How IGENSIA Education boosted its AI Visibility

Groupe IGENSIA Education (formerly Groupe IGS) is a major independent player in higher education and professional training in France. Founded 50 years ago, this federation of non-profit associations brings together 15 schools across 12 campuses. With more than 19,000 students trained every year and a network of 98,000 alumni, the group offers an open, academically rigorous, and professionally oriented education model. Its flagship institutions include ABC (American Business College Paris), ESAM, ICD Business School, IGENSIA Alternance, IGENSIA RH, IMSI, IPI, and ISCPA.

In the highly competitive private higher education sector, student recruitment is a critical issue. While Groupe IGENSIA Education has always excelled at traditional SEO, the rise of AI engines (ChatGPT, Perplexity, Gemini, AI Overview) has fundamentally disrupted the student orientation journey.

Today, prospective students and their parents ask AI engines direct and complex questions such as: "I'm looking for a Bachelor's in HR with a work-study program — which schools are the most recognized?" or "What is the best business school in Paris for international students?"

For Groupe IGENSIA Education, the challenge was significant: not only did they need to ensure that AI engines recommend their programs, but they also needed to manage this visibility across an entire multi-brand portfolio. Each school (ESAM, ICD, IPI, etc.) has its own challenges, its own target audience, and its own market. The group needed a solution capable of centralizing analysis while delivering school-specific insights.

To meet this challenge, Groupe IGENSIA Education deployed an ambitious GEO (Generative Engine Optimization) strategy, driven by BotRank.ai data. The goal was to understand how AI engines perceived each school and to identify concrete action levers to increase their overall share of voice.

1. Defining Strategic Prompts by School
The first step was to analyze the existing presence of each institution. Drawing on search data, teams identified the highest-performing queries and translated them into strategic AI prompts. Prompts specific to each field of study (HR, business, real estate, IT) were integrated into BotRank.ai for daily tracking across the main engines (ChatGPT, Gemini, Perplexity, AI Overview).

2. Producing Targeted Content
Thanks to BotRank.ai's multi-school dashboards, the group's various teams (SEO, communications, webmasters) were able to identify the topics on which certain schools lacked visibility. They then launched dedicated content creation projects to fill these gaps, structuring pages to be perfectly readable and extractable by AI models.

3. Optimizing Pages Technically
In parallel, the webmaster teams worked on the technical aspects of each school's pages to maximize their extractability by AI models. Semantic markup, data structuring, and prioritization of key information: all adjustments that enable LLMs to better read, understand, and accurately reflect each school's content in their responses.