Abstract
- A strategic approach is needed. Configurable content simplifies AI and search engine indexing and improves query response.
- Audience insight is key. Deep understanding of audience queries powers AI and search optimization.
- The flow of experience is important. Mapping the information search experience helps structure content in a way that's suitable for AI.
If you’re not yet convinced that a structured content approach is the best way to deliver omnichannel and personalized content experiences at scale, the rise of AI (and its impact on AI-powered search and SEO) could change that.
SEO is currently experiencing one of its biggest disruptions ever with the advent of generative AI tools and AI-powered search. More and more people are using some form of AI to find information, either in addition to or instead of search engines. (Editor's note: And now AI is making its way into the world of Google Search.)
As a result, the way organizations optimize their content to make it discoverable through search and AI will need to change. We believe there will be an increased need for the use of configurable content to make it easier for search engines and AI to serve content in response to specific queries.
Is this really new?
While it’s true that the search landscape is rapidly changing, it’s also true that search engines, particularly Google, have been experimenting for years with ways to provide users with concise, accurate answers directly on their results pages.
Since 2016, Google has made serious use of rich cards on its search results pages, such as “People also ask,” “Things to know,” and “Featured snippets,” enabling what is now known as zero-click search: users could get answers directly from the search results page without ever visiting a Google digital property.
Additionally, for the past decade, Google has been using AI in its algorithms to fine-tune search results based on search intent, usefulness of content, etc. And now, they are introducing “AI Overviews” within their search results.
More recently, the introduction of AI-assisted search through Google's experimental Search Generative Experience (SGE) and Bing's Deep Search has taken search to the next level. While these changes are still in their early stages, Gartner predicts that as a result of these developments, organic search traffic will decline by more than 50% by 2028 as users adopt AI-powered generative search.
Related Article: Calling all marketers: What is an AI-powered search strategy?
What does configurable content have to do with AI-powered search?
While data on the performance of AI-assisted search is not yet available, we found that much of the same content that appeared in search snippets also appeared in AI-assisted search and AI summaries: numbered lists for “how to…” questions, brief definitions or explanations for “what is…” questions, summaries extracted from specific sections of longer content, etc. If your goal is to engage, educate, and inform your audience through your content, you want to make sure the answers they show are yours.
AI tools and AI-assisted search provide these answers based on learning models that use information gleaned from the internet and, like search engines, are more likely to refer users to content that specifically addresses their query. Takeaway: Proper labeling with configurable content makes it easier for these tools to identify and refer to answers within larger pieces.
Related article: Evaluating the impact of AI-driven web browsing on SEO and marketing
How does it actually work?
Structuring content to be indexed and searched by AI tools requires a strategic and thoughtful approach that is insight-driven, implementable and iterative in nature.
Start with your audience: understand what they want
Optimizing your content, whether for search or AI (or even for AI-assisted search), starts with a deep understanding of your audience and the types of questions they're likely to ask. At a macro level, defining your audience personas and their information needs at each stage of the customer journey allows you to zero in on the information that matters to them.
To get a more detailed picture, look at behavioral metrics. While data related to AI queries is scarce right now, there is search data available that can help hone in on the wording and content of user queries. Also look at AI-suggested prompts and “questions other users ask” if you're trying to understand how users ask for specific information.
Finally, ask your audience: we're big fans of first-party research, and we've learned a lot just by asking users to describe how they would find information on a particular topic or task.
Related article: Will search become generative AI or blue links? Actually, it’s both
Extending experience flows to include AI and search
Deciding how to structure your information starts with mapping the information search and discovery experience. Experience flow diagrams dissect information use cases and break down each step to identify information needs, customer questions, decision points, and potential complexities across all channels in your digital ecosystem.
If we consider AI and search as channels in this mapping exercise, we can easily add use cases specific to these channels and define the type and structure of information needed to support them.
Modularize (and label) your content
Experience mapping helps you identify the lowest common denominator or content building blocks required to meet your audience's needs across all channels. For example, a set of instructions might be delivered as a single content object, but step 3 might also be a very useful answer on its own to an in-product help or AI query. In this case, each step should be a content chunk that can be assembled into a more comprehensive guide as needed.
It's also important to think about how you label your content: Robust taxonomies and other metadata make it easier for both search engines and AI to understand the context of your information.
Testing and Optimization
As with most search initiatives, delivering an AI-optimized content experience will likely take several cycles. Applying a strategic, audience-based approach to structuring your content is a great start. You can then fine-tune your approach by observing results, testing performance (if possible), and going back to your audience. AI is also a great tool for evaluating how your content is performing (a topic for another day).
It all starts and ends with a good content experience
Ultimately, as with any effort to get your content seen by your key audiences, success depends on the quality of the content and the experience it provides. Content that is easily discoverable and that is created and structured to meet your audience's information needs is more likely to be successful in search, whether that be algorithmic or more advanced AI-powered search.
By focusing on delivering great content and meeting your audience where they are, you will be well on your way to success.
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