What is Answer Engine Optimization? A Guide to AEO-Powered Growth

What is Answer Engine Optimization? A Guide to AEO-Powered Growth

Master Answer Engine Optimization to enhance your content's visibility in voice search and virtual assistants.

Answer engine optimization emerged as a result of the rise of generative AI chatbots like ChatGPT and Bard, as well as the popularization of AI powered voice search assistants like Alex, Siri and Google Assistant. Instead of scrolling through blue links on SERPs or looking through various websites to find the answer to their questions, consumers are now receiving singular, well-packaged, and immediate responses to their search queries. This shortening of the search process is making a huge impact on the future trajectory of search, and demands businesses to rethink how they are optimizing their content in order to be surfaced as a search engine (or more accurately, an answer engine) result. 

Before we dive into the specifics of how to leverage answer engine optimization to power your business growth, let’s clarify what exactly an answer engine is and how the cultural shift from search engines to answer engines came about. 

What is an answer engine?

In today’s digital age, where information is always just a few clicks away, the concept of search engines has become ubiquitous; however, a new player has entered the scene: the answer engine. 

While traditional search engines like Google and Bing provide a list of relevant web pages in response to a query, answer engines take it a step further by directly providing concise and accurate answers to specific questions — all with zero clicks and little to no wait time. An answer engine harnesses the power of artificial intelligence and natural language processing to understand the user’s query and deliver a direct answer, eliminating the need for users to sift through multiple search results. These engines are designed to provide instant and precise responses, making them invaluable tools for quick and efficient information retrieval. Whether you need to know the weather forecast, the capital of a country, or the definition of a word, an answer engine can provide you with the answer in a matter of seconds, revolutionizing the way we seek and consume information.

What are some examples of answer engines?

There are two main categories of search engines: generative AI bots such as ChatGPT and Bard, and AI powered voice search assistants such as Alexa, Siri and Google Assistant. Generative AI bots, such as ChatGPT and Bard, utilize sophisticated artificial intelligence algorithms to generate human-like responses to queries. These answer engines excel at understanding and generating textual information, making them valuable resources for answering a wide range of questions. With their ability to comprehend context and engage in dynamic conversations, generative AI bots are becoming increasingly popular for providing detailed and informative answers. 

Open AI launched ChatGPT in November of 2022, and it quickly gained traction, capturing the interest of researchers, developers, and users alike. The model’s ability to engage in dynamic conversations and provide coherent responses made it a breakthrough in the field of generative AI. Users can interact with ChatGPT by simply inputting text prompts and receiving detailed and informative answers in return. While ChatGPT has been widely praised for its conversational abilities, it also comes with certain limitations, such as occasional inaccuracies or generating responses that may seem plausible but are not factually correct.

Following the success of ChatGPT, Google launched their rival chatbot, Bard, in March of 2023. While Bard is functionally similar to ChatGPT, the biggest difference between the two is that Google’s service will pull its information from the web. Bard itself was an entirely new concept that was very likely spurred by a sense of urgency around competing with ChatGPT, but it is actually powered by Google’s Language Model for Dialogue Applications (LaMDA), which was unveiled two years prior. 

Another type of answer engine separate from the realm of chatbots is AI powered voice search assistants. These answer engines utilize voice recognition technology to understand spoken queries and provide immediate responses. With just a simple voice command, users can ask questions, get directions, set reminders, and perform various tasks without even touching a screen. Voice search assistants are designed to provide quick and convenient answers, catering to users who prefer hands-free interaction and real-time information. As these assistants continue to evolve and improve, they are becoming an integral part of our everyday lives, seamlessly integrating into our homes, smartphones, and other smart devices. In contrast to the relative newness of generative AI chatbots, voice search assistants are already very much integrated into consumers’ daily lives, with 40% of all internet searches in the U.S. being voice based.

What’s more, 72% of people who own a voice search device say it has become a part of their daily routine, and 65% of people who own a Google Home or an Amazon Echo don’t want to go back to keyboard searches. There’s no denying that voice search is going to continue to be an integral part of the day-to-day user experience, meaning marketers will need to know how to successfully optimize their content for it in order to succeed.

How did we shift from search engines to answer engines? 

The evolution from traditional search engines to answer engines represents a significant shift in how we seek and consume information. While search engines like Google and Bing have long been the go-to platforms for retrieving relevant web pages based on keyword queries, the rise of answer engines has transformed the landscape of information retrieval. This shift can be attributed to advancements in artificial intelligence and natural language processing, enabling answer engines to understand queries in a more nuanced manner and provide direct and accurate answers to specific questions.

