Be the source generative engines synthesize from — across every model that matters.
GEO is the strategic layer above AEO: instead of optimizing for one answer surface, we engineer the entity, citation, and content signals that make your brand the default reference across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews simultaneously.
Single-engine optimization is the most expensive mistake in modern search.
Brands invested in 'ChatGPT SEO' are watching Perplexity, Gemini, and Claude cite competitors on the same prompts. Generative engines have different training data and different trust signals — there is no single playbook that wins all five.
- ChatGPT visibility ≠ Perplexity visibility
Reddit and G2 dominate ChatGPT. Perplexity weighs primary research and arXiv. The same content rarely wins both without engine-specific signals.
- Entity inconsistency tanks retrieval
Different brand names, descriptions, or sameAs links across Wikidata, Crunchbase, and LinkedIn confuse retrievers — they pick the cleanest competitor.
- No proprietary data = no citations
Generative engines disproportionately cite original frameworks, named methodologies, and primary research. Brands without IP get paraphrased, not credited.
- Refresh cycles wipe out one-time wins
Each model retrains on its own schedule. Without continuous re-prompting and regression alerts, citations earned in week 8 disappear by week 16.
Each model trains on different data. Optimize for one and you lose the other four.
ChatGPT trusts G2 and Reddit. Perplexity weighs primary research and arXiv. Gemini leans on the Google index and YouTube transcripts. Claude rewards long-form expert content. Google AI Overviews pull from ranked SERPs. Brands that show up in all five didn't get lucky — they engineered an entity and citation footprint that satisfies every retrieval pattern at once.
Visible in one engine, invisible in the other four
Optimizing only for ChatGPT leaves Perplexity, Gemini, Claude, and AI Overviews citing competitors. Each engine has different trust signals.
Entity graph fragmented across the web
Inconsistent brand entities on Wikidata, Crunchbase, LinkedIn, and category authorities make retrievers pick the cleanest competitor instead.
Content not chunked for synthesis
Generative engines stitch together passages from multiple sources. If your content can't be cleanly extracted, the model paraphrases someone else.
No primary research footprint
Perplexity and Claude disproportionately cite original data, frameworks, and named methodologies. Brands without proprietary IP get passed over.
A 75-day stand-up, then continuous multi-engine SoV operations.
- 01
Multi-engine baseline
Week 1–2Top 250 commercial prompts run through ChatGPT, Perplexity, Gemini, Claude, and AI Overviews. Citation, sentiment, and ranking position logged per engine.
- 02
Entity unification
Week 2–4Single canonical entity model deployed across owned schema and external authorities — Wikidata, Crunchbase, LinkedIn, industry directories, and category-defining publications.
- 03
Synthesizable content
Week 3–6Pillar pages restructured into the chunk-friendly passages, comparison tables, named frameworks, and proprietary data each engine prefers to quote.
- 04
Cross-engine citation
Week 4–10Earned placements on the sources each engine disproportionately trusts — engine-specific seeding, not generic link-building.
- 05
Continuous SoV ops
Month 3+Weekly re-prompting across all five engines, regression alerts, sentiment tracking, and quarterly entity refresh as model training cycles refresh.
AdWave GEO Framework
Six layers engineered to make your brand the default reference across every major generative engine — not just one.
Multi-Engine Baselining
Top 250 commercial prompts tested across ChatGPT, Perplexity, Gemini, Claude, and AI Overviews — citation, sentiment, and position logged per engine.
Entity Unification
One canonical entity model deployed everywhere a retriever might look: Wikidata, Crunchbase, LinkedIn, schema.org, category authorities.
Synthesizable Content
Pillar pages restructured into the chunkable passages, comparison tables, and named frameworks each engine prefers to quote.
Cross-Engine Citation
Engine-specific seeding — Reddit and G2 for ChatGPT, primary research for Perplexity, YouTube + Google for Gemini, long-form for Claude.
Proprietary IP Layer
Named methodologies, original frameworks, and primary research published as canonical references engines cite back to your domain.
Continuous SoV Ops
Weekly re-prompting, regression alerts, sentiment tracking, and quarterly refresh as model training cycles update.
What ships in a 75-day GEO engagement.
Top 250 prompts scored across ChatGPT, Perplexity, Gemini, Claude, and AI Overviews.
Canonical entity deployed across owned schema and 12+ external authorities.
Top 40 commercial pages rewritten as synthesizable passages with named entities.
Earned placements on the sources each engine disproportionately trusts.
1–2 named methodologies or primary-research reports designed for citation.
Weekly SoV, sentiment, and citation regression tracking in Looker Studio.
Tone of brand mentions tracked per engine — not just whether you're cited.
Real-time notifications when a tracked citation disappears from any engine.
Senior-strategist sessions tied to your pipeline KPIs and model release cycles.
Cross-engine SoV over a 90-day GEO program.
Median trajectory across our last 18 engagements — branded share-of-voice across all five major generative engines.
Median GEO outcomes from our last 18 multi-engine engagements.
These are pulled from prompt-tracking dashboards we run across SaaS, healthcare, and professional services brands. The defining metric is cross-engine SoV — being cited in three or more engines for the same prompt — because that's what protects you when one model's training cycle refreshes.
Cross-engine share-of-voice: of 1,000 commercial prompts, ~830 trigger a generative answer, ~340 cite at least one source, and only the top ~40 sources get cited in three or more engines for the same prompt.
