ChatGPT and Bing kicked off 2023 with a bang by revealing their AI-powered chatbot and search engine. This past May at Google I/O, Google announced its brand new Search Generative Experience and it has garnered the lion’s share of the spotlight.
While we remain uncertain about the impact of these new experiences on search engine optimization, there are a few things that we know:
- Google’s Search Generative Experience (SEG) will feature source links.
- Generative AI is in its infancy, but it is not going away.
- AI uses large language models to train. Large language models use Knowledge Graphs to learn and ground their data to increase accuracy.
- Schema Markup when done in a connected way, creates a knowledge graph that AI can consume.
Organizations should use Schema Markup (also known as Structured Data) on their websites if they want to be prepared and thrive in AI search.
The last point is especially important because AI is going to need help understanding and contextualizing the content on a website to provide searchers with the right answers.
Before exploring deeper into the threats and opportunities of this new technology, let’s talk about generative AI in the context of search.
What Is Generative AI for Search?
Generative AI is a specific type of artificial intelligence algorithm that is designed to generate new content and outputs based on data they have been trained on. Some of the content that generative AI can create includes text, audio, code, and images.
Bard and ChatGPT are prime examples of generative AI chatbots that have been trained on large quantities of unlabeled, unstructured data. While generative AI chatbots are a groundbreaking development in the world of artificial intelligence, they are only the beginning.
During Google I/O 2023, the search engine giant showcased how it has incorporated generative AI technologies into its search engine and other products such as Workspace. This newly integrated AI technology will have a significant impact on Google’s responses to queries and the composition of the search engine results page (SERP).
There is considerable excitement surrounding the AI revolution. That said, there are also significant concerns around bias, plagiarism, trustworthiness, and accuracy of generative AI search results.
Currently, generative AI search engines are largely trained on unlabeled/unstructured data which can lead to inaccurate results. Adding structured data or Schema Markup to your site can allow search engines to:
- train on quality data,
- improve the accuracy of their answers,
- and give you a control point to inform generative AI on your web content.
There are underlying risks and exciting opportunities associated with the implementation of any new technology, especially when that technology is as powerful and sophisticated as generative AI.
Google’s new Search Generative Experience will have an impact on the way SEO is done. So is generative AI a threat or an opportunity for search engine optimization?
Let’s explore some of the potential threats and clear opportunities that have emerged in the wake of generative AI search.
Is AI Search an Opportunity or Threat for SEOs?
At first glance, Google’s new generative AI search has a few glaring threats to SEO.
1. Potential Loss of Visibility on the SERP
There are a lot of unanswered questions about how website performance will be measured with AI search.
Google’s generative AI search engine does showcase links that attribute information back to reputable source content. However, users may no longer need to click to read this content (resulting in zero-click searches), which limits your visibility and overall influence over the customer journey.
Ultimately, rich results, featured snippets and other top-ranked content may be overshadowed by generative AI results. In turn, this could lead to a reduction in rankings, clicks, and impressions.
2. Success Metrics of a Website Are Going to Fundamentally Change
Generative AI has the potential to condense your sales funnel. The line between clicks, impressions, and conversions could become blurred, making it difficult to attribute sales or leads to specific marketing activities.
Bing and Google have yet to reveal how sites can measure their performance in generative AI search results. For now, you will have to draw conclusions using existing metrics.
3. Hyper Long and Specific Search Queries
If you haven’t watched the Google I/O segment on search yet, we strongly recommend doing so. In their demonstration, we saw that the Search Generative Experience (SGE) allows for more natural, specific conversational search queries in comparison to the traditional keywords or questions we see today.
Image Credit: Google
This capability will lead users to conduct very specific queries. And as a result, question fragments and traditional keyword searches will become less prominent.
These long specific queries are a shift from traditional keywords and will likely have little to no search volume. It also reflects SGE’s ability to understand the context behind a query rather than the keywords used. Therefore, it is crucial for content publishers to focus on utilizing Schema Markup helping search engines to understand and contextualize the on-page content.
Furthermore, Google has previously emphasized the importance of a website focusing on content around a specific topic as a way of creating people-first content.
Instead of focusing heavily on optimizing for keywords, focus on creating content for topics within your expertise and around your customers’ needs. You can then use Schema Markup to communicate your expertise, experience, authority and trustworthiness with the AI search engine.
The world of SEO is constantly evolving. Long-time marketing professionals understand that this level of change is not a new phenomenon. To stay relevant in the world of organic search and differentiate yourself from the competition, you must adapt to the latest trends (such as generative AI) and capitalize on the opportunities they provide.
