Why Accuracy Matters: How Fyma Sets the Standard in CRE Analytics
April 8, 2025

In commercial real estate, insights are only as good as the data that powers them. Fyma distinguishes itself by delivering highly accurate analytics rather than relying on general patterns - consistently achieving 97%+ precision in real-world environments where conditions are messy, lighting is variable, and cameras aren't always ideally positioned.
What 'Accuracy' Actually Means in CRE Analytics
Accuracy demands precision - if 100 people enter a building, the system should register exactly 100. Fyma maintains 97%+ accuracy in actual operating conditions rather than controlled test environments. A UK co-working facility study demonstrated this principle: during peak hours, the technology analysed entrance footage and achieved 99.78% accuracy, missing just one visitor among 455.
Why Accuracy Is More Important Than Generic Insights
Flawed data produces inefficient pricing, poor asset performance, and lost revenue opportunities. When a sensor systematically undercounts by 15%, every downstream decision - staffing levels, amenity investment, lease negotiations - is built on a false foundation. Consistency enables CRE teams to justify decisions confidently to stakeholders with data that holds up to scrutiny.
How Fyma Delivers Market-Leading Accuracy
Advanced machine learning models trained on diverse real-world datasets. Compatibility with existing CCTV infrastructure at any quality level. Placement expertise that optimises camera selection before deployment. Real-time actionable insights with visual verification capabilities. Every count is backed by the footage that generated it.
Real-World Case Study: Runway East Bloomsbury
The system achieved 99.78% accuracy in tracking footfall at Runway East's Bloomsbury location - demonstrating performance in a real operational environment, not a test scenario. This level of precision enabled the team to make reliable decisions about staffing, event capacity, and amenity investment with full confidence in the underlying numbers.
Why Computer Vision Outperforms the Alternatives
Computer vision surpasses infrared sensors, motion detectors, and pressure pads across every meaningful dimension: broader spatial coverage, zero hardware dependency, transparent visual validation, and continuous improvement through software updates. It provides directional and behavioural context that point-sensors cannot match - and does so without capturing personally identifiable information.
"In one real-world case, we missed just one person out of 455. That's what true accuracy looks like."
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