Platform

Furnilytics is a structured data platform for the furniture industry. It combines official statistics, industry datasets, and digital market signals into a unified platform designed to help professionals monitor market developments and work with data more easily.

A central goal of Furnilytics is to make market trends more accessible to the industry. For that reason, a growing library of public indicators is made freely available. These indicators help users follow developments in furniture retail, manufacturing, trade, and related macroeconomic drivers.

Beyond the public indicator layer, Furnilytics also provides advanced datasets, including more specialised and higher-frequency data such as weekly web-scraped market signals. The platform is designed so that users can explore data on the website, access it through the API, or integrate it directly into tools such as Power BI, Tableau, Excel, Python, or R.

What the Furnilytics platform is

The Furnilytics platform is a structured data infrastructure for analysing the furniture industry. It organises market data from official statistics, trade datasets, and digital demand signals into consistent datasets that can be explored through indicators, downloaded as structured tables, or accessed programmatically through the API.

The platform is designed to make it easier for analysts, retailers, manufacturers, and industry professionals to monitor market developments across countries and over time. Public indicators provide an accessible overview of market trends, while the underlying datasets enable deeper analysis and integration into analytical workflows.

Why professionals use the Furnilytics platform

Furnilytics brings together continuously updated furniture market data, structured indicators, and flexible access options in one platform.

Always up to date

Indicators are maintained through automated and scheduled updates, helping users follow new developments as fresh data becomes available.

One structured source

Official statistics, industry datasets, and original analysis are brought together in one structured environment focused on the furniture industry.

Flexible data integration

Explore indicators directly on the website or integrate Furnilytics datasets into dashboards, BI tools, and analytical workflows through the platform and API.

How the platform works

Furnilytics data can be explored directly on the website through public indicators, examined through the structured dataset catalogue, or integrated into dashboards and analytical workflows via the API.

1

Structured datasets

Furnilytics organises market data into structured datasets covering furniture retail, manufacturing, trade, and relevant macroeconomic developments.

2

Public indicators

Selected series from those datasets are published as free indicators to help the industry track general market direction and structural developments.

3

Advanced data access

Additional and more specialised datasets are available through the platform, including advanced data such as weekly web-scraped indicators.

Why Furnilytics exists

Furnilytics was created to improve transparency in the furniture industry. Market data relevant to the sector is often fragmented across statistical sources, trade databases, industry reports, and internal company analyses. This fragmentation makes it difficult to build a consistent view of market developments across countries and over time.

The platform brings these data sources together into a structured analytical environment focused specifically on the furniture industry. By combining official statistics, trade data, digital demand indicators, and original analysis, Furnilytics helps industry professionals monitor market trends, benchmark developments, and integrate external market data into their own analytical workflows.

The public indicator library represents the open layer of the platform and is intended to improve market awareness across the industry. Additional datasets and extended access options are available for users who require more specialised or higher-frequency data.