The battle for discovery has shifted - Here’s how Sitecore and Optimizely are responding

Digital experience strategy, in recent years, has largely focused on what happens once a user arrives: the content they see, the journey they follow, the level of personalisation they receive, and whether the experience converts. 

That model is now being challenged. 

Increasingly, the first meaningful interaction with a brand is not a page view. It is an AI-generated answer, comparison, summary or recommendation. Buyers are asking tools such as ChatGPT, Gemini and Perplexity to help them understand markets, shortlist suppliers, compare options and make decisions before they ever reach a brand’s website. 

That does not make the website less important. But it does change its role. 

The website is no longer just the destination. It is also a source layer for AI systems, a proof point for brand authority, and a content estate that machines need to understand, interpret and trust. 

That is why two recent moves in the DXP market matter. 

Optimizely has announced a partnership with Conductor, bringing enterprise SEO, GEO and AEO intelligence into its platform. Sitecore has acquired Scrunch, an AI search visibility and optimisation platform. 

Different moves. Same signal. The DXP market is moving upstream. 

From managing journeys to influencing discovery 

The traditional DXP conversation has been centred on owned experiences: content management, personalisation, experimentation, commerce, analytics and optimisation. 

Those capabilities still matter. In many ways, they matter more than ever. But they now sit within a broader discovery environment where customers may form an impression of a brand before interacting with any owned channel. 

That creates a new challenge for digital, marketing and technology leaders. 

It is no longer enough to ask: 

• Is our website performing? 
• Are our journeys optimised? 
• Is our content converting? 

Organisations also need to ask: 

• How are AI systems describing our brand? 
• Which competitors are being cited when we are not? 
• Which sources are shaping AI-generated answers? 
• Which parts of our content estate are accessible, trusted and useful to machines? 
• How quickly can we respond when those signals change? 

This is not just a new reporting requirement. It is a new operating challenge. 

AI discovery sits across content strategy, technical SEO, analytics, brand governance, experimentation and platform architecture. That is what makes this a DXP issue, rather than simply an SEO or content issue. It affects how content is structured, how evidence is surfaced, how teams govern brand accuracy, and how quickly organisations can respond when the discovery environment changes. The organisations that perform best will not be those that monitor AI search in isolation. They will be those that can connect insight to action quickly and responsibly. 

Two strategic responses 

Optimizely and Sitecore are responding to the same market shift, but in different ways. 

Sitecore’s acquisition of Scrunch is a platform ownership play. By bringing AI discovery capability into the Sitecore ecosystem, Sitecore is signalling that visibility in AI-generated answers, recommendations and agent-facing experiences should become part of the core digital experience platform. 

There is logic in that approach. If AI systems are becoming a major route to discovery, then the ability to understand and shape machine interpretation should sit close to the systems where content is created, managed and distributed. Scrunch’s Agent Experience Platform also points to the fact that digital experiences increasingly need to serve both human audiences and machine audiences. 

The question will be how quickly Scrunch’s specialist capability is integrated, how much of its innovation pace is preserved, and how open the approach remains as the AI-discovery category continues to evolve. 

Optimizely has taken a different route. Rather than acquiring an AI visibility vendor, it has partnered with Conductor, an established enterprise search and AEO specialist, and combined that intelligence with Optimizely’s own agent visibility and optimisation capabilities. 

From our perspective, that is an important distinction. 

The strength of the Optimizely approach is not simply that it adds AI-search visibility. It is that it connects three things that organisations will need to manage together: how a brand appears in AI-driven discovery, how AI agents and crawlers interact with owned digital properties, and how teams can act through existing content, experimentation, personalisation and orchestration workflows. 

This is important because AI discovery is still an emerging discipline. Retrieval patterns, model behaviours, citation sources and customer usage are all changing quickly. In that environment, flexibility matters. So does the ability to bring specialist intelligence into the same operating model teams already use to test, learn and optimise. 

That is where the Optimizely direction feels particularly relevant. AI discovery is not being treated as a separate dashboard or a disconnected reporting layer. It is being connected to the broader optimisation loop: insight, action, experimentation and continuous improvement. 

The market implication 

The question isn’t whether a partnership is better than an acquisition. The important point is that both moves show where the DXP market is heading. 

Digital experience platforms are being pulled beyond the boundaries of the website. The impending battleground, if we’re not there already, is likely to be how well organisations can manage experience across three connected layers: 

• The human experience: what customers see and do when they reach owned channels. 
• The machine experience: how AI systems access, interpret and retrieve brand content. 
• The operating experience: how quickly teams can turn insight into governed action. 

AEO and AI discovery will not be solved by visibility alone. Knowing that a brand is missing from an AI answer is useful, but only if the organisation can understand why, identify the right content or technical response, make the change, test the impact and keep improving. 

That measurement point matters. AI discovery is still a developing field, and organisations should be cautious about treating early AI referral traffic, citation counts or visibility scores as fully mature performance indicators. The more useful approach is to establish a baseline, test changes, look for directional improvement, and connect AI-discovery activity back to commercial outcomes over time. 

What organisations should do now 

Start by identifying the prompts, topics and buying questions that matter commercially. Understand where your brand appears, where competitors are being cited, and which sources AI systems rely on when forming answers. Review whether your most important content is structured, current, authoritative and accessible. Look at how AI agents and crawlers are interacting with your site, and whether that behaviour aligns with your commercial priorities. 

Then connect those findings back to your roadmap. 

Some actions may be content-led: filling gaps, improving clarity, strengthening evidence, or creating more authoritative topic coverage. Others may be technical: improving crawlability, structured data, metadata, performance or content delivery. Others may be operational: defining ownership, governance, measurement and experimentation processes. 

Avoid treating AI discovery as a standalone workstream. It needs to become part of content strategy, SEO, analytics, experimentation and platform planning. 

A practical view 

These announcements are significant because they show that AI discovery is becoming a core DXP concern, something we have expected to become increasingly important as AI changes how customers research, compare and choose. 

Sitecore’s acquisition of Scrunch points to a future where AI visibility and agent-facing content experiences are embedded directly into the platform. Optimizely’s partnership with Conductor points to a more connected model, combining specialist search intelligence, observed agent behaviour and optimisation workflows. 

Both approaches have merit. Both reflect the same underlying shift. 

But in a market that is still moving quickly, adaptability matters. The ability to combine trusted external intelligence, first-party behavioural data and rapid experimentation may prove especially valuable for organisations that need to learn, respond and optimise continuously. 

For organisations already invested in Optimizely, that direction of travel is encouraging. It means AI discovery can become part of the same optimisation mindset that already shapes content, experimentation, personalisation and digital performance. 

The question is whether your platform, content estate and operating model are ready for a world where customers may encounter the brand first through what AI says about it. 

For organisations reviewing their digital roadmap, AI discovery should now be part of the conversation. Netcel’s AI Readiness & Platform Assessment helps teams understand where they stand today, where content and platform gaps exist, and how to build a practical roadmap for optimisation.