Authentication & User Identity for Immersive XR Experiences
Connect XR data to 40+ engines, tools, and platforms. Custom analytics, benchmarking, and platform metrics from our data science team. Spatial analytics for the Unity engine. Spatial analytics for the Unreal engine.
Cognitive3D captures everything that happens inside XR — movement, attention, decisions, and performance. The platform makes that data visible. The data science team is where it becomes evidence.
Focus: Making XR Evidence Measurable
Composite scores — Cyberwellness, Ergonomics, Presence, App Performance — grounded in spatial behaviour research. Interpretable sub-components, not black boxes.
Bespoke analysis scoped to your questions. A/B testing, retention modelling, spatial heatmaps, KPI tracking, training effectiveness.
Cross-application benchmarks from hundreds of millions of minutes of XR data. Comfort budgets, performance baselines, quality thresholds.
Custom deployment guides scaled to your needs — from lightweight consumer app instrumentation to enterprise-wide rollout playbooks.
Quantifies the comfort profile of the experience. Metrics grounded in cutting-edge peer-reviewed research on what induces VR sickness.
Evaluates physical strain from headset orientation and controller positioning. Horizontal, forward, and vertical reach. Roll and pitch strain.
Quantifies immersion. Sub-components include spatial coverage, controller movement, gaze exploration, and user immersion.
Benchmarked performance, degree of impact, consistency, and fluctuation. Overall scores use weighted averages and geometric means.
The following case studies are drawn from real client engagements. Details have been anonymised, but the patterns and outcomes are representative of the work the data science team delivers.
Whether you need a one-time analysis or ongoing data science support, the team is ready.
The Team Behind the Metrics, the Models, and the Evidence
We turn spatial data into decisions — measurable scores, custom analysis, and benchmarks that make XR outcomes defensible.
WHY DATA SCIENCE
Your Data Answers Harder Questions Than Your Dashboard Can Ask
We design the composite scores and the platform reports. We build custom analyses that answer the questions clients bring to us. And we work directly with customers to connect spatial behaviour data to the outcomes that matter to their business.
THE TEAM
Two PhDs in Human Spatial Behaviour
Dr. Nicola Anderson
Head of Data Science
Eye–head coordination & visual attention. Postdoctoral work at UBC studying gaze dynamics in immersive environments. Leads custom analytics engagements, directs the team's research programme, and makes spatial behaviour data accessible to client teams.
Dr. Mona Zhu
Data Scientist
Master of Data Science (UBC). MA & PhD in Cognitive Psychology (Waterloo). Expertise in spatial cognition, human factors, and perceptual processes in 3D environments. Designs and maintains the platform's composite scores, develops data pipelines, and supports custom client analytics.
WHAT WE DO
Four Capabilities. One Goal: Turn Spatial Data Into Decisions.
Platform Metrics
Custom Analytics & Reporting
Benchmarking & Standards
Integration Strategy
PLATFORM METRICS
We Design the Scores the Platform Reports
Cyberwellness
Ergonomics
Presence
App Performance
CUSTOM ANALYTICS
You Have a Question About Your XR Experience. We Answer It With Data.
A/B Testing
Onboarding variants, UI alternatives, interaction paradigms with measurable outcomes.
Retention Modelling
Churn prediction and lifecycle analysis across user lifecycle stages.
Spatial Heatmap Analysis
3D navigation patterns, attention hotspots, and spatial behaviour mapping.
KPI & OKR Tracking
Ongoing measurement against the metrics that matter to your business.
Training Effectiveness
Learning outcomes, skill transfer, and performance improvement in XR training.
BENCHMARKING & STANDARDS
Quality Is Not a Spectrum. It Is a Threshold.
The data science team maintains cross-application benchmarks built from hundreds of millions of minutes of XR behaviour data. These benchmarks provide context that no single application can generate on its own: what comfort profiles look like across app categories, where performance thresholds sit for different devices, and what “good” looks like for ergonomics, presence, and session quality.
For enterprise customers, these benchmarks have operational consequences. Quality is not a spectrum in enterprise; it is a threshold. Teams above it succeed. Teams below it lose the deployment.
Our benchmarks are increasingly being written into enterprise procurement requirements.
INTEGRATION STRATEGY
Every Deployment Is Different. Your Strategy Should Be Too.
Consumer & Independent Apps
- Focused instrumentation guide
- Event taxonomy & SDK configuration
- Key engagement & retention metrics
- Optimised for quick integration
- Lightweight & self-serve
Enterprise Deployments
- Full-stack analytics with custom instrumentation
- Bespoke data models & pipeline design
- Advanced spatial & behavioural analytics
- Dedicated DS team embedded in your workflow
- Scales with your programme & evolving questions
EVIDENCE FROM THE FIELD
Three Patterns From Analysing Hundreds of Millions of Minutes of Spatial Data
Case Study
The Onboarding That Predicted Retention
A VR fitness application tested three onboarding variants. The action-oriented variant won across every metric: longer first sessions, lower quit rate, faster return, higher frequency through sessions two and three.
First-session experience is a surprisingly strong predictor of long-term retention. The first two to five minutes carry disproportionate weight.
Your onboarding is not just teaching mechanics. It is predicting who stays.
Case Study
The Comfort Ceiling That Cut Off Monetisation
A fast-paced action game had strong mechanics but 75% of sessions were under five minutes. The comfort ceiling was cutting off monetisation before users reached the conversion window.
< 5 min typical session duration before users quit
~7 min conversion window — most purchases happen after this
Comfort is not a vague concern. It is a measurable ceiling — and when sessions end before the conversion window opens, the business case ends with them.
Case Study
The Quality Gap That Predicted Adoption
A large-scale enterprise training deployment spanned multiple VR applications built by different developers. Adoption rates varied from 3% to 90%. Apps with better performance and comfort saw dramatically higher adoption.
3–90% adoption range across apps in the same deployment
VR > Web but only when app quality met baseline
Standard benchmarks now in procurement criteria
For enterprise XR to succeed, quality needs to be measurable and enforceable. We provide both.
HOW WE WORK
Engagements Start Light and Grow as Questions Get Harder
01
Integration Strategy
What to track, how to configure the SDK, and which metrics matter. From focused consumer instrumentation to full enterprise deployment playbooks.
02
Project-Based Analysis
Scoped investigations with clear deliverables. A/B tests, comfort audits, benchmarking reports, user journey analysis. Question in, recommendation out.
03
Ongoing Embedded Support
Regular reporting, KPI tracking, and iterative analysis as your product evolves. Reporting cadences, tracking dashboards, and insights over time.