VR, AR, and MR are growing in influence across the business world; whether in training or branded customer experiences use cases, wider technology adoption is felt, and as the market reaches more business use cases, clients are trying their best to understand how XR can drive positive outcomes.

As more enterprise clients try to leverage and reek positive outcomes from XR solutions, a certain level of understanding must come with the technology and its usage.

Not only must a company understand the hardware, but enterprise clients must also understand the behavioural aspects of their workforce as they adopt immersive solutions.

Behavioural understanding encompasses a range of considerations, such as how a worker interacts with spatial computing user interfaces (UI), which can not only help employees leverage XR but also help drive trust and adoption for enterprise-grade immersive solutions.

Analytics play a significant role in this. XR provides a massive range of input data that developers can leverage to improve enterprise-grade and branded immersive services.

Tony Bevilacqua. I’m the founder and CEO of Cognitive3D, joined XR Today to discuss the relevance of 3D analytics across VR, AR, and MR applications – specifically within the enterprise, customer experience, and academic use cases. The company launched in 2015 and released its first product in 2016 – focusing on spatial analytic services.

The firm also provides XR analytics for a range of customer-facing use cases. However, the metric’s application in business and learning verticals drives excellent investment opportunities.

XR Metrics Provide New Opportunities for Enterprise and Consumer Experiences

Bevilacqua explained that his firm observed an extensive opportunity to “build metrics in a new wave to address the needs of what was going on in the XR space.”

However, the Founder and CEO explained how Cognitive3D didn’t “necessarily get there initially,” adding:

We thought originally that we were going to introduce a mobile analytics style product but realised we kind of need to turn the playbook on its head and build something unique for the XR space, and really, we operate and market it with the thesis around giving developers visibility on what’s going on inside the headset and also using the headset as a vehicle for data collection. So, helping developers get a better understanding of what’s going on inside that headset and how to build better content for it.

Moreover, Bevilacqua said that Cognitive3D works to solve client pain points across various categories, which is “dependent” on the type of content a developer or business is building.

Bevilacqua explained that the firm started in games and entertainment before moving towards the growing enterprise XR market because “the consumer market wasn’t there, but what we [Cognitive3D] did find was a really great fit in enterprise. So, enterprise for us encompasses a few primary categories. The first one would be training and simulation.”

Training and simulations are still Cognitive3D’s “bread and butter.” The CEO and Founder added:

So simulated content, how can we measure human performance? How can we demonstrate the value proposition that is associated with these [immersive] training simulation apps? – And competency, the knowledge retention, those types of outcomes. Leveraging these 3D analytics capabilities.

Bevilacqua also noted that the firm works in the consumer research space, where the firm works in “quite a few different categories of consumer research.” The most notable high-level use case is “architecture, engineering, and construction”, the CEO and Founder remarked.

Bevilacqua explained:

A lot of folks in that category will use us for wayfinding and signage, so being able to understand, if I put somebody into a virtual space, if I put somebody into a digital twin, what’s going to keep and draw their attention within that particular space. If I put signage up, if I build a space in a certain way, what path are users likely to follow as they engage with within that world.

Bevilacqua also noted that another vertical gaining value from XR analytics is product development, with the CEO and Founder adding that the automotive industry is an excellent example of that – adding:

We’ve got companies like Ford, GM, and others innovating in their product design process, and using VR technology to accelerate new design Categories. Also insights and being able to understand how their buyers might interact within those particular environments, what draws their attention, what doesn’t, and associating that behaviour with the qualitative information.

Additionally, alongside a long list of suitable end-users, another end-user that benefits from XR analytics is the retail CPG category, “so in that category, we’re thinking about planograms, store design, product packaging, interaction, those types of insights as well.”
Bevilacqua also added:
We also support over 30 academic institutions today in their academic research. So, data collection is in that particular category.
Driving XR Adoption Rates
XR analytics can also help drive XR device and software adoption across a workforce by delivering core insights into employee usage.
Bevilacqua explained:
There are two different sides to the insight that we provide support for. So, in the earliest phases of building a new project, we can provide really great insight into UX and UI in terms of how people are interacting with the experience, what’s drawing their attention, keeping their attention, how they are comprehending the content that you’re putting in front of them.
Bevilacqua noted that services like Cognitive3D help enterprise clients understand the value proposition of workplace XR solutions. The CEO and Founder stated:
Then you move from: “Are we delivering a good experience?” To: “Is this creating good value for the organisation?” When we move into that category, it really depends on the use case you’re after. So on the training and simulation side, we talk about completion, we talk about competency, we talk about retention of knowledge, precision, and work. Those are two different value propositions that you would have, and you could work on both sides of it. One of our key tools is called Scene Explorer, and this is literally an after-action review. It’s a one-to-one replay of exactly what the user did inside the headset, and you can collect that on a completely distributed basis. So, a lot of our Customers will actually use this to debug specific sessions. Especially when you start collecting a lot of sessions from testers or QA. Something along those lines, you can actually pull out the ones that maybe are the outliers and see what went wrong. What I can learn from this particular experience and how might I be able to improve it?
XR Analytics: The Ultimate Insight?
Congative3D is also working towards driving retention sessions for various use cases. Bevilacqua explained that the firm “started off by building three metrics” in order to break down what quality means in XR and, therefore improving user retention during training sessions.
He explained:
The first one is called cognitive Comfort. The second one is called cognitive immersion, and the third one is cognitive performance. So, for each of the three, we look into kind of all these different inputs that are going on in the headset to build effectively a Barometer. This is a 0 – 100 score, 50 being average within the experience, and we give you a ranking within your application of where you stand on each of those three measures.
Bevilacqua also added:
Then, within the dashboard, you can dig into each of those measures to be able to see a cognitive performance. For example, do I have bad, you know, battery dispersion? Is my FPS not so good? Where am I seeing failing frames within the scene? Where can I potentially optimise? The idea here is to provide a developer that barometer of where they stand, but also the tools to kind of uncover the ultimate insight on how they can improve their application.
The Future of Analytics
XR analytics is an emerging service that Congative3D provides; with its emergence comes a wealth of new information for clients to leverage.
Elements such as hand and eye-tracking were not commonly available in the last decade. However, the data is now becoming more manageable and more accessible for enterprise end-users. What’s in sort for the future is still yet to be seen.
Bevilacqua added:
Over the last several years, for us at least, we’ve been really focused on building core technologies. So, building all the visualisation tools, building the data pipeline, and making it work. We’re really building a new category, inventing a new data collection paradigm. That’s Really tough work. We’ve really scaled up the team over the last year or so, and now we’re starting to think a little bit more about what are the predictive elements of what’s going on within these applications, what are the insights that I can surface to the developers to help them understand where they stand from a content perspective and where they could potentially improve.