> 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/checkout-data.md).

# Checkout data

Checkout data shows how delivery options are actually presented to consumers at the moment of purchase.

Tembi captures this by selecting a representative product from each webshop and simulating a purchase. This allows us to observe the real checkout configuration - including delivery providers, methods, prices, and positioning - exactly as a consumer would see it.

<figure><img src="/files/aXfXoSZRp7vOUdsjqlNA" alt=""><figcaption></figcaption></figure>

#### What we capture at checkout

For each webshop, Tembi captures:

* Delivery providers shown
* Delivery methods (home delivery, lockers, parcel shops, etc.)
* Delivery prices and price differences by method
* Position and order of providers in checkout
* Branding and service presentation

This data is collected repeatedly, allowing changes to be tracked over time rather than as one-off snapshots.

<figure><img src="/files/G6o20F3M3W9T20riP3EL" alt=""><figcaption></figcaption></figure>

#### Historical tracking and performance monitoring

Because checkout setups evolve, historical data is critical.

With Tembi, teams can:

* See your position in each checkout and how it has changed over time
* Track how your brand and services are presented to consumers
* Monitor which delivery methods are offered and at what price
* Get a summary score for each client that reflects checkout quality and visibility

This makes it possible to move from reactive issue spotting to structured monitoring.

<figure><img src="/files/fiiNy2QFZhAbn5ga9cB1" alt=""><figcaption></figcaption></figure>

#### Competitive insights at market level

At scale, checkout data becomes competitive intelligence.

Aggregated across the market, it allows teams to:

* See how often providers appear and in which positions
* Understand who competes with whom inside the same checkouts
* Benchmark average position and visibility against competitors
* Estimate how broadly each provider is represented across the market

This provides a grounded view of competitive pressure and relative market presence.

#### How different teams use checkout data

**Sales** use checkout data to:

* Understand how prospects currently present delivery options
* Build stronger pitches grounded in the prospect’s actual setup
* Prioritise accounts where positioning improvements are realistic

**Key Account Management** uses checkout data to:

* Monitor existing clients for changes that affect revenue
* Track compliance with agreed positioning and service visibility
* Identify upsell opportunities when setups or volumes change

**Leadership** uses checkout data to:

* Understand structural differences between markets
* Track competitive dynamics over time
* Track perfomance
* Validate assumptions about market position with observable evidence

Checkout data turns delivery positioning from something assumed into something measurable - and therefore actionable.


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