Case study · Online courses
An online course business that was invisible to AI assistants
Named in 6 of 20 buyer questions before, 13 of 20 after four months.
Who: A founder-led online course business with six courses and about 9,000 past students, selling mostly through its own site.
- Questions where the course is named
- 13 of 20from 6 of 20
- Free-lesson sign-ups a month
- 310from 140
- Pages indexed
- 94%from 62%
- Directories with the correct description
- 4 of 4from 1 of 4
- Independent roundups that mention the course
- 8from 2
- Public lesson pages
- 13from 3
What changed
The course had good reviews and a loyal audience, but its best material was locked behind a login. Search engines and AI assistants could not read it, so when a buyer asked which course to take, the answer came from other sites that could.
We moved the most useful explanations onto public lesson pages, one question per page, and corrected how the course was described everywhere else it appeared. We then earned mentions in the roundups that assistants lean on when they recommend a course.
Four months in, the course was named in 13 of the 20 buyer questions we ask every week, up from 6. Free-lesson sign-ups more than doubled, and the owner could see which pages and which mentions had moved the numbers.
- Start6
- Month 17
- Month 29
- Month 311
- Month 413
The situation
A course business with strong reviews found that ChatGPT and Perplexity rarely recommended it, even for the exact topic it taught.
What they wanted
- Be named when a buyer asks an assistant which course to take
- Turn more of its search visitors into free-lesson sign-ups
- Know, week by week, whether the work was helping
What we found
- The best lessons sat behind a login, invisible to search
- Few independent roundups mentioned the course
- The course description differed across four directories
What we did
- Published public lesson pages for the ten most-asked questions
- Corrected the description on every directory
- Earned mentions in six learner roundups
How the engagement ran
Weeks 1 to 2
1. Audit and baseline
We read the site the way a crawler does, asked twenty buyer questions across the main assistants, and recorded who was named. That first set of answers became the baseline for everything after.
Weeks 3 to 6
2. Fix the foundations
We corrected the course description on every directory, fixed the pages that were not indexed, and wrote the briefs for the first public lesson pages.
Weeks 7 to 12
3. Publish and earn
Ten public lesson pages went live, each answering one real question. In parallel we reached out to learner roundups and earned six mentions.
Weeks 13 to 16
4. Measure and plan
We compared the weekly answer ranges with the baseline, kept what moved them and planned the next twenty questions.
What surprised us
- The single biggest gain came from fixing the description on the four directories, a one-day job
- Two lessons we thought were too basic to publish became the most-cited pages
What they keep
- Ten public lesson pages written to the business's voice
- A corrected description on every directory
- A weekly report with the answer ranges and what changed
How we measured it
Twenty fixed buyer questions, asked each week on the main assistants. We count a question as a win when the course is named in the answer, and we report the range across the weeks rather than a single week. Sign-ups come from the site's own analytics.
For the first time we could see how assistants talk about us and what moved the numbers.
What is next: Expand public lessons to the next twenty questions.
Results
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