--- title: "Vocational Skills EdTech AI Search & Organic Growth Case Study" canonical: https://snezzi.com/case-studies/vocational-edtech-case-study/ source: https://snezzi.com/case-studies/vocational-edtech-case-study/ --- > Canonical page: https://snezzi.com/case-studies/vocational-edtech-case-study/ Customer context ## About Confidential Vocational EdTech Confidential Vocational EdTech is a vocational edtech company based in India. This record covers the baseline and scope described below; it does not imply that every company begins from the same conditions. [Visit company website](#) Industry Vocational EdTech Location India Founded 2018 Team 50-200 Starting problem ## Career-shifters research in AI, the brand wasn't there A hybrid online + offline vocational EdTech places students into job-ready skill tracks, with most enrollment running through Meta and Google ads. Cost per qualified lead kept climbing every quarter. Meanwhile, prospective students, mostly first-time career-shifters, were starting their research inside ChatGPT and Google AI Overviews with questions like 'best vocational course after 12th', 'skill courses with placement', and 'how do I switch careers without a degree'. The brand was invisible in those answers; competitors got the citation. - CAC on Meta + Google rising 30% YoY without matching enrollment growth - Zero presence in AI-assisted career-research queries - Generic 'top vocational courses' pages on competitor sites were cited instead Work delivered ## Owning the AI career-research funnel We built a career-pathway content engine designed for how career-shift students actually decide on a vocational track. Outcome-led content (placements, salaries, career arc) rather than feature-led course descriptions, all structured for AI citation. 1. 01 ### Career-Pathway Pillars Built a pillar page per skill track with eligibility, duration, fees, placement outcomes, and FAQ schema. 2. 02 ### Decision-Stage Content Created 'compare X vs Y course' and 'which track is right for me' content tuned to the exact phrasing students use in ChatGPT. 3. 03 ### Course + EducationalOrganization Schema Implemented Course, EducationalOccupationalProgram, and FAQ schema across every program page. 4. 04 ### Outcome Attribution Tagged every enrollment lead with its discovery source (AI platform, organic, paid) so the team could see AI-driven enrollment growing in real time. Methodology ## How the work progressed The sequence and durations below come from this engagement record. 1. Phase 1 · 3 weeks ### Audit & Career-Pathway Mapping Mapped every skill track to the real questions students ask AI about it. 2. Phase 2 · 8 weeks ### Pillar Build Built per-track pillars with full FAQ, eligibility, placement outcomes. 3. Phase 3 · Ongoing ### Decision Content Layered comparison + 'which track is right for me' content tuned for AI buyer-decision queries. 4. Phase 4 · 2 weeks ### AI Attribution Wired AI-source tagging into enrollment forms; weekly reporting on AI-attributed leads. Reported for this engagement ## Measured movement over 9 months These values are specific to Vocational Skills EdTech's baseline, scope and measurement period. They are evidence of this engagement, not a forecast or guarantee for another brand. AI Citations on Career Queries 8X Cited by ChatGPT, Google AI Overviews, and Perplexity for 'best vocational course' and decision-stage queries. Organic Enrollment Leads 240% Organic-attributed enrollment leads more than tripled inside nine months. Paid CAC Reduction 28% Lower paid CAC as AI and organic leads scaled and converted at a higher rate. Monthly Enrollments / AI source 180+ Monthly enrollments attributed directly to AI-search referrals. > “Students don't open a search engine anymore. They open ChatGPT and ask 'what should I do after 12th'. We're finally the answer in those conversations.” What this suggests ## Lessons from the engagement 1. 01 First-time career-shifters trust AI assistants more than ad copy. Being cited beats being advertised. 2. 02 Outcome-led content (placement, salary, career arc) outperforms feature-led content in AI citation rates by 4-6X. 3. 03 Per-track pillar pages with FAQ schema get cited far more than generic 'top courses' listicles. 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