When I started in marketing, SEO was a simple science: Use SEMRush; identify the keywords with the highest monthly volume and lowest competition; and write content that included those relevant keywords in headlines, paragraphs and bullets. Optimization relied solely on structural integrity of headings and title tags and domain authority.
I guess I didn’t know the good old days of search until they were gone. Really. Ranking felt easy and repeatable. So easy and repeatable that in my first marketing role, I was able to get us ranking for over 300 key terms in Google’s top three. We cancelled all paid ad spend, and the majority of our revenue came from Google organic.
Unfortunately since then, search and organic optimization has changed tremendously. But as someone who used to love to live in the weeds of tactical SEO, I can say this: the fundamentals are still the fundamentals:
- Know your audience, their pains, problems, and the search queries they conduct
- Then build clear and trustworthy answers to their questions
It’s still easy, in theory. In practice, well that’s a whole other story. I’ve been working on AEO and GEO myself for Capture’s new website…so I’ve personally been putting in the work lately, and I wanted to share my strategy with you.
In this blog, I’m going to share (what I believe to be) the strongest levers to pull on GEO that a college marketing or enrollment team can chip away at on their own time and budget, without hiring an agency (who, like me) is still just figuring it out.
What is GEO, and how is it different from SEO?
The speed to rank happens much quicker than it used to. Five to ten years ago, it could take up to 90 days for Google to re-crawl your website and decide if your content ranks. Now? It can happen within days.
- Crawl Cadence: Established and high-authority sites are visited by AI bots (GPTBot, OAI-SearchBot, or Google’s crawlers for Gemini) daily to weekly.
- Update Speed: For new or modified content, fresh data can appear in live AI search results and citations within 24 to 72 hours, provided the page is already indexed and ranks well organically.
- On-Demand Fetching: AI retrieval bots often pull specific text blocks or use cached search indices (like Bing or Google indexes) at query time, meaning minor textual corrections on popular sites can propagate in less than a day
Why should colleges care about AI search now?
Because your future students are already researching you this way — often before they ever reach your site. In Capture’s 2026 Enrollment Engagement Report, a survey of more than 2,800 high school juniors and seniors, 47% said they already use AI tools during their college search, and 81% of those students reached for external platforms like ChatGPT and Gemini. They told us they use AI most for discovery, comparison, and quick answers. These are the exact moments when your institution is either represented accurately or left out entirely.
This makes the prevalence of the dark funnel much more obvious. Students already explore your programs, outcomes, and reviews without ever identifying themselves; more than half apply or request information with no prior direct contact at all. But at least that activity was happening on your website — and if you use Capture, you could track it.
With students relying heavily on platforms like ChatGPT at the beginning of their search, you run the risk of losing website traffic entirely if an AI can’t find clear information about your programs. Or worse, it will guess, quoting a Reddit thread instead of you.
When a model answers, “best value colleges in Ohio” or “schools with strong game design,” it pulls from whatever it can read and trust across the web. If your site is vague, outdated, or hard to parse, you’re left out of a conversation your prospects are already having.
How do you optimize a college website for AI search?
I know I’m sounding like a broken record, but: the fundamentals of ranking in any search query is the same: useful content, clear structure, and credibility. Here are the easiest wins you can make on your website right now that can ensure your college gets mentioned. And you can do it yourself, without hiring an agency, or making some massive investment.
Before you do any of these steps, though, I highly recommend investing in a search optimization platform like SEMRush or Profound. These will give you insights into the queries you should be optimizing for, and track your performance over time.
And if you don’t have budget for that…go old school. Make a list of the queries you think matter most to your institution — and start with 10-20 of those. Then, type those into ChatGPT, Gemini and other search engines to see how your institution is cited. This gives you a low-cost direction of where to be investing your time.
Now, onto optimizations.
1. Answer the questions students actually ask in your website copy
AI search rewards content that reads like a direct answer, not your marketing team’s brochure. So, the pages that get pulled into AI responses lead with the answer and explain underneath.
Time investment: One focused day to build your question list, then about 30 minutes per page to rewrite. Start with 10 pages.
Step 1: Build your question list (2–3 hours)
Pull from four places, in this order of usefulness: your admissions inbox (search for question marks in the last 90 days of inquiries), your chat transcripts, your counselors, and Google’s “People Also Ask” box. Write them down in the exact words students use. Not “tuition and fees information” — “how much does it actually cost to go here.”
Step 2: Rank by page value (30 minutes)
Map each question to the page that should answer it. Your tuition, financial aid, admissions requirements, and top three program pages will cover most of the volume. This is where you start.
Step 3: Rewrite the headings (30 minutes per page)
Turn key website headings into real questions — “How much is tuition at [School]?”, “What’s the deadline for early action?”, “Does [School] offer merit scholarships?” Put a clear, complete answer in the first sentence or two, then add the detail below.
The rule I’d hold yourself to: if someone read only the first two sentences under a heading, would they have their answer? If not, you’ve buried it.
2. Build an FAQ section for each key website page
FAQs give AI a clean, structured version of exactly the Q&A format these systems love to surface. This one has two halves: the writing, which anyone on your team can do this week, and the schema markup, which is a bonus round that may need a hand from someone technical.
Do the first part regardless. In full transparency, it’s the step I’m still sitting at with our new website.
The part you can do yourself: write the FAQs
Time investment: About 45 minutes per page. Start with your five most important pages.
