How AI Search Affects Your Engagement Data (and What's Next)

Overview

If you're actively using Engagement Insights to track top-performing content, you probably have questions about how AI Search fits into the picture. This article explains how AI Search interacts with your current page view data, what to expect for your top content reports, and what's on the roadmap for AI Search-specific analytics.

Will AI Search Affect My Page View Numbers?

The short answer: it depends on how students engage with the results.

When AI Search surfaces content, it displays a response with citations linking back to the original resource — but that interaction alone does not count as a page view. If a student gets the answer they need directly from the AI response without clicking through, that will not register in your Engagement Insights.

However, if a student wants to dive deeper — watching a video, completing a virtual experience, or visiting a full resource page — they'll click through as they normally would, and that click-through will count toward your page views just like before.

What this means for your top 10 report:

• Some content may see a dip in page views if students are getting what they need directly from AI Search responses.
• Other content may hold steady or even increase, as AI Search actively surfaces and promotes relevant resources that students might not have found on their own.
• The net effect will vary depending on your content type, depth, and how your students naturally engage.

This is worth keeping an eye on as AI Search rolls out more broadly — and it's a great reason to make sure your content is rich enough that students want to click through for more.

Will There Be a Dedicated AI Search Analytics View?

Yes — this is actively on our roadmap, and it's a priority for us.

We know that visibility into AI Search activity is important for understanding how students are engaging with your platform in new ways. Planned analytics features include aggregate chat engagement metrics, CSAT scores, and feedback reporting. We're also evaluating query-level visibility — the ability to see what students are actually searching for — and will share more details on what the dashboard will include and where it will live as we get closer to release.

We don't have a finalized format to share just yet, but your feedback directly shapes how we build it. If there are specific data points that matter most to your team, we'd love to hear them — share those ideas with your CSM.

Will I Be Able to See What Students Are Searching For?

This is one of the most exciting things coming, and your instincts here are spot on.

The ability to see top search terms, common questions, and trending topics is exactly the kind of insight we're building toward. This data will be invaluable for helping you understand the language your students actually use — which, as you've noticed, can be very different from the language on your pages — and for identifying content gaps or opportunities to update how resources are described.

One thing worth knowing now: AI Search uses semantic retrieval, meaning it understands the intent behind a search, not just the exact words used. So if a student searches "who can help me with my resume" or "career advisor," the system will look for content that matches that meaning — including staff bios, pages, and resources that speak to those topics, regardless of whether those exact words appear.

That said, your observation about the word "advisor" appearing in staff bios is a great content strategy insight. Even though AI Search doesn't require keyword-matching the way traditional SEO does, having clear, natural language in your staff bios, resource descriptions, and page content helps the system surface the right results more reliably. Encouraging your team to write in plain, student-facing language is always a win.

The Bottom Line