3 Things to Look for in a DXP as Conversational Search Changes the Game

Dan Drapeau is Managing Director at DXP Catalyst Consulting and a CMS Critic contributor. 

Search is changing. Instead of typing keywords and clicking through ranked pages, users increasingly expect fast, relevant answers, often delivered through conversational tools like ChatGPT, Perplexity, or intelligent site search. They’re landing on your website “from the side,” bypassing the homepage, and expecting to ask questions in natural language and get immediate responses.

This shift, accelerated by the rise of Search Generative Experience (SGE) and the emergence of Generative Engine Optimization (GEO), is reshaping how digital platforms are selected and structured. Traditional SEO practices are no longer sufficient. Content must now be discoverable by both search engines and generative AI systems.

To keep pace, organizations are reevaluating their digital architecture. Some are adopting full-featured Digital Experience Platforms (DXPs), while others are building their own solution ecosystems using best-of-breed tools like CMS, enterprise search, analytics, and more. Regardless of the approach, the same principles apply: content must be structured for reuse, delivered intelligently across channels, and trackable at every touchpoint.

Here are three key areas I focus on when helping organizations evaluate the readiness of their digital experience ecosystem, which is what a modern DXP truly represents, in the era of conversational search.

1.  Structured Content and Findability by Design

At the heart of any DXP or composable solution is the content layer, powered by a content management system (CMS). It governs how content is created, structured, and published. To support SGE and GEO, this layer must do more than manage pages. It needs to produce structured, reusable content that systems can understand and deliver in context.

Generative AI tools require predictable, well-modeled inputs. Content trapped in PDFs, inconsistent formats, or unstructured blobs is unlikely to be surfaced accurately. Structured content models, semantic tagging, and field-level metadata are essential for discoverability.

When evaluating a DXP or CMS, look for:

• API-accessible metadata and structured content elements
• Support for semantic models and content relationships
• Schema markup applied consistently across content types
• Editorial workflows for FAQs, summaries, or step-by-step formats
• Extensibility for AI use cases like conversational grounding or previews

Findability starts with how content is modeled. If it cannot be accessed or interpreted by AI, it will be excluded from conversational experiences.

2.  Search Integration That Supports Conversational Interfaces

Conversational search is not limited to chatbots. It can be delivered through a standard search bar, as long as the system can interpret natural language, understand context, and return more tailored responses. The interface may look familiar, but the experience is far more dynamic.

Delivering on that promise requires search capabilities that extend beyond CMS indexing. Your architecture should support:

• API-based indexing of structured content and product data
• Multi-source search across support content, blogs, product catalogs (if applicable), and more
• Fine-tuned ranking, filtering, and fallback logic
• Compatibility with conversational UX, such as voice or natural language input

Some DXPs are starting to offer search integrations with conversational overlays or even RAG (retrieval-augmented generation) frameworks. Even if you’re not enabling full conversational search today, the technical foundation should be ready.

3.  Governance and Observability

As generative interfaces become the first point of interaction for many users, governance and observability are no longer optional. Teams must control what is published, how it is indexed, and how it performs in real-world usage.

Your CMS or DXP should provide access controls, publishing workflows, preview tools, and the ability to manage visibility through scoped indexing, robots.txt, or noindex tags. While you cannot always prevent AI from referencing public content, you can influence how and where it appears.

Beyond control, your team needs visibility. Modern platforms should offer analytics that go beyond traffic and conversions to include:

• User search queries and failed results
• AI interpretation of structured content
• Behavioral patterns that reveal content gaps
• Metadata performance insights and tuning opportunities

These feedback loops help you identify what users are looking for, where they are not finding it, and how to improve content delivery. Observability is critical for adapting to shifting search behavior.

What to Do Next

You do not need to solve for every edge case today. But as SGE and conversational interfaces gain traction, platform evaluations must evolve.

Use this checklist to guide your next discussion:

• Is your content layer structured to support AI-ready delivery?
• Can your systems surface and connect that content across search, personalization, and chat interfaces?
• Do you have insight into how users are interacting with content, including intent signals and discovery gaps?

Search is no longer just a feature. It is becoming the interface between your users and your brand. Whether you are investing in a traditional DXP or building a best-of-breed composable stack, choose an architecture that is structured, discoverable, and observable – one that supports GEO from day one.

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