Catching Up in Higher Ed Marketing

In consumer-based marketing, AI has been a hot topic on the conference circuit for years, and marketing in higher education is finally catching up. At Indian River State College (The River), we take a Direct-to-Consumer (D2C) approach to marketing and communication, pushing our teams to innovate with AI at the pace of tech rather than that of higher education. Here, AI is native, not just introductory and experimental. It’s how we connect in ways that matter, while keeping grounded in our core  purpose: to support our students.

At The River, we’ve validated what many in the D2C space already know: prospective students, parents, and donors aren’t just searching for information on Google or social media; many are using AI chatbots to get the information they need. This realization came when our web analytics revealed a steady stream of visits coming directly from AI-powered tools like ChatGPT and Gemini. In fact, sessions originating from LLM-driven sources more than doubled in Q2 2025 as compared to Q1. This trend mirrors a broader shift in search behavior; research by Linehan and Guan found that 63% of websites now receive at least some traffic from AI chatbots, and ChatGPT alone accounts for about half of all AI-driven referrals. In other words, AI is fast becoming a new gateway to reach our key stakeholders.

Higher education institutions are not exempt from this shift, as our own data revealed. Based on this shift in consumer behavior, our Marketing & Communications team pivoted to treat AI as a strategic partner in our ecosystem rather than a novel tool. The remainder of this article explains this approach, from monitoring AI-sourced traffic to curating content optimized for AI-generated responses, offering reflections on both the opportunities and challenges of embedding AI into college marketing.

How We Realized the Importance of AI-Driven Search

Unlike traditional search engines that list dozens of links in response to a user query, AI platforms deliver answers in a conversational format with information from multiple sources in one response. This convenience is attracting users: one 2024 survey by Mindbees showed 17% of U.S. respondents prefer using AI chatbots over search engines for quick, precise answers. ChatGPT and similar tools act like “virtual advisors,” cutting through the clutter of ads and optimized content to provide straightforward responses. In higher education, this means parents can ask pressing questions about a college and its programs and receive an instant, personally tailored answer (instead of combing through search results and paid search ads).

At Indian River State College, we realized the enormous potential of AI searches for changing the way to engage potential students and other stakeholders. Yet there is a possible downside, given the probabilistic way that AI systems generate output: inaccurate information. For example, several students recently asked an AI assistant whether Indian River State College was open on Presidents’ Day. The chatbot confidently replied that the College would be closed for the holiday, but we were open. This led to several students not showing up for class – a small but telling error that highlights a core challenge: when AI lacks up-to-date or specific information, it will fill in the gaps with an answer that sounds plausible, even if it’s wrong.

In this case, the AI likely assumed we followed federal holiday closures by default, but assumptions aren’t facts. This incident reinforced for our team the importance of monitoring the information AI platforms pull from our site, to identify gaps where clarification is needed, and to remember that even the smartest models can mislead or “hallucinate” when they don’t know the answer. Our subsequent curation of clear, accessible, and up-to-date content is one way we mitigate this risk, helping to reduce the instances in which AI tools resort to guesswork.

Gaining Insight: Monitoring AI Traffic at Indian River State College

The first step in the College’s new approach to managing online visibility is to identify and track AI-originating traffic in our web analytics. Using Google Analytics 4 (GA4), we set up filters to surface referrals from known AI domains, such as chat.openai.com (ChatGPT’s referral domain). This process, sometimes called creating an “AI traffic report,”allows us to isolate how many users are surfacing our site via AI tools (as well as which pages they land on).

The effort was enlightening. We discovered that certain pages on our site act as “AI magnets.” For instance, our admissions FAQ and a blog post about our unique programs were disproportionately popular among AI referrals. This makes sense: these pages directly answer common questions (tuition costs, program highlights, campus life) that people might pose to an AI assistant, which highlights the strategic value of this type of monitoring. By keeping an eye on AI referrals, we were able to see which topics AI platforms view as authoritative. As noted in a recent industry study, “monitoring your AI traffic can show you which sources send users your way, which pages on your site act as AI traffic magnets, and how that traffic is changing or growing over time” (Linehan and Guan).

Interestingly, analytics data provide a feedback loop: if we notice a spike in ChatGPT-driven visits to a new scholarship page, it likely means users are asking ChatGPT about “scholarship opportunities at Indian River State College”— and getting our content as a response. That’s a signal of what information people want from us via AI. Conversely, if an important page (say, our nursing program description) never shows up in AI referrals, our content isn’t being picked up by the AI, and this is a gap we need to address.

Another benefit of reviewing analytics data is being able to discern substantive AI traffic from mere curiosity clicks. When someone visits from an AI recommendation, we track engagement. Do they explore more pages? Do they initiate an application or request information (what we define as “key conversions”)? By carefully analyzing the data, we’ve learned that some AI-sourced visitors are deeply engaged while others are not.  

Unsurprisingly, tracking AI-search visitors has become a new part of our marketing analytics regimen. Just as we’ve long monitored traditional search, social, and email metrics, we now include AI referral trends in our reports to leadership. It’s an early warning system for how our digital presence is faring in the AI-driven world. And it sets the stage for the next step: if we know where AI is sending people, we can deliberately optimize those touchpoints with relevant content that adds value.

