Do you know the difference between a search engine and an answer engine?
No, that isn’t a trick question. Here’s a different question that will make it easier to explain: How did the Romans tell time at night? Any guesses?
Stay with me for a moment, because this fairly obscure question makes a really good point.
You can Google this question on any device and you’ll get the same answer: “water clocks calibrated by sundials.”
When you do a desktop search, the answer appears at the top of the page as a rich result (also known as a featured snippet) – a small summary box providing the answer, without needing to click on the link.
Yikes – goodbye organic traffic? We’ll get to that.
If you ask Google Assistant, your AI butler will read this same summary back to you.
Hey Google, that’s impressive, creepy, and awesome – the AI trifecta.
But on a serious note:
How can a search engine answer questions this complex?
The short answer is out of necessity.
Users want highly accurate answers to very specific questions across all devices and they want that answer to be the definitive answer.
So to keep their users happy, Google and Bing (albeit to a lesser extent) now process, evaluate, and summarize what they believe is the single best answer to every question, whether informational, transactional, or navigational.
The classic ten blue links are becoming window dressing.
Search engines have become answer engines.
So how does an answer engine work under the hood?
It may seem like witchcraft, but Google and Bing accomplish this using highly sophisticated natural language processing (NLP), machine learning, and real-time big data collection to understand the relationship between user intent and content.
This AI-driven approach gives them the ability to answer complex user questions.
Custom-built answers are then presented in a variety of formats and shown as featured snippets (Google calls them rich results)…
This shift to a question-answer economy creates a lot of questions. Questions like:
- How does this shift affect SEO and organic traffic?
- Should online publishers be worried?
- What can you do to keep up with Google?
- How can SEO specialists and content creators optimize content for the emerging answer economy?
Let’s get into it!
What is the definition of Answer Engine Optimization?
Answer Engine Optimization (AEO) is the process by which marketers create and structure their content for answer engines.
The goal of AEO is to create highly useful content that answers users’ questions in the most accurate and concise way possible. It also involves making your content as machine-readable as possible, so Google knows exactly what your content is intended for.
Marking up web content using structured data markup or semantic HTML5 helps answer engines like Google to differentiate between recipes, how-to guides, or articles.
If Google understands the purpose of your content, it can present it as rich results/featured snippets.
Why Frase built The First Answer Engine Optimization Platform
Frictionless Content Discovery = Customer Success
We believe that it should be easy to quickly and efficiently answer your website visitors’ questions.
Buyer enablement is about adapting to the way your buyers actually conduct their research — and eliminating any obstacles to the vital self-education process.
Instead of making your content passive, and hidden behind navigation menus, subpages, or chatbots, Frase turns your content into active, on-demand experiences that drive demand for your products.
Frase aims to make access to your website content frictionless through question answering and voice search.
How does AEO differ from SEO?
Answer engine optimization (AEO) and search engine optimization (SEO) are related terms. While the goal of SEO is to get your page to rank number one in organic search, the goal of AEO is to get Google to present your content as a featured snippet/rich result.
Whereas SEO includes techniques like gaining backlinks, page authority, and optimizing on-page factors, AEO is the practice of making your content question-centric and machine-readable.
Featured snippets are often shown above the top organic result and used by voice assistants such as Google Assistant and Siri when reading answers to users. This makes acquiring featured snippets highly valuable. AEO should, therefore, be part of any holistic SEO strategy.
Answer Engine Optimization and Featured Snippets
Featured snippets, now called rich results by Google, were introduced back in 2013 as quick answer boxes and officially rolled out in 2016.
As mobile searches surpassed desktop, Google needed a way to provide a single answer to user questions.
The traditional ten blue likes just weren’t suitable for smaller device screens and slower mobile internet. And this need to improve the mobile experience was only compounded by the rise of voice search and smart speakers.
Enter featured snippets.
Since then, Google has continually expanded its featured snippet capabilities and now has around 29 different types, with a few still in beta.
A Quick Look at Featured Snippet Data
So how scared should we be of featured snippets? Do they present an opportunity or a risk?
