The specialist AEO and GEO agency, with our own AI search monitoring platform.
Focus vertical — EdTech & education.
We track how ChatGPT, Claude, Gemini and other LLMs describe your courses, programs and platform, diagnose what is keeping you out of "what should I learn" answers, then execute the answer engine optimisation work end to end. Built on an AI monitoring tool we developed in-house and configure around your subjects, formats, competitors and learner profiles.
Learners and career-changers now decide what to study, and where, inside ChatGPT and Claude long before they compare providers on your website.
Answer engine optimization and generative engine optimisation are the layer where those study decisions get shaped, and it is the layer where most education providers have no presence, no data and no plan in place.
You rank on Google but you do not exist in AI search.
Search rankings and AI visibility run on entirely different signals, and ranking well on Google gives you almost no head start in AI search. Language models do not read search results pages. They draw on their training data, on third-party citations and on how clearly your courses are described across the web, which means you can hold page one for "learn Python online" and still be completely absent from ChatGPT, Claude and Gemini responses.
AI sorts you into the wrong category of provider.
You do appear in answers, just framed as the wrong kind of offering. Your course gets called a bootcamp, your bootcamp gets called a short course, your degree program gets lumped in with self-paced tutorials. The category signal you give off across your site and external sources is weak or contradictory, so language models default to the wrong framing at the exact moment a learner is deciding what type of program fits their goals, which is arguably more damaging than not appearing at all.
Your courses get described inaccurately.
AI models describe your format, level, duration, prerequisites and outcomes based on what they have learned, and what they have learned is often outdated, incomplete or wrong. A cohort-based program gets described as self-paced. A beginner course gets pitched to advanced learners. Certifications and career support get left out entirely. All of this is shaping what learners expect before they ever land on your enrolment page.
Your visibility swings between queries.
You show up in some AI responses and are missing from others, even for near-identical prompts. Your brand signal is too inconsistent for AI systems to include you with confidence, so two learners who phrase the same question slightly differently end up with two completely different recommendations, and yours often only makes one of them.
The signals that decide whether AI recommends your courses.
EdTech and education have a particular set of signals that drive visibility in AI search and the accuracy of how AI describes your programs. These are the six we track, diagnose and improve through our monitoring platform.
01
Skill and topic coverage.
Are you surfacing in answers to the specific skill queries that drive enrolments — "best course to learn Python for data science," "where to study UX design online," "best bootcamp for switching into product management"? When the answer is no, you are missing the exact moment a learner converts an intention into a shortlist.
02
Format and level accuracy.
Does AI correctly describe your format and level — self-paced or cohort-based, beginner or advanced, with or without a certificate, mentor-led or fully on-demand? Misreads here send the wrong learners to your funnel and quietly send the right ones to competitors.
03
Category positioning.
Does AI place you in the correct category — bootcamp, short course, professional certificate, degree program, MOOC, corporate training? Education categories overlap heavily, and when language models cannot confidently place you in one, learners comparing options across categories never see you in the comparison.
04
Career outcomes and credibility.
Do AI responses connect your programs to actual career outcomes — job placement, salary uplift, hiring partner companies, completion rates? "Helps you get hired" is a stronger AI signal than "teaches you the skill," and the providers that surface with outcome language consistently win the recommendation.
05
Language and geographic fit.
Are you being recommended to learners in the right languages, time zones and regions? Accreditation, language of instruction, eligibility and local recognition all shape which programs AI surfaces for a learner in Berlin versus Bangalore versus São Paulo, and most providers leave this signal completely unmanaged.
06
Share of Voice versus key rivals.
How often do you appear against the three to five providers who matter most in your subject and learner segment? Share of Voice in AI search is the most direct read on how likely you are to be recommended, and it tends to be a leading indicator of enrolment volume a cohort or two ahead of the funnel.
A monitoring platform that is built around your subjects and learner segments. We do not offer just a generic template.
We built our own AEO monitoring platform in-house, and we configure it around your courses, categories, competitive set, positioning and the queries your learners actually run. The competitors we track are the providers you actually compete with, and the metrics we surface map to how AI search visibility translates into enrolments in your specific niche.
We are a full-cycle agency, which means we do not hand over a dashboard and walk away. We analyse, we diagnose, we build the roadmap and we execute, either alongside your team or as a fully outsourced function.
Custom prompt library.
Tell us the subjects, formats and learner segments you want to monitor, generate prompts automatically and pick the ones that fit, or upload your own. You get a fully configured AEO monitoring dashboard built around the segments that matter to your enrolments, not a default one.
Configurable Niche metrics.
Mention Rate, Share of Voice, Average Rank, Category Accuracy, Outcome Signal Strength, GEO Score and several others, all weighted and reported against the goals you actually care about. The dashboard is customisable from the ground up, so the view your team logs into reflects how your business measures success.
Adjustable competitor lists.
Nobody knows your real competitor set better than you do, and AI knows even less than that. You can adjust the providers you want to monitor and benchmark against at any time, on your terms and at the cadence that suits your enrolment cycle.
Full setup support by our team.
As a full-cycle AEO and GEO agency, we are involved from step zero. We set the tool up, tailor it to your subjects and learner profiles, and guide you through prioritising the GEO initiatives that will move the needle first. Execution can run with your team, with ours, or with a blend of both, depending on the bandwidth and capabilities you have in-house.
