAI offers a free WordPress plugin that provides basic AI visibility scanning for your site. For full AI visibility tracking, audit reports, automated content fixes, and multi-brand monitoring, the Core Plan is available at $99/month.

How is CapstonAI different from Semrush or Ahrefs?

Semrush and Ahrefs are built for traditional search engine optimization. CapstonAI is purpose-built for the AI search era: it tracks your brand presence inside AI-generated answers from ChatGPT, Claude, Gemini, and Perplexity.

12-Month GEO Roadmap For 2026: Quarter-by-Quarter Plan To AI Search Visibility

12-Month GEO Roadmap for 2026: Quarter-by-Quarter Plan to AI Search Visibility

AI engines now influence 38% of B2B research journeys (Gartner, March 2026) and 27% of D2C consideration paths (Bain × CapstonAI, Q1 2026). Yet 71% of marketing teams still operate without a GEO (Generative Engine Optimization) roadmap — they ship tactics, not programs. The CapstonAI Q1 2026 cohort that ran a structured 12-month roadmap reached 47% citation rate (vs. 11% for ad-hoc teams) and grew AI-attributed pipeline 6.4× faster. Here’s the exact quarter-by-quarter plan, sequenced for compounding wins, with budget anchors and team load by phase.

TL;DR: A 12-month GEO roadmap sequences: Q1 = baseline + foundations (audit, schema, prompt panel, 2 pillar pages), Q2 = content scale (8 comparison pages, 4 pillars, PR push), Q3 = authority (original research, podcast tour, Wikipedia, aggregator profiles), Q4 = optimize + expand (refresh cycle, new engines, geo expansion, attribution maturity). Budget anchor: €60k-€180k Y1 depending on scope. Outcome: 4-6× citation lift, durable AI-attributed pipeline.

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The 11-step playbook

Step 1: Month 0 — Baseline + executive alignment. Run a citation audit across ChatGPT, Perplexity, Gemini, Claude with a 25-prompt panel. Document zero-state: citation rate, share of voice, competitor dominance map. Present to leadership with 12-month projection. Lock budget + team commitment before tactical work starts.
Step 2: Q1 Month 1 — Technical foundations. Audit + fix: robots.txt (unblock GPTBot, PerplexityBot, ClaudeBot, Google-Extended where appropriate), llms.txt deployment, sitemap hygiene, Organization + sameAs schema with Wikidata link. Estimated load: 1 technical SEO + 1 dev for 3 weeks.
Step 3: Q1 Month 2 — Content foundations (2 pillar pages). Publish 2 cornerstone pillar pages: “What is [your category]” + “Best [category] in 2026”. 1 800-2 800 words each, FAQPage + HowTo schema, named author with credentials, visible date. These become Q2-Q4 internal-link anchors.
Step 4: Q1 Month 3 — Prompt panel + tracking infrastructure. Lock 25-prompt panel covering 5 buyer-journey stages. Set up weekly tracking via CapstonAI / Profound / Peec AI. Build shared dashboard for marketing + sales. Establish baseline metrics (citation rate, SoV, quote inclusion rate) for monthly review.
Step 5: Q2 Months 4-5 — Comparison content scale. Ship 6-8 comparison/listicle pages (“X vs Y”, “alternatives to X”, “best X for [persona]”). These match Perplexity + ChatGPT preferred citation formats. Each: 1 200-1 800 words, FAQPage schema, competitor naming with proper context.
Step 6: Q2 Month 6 — PR + earned media push. Coordinated outreach: 3-5 tier-1 press placements (TechCrunch, The Information, vertical trades), 4-6 podcast appearances with transcripts, 8-12 newsletter mentions. Goal: build the source diversity AI engines reward (8+ outlets minimum).
Step 7: Q3 Months 7-8 — Authority through original research. Publish original research: industry benchmark, customer survey, or proprietary dataset. CapstonAI’s own Q1 2026 cohort report drove 12 citations in 60 days. Annual benchmarks become durable citation magnets across all 4 engines.
Step 8: Q3 Month 9 — Wikipedia + aggregator + Wikidata. If notable enough: Wikipedia article (hire WikiExperts.com or specialist editor; never write your own). Wikidata entry with sameAs links. Complete G2/Capterra/Software Advice profiles + drive 50+ verified reviews. These become foundational AI sources.
Step 9: Q4 Month 10 — Refresh cycle (everything older than 9 months). Revisit Q1 + Q2 content. Update stats, add 2026 dates, refresh examples, expand FAQs. Perplexity + Google AI Overviews favor recent content (3.4× citation lift). Establish quarterly refresh as permanent operating cadence.
Step 10: Q4 Month 11 — New engines + geographic expansion. Add tracking for emerging engines (Grok, Mistral Le Chat, You.com, DeepSeek). If multi-market: localize 4-6 top pages per priority geo with native-language FAQ schema and local entity links.
Step 11: Q4 Month 12 — Attribution maturity + Y2 plan. Connect AI citation data to pipeline (GA4 referrer + direct + branded search lift + sales-qualified mentions). Run cohort comparison: AI-touched accounts vs. control. Build Y2 budget request with documented ROI. Lock Y2 priorities.

Concrete case study

Real customer pattern (anonymized) showing the impact of this playbook:

Metric	Month 0 (baseline)	Month 12	Delta
Citation rate (4 engines, 25-prompt panel)	9%	47%	+38 pts
Share of voice vs. top 5 competitors	7%	31%	+24 pts
AI-attributed sessions (GA4)	~120/mo	~3 100/mo	+2 483%
AI-attributed SQLs	1/mo	18/mo	+1 700%
Pipeline influenced by AI citations	€8k/mo	€164k/mo	+1 950%

Common errors with 12-month GEO roadmap

Skipping the baseline audit. You can’t measure progress without a zero-state. Run the audit before publishing anything new.
Front-loading content before foundations. 10 new pages on broken schema and blocked bots = 10 invisible pages. Q1 foundations come first.
Ignoring the refresh cycle in Q4. Stale 2026 content tanks Perplexity rankings instantly. Refresh is non-negotiable.
No executive alignment at Month 0. GEO programs that lose budget at Month 6 never compound. Lock 12-month commitment upfront.
Treating GEO as a side project. Cohorts with <0.5 FTE allocated grow 3.1× slower than cohorts with 1+ FTE. Resource the program properly.

FAQ — 12-month GEO roadmap

How long until I see meaningful results from a 12-month roadmap?

First citation lifts appear in Months 2-3 (foundations + early content). Compounding starts Month 6 (post-PR push). Step-function happens Month 9-12 (post-original-research + refresh cycle). Plan for the full 12 months.

Can I run this with a small team (1-2 people)?

Yes — but stretch the timeline to 18 months. Or outsource Q2 content scale + Q3 PR to specialized agencies. CapstonAI’s cohort data shows 1 FTE + 1 agency hits Month 12 milestones; 0.5 FTE solo takes 18+ months.

What’s the minimum budget for a serious 12-month GEO program?

€60k-€80k Y1 for B2B SaaS with strong existing content. €120k-€180k Y1 for D2C or new-entrant brands needing PR + original research. Major cost drivers: content production (€20k-€60k), PR (€15k-€40k), tools (€8k-€15k), tracking + analyst time.

Tools and related reading

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Last updated: May 2026. Sources: CapstonAI Q1 2026 cohort (86 customers, 24 800 LLM responses analyzed), Gartner, Forrester × CapstonAI survey, Bain × CapstonAI analysis, WARC × CapstonAI, vendor disclosures.