About us

Spatialzr

We believe every real estate decision can generate a positive impact on the city, society and the environment.

Our mission is to make location a standard reference in professional real estate decisions, by turning public spatial data into simple, comparable and auditable indicators.

Spatialzr provides LISA (Location Score for CRE), a location score designed as a reference column in the models of investors, property companies, banks, retailers and portals. LISA analyses each site across six key factors – metropolitan area, accessibility, retail activity, economic activity, urban life and environment – to deliver a global, objective view of a place’s potential.

We believe high‑quality spatial data should power real estate strategies that are not only innovative, but also resilient and beneficial for all stakeholders: investors, operators, municipalities and citizens.

Our path

In two years, Spatialzr has designed, tested and consolidated a standard location score for commercial real estate:

2023: Exploration of needs in the real estate scoring market and architecture of the first public‑data aggregation model.
2024 / 2025:
- Sector POCs with real estate groups and retailers, running pilot studies in London, Paris, Lyon, Lille and tertiary French regions.
- First industrialised version of the score.

We follow a continuous improvement approach: every POC, every dataset and every regulatory change feeds into the value of our score.

Why Spatialzr?

In commercial real estate, most models start with financial metrics. Spatialzr does the opposite: we start from location intelligence as the fundamental layer – spatial data, accessibility, points of interest, urban and environmental context – and then stack building, asset and market data on top. This is what makes the LISA score a true location standard, not just a bolt‑on to traditional valuation models.

Research such as McKinsey’s shows that nearly 60% of a real estate model’s predictive power can come from location and neighbourhood characteristics, far beyond rents or yields alone. Spatialzr responds to this by offering a location score specifically designed for commercial real estate (CRE), turning complex open data into a reliable indicator to assess a site’s potential – across office, retail, logistics or residential use cases.

Whether you are an investor, broker, developer, valuer or asset manager, LISA becomes a shared column that helps you compare sites, analyse portfolios and select the best locations in a location‑first mindset

Source (insight on location-related predictive power): McKinsey & Company, “Getting ahead of the market: How big data is transforming real estate”, 2018.

A reference layer for CRE decisions

Real estate assets are fixed and long‑term: location is therefore key. At Spatialzr, we believe reference data should be built on public spatial data – scalable, structured and universal. On this basis, LISA is designed as a standard reference layer for real estate decisions.

Our methodology evaluates each site across six weighted factors:

📍 Metropolitan area
🚉 Transport accessibility
🛍️ Retail activity
🏢 Business density
🌆 City life
🌿 Environmental factors

The resulting score can be adjusted to reflect best use – office, retail, logistics, residential – or kept as a standard score for general assessment. It can be enriched with complementary data (transactions, footfall, ESG, turnover, etc.) or tailored to a specific investment strategy.

What makes us unique

Spatialzr designs LISA as a standard location building block, meant to plug into existing models rather than replace them. While many solutions remain black boxes or closed interfaces, LISA delivers a transparent score, based on structured public data, that you can use as a reference column inside your own models.

Plug and play score

No integration nequired

Transparent methodology

Supports all major CRE asset types

Global and extensible by design

Ethical data use only

Built to become an industry standard

Global

All CRE asset types

From Location first to full CRE intelligence.png

Our Values: Impact property investment

Sustainable development

We are driven by the ambition to help build sustainable cities by promoting densification, resource conservation and resilient urban environments.

ESG Framework

The current context reminds us how critical it is to preserve resources. We help prepare tomorrow’s world today by encouraging sustainable behaviours.

Sutainable finance

Our algorithms and the way we process data are shaped by a commitment to more responsible finance.

Who is behind Spatialzr?

Spatialzr is led by Cyril Théret, with more than 20 years of experience building marketplace platforms and data solutions for real estate and finance in France and the United Kingdom. This dual market‑and‑data background fuels the design of LISA as a location standard that investment, asset management and risk teams can use directly in their models.