AI Search Optimization (GEO/AEO)
Visibility and measurable acquisition across AI Overviews and conversational search engines.
Overview
AI search changes both where answers appear and how they can be measured. The work has two halves: making content structured and credible enough to be cited, and building measurement that separates LLM referral traffic from AI Overview exposure.
At Practo I built that measurement framework for leadership reporting and used it to grow AI-driven transactional demand across markets.
Problems this solves
- No reliable way to measure AI search visibility or referral traffic
- Content that answers user intent but is not structured to be cited
- Leadership asking for an AI search position with no baseline to work from
- Programmes that treat AI search as separate from organic acquisition
Typical deliverables
- AI search visibility baseline and measurement framework
- Separation of LLM referral traffic from AI Overview exposure in reporting
- Content and entity structure recommendations for citation
- User-intent programme covering AI Overviews and conversational search
- Reporting cadence for leadership
Best suited for
- Businesses seeing AI surfaces intercept research-stage demand
- Teams that need defensible AI search measurement before investing
- Marketplaces where transactional intent is moving into AI answers
AI Search Optimization (GEO/AEO) — frequently asked questions
Related services
Content planned against real demand and produced through operations that hold up at scale.
Organic growth built into the product surfaces themselves, in partnership with Product, Engineering and Analytics.
Crawl, indexation, architecture and rendering fixed at the level of the system rather than the page.
Related case studies
Considering a AI Search Optimization (GEO/AEO) engagement?
Start with a short conversation about the problem you are trying to solve.
Prefer email? nitesh.0903@gmail.com