One of the key drivers behind this shift is the increasing demand for instant and precise information. Traditional search engines often presented users with a list of relevant web pages, requiring them to navigate through multiple sources to find the desired answer. This process could be time-consuming and often required the user to skim through lengthy articles or websites. Answer engines, on the other hand, leverage AI algorithms to interpret the user’s query, extract relevant information, and deliver a concise answer. This streamlining of the search process eliminates the need for users to sift through search results, providing them with the desired information quickly and efficiently. In short, consumers are become more and more impatient — and answer engines are rising to the challenge to combat that desire for faster, more accurate information delivery. 

The emergence of voice-enabled technologies has also played a significant role in the rise of answer engines. Voice assistants like Alexa, Siri, and Google Assistant have made it essentially effortless to ask questions and receive immediate answers. Users can simply speak their queries, and the AI-powered voice assistants leverage natural language understanding to provide spoken responses. This shift towards voice-based interaction has further propelled the demand for answer engines, as they offer hands-free access to information and cater to the growing preference for voice search.

What is answer engine optimization?

Now comes the fun part.  

AEO, or Answer Engine Optimization, refers to the practice of optimizing content to provide direct zero click answers to user queries. This can be on a Generative AI powered Chatbots like Bard or ChatGPT, search engine results pages like Google or Bing or voice search products like Alexa or Siri. Answer engine optimization is also known as LLMO, or Large Language Model Optimization, highlighting the process of optimizing large language models (LLMs) and influencing its learning and training data and feedback loop to ensure that your brand is intentionally present in the right spaces at the right times. 

AEO is arguably a subfield or an evolution of SEO (search engine optimization), with a similar principle of needing to understand the user’s search intent and how best to answer it. While AEO shares a common goal with SEO to provide highly useful content that answers users’ queries as accurately and concisely as possible, AEO specifically focuses on creating content that is a direct answer to the question, so that is easily readable, crawlable and presentable by AI answer engines and voice search assistants. 

How does SEO differ from AEO? 

Search Engine Optimization (SEO) and Answer Engine Optimization (AEO) are two distinct approaches to optimizing content for search engines, each with its own focus and objectives. SEO primarily revolves around improving website visibility and rankings on traditional search engines like Google and Bing. It involves optimizing various aspects such as keywords, featured snippets, structured data markup, link building, and site structure to ensure that a website ranks higher in search results pages. SEO aims to attract organic traffic by providing valuable and relevant content that matches user search queries, with the goal of increasing website visibility and driving traffic to the site.

On the other hand, AEO is a more specialized approach that specifically targets answer engines or AI-powered platforms that directly provide answers to user queries. AEO focuses on creating content that directly answers specific questions in a concise and accurate manner. It involves understanding user intent, optimizing content structure, and using language that is easily crawlable and comprehensible by AI answer engines like ChatGPT or Bard. AEO aims to position content as the direct answer to user queries, ensuring that it is easily discoverable and displayed prominently on answer engine platforms.

While SEO and AEO share the common goal of improving online visibility and attracting relevant traffic, they differ in their execution and target platforms. SEO strategy is broader in scope, catering to traditional search engines and aiming for higher rankings, while AEO is more specialized, targeting answer engines and focusing on directly answering user queries. Implementing both SEO and AEO marketing strategies can be beneficial, as it allows businesses to optimize their content for a wider range of search platforms and cater to different user preferences in seeking information.

How to perform answer engine optimization for your business

With the rapidly increasing popularization of answer engines, it is crucial for brands and marketers to grasp the art of optimizing and influencing the outputs of these engines. You can begin by identifying, understanding, and influencing the data sources on which these engines rely for training. AEO involves ensuring that the content and data you publish are easily accessible and can be utilized to train answer engines, enabling you to have an impact on their output. This is where the power of community building and user-generated content shines, as socially-validated content pieces can serve as the fundamental sources from which answer engines extract their information.

To truly comprehend what generative AI deems an optimal answer, a valuable approach is to input the questions commonly asked by your target audience into the platforms they use for inquiry. By reverse-engineering the structure of your content based on the resultant answers, you can create a foundation that aligns with the expectations of users. To enhance the quality and value of your content, you can then infuse it with a unique brand perspective or add value that sets your business apart. This approach ensures that your content not only satisfies user queries but also adds a distinct touch that resonates with your brand identity.

To kick-start your AEO process, here are some key, actionable step to implement:

  • Identify the sources of data to which AI language models are trained on
  • Create a clear “About Us” page
  • Build reputability by working to be included in media mentions, review websites, award pages etc.  
  • Ensure that the content and data that you are publishing is easily crawlable by AEOs
  • Reverse engineer the structure of your content by inputting questions that your audiences typically ask  

The future of search is in AEO and LLMO, so if you’re not already optimizing for answer engines, this is your sign to get started, If you need help, you can download our free guide on Answer Engine Optimization to get everything you need in order to start powering your business growth through the rise of answer engines. 

Nicole Li
Nicole is a growth and content analyst with experience in branding, strategic copywriting, and social media planning for DTC brands and venture-funded startups.


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