Apr 30, 2025 7:00:39 PM 11 min read

From Search To Spotlight: How We Engineered A Spot In Google’s AI Overview

When someone searched for “Best LinkedIn marketing agency India,” Vajra Global appeared in Google’s AI Overview.

It wasn’t a coincidence. It was the outcome of a deliberate strategy built around a new paradigm: Answer Engine Optimization (AEO). We made a conscious shift from optimising for search engines to optimising for how AI retrieves, understands, and presents information.

AEO is quietly redefining how search works. And if your business depends on organic visibility, it deserves your attention.

Why AEO Matters Right Now

Search is no longer about who ranks first for a keyword; it’s about who provides the clearest, most trusted answer to a real question. And increasingly, that answer is being selected by an AI model.

Tools like Google’s AI Overview, ChatGPT, and voice assistants are reshaping how people access information. They favour conversational queries, concise answers, and credible sources. That’s exactly what AEO is designed to optimise for.

AEO builds on the foundations of traditional SEO and featured snippets, but goes further, optimising for how AI understands, selects, and presents complete answers in a conversational context.

We applied these principles to our LinkedIn service page (https://vajraglobal.com/linkedin-marketing-agency/) and the results were immediate.

Here's how we approached it.

Our Approach to Answer Engine Optimisation

1. Diagnosing AEO opportunities

We began by revisiting the basics - content, structure, schema - but through an AI lens.

Our audit focused on more than keyword density or page speed. We examined how questions were framed, how information was layered, and whether the existing schema made it easy for AI to understand the page’s purpose.

This process revealed subtle but significant gaps. Certain answers weren’t prominent enough. Some sections lacked clarity. Others had deeply layered content that made sense to a human reader but was difficult for AI to interpret.

Identifying these gaps gave us a focused blueprint - an AEO strategy on what needed to change and why.

2. Restructuring for AI readability

Information alone doesn’t get you selected. It has to be easy for AI to extract the answer.

We refactored the page structure to make answers more visible, right at the top where both people and AI expect them to be. Long paragraphs were replaced with skimmable sections. Key takeaways were highlighted. Complex ideas were broken into short, digestible blocks.

This wasn’t just for the AI algorithm. It also significantly improved the user experience. And in AI-led search, good UX is good SEO.

3. Enriching with structured intelligence

We then addressed what most websites overlook: structured data.

While surface-level optimisation can take you part of the way, AI systems rely heavily on schema to interpret context. We implemented FAQ schema, How-To markups, and entity-based relationships, which made it easier for search engines to “understand” not just what the page says, but what it means.

This invisible layer of intelligence gives AI engines the confidence to select your page as the right source. It’s not flashy, but it’s foundational.

4. Aligning with conversational intent

Search engines now sound more like people, and content needs to reflect that.

We rephrased large portions of the content to mirror how users naturally ask questions. Long-tail queries, voice search phrasing, and everyday language were all part of the rewrite.

Our goal was to sound less like a brand explaining itself, and more like a helpful expert answering a real question.

This shift not only improved AI readability, it made the AI-optimised content more accessible to actual users as well.

5. Strengthening authority signals

Search engines prioritise content that comes from credible, verifiable sources. So we set out to strengthen our E-E-A-T: Experience, Expertise, Authority, and Trust.

We embedded trust signals throughout the page, including expert bios, real client examples, third-party citations, and relevant credentials. The content wasn’t just informative; it was backed by real-world experience and external validation.

This is especially important in an AI context, where the model is trained to value reliable, well-sourced answers.

6. Committing to continuous optimisation

The final, and perhaps most important, part of our approach is continuity.

AI is changing fast. Search behaviour is shifting even faster. What works today may not work six months from now.

We treat AEO as an ongoing process. Our team regularly monitors AI behaviour, tracks algorithmic changes, and adapts content accordingly. It’s not about chasing trends, but about building resilience into our visibility strategy.

What This Means for Business Leaders

Most businesses are still optimising for the search engines of five years ago. But AI has rewritten the rules, and the goalposts have moved.

Search is no longer about being discoverable. It’s about being selected. And in a world where AI algorithms decide which voice gets selected, clarity, context, and credibility matter more than ever. The brands that understand this shift and act on it will have a significant edge in organic discovery, brand authority, and long-term visibility.

At Vajra Global, we work closely with brands to help them move from being found to being chosen. We build content ecosystems that are structured for where search is headed, not where it’s been. Answer Engine Optimisation is one way we make that happen.

If you’re thinking about how your business can stay relevant in an AI-led search world, let’s have that conversation.

Our team would be glad to walk you through what worked for us and how it can work for you.