> For the complete documentation index, see [llms.txt](https://tembi.gitbook.io/tembi-knowledge-base/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://tembi.gitbook.io/tembi-knowledge-base/start-here/how-it-works.md).

# How it works

Tembi builds a structured, high-quality dataset by combining multiple data layers around each webshop and the organisation behind it.

The goal is not just to collect data, but to ensure that every webshop included represents a real, operating business that can be analysed, compared, and tracked over time in order to provide actionable market intelligence.

#### 1. Identify and validate active webshops

We continuously identify webshops across each market and validate that they are active and operational.

By interacting with the webshop flow, we can confirm that a site is functional and selling - not parked, outdated, or inactive. This step is critical for maintaining a clean and reliable market universe.

#### 2. Observe live webshop behaviour

We observe key elements of how webshops operate in practice, including checkout behaviour.

This allows us to validate that the webshop is actively trading and to capture consistent operational signals over time, rather than relying on static or self-reported information.

#### 3. Analyse products and brands

We analyse what each webshop actually sells.

This includes:

* Product categories and assortment structure
* Brands offered and their positioning
* Number of products and product weight and size information

Product and brand data provides essential context for understanding differences between webshops and how markets are structured.

#### 4. Capture technology and integrations

We identify the core technologies each webshop is built on.

This includes:

* E-commerce platforms and frameworks (for example Shopify, WooCommerce, Magento)
* Payment providers and checkout components
* Logistics, marketing, and data integrations

Technology data adds an additional layer of context and allows markets to be segmented by operational maturity and setup.

#### 5. Connect webshops to real organisations

Each webshop is linked to organisational and company-level data where available. We connect webshops with the relevant national company registry to retrieve organisation numbers, ownership structures, and company attributes.

This includes:

* Organisation and registration numbers
* Ownership and group structures
* Operational and financial indicators where available

This ensures that data and analysis is based on real companies rather than disconnected domains.

#### 6. Model size, activity, and growth

All data layers are combined to estimate webshop size, activity, and growth dynamics.

By bringing together behavioural signals, product data, technology setup, and organisational context, Tembi enables consistent comparisons across markets, segments, and competitors.


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