GEO vs. AEO — when to run which.
AEO is the right entry point for brands new to AI search. GEO is the right scale-up for brands that need durable visibility across the entire generative landscape.
GEO pays back fastest for these three buyer profiles.
VP Marketing at a category-defining SaaS
Triggered when buyers say 'I asked ChatGPT and it recommended a competitor' — and you can't tell which engines are losing you deals.
We build cross-engine SoV monitoring, unify the entity graph, and engineer named frameworks that get quoted as the canonical reference in your category.
CMO at a multi-location healthcare brand
Triggered when patient research is shifting from Google to ChatGPT and Gemini, and your local SEO investments aren't translating.
We focus on doctor and clinician entity authority, location-level structured data, and earned citations on the medical sources LLMs treat as authoritative.
Marketing Partner at a top-tier professional services firm
Triggered when prospects start every conversation with what an AI told them — about you, or about your competitor.
Expert-author entity graphs, named methodologies, primary research publication, and citation seeding on the legal/finance/consulting authorities each engine respects.
From cited in 1 engine to cited in 5 — across 1,200 patient prompts.
A 14-location specialty practice was visible in ChatGPT for branded queries but invisible in Perplexity, Gemini, and Claude. We unified physician entities across Wikidata, Doximity, and 8 medical authorities; restructured the top 38 condition + treatment pages; published a named diagnostic framework as proprietary IP; and seeded earned citations on JAMA-adjacent publications and 4 medical podcasts with full transcripts. By day 90, the practice was the most-cited specialty brand in its category across all five engines.
Each industry has a different cross-engine pattern.
B2B SaaS
ChatGPT visibility maxed out — Perplexity and Claude cite competitors on the same prompts.
Cross-engine SoV that protects pipeline as buyer research fragments across models.
See playbookHealthcare & Med Spa
Patient research shifting from Google to AI assistants you're invisible in.
Physician entity authority that wins clinical, treatment, and condition prompts in every engine.
See playbookLaw Firms
AI assistants recommend legacy firms by default on practice-area queries.
Practice-area entity graphs and named frameworks that win signed-case prompts.
See playbookEcommerce
Comparison prompts cite Amazon and review aggregators instead of your PDP.
Product entity authority + structured comparison content cited across shopping research.
Real Estate
Buyer/seller research happens in ChatGPT and Gemini before any agent contact.
Neighborhood and agent entity authority cited in pre-contact AI research.
See playbookProfessional Services
Niche expertise paraphrased without attribution by every major LLM.
Expert-author entity graphs + proprietary IP published as the canonical reference.
GEO is a scale-up — not an entry point.
- Brands already running AEO or strong SEO that need durable cross-engine visibility
- Category leaders or challengers with genuine domain expertise to publish
- Multi-location healthcare, legal, financial, and consulting firms
- B2B SaaS brands where buyer research has shifted to AI assistants
- Teams willing to publish proprietary frameworks and primary research
- Brands without an existing SEO or AEO foundation
- Companies unable or unwilling to publish original IP
- Teams looking for a one-time fix rather than a continuous program
- Brands with content fully gated behind login or paywalls
We built cross-engine GEO before most agencies could spell it.
Most AI search agencies optimize for ChatGPT and call it GEO. We engineer for all five engines simultaneously, with engine-specific signals and continuous monitoring.
We re-prompt every tracked query weekly across ChatGPT, Perplexity, Gemini, Claude, and AI Overviews. Most agencies test one engine and extrapolate.
Reddit and G2 for ChatGPT. arXiv and primary research for Perplexity. YouTube + Google index for Gemini. Long-form expert for Claude. SERP for AIO. Different work, different placements.
We help you build the named frameworks, methodologies, and primary research that engines cite back to your domain — not generic content.
We measure not just whether you're cited but the tone of the mention. Negative SoV is worse than no SoV.
The tooling we run quietly in the background.
Multi-engine prompt tracking
Cross-engine SoV analytics
Sentiment + citation regression
Enterprise schema deployment
Canonical entity unification
Citation network + audience research
Automated prompt regression
Executive cross-engine dashboards
Educational reading we send to every new GEO client.
The single-engine tactic that GEO scales across the full generative landscape.
The Reddit and G2 signals that disproportionately drive ChatGPT citations.
Why AIO behaves differently than every other generative engine.
The two engines most B2B brands underweight in their AI search strategy.
How we monitor cross-engine SoV continuously, not as one-time audits.
The third-party sources each major engine disproportionately trusts.
What CMOs and Heads of SEO actually ask in scoping calls.
Real questions from discovery calls — clustered by what they care about most.
GEO compounds when paired with these.
The single-engine tactic GEO scales across all five major generative engines.
ExploreContinuous cross-engine SoV monitoring and regression alerts.
ExploreEngine-specific earned placements that move retrieval weights.
ExploreCluster systems that strengthen entity authority across all engines.
ExploreEarned placements on the publications each engine disproportionately trusts.
ExploreFounder-voice IP that becomes the canonical reference engines cite back.
ExploreSee exactly which engines cite you — and which cite your competitors.
We'll run your top 50 commercial prompts through ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews, then send back a cross-engine SoV report with the entity, schema, and citation gaps blocking multi-engine visibility. Turnaround is 5 business days.
- 5-day turnaround
- No commitment
- Senior strategist call