XR as a Data Source: What Conversations at AWE EU in Vienna Have Taught Us

At AWE EU in Vienna, one of the largest Extended Reality (XR) events, alongside AWE USA, a key theme that emerged was the critical role of data analytics in shaping the future of XR adoption and market expansion. Despite the growing presence of immersive technologies across industries, many companies still rely heavily on anecdotal case studies and qualitative surveys to evaluate success rates and Return on Investment (ROI) metrics. While these approaches offer valuable insights, they often fall short of providing the actionable, quantifiable data needed to make informed decisions and demonstrate tangible benefits to stakeholders. This gap underscores a significant challenge in the XR market: educating industries on the benefits of XR, while using data-driven evidence to validate its impact. By leveraging advanced analytics, companies can move beyond narratives to deliver robust metrics that not only justify investment, but also guide optimization and scaling efforts, paving the way for broader adoption.

The insights gathered from AWE EU in Vienna highlight a significant shift in the XR industry, emphasizing the importance of transitioning from qualitative to data-driven methods for evaluating success. While many companies still lean on case studies and qualitative surveys to measure ROI and demonstrate impact, organizations like Cognitive3D, Virtualitics, and InContext Solutions are approaching this via a different method by investing in advanced data analytics. The company extracts detailed user interactions, specific to Virtual Reality (VR) and Augmented Reality (AR) environments, allowing you to address insights that set your application apart from the market. This focus on capturing detailed user interactions allows for a more nuanced understanding of how XR solutions perform, offering tangible evidence to clients and stakeholders.

The reliance on qualitative methods across the industry reflects broader challenges in educating stakeholders about the potential and the use of XR technologies within enterprise. The majority of data are gathered via surveys and qualitative measures such as case studies that demonstrate the solutions capabilities. If there is quantitative data or feedback, it is often high-level, small scale, and vague in operational and implementation specifics. While these methods provide valuable insights on the technology, they do not leverage the capability of the technology in its entirety, leaving its broader benefits end educational value underexplored. Addressing this gap through robust data analytics, such as user-level specificity, location/gaze/eye/body/hand tracking, and heat maps can foster better decision-making and play a pivotal role in overcoming adoption barriers. As the industry matures, combining these efforts with strategic education initiatives can transform how XR’s value is communicated, leading to more meaningful adoption and scaling of immersive technologies.

Based on the insights gathered at AWE EU in Vienna, below are key recommendations for companies seeking to enhance their XR strategies and adoption:

• Invest in Data Analytics: Companies should prioritize building robust data analytics capabilities to measure detailed user interactions, track ROI, and demonstrate the impact of XR solutions. Tools like Cognitive3D’s analytics platform can help gather actionable insights, allowing organizations to refine their offerings and provide concrete evidence of value to stakeholders.
• Adopt Quantitative Metrics: Shift away from solely relying on qualitative methods such as case studies and surveys. Integrating quantitative metrics gathered on the XR device with other operational data sources can uncover inefficiencies that were not clear through traditional analysis. For example, DHL conducted a pilot project using TeamViewer’s Vision Picking software on AR headsets, and discovered that this integration led to a 25% increase in efficiency, uncovering inefficiencies in traditional methods. This approach will not only appeal to enterprise clients, but also position XR companies as data-driven innovators.
• Enhance Developer Engagement: A thriving developer community is critical for creating immersive and scalable XR solutions. Companies like Niantic and Tropos AR highlight the importance of making development tools accessible and providing incentives for developers to engage deeply with the platform. Hosting hackathons, offering free resources, and creating open-source initiatives can help foster this engagement.
• Leverage AI to Scale Solutions: While cautious adoption of AI is evident across the industry, companies should explore AI-driven personalization and automation to enhance user experiences and operational scalability. AI integration can also support data collection and processing, making it easier to provide real-time insights and feedback loops.
• Educate Stakeholders: Many organizations and clients lack a deep understanding of XR’s potential, leading to slow adoption. Companies should focus on educating stakeholders about the tangible benefits of XR through webinars, detailed use cases, and ROI-driven demonstrations. Collaboration with alliances and organizations, e.g., the Augmented Reality for Enterprise Alliance (AREA), with the goal of achieving a wider adoption of AR, can further amplify these efforts.
• Address Hardware Limitations: Hardware remains a bottleneck for XR adoption. Companies must balance their software capabilities with the current state of hardware technology, offering modular or phased solutions that align with what existing devices can support. Meanwhile, advocacy for hardware advancements, possibly through partnerships with manufacturers, can accelerate progress.
• Target Education and Training Verticals: As seen with some operators’ emphasis on educational applications, such as Pico and ArborXR, the training and education sectors represent a significant growth opportunity. Companies should tailor XR solutions to address specific educational challenges, such as immersive learning environments, virtual labs, or interactive training modules, while also seeking government or institutional funding for broader adoption.
• Collaborate and Share Knowledge: The industry can benefit from increased collaboration across companies to share best practices, insights, and even datasets. Creating a shared platform or repository for anonymized data could help smaller companies understand market trends and enhance their strategies.