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Editorial

Yet Another Case for Composable Content: AI-Powered Search

4 minute read
Lindy Roux avatar
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Composable content will make it easier for search engines and AI to serve up your content in answer to specific queries.

The Gist

  • Strategic approach needed. Composable content simplifies AI and search engine indexing for better query response.
  • Audience insights critical. Deep understanding of audience queries enhances AI and search optimization.
  • Experience flows essential. Mapping information-seeking experiences aids in structuring AI-friendly content.

If you weren’t already convinced that a structured content approach is the way to go in order to deliver omnichannel and personalized content experiences at scale, the proliferation of AI (and what that means for AI-powered search and SEO) might tip the scale.

Right now, SEO is undergoing one of the most significant disruptions ever with the emergence of generative AI tools and AI-powered search. More people are using some form of AI in their search for information, either in addition to or in place of search engines. (Editor's note: and now AI is infiltrating Google search land).

As a result, the way that organizations optimize their content for findability, whether through search or AI, will have to change. I believe there will be an increased need for the use of composable content to make it easier for search engines and AI to serve up your content in answer to specific queries.

Is This Really New?

It’s true that the search landscape is changing rapidly, but it’s also true that search engines — Google in particular — have been experimenting for years with ways to deliver succinct and accurate answers to users directly on their results pages.

Since 2016, Google has been using rich cards such as “People Also Ask,” “Things to Know” and “Featured Snippets” in earnest on its results pages, which has resulted in what is now known as zero-click searches. Audiences were able to get their answers directly from the search results page without ever having to visit the organization’s digital properties.

In addition, Google has been using AI in its algorithm for the past decade to fine-tune results based on things like search intent and helpfulness of the content. And now it's onto "AI Overviews" within search results.

More recently, search has jumped to the next level with the introduction of AI-assisted search via Google’s experimental Search Generative Experience (SGE) and Bing’s Deep Search. It's early days for these changes, but Gartner predicts that as a result of these developments organic search traffic will decrease by 50% or more by 2028 as users embrace generative AI-powered search.

Related Article: Marketers: What's Your AI-Powered Search Strategy?

What Does Composable Content Have to Do With AI-Powered Search?

While data on AI-assisted search performance is not yet available, we have noticed that much of the same content that was showing up in search snippets is also showing up in AI-assisted search and AI summaries. Numbered lists in answer to the question “how to…,” brief definitions or descriptions in answer to “what is…” and high-level summaries pulled from specific sections of longer content pieces. If your goal is to engage, educate and inform audiences with your content, you want to make sure yours is the answer that shows up.

AI tools and AI-assisted search are delivering these answers based on learning models that use information scraped from the internet, and, like search engines, they are more likely to reference content that specifically addresses the user’s query. The takeaway: If you use composable content and label it appropriately, it will be easier for these tools to identify and reference the answers contained within larger pieces.

An aisle of ld vintage wooden library card catalog cabinets separated by a tiled floor in piece about AI-powered search.
The takeaway: If you use composable content and label it appropriately, it will be easier for these tools to identify and reference the answers contained within larger pieces.Lyudmila on Adobe Stock Photos

Related Article: Assessing the Impact of AI-Driven Web Browsing on SEO and Marketing

How Does It Work in Practice?

Structuring your content to be indexed and found by AI tools takes a strategic and thoughtful approach, and is grounded in insights, implementable and iterative in nature.

Start With Your Audiences: Understand What They Are Asking

Optimizing content, whether for search or AI (or AI-assisted search for that matter), starts with a deep understanding of your audiences and the kinds of questions they are likely to ask. At a macro level, defining audience personas and their informational needs at each stage of the customer journey will help you stay laser focused on the information that matters to them.

To get a more granular picture, look at behavioral metrics. While data related to AI queries is scant for now, we do have search data that can help us zero in on the phrasing and substance of user queries. We also look at AI-suggested prompts and “people also ask” if we’re trying to understand the way users may ask for specific information.

Finally, you can ask your audiences! We’re huge fans of first-party research and have learned a lot by simply having users walk us through the way they might look for information on a specific topic or task.

Related Article: Will Search Be Generative AI or Blue Links? Actually It's Both

Expand Your Experience Flows to Include AI and Search

Deciding how to structure information starts with mapping the experience of seeking and finding a piece of information. Experience flow diagrams put informational use cases under a microscope to break down each step and identify the informational needs, customer questions, decision points and potential complications across every channel in your digital ecosystem.

If we consider AI and search to be channels in this mapping exercise, we can easily add use cases specific to these channels to help us define the types and structure of information needed to support them.

Modularize (and Label) Your Content

Experience mapping helps us to identify the lowest common denominator or content building block that will be needed to meet audience needs across all channels. For example, a set of instructions may be served up as a single content object, but step 3 may also be a very useful answer on its own for in-product help or an AI query. In this case, you’ll want each step to be a content chunk that can be assembled into a more comprehensive guide as needed.

Learning Opportunities

It's also important to think about how you label your content. Using a robust taxonomy and other metadata will help both search engines and AI understand the context of a piece of information.

Test and Optimize

As with most search initiatives, delivering an AI-optimized content experience is likely to take some cycles. Applying a strategic and audience-based approach to structuring your content is a great start, and then observing the results, testing performance (where possible); and going back to your audiences will help you fine-tune the approach. AI is also a great tool for assessing content performance (a topic for another day!)

It Starts and Ends With a Good Content Experience

At the end of the day, as with all other efforts to ensure your content is seen by key audiences, your success depends on the quality of your content and the experience it delivers. Content that is created and structured to be easily found and meet the informational needs of your audiences will naturally be more likely to succeed in search — whether it’s an algorithm or more advanced AI-powered search retrieving the information.

Focus on delivering great content and meeting your audiences where they are, and you’ll be off to the races!

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About the Author
Lindy Roux

Lindy Roux is executive vice president and partner at Tendo Communications, a B2B content agency based in San Francisco. She has over two decades of experience in content and digital strategy, CMS, SEO, user experience, consumer insights, branding and analytics. Connect with Lindy Roux:

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