Recent data estimates that:
- 41% of question queries have featured snippets (SEMrush data)
- 22.67% and 17.72% of comparison and preposition keywords respectively trigger featured snippets (SEMrush data)
- Around 12.29% of search queries have featured snippets (Ahrefs data)
- When no featured snippet appears 26% of clicks go to first URL (Ahrefs data)
- But when a featured snippet appears, 8.6% click on the featured snippet and 19.6% click on the first result (Ahrefs data)
- CTR for high-volume keywords increased by over 114% when the results appeared as featured snippets (Hubspot data)
(all links to data available in the resources section below)
What do the numbers mean?
In short, featured snippets are eating into organic CTR as they become commonplace in search results. As the quality and capability of featured snippets improve, it is likely they will steal even more clicks from the top organic search results.
This makes optimizing your content for featured snippets crucial for conversion rate optimization (CRO).
How do Featured Snippets Work?
Google developed rich results based on schema.org markup. Schema markup allows platforms like Google to understand the intent of different content types.
Is it easy to add to a website?
It’s pretty easy. You add JSON-LD markup to the <head> of your content, depending on the type of rich result you want to be eligible for.
Structured Data Markup Example
The code below shows the markup for an FAQ page. Each question is tagged and assigned an answer.
Google has a tool that allows you to test your code then preview your markup to see how it would be rendered as a rich result:
Adding the code to your content doesn’t guarantee that Google will display it as a rich result.
In fact, most SEOs believe Google only harvests rich results from the top 10 pages.
Answer Box vs. Featured Snippet – What’s the Difference?
Featured snippets, rich snippets, rich results, answer boxes – that’s a lot of jargon.
Let’s clear up the terminology.
Rich results are the official name for featured snippets (formerly rich snippets). They are often confused with answer boxes.
An answer box is different from a rich result because it only presents information from Google’s Knowledge Graph and therefore does not attribute a source.
For example, if you query “define marketing,” Google returns a box with a definition and no source. This result is from Google’s own dictionary:
Rich results, or featured snippets as they are commonly known, summarize a piece of non-Google content and cite the source.
Try it yourself:
Query “top ai trends 2019” and you’ll get a box with a summary text, numbered list, image, and source.
This is a type of rich result.
Behind the scenes, Google is pulling data from the blog post and choosing how to present it to readers. If you see a slightly different result, this is Google experimenting with how to present the content.
Featured Snippet Example: Recipe
There are many different types of content online and Google reflects this in its rich results.
Searching for recipes, Google can display a list of ingredients or show your user ratings.
Featured Snippet Example: FAQs
Marketers like Neil Patel are also starting to implement FAQ markup on normal blog posts. This results in his article on digital marketing also displaying the questions it answers as dropdown boxes:
Featured Snippet Example: Video Carousel
Carousels can display top news stories, trending items on social media including Twitter, Facebook, and Instagram. Or in this case video content:
Featured Snippet Example: Events
Rich results also work with local search: Event card rich results can show you upcoming events in your local area.
Featured Snippet Example: People also ask
Often Google shows a “people also ask box.” Different to the FAQ rich result, these questions feature answers from a variety of sources.
There is no specific markup for the people also ask box. Google just pulls what it thinks is the best answer to each question.
For a full list of rich results types check out our resources section below.
Featured Snippets – What’s to Come?
Google is experimenting a lot right now. Here are some of the features to keep an eye on:
- Featured snippets currently in beta or pilot include Fact Check, Data Set, Top Places List, and Speakable rich results.
- The Speakable rich result will allow users to tag content that is suitable for text-to-speech and shows Google’s commitment to improving voice search results.
- Google is also toying with showing multiple featured snippets.
- Google is also using near-matches to display the closest possible answer.
Conclusion: Featured snippets are here to stay. Their functionality will become increasingly sophisticated.
Answer Engine Optimization and Voice Search
What role does voice search play in all this?
Voice search is a major driver behind the shift from search engines to answer engine.
In 2016, at its I/O conference, Google estimated that 20% of mobile search queries were made using voice search.
Doing some simple math: Assuming a very low number of 50% mobile searches would put the total number of Google voice searches at 10% (it’s definitely higher). And this was 2016 (Google hasn’t since released new numbers)
With the widespread adoption of virtual assistants, this number is likely to be much higher. Over the next couple of years, voice search adoption rates are expected to skyrocket.