Step 1: Write 5–8 real FAQs per page
Use the question list you built in step one. Two rules that matter more than anything else here: every answer has to be visible on the page to a human reader, and every answer has to stand on its own.
Assume an AI is going to lift that answer and show it to someone who never sees the rest of your page — so “as mentioned above” and “our program” are dead weight. Say “University of Toledo’s nursing program.”
Then, work with whoever manages your website to get the content on each page.
Now, here comes the bonus round: adding schema markup.
Here’s where I’ll be totally honest with you. Adding schema is genuinely valuable, and it’s also the step where a lot of marketing teams stall out, because depending on your setup, you may need someone from IT, your web team, or whoever owns your CMS to actually get it implemented.
Time investment: About 30 minutes of your time to generate and validate, plus however long your web team’s queue is.
Step 2: Generate the schema (15 minutes)
Schema markup is a small block of code that labels your content for machines. It tells a search engine or AI system “this is a question, this is its answer, this is an academic program, this is the institution” instead of leaving it to infer from paragraphs.
Free tools like Google’s Structured Data Markup Helper or TechnicalSEO.com’s schema generator will build the code from a form, or you can simply ask your AI engine of choice to generate schema mark up based on your page content. (That’s what I usually do.)
Step 3: Get it on the page
This is the step where you may need backup. If you’re on WordPress with admin rights, you can paste it straight into a Custom HTML block — it doesn’t have to live in the <head>. If you’re on a locked-down CMS or a custom build, you’ll need to work with your web team on getting this up. Once it’s on your site, run the page through validator.schema.org once it’s live.
3. Ensure the facts across your websites are consistent
AI models cross-check information across sources. When your tuition figure, deadline, or program list says one thing on your site and another on an old landing page or directory, the model drops you or picks the wrong version.
Time investment: One day for the initial audit and fixes. Then 2-3 hours, quarterly.
Step 1: Inventory where you exist (1 hour)
Google your institution name and write down every result on the first three pages. The usual suspects: your website, Google Business Profile, Niche, Wikipedia, College Navigator, Common App, your state system’s directory, and any old microsites from campaigns nobody shut down. That last category is where most of the inaccurate information lives.
Step 2: Audit the core facts (2–3 hours)
Build a simple spreadsheet with one row per fact and one column per platform. The facts worth tracking: tuition and fees, average net cost, application deadlines, test-optional status, enrollment size, student-faculty ratio, and your full program list. Use consistent formatting everywhere (pick “20” or “twenty” and stick to it). You will find contradictions. Most schools do.
Step 3: Fix and date everything (3-4 hours)
I recommend doing this in one fell swoop if you can…but if you can’t, break it up over the course of one week. You’ll want to update stale numbers, kill or redirect dead microsites, and add a visible “last updated” date to every page carrying a number. That date is a credibility signal to both readers and models.
4. Focus on sourcing positive reviews regularly
Reviews have always played an integral role in search performance, but it’s gotten more important with AEO and GEO.
AI answers synthesize the whole web and lean heavily on third-party voices: Reddit, Niche, Google reviews, news coverage, and .edu links from other institutions. A page you wrote praising yourself carries less weight than a real student saying the same thing elsewhere when it comes to search optimization.
Time investment: 2–3 hours to set up the machinery. Then about 30 minutes a month to run it, and 30 minutes a week to monitor.
Step 1: Build the ask into things you already do (ongoing)
The trick is that you never want to run a “review campaign” — you want review requests living inside communications you’re already sending. Add a line with a direct link in email communications like a parent newsletter, alumni outreach, and post-event communications. One of my favorite tips for reviews is to print QR postcards for family weekend, homecoming, etc. To hand out in-person or mail as a follow-up with a hand-written note.
Step 2: Prioritize by authority (ongoing)
Niche and Google first — they carry the most weight and get cited most. Facebook and others after. Aim for a steady trickle rather than a spike; twenty reviews arriving the same week looks manufactured to both platforms and readers.
Step 3: Monitor, which is the genuinely hard part
Set Google Alerts for your institution name plus “reddit,” and check the r/college and r/ApplyingToCollege threads about you quarterly. You’re there to catch factually wrong information — a wrong tuition number, a program listed as discontinued that isn’t — and correct it politely with a source.
The final point
If it feels like the ground is shifting under you again… it is. It always is. The good news is what we’re seeing here is the same product with a different label.
It’s scary out there guys, but if you focus on the fundamentals (understand the question, give the clearest and most credible answer, and make it easy to find and trust), you’ll do just fine.
Frequently asked questions
What’s the difference between SEO and GEO?
SEO aims to rank your page in a list of search results. GEO (Generative Engine Optimization) aims to get your information into the AI-generated answer itself. Both rely on useful, well-structured, credible content.
Do colleges need an agency to optimize for AI search?
No. The core work — writing clear answers, adding FAQs and schema, keeping facts consistent, encouraging reviews, and citing data — can be done in-house with existing tools and no additional budget.
What is schema markup, and why does it matter for AI search?
Schema markup is structured code added to a webpage that labels its content (a course, an FAQ, an organization) so machines can read it precisely. It helps AI systems understand and surface your content accurately.
How do AI tools decide which colleges to recommend?
They synthesize information from across the web — your site, reviews, directories, forums, and news — and favor sources that are clear, consistent, credible, and backed by data.
How long does it take to see results from GEO?
It varies, but foundational fixes like clearer answers, schema, and consistent facts can improve how AI systems represent your school within weeks, since these tools re-crawl and update frequently.
