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AI’s impact on customers and businesses is reshaping both content discovery and marketing strategies. The integration of AI overviews in search engines fundamentally altered traditional top-of-funnel discovery. Google’s AI Overview, Copilot Search, ChatGPT and others are reducing click-through rates by offering aggregated responses to search queries. Businesses that relied on website visits to expand their customer base are now losing more than half their engagement to AI overviews provided by search engines.
This isn’t new. Search Engine Optimization (SEO) has been a marketing best practice for decades, as businesses aimed for top positions in Google’s search rankings. Today, not being cited in answer engines is the modern equivalent of being on the second page of Google’s search results. Only in this instance, the second page doesn’t exist.
The shift from traditional SEO to AI-driven discoverability requires a focus on structured, high-quality content. To further explore what marketers need to do to ensure contextual relevance for their brands, we spoke to Clayron (Cj) Pace, Go-to-Market Product Marketing Manager for Contentful. The conversation explored the importance of treating content as data and using composable DXPs to ensure consistent brand representation across platforms.
How Has AI Affected Top-of-Funnel Discovery?
Brand websites are no longer places of discovery for many customers. AI overviews now answer user queries directly within the search interface. This removes the need for a user to ever click through to a brand's website, forcing brands to address discovery by other means.
These days, a brand's "digital front door" is often a short AI summary that the brand didn't even write, rather than its homepage. “Too often, you're stuck hoping that the overview has properly represented you,” Pace said. "That's a big change in terms of discoverability, because if you aren’t being surfaced in the way you intended, a lot of what you've done from a messaging and positioning and curation standpoint just evaporates away. There’s a lot of uncertainty around how answer engines cite brands. You just don't really know how your brand is showing up.”
Brands also need to be aware of the potential for answer engines to include competitors’ content. “With SEO, you might Google ‘Contentful’ and the worst you’d see would be some well-to-do competitor with an ad at the top of the Google search list,” Pace said. “But if you were to go to Google now and ask it ‘Give me a CMS platform and tell me more about Contentful,’ there's a very real chance the AI overview can give you what you want, but surface your competitors at the same time."
Does SEO Still Matter From a Discoverability Standpoint?
SEO still matters, though its role is evolving. Plenty of users are still discovering brands through search engines. Keywords still matter. But they need to be added in a contextually relevant way — supporting the questions customers are likely to ask an answer engine.
Brands can learn from the early days of SEO and apply them to their current content strategies. When SEO was new, marketers stuffed their articles and blogs with keywords to get their content on Google’s front page. While that worked temporarily, customers and search engines caught on, and such keyword-rich but idea-poor content became ignorable. Eventually, marketers used tools to see how SEO improved their web traffic. “SEO was really good at opening up that black box, so you knew exactly where users were engaging with you. But now some of that is kind of lost,” Pace said.
Fast forward to today. There’s murkiness around how answer engines cite and surface content, similar to the early Google algorithm. Yet, many marketers are trying to game the system with a deluge of AI-created content. While AI tools can help marketers produce content faster, they aren’t necessarily getting better content that’s more likely to be cited by answer engines.
Why is High-Quality Content Necessary for Discoverability?
As brands try to adapt to shrinking budgets, changing customer behaviors and discovery challenges, they’re trying any and all tactics to get their content in front of customers. Many are making the mistake of using AI to rapidly churn out generic, low-quality content. Sadly, this has the opposite effect of what’s intended.
Much like the keyword-stuffing fails of content intended to game SEO, quantity over quality isn’t necessarily the answer here. Answer engines aren’t impressed by high volumes of emotionally flat content. Further, human readers mistrust content that’s obviously produced by AI. Thus, producing a glut of content actually erodes customer trust rather than improving a brand's visibility.
“Because answer engines are pulling so many sources together, they're trying to grab distinctive content, or credible, authoritative content,” Pace said. “Some teams are treating AI less like a workflow accelerator and more like a modern printing press. They’re trying to get everything out as soon as possible, when what actually matters is being unique, standing out and accurately representing your brand.”
What Role Does Structured Content Play in Discoverability?
To succeed in an AI-driven search environment, marketing teams must stop treating content as static, generic or disposable. Teams need to think about content as organized data. AI answer engines don’t read HTML pages or website layouts like humans; instead, they look for answers in clear, parsable data. "Answer engines quote exactly what they can read, trust, rearrange and pull from a web page,” Pace said. “What makes it easier for the answer engine to accomplish that is content that’s structured, treated like data and not necessarily like a page."
Generative engines now act as the arbiters of relevance, deciding which brands are part of the user journey. If it omits your key differentiators or summarizes your pricing based on outdated info, that still becomes the ‘Brand Truth’ the user accepts — sometimes without further question.
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So what does this mean for your brand? It means fewer click-throughs, lower engagement, and/or reduced brand visibility. Brands risk becoming contextually invisible, further hindering discoverability.
On the other hand, content treated like structured data provides the exact amount of machine-level intelligibility an answer engine needs to read, understand, trust and accurately cite a brand. Further, structuring content as data ensures that its context doesn’t change. This allows the exact same piece of content to be reused seamlessly across web, mobile or IoT devices ensuring your brand, your messaging and your experience is consistent across all digital touchpoints.
How does a Composable DXP Assist In Making Content Better for Answer Engines?
Legacy Content Management Systems (CMS) embed content meaning into HTML and visual layouts, forcing answer engines to guess the information’s meaning, relationships and accuracy in answering questions.
In contrast, a composable DXP breaks content down into modular, structured objects with clear fields, relationships and metadata. This produces enough structure for answer engines to properly read, understand and cite a brand.
Since discoverability is now happening through both search and answer engines, brands need all the help they can get putting their content in front of customers. “With a composable headless setup, each piece of content has a structured object, a clear field, metadata and a clear relationship between all these various items. And this is exactly what a machine or an answer engine needs to make sense of your brand,” Pace said.
How Can Brands Avoid Becoming "Contextually Invisible"?
Answer engines synthesize information into a single, comprehensive summary, so they’ve eliminated the concept of scrolling through results or navigating to a second page. If a brand fails to secure its place within these AI overviews, it effectively ceases to exist for users at the top of the funnel.
Brands can’t afford to become hidden to potential customers in these early days of answer engine discoverability. Rethinking content strategies will help them get noticed by both answer engines and humans. Treating content as a high-quality asset with structured data that answers customer questions will increase your brand’s chances of appearing in an AI overview. Using a composable DXP can improve your content and make it reusable across devices. Quality over quantity will ensure your content is relevant, seen and trusted.
Contentful can help make your content contextually visible. Learn more at contentful.com.