How Does Voice Search Get its Results?
For many search results, virtual assistants like Google Assistant use featured snippets for their voice search answers.
Try asking Google Assistant “what are the top 5 ai trends for 2019?”
It will return the same list as the desktop result, just spoken out loud. It is reading the featured snippet.
Google Assistant cites sources by saying “according to” and then the website name.
What does this mean?
It’s actually good news: optimizing content for featured snippets also automatically optimizes it for voice search.
Why? Voice search results actually use the same NLP pipeline as rich results. Results are parsed, evaluated and summarized by Google’s AI. These text results are then converted to speech. This is done by reading out rich results.
Answer Engine Optimization and HTML markup
The internet is a messy place. HTML, the language used to mark up web pages, is not particularly useful to answer engines.
At least it wasn’t. Most web pages used things like <div> elements to mark different elements.
But this type of HTML markup makes it difficult for Google to scrape a webpage and know about the structure and intention of the information.
Enter HTML5 – the most recent edition of HTML. This version allows for semantic markup. Effectively, the tag label states what function a page element has. Common HTML5 tags include:
- <header> – marks the header section
- <nav> – marks the navigation bar
- <section> – delineates one section of content
- <article> – outlines an area of text
- <main> – shows the main body of content
- <footer> – marks the footer of the page
This HTML markup, combined with Google’s structured data, JSON-LD, tells Google extra information and makes it easier for Google to display rich results.
The Challenges of Answer Engine Optimization
It’s clear that the AEO revolution is shaking up the world of online content. SEO is now AEO and it may seem that Google is the big winner.
Rich results steal organic clicks and SERP real estate is getting scarce. And with voice search, it’s unclear exactly how publishers will benefit at all.
So what can content marketers and SEOs do to reel in Google?
One major deficit is the overall content experience. While Google’s tech is in the ascendancy, the average content experience is in its infancy.
To even stand a chance, content publishers need to address the following problems:
1) Long-tail search queries – landing pages can’t cope anymore
Search queries are becoming so specific that a single landing page on your website can’t answer all your users’ questions
This trend is also reflected in Google’s move away from the ten blue links and towards rich results and featured snippets.
2) Content strategy – old content marketing tactics will fail
Old-school content marketing tactics are not going to reach users who want an answer to a specific question. The content creation process needs an AEO approach and effective content marketing campaigns will need to serve the answer economy. The question is how?
3) User data – it’s hard to know how well your content answers user questions
Google is able to plug its featured snippet data into its AI to improve results. But websites can’t do this. Google Analytics data doesn’t tell you how well your content is answering a user’s questions.
4) User experience – websites are falling behind Google Assistant
Let’s be honest. Site search experiences suck. Site search is hopelessly outdated and if you want to find an article among Hubspot’s 17,000 or so, it’s like finding a needle in a haystack. And the point is that users don’t want to find an article, they want to find a single answer.
It’s clear that we need a content revolution.
Answer Engines: How Tech is Responding
The world of tech is beginning to respond. Companies like Frase are creating solutions to these problems. Frase uses the same AI-driven question-answering technology to provide a Google Assistant-type experience for your website users.
Frase’s Answer Engine functions like a chatbot (but a whole lot more advanced.) Users are able to have a conversation and find the answers they need, creating a more engaging customer experience.
As they ask questions, the answer engine records user data and is able to provide the optimum answer without users opening a new tab. This data allows you to see how well your content is answering user questions.
And the best part is that this data provides actionable AEO insights, allowing you to dominate Google rich results while other websites keep guessing and hoping.
Join us in the revolution.
Frase powers the Answer Economy.
Below is a list of relevant articles and research on answer engine optimization:
- Google Structured Data Guidelines (Google)
- Rich snippet preview tool (Google)
- Structured Data Testing Tool (Google)
- What is the Answer Economy? (Frase)
- What is an Answer Funnel? (Frase)
- Evolution of Featured Snippets (searchenginepeople)
- Official Google Blog on featured snippets (Google)
- Jason Barnard on AEO (SEMrush)
- SEMrush featured snippet data
- Ahrefs featured snippet data
- Hubspot features snippet data
- List of HTML5 tags (bitdegree)