Curating Content for AI: “AI SEO” and Brand Alignment

Knowing that AI chatbots are reading and recommending our content, we are continuously working to adapt that content with these digital intermediaries in mind. Traditional SEO (Search Engine Optimization) is about leveraging Google’s algorithms; Marketers have been focused on using keywords, meta tags, and backlinks to rank higher on a search results page. Now, we’re practicing what some have dubbed “AI SEO” or Generative Engine Optimization (GEO) (Delgado).

Based on this new optimization process, we’ve resolved on a few key tactics (which echo best practices being discussed across the industry):

1. Talk like a person: We write online content in a tone that’s clear and human, avoiding jargon or robotic phrasing. AI models are trained on everyday language, so content that “reads” naturally is easier for them to digest. I’ll often ask my team, “Is this something you would say to your friend?”, and if the answer is no, we rewrite. It’s that simple. This is a massive cultural change at the institution, and we’re still working to have this approach across the board, not just in marketing-specific language.
2. Be concise, even when it’s hard: As a college, it’s easy for us to over-explain, but that won’t work here. Much like writing featured snippets on Google, we ensure that our content addresses common questions in the first few sentences. If we publish a page about campus safety, the opening lines might directly state our safety ranking, resources, and commitment. That way, if someone asks an AI, “How safe is IRSC’s campus?”, the bot can provide that answer directly.
3. Use “AI Listening” to generate ideas: We actively use AI tools in partnership with research platforms like Google Search Trends to interact with and generate ideas on what content ideas are best to prioritize. For example, if we notice traffic driven by questions about housing options, but our existing pages barely mention on-campus living, we may partner with ChatGPT to figure out why.
4. Kill the keyword obsession: Rather than obsessing over the perfect keyword, we incorporate related terms and questions that provide context. For example, alongside “Indian River State College,” we’ll mention “community college in Florida,” “affordable tuition,” “bachelor’s programs,” etc. This aligns with how AI understands content by context, not just exact matches.

In implementing these tactics, we essentially treat the AI model as an audience of its own, but one that “reads” everything and might selectively quote us. It’s a fascinating new dimension to content strategy.

One concrete step we took on the technical side was ensuring our site is accessible to AI crawlers. For instance, OpenAI’s crawler (used by ChatGPT’s browsing feature and potentially for training data updates) was explicitly allowed in our robots.txt file, per emerging GEO recommendations (Delgado). We also made sure our sitemap was submitted to Bing since Bing’s index could feed Microsoft’s Copilot and other GPT-based tools.

These behind-the-scenes tweaks ensure that when AI systems go looking for college information, they can find and index our latest content without roadblocks. All of this work is done so that we’re searchable and relevant for our customers (potential students) and active audiences. We’re here to provide value, and AI helps us do that while retaining our distinct brand voice and presence.

Integrating AI into our marketing strategy also raises important ethical and governance considerations. As noted above, one concern is accuracy. As a result of key design features, AI chatbots can sometimes produce incorrect or outdated information. At Indian River State College, we see it as our responsibility to minimize that risk as a core value. That’s why providing current, factual content is so important, as is keeping humans in the loop: we’re effectively fact-checking on the front end by curating what’s available for AI to find and monitoring back-end results for signs of AI error.

Conclusion: AI’s Lasting Impact on College Marketing

Our journey of embracing AI for marketing and communications at Indian River State College is still unfolding, but a few clear themes have emerged. AI is not just a tool we use; it’s an essential part of the information ecosystem. . Just as we consider students, faculty, alumni, and search engines in our communication plans, we now consider AI platforms as well. By proactively monitoring AI-driven traffic and tailoring our content for AI consumption, we ensure that when someone’s personal chatbot “recommends” the college, it does so with correct and compelling information. This approach has helped us reach people we might have missed, reinforce our brand messaging in novel channels, and learn more about the questions and interests of our audience in the process.

AI use statement: Generative AI was used in the sourcing and editing of this article. The author sourced leading industry trends and then used LLM to revise for clarity and cut down the article from its original length.

Works Cited

Caylor, Bart. “Embracing ChatGPT for Higher Education: Balancing Brand Authenticity with AI Innovation.” Medium, 30 Aug. 2023

Cumberland College. “How to Optimize Content for AI Research Tools Like ChatGPT.” Cumberland College Blog, 12 June 2025

Delgado, Isabel. “Generative Engine Optimization (GEO): SEO for ChatGPT and AI-Driven Search Engines.” Benchmark Email Blog, 11 Mar. 2025

IRSC Web Analytics Data (GA4) – AI Tools Traffic Report, Apr–July 2025.

Linehan, Louise, and Xibeijia Guan. “63% of Websites Receive AI Traffic (New Study of 3,000 Sites).” Ahrefs Blog, 6 Feb. 2025

Linehan, Louise. “AI Chatbots Are Shaking Up Search: What’s Next?” MindBees Blog, 20 Mar. 2025

Linehan, Louise. “AI Traffic Has Increased 9.7x in the Past Year.” Ahrefs Blog, 2025

MindBees. “How to Track AI Referral Traffic in Google Analytics 4.” MindBees Blog, 8 Apr. 2025