> 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/jobs-library/finding-the-right-new-customers.md).

# Finding the right new customers

In this section, we show how to use Tembi to identify and prioritise new customers.

Most markets contain tens of thousands of webshops. Manually separating relevant prospects from noise is unrealistic. Tembi helps you narrow the market to a short, qualified prospect list based on concrete signals from checkout and webshop data.

Instead of broad outreach, you can focus on prospects where the commercial fit is strongest - and where timing is right.

{% @arcade/embed url="<https://app.arcade.software/share/c6EMc1hCKCjY7S25Htra>" flowId="c6EMc1hCKCjY7S25Htra" %}

#### Use filters to narrow down the right prospectsTembi provides a range of filters that allow you to narrow the market and identify relevant prospects.

Filters can be combined to create precise views of the market based on commercial and operational criteria.

Common ways to identify potential customers include filtering by:

* **Technology and platform** – for example Shopify, WooCommerce, Magento
* **Current delivery providers and methods** – which providers are used and how delivery is offered
* **Product portfolio** – categories, price levels, size and weight characteristics
* **Geographical location** – country, region, or local focus
* **Size estimation** – an indication of webshop scale and activity
* **Export markets** – domestic versus cross-border sellers

Filtered views can be saved and reused, making it easier to maintain consistent prospecting criteria across teams.

#### Set up favourites to build your shortlist

Once you have defined a set of filters that identify relevant prospects, you can save them as favourites.

Favourites allow you to:

* Quickly return to the same shortlist without rebuilding filters
* Maintain consistent criteria over time
* Share a common view across team members

This makes it easier to keep a stable, up-to-date shortlist of potential customers as the underlying data changes.

{% @arcade/embed url="<https://app.arcade.software/share/2RbvZbkJu3Eumy5i6yHD>" flowId="2RbvZbkJu3Eumy5i6yHD" %}

#### Understand the webshop checkout

Checkout shows how delivery is actually configured for a given webshop.

It reflects the choices the merchant has made about providers, methods, pricing, and presentation - and how these are surfaced to customers.

From the checkout, you can observe:

* **Delivery providers and their position**
* **Delivery methods** (home delivery, lockers, parcel shops, etc.)
* **Delivery prices**
* **Delivery time per provider**

This information helps you understand the webshop’s current delivery setup and how it compares to similar retailers in the market.

{% @arcade/embed flowId="OOthFrnBfLSbFYVrHzgu" url="<https://app.arcade.software/share/OOthFrnBfLSbFYVrHzgu>" %}

For more details see:

* [Checkout data](/tembi-knowledge-base/start-here/checkout-data.md)
* [Checkout score](/tembi-knowledge-base/product-how-to/checkout-score.md)

#### Use product insights to qualify the prospect and personalise your pitch

Product insights help you understand what a webshop sells and how it positions itself.

This information can be used both to assess whether a prospect is a good fit and to tailor your outreach.

Look for signals such as:

* **Product categories and assortment structure**
* **Brands carried**
* **Price level and positioning signals**
* **Product attributes that affect delivery** (for example size and weight patterns)

Use these signals to:

* Prioritise prospects that match your existing customer profile
* Tailor outreach to the prospect’s assortment and positioning
* Bring one or two concrete suggestions that relate directly to what the webshop sells

This keeps conversations relevant and grounded in the prospect’s actual business.

{% @arcade/embed flowId="TrtOEHiVPb4MKpYeIMgo" url="<https://app.arcade.software/share/TrtOEHiVPb4MKpYeIMgo>" %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://tembi.gitbook.io/tembi-knowledge-base/jobs-library/finding-the-right-new-customers.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
