The full methodology, end to end
geo.wikiseo.ai is not a black box. Here is exactly what happens between you adding a prompt and seeing a concrete playbook of fixes in your dashboard.
- 01
You define buyer-intent prompts
Add the questions your prospects type into ChatGPT, Perplexity or Gemini when researching your category. Or let geo.wikiseo.ai auto-generate a starter set — ~25 prompts in 3 topic folders, sized to your plan — from your brand name and website at sign-up. These are the questions you want to win.
- 02
We answer them across 4 AI assistants — weekly to daily
On your plan's scan days at 02:00 UTC — every Monday on Starter, up to every morning on Authority — each active prompt is sent in parallel to OpenAI GPT, Anthropic Claude, Perplexity Sonar, and Google Gemini. Web search is enabled. The full answer text, citations, and grounding metadata are stored.
- 03
We parse citations and brand mentions
Every cited URL is extracted and classified across 1,500+ domains in five categories: Editorial, UGC, Reference, Corporate, Institutional. UGC is sub-typed: Reddit thread, Quora answer, G2 review, YouTube transcript, Stack Overflow. Brand mentions in the answer text are detected with word-boundary regex against your name plus aliases, scored for sentiment by Claude Haiku.
- 04
We compute visibility metrics
Brand Mention Rate (% of answers that mention you). Citation Rate (% of answers that cite your domain). Share of Voice (your mentions vs all tracked competitors). Avg Position (where you appear when you do). Sentiment average. Each metric has a 7-day window plus a 14-day baseline for delta calculation.
- 05
We surface what changed
The dashboard shows weekly deltas, top cited sources by category, recent answers where you appear, and Playbooks driven by a deterministic rule engine (30+ rules): Wikipedia gaps across languages, low mention rate, Reddit and review-site opportunities, negative sentiment, competitor overlap, lost citations.
- 06
You get a playbook — automatically or in one click
Playbooks generate automatically after your scans, or on demand for a weak prompt or a competitor that wins prompts you should win. The rules read the data (their top sources, the prompts where they dominate, your gap) and return concrete steps with confidence and effort bands — deterministic rules, not an LLM: same data in, same plan out, at no per-playbook cost.
- 07
You get a weekly email digest (optional)
Enable weekly reports in Settings and geo.wikiseo.ai emails you every Monday: 3 KPI cards with deltas, the brand appearances that are new this week, what you lost from last week, top sources cited with diff, and a 5-bullet AI executive summary. The whole report renders in 5 to 10 seconds.
What the numbers cover
Frequently asked
- How is this different from a regular SEO tool?
- Traditional SEO tools track Google rankings. geo.wikiseo.ai tracks the five AI answer surfaces that increasingly mediate buyer research — including Google's own AI Overview, which shows above the organic top 10 now. If AI assistants cite a competitor instead of you, the deal moves on. Rank tracking misses this entirely.
- Why these five AI answer surfaces specifically?
- ChatGPT, Claude, Perplexity, Gemini and Google's AI Overview cover the overwhelming majority of consumer AI search traffic (Anthropic + OpenAI + Perplexity + Google). Each has a distinct citation behaviour: Perplexity is the most generous with sources, ChatGPT cites Wikipedia and major media heavily, Claude favours technical references, Gemini and AI Overview lean on Google's Knowledge Graph and search index. Tracking all five gives you the full picture.
- How accurate is the brand matching?
- Word-boundary case-insensitive regex against your name plus any aliases you configure. False positives on common-word brands (Apple, Square, Notion) are blocked because the regex requires word boundaries on both sides. False negatives on misspellings can be reduced by adding aliases in Settings.
- Why daily and not real-time?
- AI assistant answers fluctuate within an hour. Daily aggregation smooths the noise. Real-time tracking would multiply API costs by 24 without giving you actionable signal, since you cannot publish a Wikipedia article between morning and afternoon to fix a problem.
- What happens if a competitor stops appearing in answers?
- The weekly digest has a Lost section that lists prompt and model combinations where you or a competitor had mentions last week but zero this week. This is the leading indicator that a content piece has fallen out of the AI training cut-off or been outranked by newer content.
- Can I monitor multiple brands or competitors per workspace?
- Each brand is its own workspace with its own plan; a self-serve account can create up to 2 brands (need more? contact us and we set them up by hand). Within any workspace you can add competitors as tracked entities; each gets its own mention detection and citation taxonomy.
- Who is behind geo.wikiseo.ai?
- geo.wikiseo.ai is built by Wikibusines, a 15-year-old AI visibility agency with 300+ Wikipedia article placements across 50+ language editions. Clients include Frankfurt School of Finance, Crypto.com, and ChargeAfter. We built geo.wikiseo.ai first for internal use and opened it as a product in 2026.
See it on your own brand
Create a free account in under a minute, add your brand, and start tracking how the AI engines see you. No card required to begin.