The key opportunities created by generative AI search include the following:
1. Provide a Better Customer Experience
You can provide customers with a better experience by answering their queries directly on the search engine results page. Today, content publishers can already utilize rich results such as FAQ and How-To as well as other features like Featured snippets to answer the questions in search.
However, the generative AI search engine can help you reduce friction with your customers by showing users the key information they need to know or providing follow-up information.
The eCommerce industry is one of the first industries to be truly disrupted by this because Google already has great eCommerce data from Google’s Shopping Graph for their AI search engine to train on.
Image credit: Google
Generative AI can shorten the consumer funnel by allowing searchers to convert immediately through the SERP and purchase an item directly from the SERP instead of having to navigate the site. This will mean that conversion data and source-to-conversion pages will be one of the key metrics during this evolution.
2. Links Are Not Going Away
Based on the demo and the responses from the early experimental rollout of Search Generative Experience, Google’s generative AI search engine is linking back to sources more frequently than initially expected. In fact, Google’s SGE demo gave a lot of real estate to the websites where the content was originally sourced from.
Though far from perfect, this is an opportunity for search engine optimizers to capitalize. We believe that content publishers can focus on optimizing their website for search by following Google’s guidelines of creating people-first content and E-E-A-T, optimizing on-page experiences for your audience, and monitoring or optimizing core web vitals.
It doesn’t matter whether you are new to search or simply want to stay ahead of the pack. You should refine all these key SEO areas to gain an edge over the competition.
3. Schema Markup Is Key to Helping AI Search Engines Understand Your Content
In a keynote address at Pubcon 2023, Fabrice Canel from Bing expressed that annotating great content with Schema Markup is how search engine optimization experts should prepare for generative AI search.
Thus, you should craft compelling, people-first content before implementing Schema Markup across all web pages. Schema Markup helps search engines understand the content on your site so it can provide users with useful results.
While many SEO teams already use Structured Data to achieve rich results, few implement proper semantic Schema Markup across their entire site. To help generative AI search engines truly understand and contextualize your content, you need to ensure your Schema Markup is connected to other entities on your site and other external authoritative sources.
Implementing connected Schema Markup can help you develop your knowledge graph that generative AI search engines can then utilize to infer new knowledge.
Help AI search engines contextualize your website
Learn how to implement connected Schema Markup and help search engines understand your content.
At Schema App, we are a semantic technology company. Since we started doing Schema Markup at scale in 2016, we’ve focused on implementing proper, connected Schema Markup across our customers’ sites to help search engines fully understand and contextualize their content.
If you are looking to optimize your website for AI search using Schema Markup, get in touch with our team for more information.
4. Focus on Content Quality
Over the previous year, Google launched a helpful content system intended to ensure that content is “people-first” instead of “search-engine first.” This emphasis on content made by people, for people, demonstrates Google’s commitment to providing users with relevant results that address their pain points. These changes are aligned with the type of content that Google SGE and the new Bing experience are highlighting.
Generative AI is still in its early stages and the accuracy of their answers is still questionable. In light of this, there is an opportunity for content publishers to create high-quality, trustworthy content for Google’s generative AI search engine to train on.
You should also ensure that your content is created by human writers and that each piece of copy addresses specific topics relevant to your audience.
SEO Is Changing
The bottom line is that the SEO landscape is evolving quickly. Google’s Search Generative Experience is still in its experimental phase and we don’t know its full impact on SEO or the SERP.
While it is unclear what these changes will mean for your SEO strategy, now is the time to start preparing for this change. In a world where many circumstances are out of your control, you should focus on the factors that you can manage – such as the quality of the Schema Markup on your website.
Schema Markup is one of the SEO tactics you can implement immediately to prepare for AI Search and Schema App can help your business implement semantic Schema Markup using our end-to-end solution. Get in touch with our team to learn more about how we can help you prepare for generative AI search.
Martha van Berkel is the co-founder and CEO of Schema App, an end-to-end Semantic Schema Markup solution provider based in Ontario, Canada. She focuses on helping SEO teams globally understand the value of Schema Markup and how they can leverage Schema Markup to grow search performance and develop a reusable content knowledge graph that drives innovation. Before starting Schema App, Martha was a Senior Manager responsible for online support tools at Cisco. She is a Mom of two energetic kids, loves to row, and drinks bulletproof coffee.