GEO Operating System, Research → Sense → Decide → Act → Verify

Off-page earned-media & PR execution (loop step 4b, Act / Off-page; owner: the brand's GEO lead). ~85% of AI citations come from third-party pages, so this is the highest-leverage lever. Work the gap-ranked off-page targets from GEO Decide across the source categories the models actually cite:

- Editorial / digital PR: pitch data, contrarian takes and named frameworks to publications the models already cite; earn mentions in 'best [category]' and '[competitor] alternatives' listicles (Barnacle SEO). Keep a brand kit ready. Human approval the owner before any outreach.

- Reddit & community (via Reddit): genuine participation in threads that already rank for target queries, answer real questions, never spam (Reddit punishes self-promotion; manufactured seeding backfires).

- Reference / directories: complete and correct Crunchbase, G2, Wikidata and industry directories, fastest wins, can move within 24h.

- Source correction (sentiment): for weak themes, politely ask the most-cited inaccurate/outdated sources to update (templated outreach) and solicit reviews on the platforms the models cite.

- Guardrails: white-hat / low-risk grey-hat only, no fake reviews, sock-puppets, hidden text or manufactured consensus.

Feeds GEO Verify.

Research & build the tracked prompt set (loop step 1, Foundation; reviewed quarterly, owner: the brand's GEO lead). Define WHAT we track before measuring anything, using the GEO best-practice prompt framework.

1 · Research the prompt set (best practice), cover all three axes:

- Journey stages: *awareness* (problem-aware, pre-category, concerns/objections mined from sales calls, Reddit, 'what worries people about [category]'), *consideration* ('best [category]', segment-specific variants), *purchase* (where commercial intent exists).

- Customer context: ICP segments, use-cases, constraints, reverse-engineer from the brand's nav, pricing tiers and positioning if not documented.

- Geography: track core prompts per target region.

- Seed from the brand's top non-branded Google Search Console queries, converted 1:1 into natural questions.

- Keep brand-evaluation prompts ('grex vs X', 'is grex worth it') in a SEPARATE tag/project so guaranteed mentions don't skew visibility.

- Target ≈50–100 tagged prompts (stage · intent · segment · region) + a separate sentiment-theme set (safety, support, pricing, reliability, …).

2 · Build in Peec (primary), or another LLM-analysis tool. Create/organise the prompts in Peec.ai with those tags; add competitors (with name aliases); select tracked models (ChatGPT, Google AI Mode, Perplexity, Gemini). Cross-check coverage in LLMrefs if connected.

3 · Handoff: once the set is live and collecting, weekly GEO Sense begins. Re-run quarterly to expand clusters and retire dead prompts. Human approval the owner to approve the prompt set before it goes live.

Weekly re-measure & report (loop step 5, Verify; owner: the brand's GEO lead, weekly + monthly deep-dive). Close the loop honestly.

- Re-measure the same prompt set via Peec.ai and compare to the pre-action baseline.

- Report trend and correlation, NOT causation, AI answers are probabilistic and attribution is noisy, so track which actions *preceded* movement and build the picture over weeks; never claim one post/mention 'caused' a change.

- Promote tactics that correlate with sustained lift; drop those that don't. Feed self-reported 'how did you find us?' data into the AI-attributed-leads metric (cross-check traffic via Google Analytics, directional only; LLM visits are undercounted).

- Monthly: NotebookLM qualitative synthesis over exported answers to surface recurring narratives/complaints.

- Post the internal weekly trend report automatically; escalate before any external or client-facing reporting.

Loops back to GEO Sense.

On-page content & optimisation (loop step 4a, Act / On-page). Execute the on-page items from GEO Decide so the brand's own pages get retrieved *and* cited. Produce long-tail, ICP-question content, and hold every page to the extractability bar:

Write for extraction

- Lead with the answer, the first 40–60 words of each section answer the query directly and declaratively (no scene-setting; that's the #1 citation-killer).

- Question-based H2s that mirror real prompts; one H1 per page; paragraphs <120 words; a summary at the top of each section; tables, bullets and numbered steps.

- Be specific & declarative, concrete numbers, dates, named processes; put the brand first in numbered lists.

- Gut check: screenshot any one H2 section, does it answer the question on its own?

Own the high-yield formats

- Build and defend listicles / comparisons, 'best [category]', '[competitor] alternatives', 'X vs Y' (the most-cited format; keep tables genuinely balanced). Consolidate thin single-topic posts into comprehensive listicles with a pillar hub.

Technical & trust

- Schema (Organization, Article w/ author + dateModified, FAQPage, Product/BreadcrumbList), must reflect visible content; validate before publish.

- Entity consistency, identical brand name / NAP / descriptors; real author bios + credentials.

- Retrievability, server-rendered, fast, crawlable; AI bots allowed in robots.txt.

Freshness & quality floor

- Quarterly refresh of top citation-earning pages; bump dateModified honestly.

- No raw-AI slop, every page passes 'would I read this myself? does it add value others miss (original data, first-hand insight)?' Human approval editorial/Tom approval before publish.

Feeds GEO Verify.

Weekly AI-visibility pull (loop step 2, Measure; owner: the brand's GEO lead, weekly). With the tracked prompt set live (see GEO Prompt Research & Build), pull the week's data via Peec.ai:

- Visibility % (answers mentioning the brand), position (rank when mentioned), share of voice vs competitors, sentiment by theme, citation rate vs platform benchmark (ChatGPT ≥2.0 · Google AI Mode 1.1–1.5 · Perplexity 1.5–2.0), and the top cited sources.

- Segment every metric by tag (stage · intent · segment · region), never read a single blended number.

- AI answers are probabilistic: trust the weekly aggregate, not day-to-day swings (≈30% of brands hold visibility answer-to-answer).

- Record the values on this board's metrics, compute week-over-week deltas, post a short summary to Slack/Claude.

- Optional daily lightweight check (visibility + sentiment on the top prompts) that escalates only on a material move.

Output feeds GEO Decide.

Continuous, background, run by the GEO expert; visibility is low by design.

1. Find Reddit/forum threads where our ICP asks questions AI search later draws on.
2. Post genuinely helpful, non-spammy comments that surface the brand's POV.
3. Vary accounts/timing to stay natural and within subreddit norms.
4. Note seeded threads so we can later check whether they show up in AI answers.

Inputs: target query/topic list.

Outputs: seeded high-signal threads feeding AI-search answer sets.