Lead the Way with Generative Engine Optimization

The relationship between user behavior and search engine algorithms is a dynamic dance—one that keeps digital marketers on their toes as they strive to boost brand visibility.

On the one hand, Google notoriously tweaks its algorithmsin their constant push to address users’ intent more effectively. On the other, significant alterations to Google’s search engine results pages (SERPs) in recent years fueled significant changes in user behavior, including the continued rise of zero click searches.

And then in 2023, an academic article by researchers at IIT Delhi and Princeton University made waves in the digital marketing world. “GEO: Generative Engine Optimization” charted a new path forward, highlighting the transformative potential of AI-powered engines for online search.

Ever since, GEO remains a hot topic for professionals at the cutting edge. Even now, data scientists and digital marketing specialists continue to debate what GEO should look like in practice. So let’s try and solve this question—not to settle it once and for all, but to provide you with a clear path forward.

What is Generative Engine Optimization (GEO)?

Conventional search engines like Google, Yahoo, and Bing crawl websites and index their content. Their algorithms then rank individual webpages in their SERPs, with pages assessed as most relevant to the user query appearing first.

By contrast, generative engines (GEs) such as Perplexity AI, SearchGPT, and Brave integrate artificial intelligence (AI) to produce results. They collate information from various online sources to synthesize personalized responses using large language models (LLMs). Google AI Overviews and Microsoft Copilot rely on similar technology.

One Field, Countless Acronyms

You may have noticed that the name for this emerging field remains disputed. The IIT Delhi and Princeton research teams opted for “generative engine optimization” (GEO). Meanwhile, the Harvard Business Review chose large language model optimization (LLMO), and a Forbes article opted for generative AI optimization (GAIO).

Generative Engine Optimization (GEO)

GEO centers on optimizing for AI-driven search engines that leverage generative models, such as conversational AI like OpenAI's ChatGPT or Google's Bard. This approach is deeply tied to user behavior and the transformative impact generative AI is having on search, emphasizing the need for marketers to adapt to a world where users often interact with AI-generated summaries and recommendations rather than traditional web links.

Large Language Model Optimization (LLMO)

LLMO narrows the focus specifically to large language models (LLMs), such as GPT-4 or Google's PaLM. This term is more technical, highlighting the optimization of content and strategies to work seamlessly with the capabilities and limitations of these advanced models. For instance, it may include ensuring that a business’s data is structured;, whether in customer interactions, search engine outputs, or chatbot responses.

Generative AI Optimization (GAIO)

GAIO has the broadest scope of the three terms, encompassing strategies for optimizing all forms of generative AI applications. Hence, it includes not only text-based generative models like LLMs but also image-generation tools, AI video creators, and other generative technologies. This term is popular in business and tech discussions, especially at the executive level, as it reflects a more holistic view of how generative AI can impact everything from marketing to operations and beyond.

Even though there’s clear differences between these terms, the core principles linking users, search, and generative engines remain consistent. For simplicity and focus, we’ll use GEO as our reference point in this primer.

Benefits of Implementing GEO

The primary benefit of effective GEO is boosting your brand’s visibility through generative engine output. By optimizing your content for AI-powered engines, you increase your chances of being featured in their responses, which extends your reach and engages a broader online audience.

But that’s not all. The in-depth research required to produce impactful GEO will provide you with a more holistic understanding of your customers’ needs, motivations and intentions. This enables you to adapt your overall digital marketing strategy with greater purpose and, ultimately, offer an enhanced user experience.

Finally, as an early adopter, you can set the pace in your niche. By getting to grips with this emerging technology at an early stage, you can secure a competitive edge in the crowded online marketplace.

SEO and GEO: Compare and Contrast

In a way, conventional search engines and generative AI engines share the same fundamental purpose: to respond as effectively as possible to users’ queries. Similarly, SEO and GEO share the same objective: to improve the visibility of online content in search results.

Key Commonalities between SEO and GEO

While generative engine optimization introduces new layers of complexity, many foundational SEO practices remain highly relevant. Here are the key commonalities that serve as the building blocks for both strategies:

• Keywords: Effective keyword management remains essential for successful GEO, although we recommend deeper user research, as understanding nuanced user intent can significantly enhance the quality and accuracy of results generated by AI-powered engines.

• E-E-A-T: Google’s guidelines on creating helpful, reliable, people-first content remain just as relevant to generative engines. Content that demonstrates expertise, experience, authoritativeness, and trustworthiness draws favor from both conventional and AI-powered search platforms.

• Structured data:Schema markup enables conventional as well as generative engines to access unambiguous data in easy-to-process formats. Add markup tags to highlight products, local businesses, or upcoming events.

• Technical accuracy: Much like conventional search engines, AI-powered engines also consider factors including a website’s loading speed, crawlability, and mobile optimization when assessing the overall quality of its content.

