Most SEO proposals describe outcomes and skip process. This page does the opposite. Below is the actual sequence of work in a CASRAI Academic SEO + GEO engagement, phase by phase, so your team knows exactly what happens, in what order, and what you receive at each stage.
This is the same methodology CASRAI runs on its own site, casrai.org, where it currently produces 71,465 organic Google clicks and 12,789,147 impressions in a trailing 28-day period, at an average position of 7.8 site-wide. It is also how CASRAI holds multiple #1 Google rankings on high-intent buyer and trust queries achieved through this same methodology. We are not proposing an untested process — we are offering to run the process we already use on our own institutional content.
Phase 1: Discovery & Audit
Every engagement opens with a full audit of where your institution currently stands — in traditional search and in AI answer engines.
- Search Console and technical baseline. We pull existing indexing status, crawl errors, current rankings, and click/impression history for your domain to establish a real starting point, not an assumed one.
- AI-citation audit. Using LLM-citation tracking data, we check whether ChatGPT, Google AI Overviews, and Perplexity currently cite your institution's pages when people ask questions your institution should be the authoritative source on — and if they don't cite you, we identify which domains they cite instead. This is measured with real citation-tracking data, not inferred from guesswork about how AI models behave.
- Structured data and metadata review. We check whether your research and publication pages carry the metadata academic indexing systems expect (Highwire/PRISM tags, schema markup, Google Scholar inclusion signals) and flag what's missing.
- Deliverable: a written audit report covering current organic performance, AI-citation status, and a prioritized list of technical issues.
Phase 2: Keyword & Topic Research
We do not start from generic keyword-tool output. Every topic we recommend is verified against real search demand before it goes into a content plan — the same discipline behind CASRAI's own 357 new content pages, each individually researched, written, fact-checked, and published in a single continuous cycle spanning the US, UK, Canada, and Australia.
- Search-demand verification for every candidate topic, using live query and volume data specific to your institution's field and geography.
- Mapping topics to the actual questions your researchers, prospective students, journal authors, or partner institutions are asking — including the conversational, longer-form questions typed into AI assistants, which differ in phrasing from traditional search queries.
- Gap analysis against your existing content library to identify what's missing, what's thin, and what's already ranking but under-linked.
- Deliverable: a prioritized topic and keyword roadmap with search-demand evidence attached to each item.
Phase 3: Technical SEO Fixes
- Metadata correction across priority pages: titles, descriptions, canonical tags, structured data.
- Indexing fixes: resolving crawl errors, orphaned pages, and sitemap gaps identified in Phase 1.
- Academic-specific markup: Highwire/PRISM tagging and schema for research output, faculty profiles, and journal content where applicable, to support Google Scholar and academic indexer inclusion.
- Internal linking architecture: connecting high-authority existing pages to newer or under-performing ones so link equity flows to where it's needed.
Phase 4: Content Strategy & Production
Content is written, fact-checked, and published against the verified roadmap from Phase 2 — not written first and checked for demand after. Each piece is scoped to a real, confirmed query before a draft begins. CASRAI's own page on this exact topic, /guides/academic-search-engine-optimization-aseo, ranks #3.3 for "academic seo" with an 11% click-through rate, well above typical CTR at that position — evidence that demand-verified, fact-checked content converts into clicks, not just impressions.
Phase 5: GEO-Specific Structuring
Ranking in traditional search and being cited by an AI answer engine are related but not identical problems. GEO work is layered onto every piece of content we touch:
- Structuring answers so they can be extracted cleanly — direct answers near the top, clear entity definitions, unambiguous attribution of facts to your institution.
- Re-auditing AI-citation status after publication, using the same LLM-citation tracking data from Phase 1, to confirm whether new or restructured content is being picked up as a cited source.
- Iterating on structure where a page ranks well in Google but is still not being cited by AI answer engines — these are treated as two separate, trackable outcomes, not one.
Phase 6: Reporting Cadence & What Gets Measured
You receive regular reporting against a fixed set of metrics, tracked from the Phase 1 baseline:
- Organic clicks, impressions, and average position, sourced directly from Search Console.
- AI-citation status per tracked query, sourced from LLM-citation tracking data — cited or not, and by which model.
- Indexing and technical health status for pages touched in the engagement.
- Content published against the roadmap, with individual page performance.
No projected traffic numbers, no promised ranking positions — every report is built from what actually happened, measured against where you started.
Engagement Structure
Academic SEO and GEO can be scoped together or separately, depending on where your institution currently stands. Pricing is quoted per engagement based on site size, current baseline, and scope of the content roadmap — there's no published starting rate because the work varies too much institution to institution to make one honest.
The audit in Phase 1 is free and comes with no obligation to continue — it's the fastest way to see exactly where your institution stands today, in both Google and AI answer engines.
