What is AI Search Optimization?
We are increasingly turning to AI chat tools like ChatGPT, Perplexity and Gemini to find information, products and services. This presents a once-in-a-generation opportunity for businesses that can adapt their marketing strategies to ensure these AI tools recommend their offerings. Successfully navigating this new era of AI search optimization requires a strategic approach beyond traditional SEO.
The Rise of AI Search and its Foundational Reliance on Traditional SEO
There is a huge shift in the world of search, with AI chat tools like ChatGPT, Perplexity, and Gemini gaining significant traction, indicated by a 50% increase in ChatGPT interest in three months and major search engines losing users in some areas. This disruption means that ranking on Google through traditional SEO alone is no longer sufficient for visibility in AI search, whether it's Google's AI Overviews, AI mode, or other tools.
However, traditional SEO remains a "really important foundation" for AI search optimization. When AI tools like Perplexity search for information (e.g., "best travel backpacks"), they perform web searches in the background across various search indexes like Google, Bing, and Brave, then summarize the content they find. The articles these tools use as sources are often optimized for straightforward SEO-type phrases, meaning businesses first need to rank well in regular search to be recommended by AI tools. Despite this, traditional search's days are "for sure numbered," but SEO is still fundamental for success in this new era.
Three Core Components of AI Search Optimization (AISO)
Broadly, AISO involves three main elements: regular SEO, optimizing your content, and shaping/increasing the sentiment and mentions of your brand, products, and services online.
Content optimization is crucial; AI tools tend to use and cite content that is written in a specific way: short, simple sentence structures, clear headings, and content organized for quick scanning. Adding an intro paragraph with a summary or clear answer (similar to optimizing for Google's featured snippets) is also important. A key differentiator is sharing firsthand experience, data, and statistics that AI cannot produce itself, making your content more valuable as a source. Content that is nicely presented, not cluttered with ads, frequently updated, includes author information, and provides in-depth research is more likely to be featured. Different content types, such as videos, Quora threads, or Reddit threads, can also be cited by AI answers, highlighting the importance of a diverse content strategy.
Increasing mentions and improving brand sentiment across the web is an often-overlooked but critical component. AI tools pull information from a multitude of sources, including high-authority publications (e.g., NYAG, Wired.com) and user-generated content sites (e.g., Apple forums, Reddit, YouTube, Kora). They pick up on sentiment, common threads, and features that appear repeatedly to form their recommendations. This requires businesses to be crystal clear about what they want to be known for (e.g., Zugu cases for durability and functional design), ensuring those features are consistently highlighted across various websites. This is a departure from traditional SEO, where just ranking at the top was often enough; now, businesses need to "make their case online" so AI tools understand why to recommend them.
Monitoring AI Search Performance and its Strategic Business Impact
Monitoring AI search performance is "much fuzzier" than traditional SEO because answers are created dynamically. New tools are emerging, such as Semrush's AI toolkit, which allows marketers to track how their brands are recommended across different AI search platforms like ChatGPT, Search GPT, and Perplexity. This toolkit provides insights into market share against competitors, brand sentiment (positive or negative perception), and identified strengths and weaknesses based on user-generated content.
Crucially, these AI toolkits offer AI strategic opportunities, providing suggestions that go beyond typical SEO feedback. For example, they might recommend producing content on a specific topic or even suggest upgrading digital advisory and customer service if those are areas where a business is falling short. This means marketers, armed with such tools, can influence other departments within their organizations by funneling direct customer feedback to improve products and services, making them more central to overall business strategy.
The reports can offer insights into market position, market share trends, emphasize specific brand attributes (e.g., Vanguard's low-cost fees), suggest areas for improvement (e.g., more human interaction in digital advisory services), and identify content gaps based on query intent and specific topics. This enables the creation of content that fills knowledge gaps for AI tools, leading to better recommendations. Constant monitoring and tweaking of content format and targeting are essential, with some changes showing results rapidly.