Key Differences between SEO and GEO

Understanding the distinctions between SEO and GEO is critical for adapting your digital strategies to generative engines, too. While traditional SEO focuses on optimizing content for indexing and ranking, GEO requires a shift toward meeting the sophisticated capabilities of AI-powered engines.

• Synthesizing, not cataloguing: Conventional search engines crawl and catalogue every possible webpage before ranking them based on the quality of their response to specific queries. By contrast, generative engines search and pull content from different sites in order to synthesize a personalized response tailored to the user’s query.

• Focusing on context: Generative engines use natural language processing (NLP) to evaluate the context of a phrase or statement. While conventional search engines do this to some degree, their capabilities focus far less on interpreting language.

• Interpreting natural language: Deploying NLP means that generative engines interpret and manipulate written human language far more accurately. This allows GEs to infer meaning and thereby assess more effectively whether specific content responds to a given user query.

Most notably, keywords and conventional E-E-A-T impact generative search engines less dramatically. Although keywords influence which content GEs select when synthesizing responses, these complex processes take many other factors into account.

An Integrated Strategy for SEO and GEO

In light of the differences between these technologies, digital marketers should not view GEO as merely an off-shoot of SEO. While the two share some common features that marketers should leverage, GEO calls for specific measures and tactical adjustments.

In short, astute digital marketers should aim for an integrated strategy, optimizing content to appeal to conventional search engines and generative engines alike. Let’s examine how to achieve this.

1. Adapt Your Keyword Strategy

Generative engines, like conventional search engines, rely on keywords to identify content relevant to a search query. However, generative engines focus even more strongly on user intent, so you should broaden the scope of your research, prioritizing conversational queries and semantic keywords.

2. Integrate Content into the Broader Context

Generative engines rely on a wide range of metrics to assess the E-E-A-T parameters, which includes examining how content integrates into the broader context—meaning: better review your content.

Does it answer the questions your target groups are asking in AI-powered search queries? Is it both cohesive and comprehensive? If your content only answers parts of key questions, or fails to provide sufficient detail, GEs might look elsewhere when synthesizing a response.

3. Write Like a Real Person

Natural language processing capabilities enable generative engines to interpret, manipulate, and produce human language in a more conversational format. As such, you should strive to make your online content as easy as possible for generative engines to parse and interpret. Test your copy in writing tools such as Hemingway Editor, which can help you find simpler and more natural formulations.

Integrating conversational queries, rather than just stand-alone short-tail keywords, will also appeal to AI-powered search engines. But don’t forget that NLP-based tools continue to evolve at a rapid pace.

4. Cite Your Sources to Establish Authority

The authors of that watershed GEO paper identified three generative engine optimization factors as the most impactful: citing sources, adding statistics, and authoritative language.

Citing sources may seem slightly abstract at first glance, especially from a marketing perspective. However, backlinks to review platforms, and authoritatively integrating statistics that outline your brand’s excellent online reputation, should all catch the attention of generative engines.

5. Make the Most of Schema Markup

Despite their ability to process natural language, generative engines also rely on structured data to understand website content. Implementing this unambiguous code in your website makes it easier for search engines – both conventional and AI-powered – to characterize and categorize your website and its content.

Different types of schema markup highlight different key aspects, from review scores to product information. Integrate these snippets of code to assist search engines in sourcing and delivering relevant, accurate information about your business.

6. Test, Trial, and Experiment

Remember that GEO only began to emerge very recently, with digital marketers now striving to adapt and keep pace with rapid technological innovation. Just like with SEO, the tools and user behavior constantly evolve, too, so digital marketers should adopt a flexible strategy.

Integrate different formats, such as text, images, and video, to engage your human audience, conventional search engines, and generative engines. By conducting A/B testing of different formulations, phrases, and techniques, you can glean insights into which appeal most to generative engines.

At present, hard-and-fast answers appear hard to come by. Investing time in exploring the world of GEO is an opportunity for your brand to stay ahead of the competition.

Laying a Solid Foundation

Many practical aspects of GEO remain uncertain, so digital marketers should adopt an iterative approach built around experimentation. What is already clear, however, is that several SEO fundamentals remain equally relevant for GEO. So, before you start building up a sophisticated strategy for this emerging technology, make sure you’re starting from a solid foundation.

For brands with multiple stores, this means ensuring that location data is consistently up to date across as many platforms as possible, from business directories and review platforms to local pages on your website.

The most efficient and effective way to ensure consistency? Deploy a location marketing platform like Uberall, featuring sophisticated tools and AI-powered assistants to help you manage wide-ranging location data – including reviews, messages, and social media content – from a single, centralized platform.

Curious?Request a demo today and take your first step towards the future of marketing.