FORKOFF AI SEO is a full-stack retrieval service that engineers schema, content, technical, and AI-tailored layers for AI and Web3 founders across ChatGPT, Claude, Perplexity, Gemini, Bing Copilot, and Google AI Overviews. Weekly per-surface receipts on the audit ledger.
Five patterns we see when a brand tries to compound AI SEO across the 6 retrieval surfaces and the work stalls inside the first quarter. Each row is the FORKOFF fix. Read it before you book the audit call.
Brand pays one team for traditional SEO and another for AEO/AI-search work with zero cross-channel coordination. Schema gets done twice (once for Google rich-results, once for AI-search). Content gets shipped twice. Pipeline attribution is fragmented because the two retainers report on different KPIs. Buyer journeys that cross both surfaces (which is most B2B journeys in 2026) get accounted for by neither team.
One engagement, one operator, one schema graph reused across both surfaces. Weekly cross-channel attribution receipt: pipeline split between Google blue-link traffic and AI-search citation lift, with the buyer-touchpoint sequence reconstructed from server-log + GA4 + AI-search-referrer signals.
Brand measures pipeline against Google organic traffic only OR against AI-search citation lift only. Either model misses 30 to 60% of attribution because most B2B buyers in 2026 cross both surfaces during the journey: they ChatGPT-research the category, Google-rank-check the shortlist, then return to AI-search for a final comparison. Single-funnel measurement systematically undervalues the work.
Dual-funnel attribution model: Google SERP rank tracker on the priority transactional queries (where Google still owns 80%+ of buyer traffic) AND AI-search citation tracker on informational + comparison queries (where AI-search owns 60%+). Cross-attribution receipt every week: which content compounded on which surface.
Same content shipped to both surfaces without query-intent split. Transactional queries ("buy X", "X pricing", "X demo") still belong on Google blue-link surfaces because buyers click to action sites, not synthesized answers. Informational queries ("what is X", "X vs Y", "how does X work") belong in AI-search where buyers consume synthesized comparisons. Treating both query types identically wastes effort on both sides.
Query-intent split in week one. Transactional queries get classical SEO depth: schema, on-page, site-speed, internal-link architecture. Informational queries get AI-search depth: canonical Q&A, parasite ladder, multi-engine bias-tuning. Effort allocated where the buyer-journey conversion economics are highest per query type.
Schema graph built twice. SEO retainer ships FAQ schema for Google rich-results; AEO retainer ships canonical Q&A for AI-search. Same Q&A, different sandbox of work, double the cost. The retainers do not coordinate because they run on different cadences and different KPI dashboards.
Single canonical schema graph designed for dual-surface reuse. FAQ schema validates on Google Rich Results AND serves as canonical answer unit for AI-search retrieval. Article + Service + Organization schema engineered once, used twice. Schema reuse efficiency tracked: target 80%+ shared graph across surfaces.
Brand assumes Google organic traffic stays flat as buyer journeys move to AI-search. The data already shows this is wrong: AI Overviews has reduced blue-link click-through 30 to 50% on informational queries through 2025-2026. Brands without a migration plan watch Google traffic decline while pipeline silently migrates to AI-search surfaces they never invested in.
Migration plan in week one: query-by-query forecast of how much traffic each commercial query will lose to AI-search over the next 12 months, with re-investment ratio shifting from Google-only to dual-funnel as the migration accelerates. Quarterly migration-progress audit; investment ratio re-balanced per query as AI-search share grows.
Traditional SEO competes for a Google rank that buyers increasingly skip. Most AI agencies sell content only. FORKOFF AI SEO engineers the schema, corpus, authority surface, and per-surface receipt that decide which brand ChatGPT, Claude, Perplexity, Gemini, Bing Copilot, and Google AI Overviews reach for. Canonical AEO hub sits at Answer Engine Optimization; multi-engine umbrella sits at AI Search Optimization and the broader pillar lives at GEO.
Three engagements across AI infra, B2B SaaS, and a Web3 protocol. AI SEO retainers that rewired the schema graph, shipped the authority surface, and reported a per-surface receipt the founder could read in two minutes. Pair the retainer with Answer Engine Optimization for the canonical citation hub or AI Search Optimization for the multi-engine umbrella.
Schema reuse efficiency across Google rich-results + AI-search canonical retrieval. One build, two surfaces.
Cross-attribution model reconstructs pipeline from Google blue-link + AI-search touchpoint sequences via GA4 + server-log + referrer signals.
Monthly retainer floor. 90-day minimum, capped at 5 engagements per quarter.
You keep the canonical schema graph, query-intent split, cross-attribution dashboard, and quarterly migration plan.
Three options for shipping AI SEO. Match the engagement to the surface coverage you actually need, the schema discipline you can sustain, and the per-surface receipt cadence you want shipped weekly.
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| Feature | FORKOFF AI SEO ServicesHybrid dual-funnel · Google + AI-search · cross-attributed | Classical SEO retainerGoogle blue-link only · no AI-search · single funnel | AI-search-only spokeAEO / GEO / LLM-SEO single-lane · skips Google traffic |
|---|---|---|---|
| Funnel coverage | Both: Google blue-link SERP + AI-search portfolio in one engagement | Google blue-link only; AI-search treated as future scope or out of scope | AI-search only; Google blue-link traffic decline accepted as drift |
| Attribution model | Cross-funnel attribution: GA4 + server-log + AI-search referrer reconstructs buyer-touchpoint sequence | Single-funnel: Google organic traffic only, AI-search invisible | Single-funnel: AI-search citation only, Google traffic invisible |
| Query-intent split | Transactional queries -> SEO depth on Google; informational queries -> AI-search depth across portfolio | All queries treated identically; SEO discipline applied uniformly | All queries treated as informational; transactional Google traffic ignored |
| Schema reuse efficiency | One canonical schema graph reused across both surfaces; target 80%+ shared | Schema built for Google Rich Results only | Schema duplicated for AI-search canonical Q&A; Google rich-results not validated |
| Migration plan | Quarterly migration audit: how much Google traffic lost to AI Overviews vs AI-search citation gain | Treats Google traffic as flat; ignores AI Overviews CTR decline | Treats Google traffic as deprecated; over-invests in AI-search |
| When to choose this | B2B brand whose buyers cross both Google blue-link AND AI-search; transactional + informational query mix | Brand whose buyers stay on Google for both transactional and informational queries (rare in 2026) | Brand whose buyers have already migrated to AI-search; Google traffic decline is acceptable |
| Pricing model | $1,500 sandbox audit · retainer by application · outcome-priced milestones | Hourly retainer with monthly rank report | Per-spoke pricing depending on lane (AEO / GEO / LLM-SEO / Perplexity SEO each at $1,500 sandbox) |
20 to 40 commercial queries, 6 retrieval surfaces (ChatGPT, Claude, Perplexity, Gemini, Bing Copilot, Google AI Overviews), one full-stack AI SEO map. You get the gap diagnosis, schema audit, corpus and authority plan, and 90-day shipping order in 5 business days. If FORKOFF cannot find actionable AI SEO gaps, the fee gets refunded. Retainer kicks in at by application per month after the audit lands.
6-surface bench, schema graph, canonical Q&A, authority ladder, and an original-data drop shipped in the first 60 days. Weekly Monday per-surface citation receipt. Outcome-priced. Scaleable up or down at quarter end. Pair the retainer with AEO, AI Search Optimization, or LLM SEO depending on the retrieval surface that wins your buyer.
Engineer every AI search surface, not just classic Google SERPs.
Become the answer, not the link. Schema, FAQs, and content gravity.
Rank inside generative engines, where the new SEO battle is fought.
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