Execute with your team or with our support, depending on your internal capabilities.
We adapt monitoring and AEO implementation to your subjects, internal metrics, and workflows.
We adapt monitoring and implementation to your category, your internal metrics and the workflows your team already uses. Strategy, execution and our in-house monitoring platform run as one engagement, so the work shows up in AI search visibility you can actually measure.
4 STEPS
AEO monitoring,
Monitor AEO – if & how you appear in AI search:
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mention rate,
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share of voice,
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brand attribute signals,
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topic coverage matrix,
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brand & source co-occurrence,
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your brand GEO score & dynamics,
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& any other tailored criteria.
Learn how AI systems describe:
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your course format & level perception,
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price and value perception,
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difficulty and prerequisites,
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career outcomes and certification,
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learner fit,
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& not limited to.
1
GEO readiness,
Analyse your GEO readiness:
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own resources programming layer,
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own resources content layer,
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third party presence,
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citations.
Check competitor visibility:
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who gets recommended,
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in what contexts,
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with which attributes,
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how positioning changes over time.
Understand which sources influence AI outputs:
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review and rating platforms,
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media mentions,
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syllabi and documentation,
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forums, Reddit, Quora,
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learner communities, alumni reviews, etc.
2
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quick-win identification,
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authority signal prioritization,
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content & curriculum-page recommendations,
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external visibility opportunities,
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phased execution framework,
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our team support,
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dynamics tracking.
Get a 90-Day GEO Roadmap.
3
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website & semantic structure recommendations,
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course and program pages optimisation,
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syllabus & curriculum page optimisation,
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AI-oriented content strategy,
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content creation & placement automation,
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review platform visibility increase,
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external mentions & authority building,
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Reddit, Quora & community presence,
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competitive positioning optimisation.
Enjoy Generative Engine Optimisation Support
4
What GEO fixes look like in practice.
These are the patterns that come up repeatedly across EdTech and education engagements. The specifics shift from subject to subject, but the mechanics behind the fix stay consistent.
"We appear in AI answers but we are described as the wrong type of program."
Correcting the category framing.
GEO Fix:
When category signals are inconsistent across the provider's website, external profiles and third-party mentions, AI models draw from contradictory inputs and default to generic framing. A homepage that says "bootcamp," course pages that say "intensive program" and reviews that say "short course" all feed into the same problem. The fix involves aligning category language across owned and external surfaces, rebuilding program pages around consistent format terminology and updating Course Report, SwitchUp and LinkedIn profiles to reinforce the correct positioning.
What to expect: AI descriptions of the program become more consistent as aligned signals replace the contradictory ones. With corrections across owned and external sources, the shift typically becomes measurable within six to ten weeks.
"ChatGPT keeps saying our course is self-paced when it's actually cohort-based."
Fixing format and level signals.
GEO Fix:
When program pages are thin on structured detail about cohort schedules, mentor sessions and live components, AI models fill the gaps with assumptions drawn from competitor pages and older reviews. The fix involves rebuilding program pages as citable, structured content blocks with explicit format, cadence and level data, adding FAQ schema, publishing comparison content against self-paced alternatives and distributing the corrected information through trusted third-party channels.
What to expect: format descriptions in AI responses improve as the structured content gets indexed and picked up externally. Four to eight weeks is a typical window before the correction becomes visible in monitored responses.
"We never appear when someone asks AI for a course recommendation in our subject."
Building skill and subject presence from 0.
GEO Fix:
Strong SEO performance does not automatically translate to AI presence. When skill and outcome signals are too thin or too scattered, language models cannot surface courses with any confidence. The fix involves building skill-based landing pages around consistent terminology, creating "best course for" and career-outcome comparison content targeting high-intent prompts and expanding external authority through education media, expert instructor contributions and review platform updates.
What to expect: subject and skill presence builds incrementally as signals accumulate. Providers starting from near-zero typically see measurable improvement in AI-generated learning recommendations within eight to twelve weeks of a coordinated push.
"Our visibility across ChatGPT and Claude swings wildly from one query to the next."
Stabilising multi-LLM visibility.
GEO Fix:
When different language models return different descriptions and different competitive sets for near-identical learner queries, the root cause is usually semantic inconsistency across the website, metadata and external mentions. The fix involves standardising terminology around format, level and outcomes, improving internal linking between related subjects and skill paths and setting up continuous monitoring across ChatGPT, Claude, Gemini and Perplexity to track variations and respond to them as they emerge.
What to expect: stability improves as the underlying signals become more consistent across sources. Monitoring is essential here as without a baseline across multiple LLMs it is difficult to tell whether changes are having any effect.
Who we work with:
Our AEO and GEO work spans online learning platforms and MOOCs, coding bootcamps and tech academies, professional certification providers, language learning apps, K-12 EdTech, higher education and university online programs, corporate training and L&D platforms, executive education, test preparation services, vocational and trade schools, creative and design schools, AI and data science academies, children's learning apps, tutoring marketplaces, and traditional offline schools and institutes expanding their digital presence.
In marketing since 2009. In AI search since it became a category.
Our team has worked with international brands across SaaS, e-commerce, fintech and professional services for over fifteen years, originally as ContActive Tech Communications.
Today, that same senior team applies its strategic and technical expertise to answer engine optimisation, generative engine optimisation, and AI search visibility.