Generative Engine Optimization (GEO) and AEO Services in India

Answer engine optimization (AEO) focuses on having your content selected as the answer to a question, whether in featured snippets, People Also Ask, voice assistants or AI tools. Generative engine optimization (GEO) focuses on AI systems that generate answers by summarising many sources, such as AI Overviews, ChatGPT, Perplexity and Copilot, and on being one of the sources they use and cite.

Both terms describe extensions of SEO rather than a replacement. The same foundations apply: search engines and AI systems must be able to access your content, understand it and trust it.

Each system works differently, and none publishes a complete formula. In general, AI search features retrieve relevant pages from a search index, then generate an answer and cite some of the pages used. Google has said that AI Overviews draw on its core search systems, and that pages need to be indexed and eligible to show a snippet. ChatGPT search and Perplexity use their own crawlers and search partners, and Copilot draws on Bing.

This means traditional visibility still matters. Pages that rank well, answer questions clearly and come from trustworthy sources are more likely to be retrieved and cited.

Google’s guidance says there are no additional technical requirements for AI Overviews beyond being indexed and eligible for a snippet, and that the same SEO best practices apply. Controls such as nosnippet, data-nosnippet and max-snippet also affect whether and how content is used in these features.

In practice, pages that are well structured, answer questions directly, demonstrate expertise and satisfy the searcher’s intent tend to perform better in both classic results and AI features. We focus on those fundamentals rather than tricks that claim to game the system.

AI companies use different crawlers for different purposes, and you can set rules for each in robots.txt. For example, OpenAI distinguishes between OAI-SearchBot, used for ChatGPT search results, and GPTBot, used for training models. Google-Extended lets you control whether content is used for some of Google’s AI models, but Google states it does not affect inclusion in Google Search, including AI Overviews.

Content that AI systems can use easily tends to share a few qualities. It answers the main question clearly near the top, uses headings that match the questions people ask, explains concepts in plain language, presents steps, comparisons and definitions in structured formats, includes specific facts and examples, cites reputable sources and states who is behind the content.

This is also what makes content useful for human readers, which is exactly the point. Our content SEO service applies these principles across your site.

AI systems form a picture of your business from many sources: your website, Google Business Profile, social profiles, directories, reviews, news mentions and other websites. If those sources describe you inconsistently, with different names, services, locations or outdated details, AI answers may describe you inaccurately or not at all.

We align your core business facts everywhere, add organisation structured data with links to your official profiles and strengthen reputable mentions through link building and digital PR.

llms.txt is a proposed standard: a simple text file that summarises a website’s key pages for large language models. Some AI tools may read it, but it is not an established ranking or citation factor, and Google has said it does not use it for Search. We can add one because it is low-effort and harmless, but we do not present it as a solution on its own. Accessible, helpful pages matter far more.

Microsoft Copilot draws on Bing’s index, and Bing data also supports other AI experiences. Many businesses ignore Bing because Google dominates traditional search in India. Verifying your site in Bing Webmaster Tools, submitting sitemaps and using IndexNow to notify Bing of new and updated pages quickly are simple steps that support visibility in these assistants.

Measurement is still developing. We combine several approaches: checking AI answers for your priority questions and brand queries regularly and recording which sources are cited, tracking referral traffic from AI assistants such as ChatGPT, Perplexity and Copilot in Google Analytics 4, monitoring Search Console performance, which includes Google’s AI features within web search data, and using AI visibility tools where appropriate.

Because AI answers vary by wording, location and time, trends across many checks are more meaningful than any single result.

Any business whose customers research by asking questions benefits. It is especially important for SaaS and technology companies whose buyers compare tools, healthcare and wellness providers answering common questions, education providers explaining courses and admissions, financial services explaining products, and professional firms whose expertise is their product. For these businesses, being the cited, trusted source builds authority even when fewer people click through.

AI search is new, and some offers are overstated.

When AI answers satisfy simple questions directly, some informational searches send fewer clicks to websites. At the same time, people who do click through from AI answers often arrive better informed and closer to a decision. The goal shifts from maximising raw traffic towards being the trusted source for your topics and capturing high-intent visitors. Reporting should reflect that by looking at conversions and brand visibility, not traffic alone.

The main factors are the number of priority topics and pages, the technical condition of your site, how much content needs restructuring or creating, brand consistency work across profiles and directories, and the depth of monitoring required. Because it builds on SEO, it is usually most efficient as part of an integrated SEO programme. We scope it after the baseline review.