How to Optimize for Generative Search Engines

Although the jury is still out as to how LLM and AI search engines will affect SEO tactics and search rankings long-term, the widespread rise of ChatGPT indicates they are here to stay. As more individuals opt for these resources, it is important for marketers to adjust their content strategy to meet these changes and stay apprised of what generative search engines prioritize through proactive generative engine optimization.

Why is GEO Matters for SEO

Rumors in the hall suggest traditional search may soon be something of a relic replaced by AI search platforms. So should auld acquaintance be forgot? And how much stock should you put into preparing for these changes? Does this mean the last 15 years you’ve been optimizing your business for traditional search was all for naught?

Not hardly. Generative engine optimization and SEO are inextricably woven together through algorithmic integrations with large language models (LLMs). What serves one only stands to facilitate the other. Here at Mostly Serious, we are tuning our approach to the key of AI to keep our content strategies in harmony with the future.

Will Generative Search Engines Replace Traditional Search?

While we aren’t ready to say goodbye to the Google Search Bar just yet, more people are opting to use AI search engines. These search generative experiences (SGEs) save time while delivering more relevant, personalized search results due to their ability to parse user intent. With these platforms now readily available, traditional search's ability to provide a list of webpages, seems comparably limited. Even when accounting for rich snippets or featured questions, it still lacks the depth and responsiveness of SGEs.

Generative search engines (GSEs), currently available through platforms like Google’s beta SGE and Perplexity.AI, offer the promise of a better, more streamlined experience. Providing synthesized results that provide comparisons, summaries, and extra resources in a simple search. These results often eliminate the need to break queries into multiple searches. Coupled with interactive chat boxes for follow-up questions, GSEs often result in a faster more integrated experience.

Generative Engine Optimization

New platforms for search mean marketers must calibrate their approach to meet the needs of evolving trends. Never shirking an opportunity for a new acronym, enter generative engine optimization, or GEO.

We’ve previously covered the importance of developing high-quality content that answers search queries so your pages are poised to have best-fit answers. Focusing on GEO and its strengths continues to take this to the next level. Through natural language processing, these engines use context, semantics, and user intent to align results with search intent.

This renders traditional approaches to keyword optimization less effective for ranking in GSEs. Notably, a study conducted by Princeton University, Georgia Tech, Allen Institute for AI, and IIT Delhi, found optimizing content for specific keywords decreased a text’s rankings by 10%. Although less notable in traditional search, this finding aligns with SEO trends since Google's helpful content update.

How to Optimize for AI Search

A safe bet to prepare for this transition is to shore up structured data so GSEs can effectively crawl your pages. However, the aforementioned study additionally identified three current areas for improving visibility within generative engines:

1. Referencing Citations
2. Incorporating Quotes
3. Utilizing Statistics

These attributes garner results likely related to improvement in specificity and credibility in line with traditional SEO guidelines. To that end, it makes sense that content that illustrates experience, expertise, authority, and trustworthiness using these elements is more likely to rank within GSEs.