With Country Segmentation, Paddle Billing sellers can automatically segment their subscription revenue by country. Sellers can better understand their business performance in specific countries, unlocking insights around pricing, growth, retention and monetization strategies.

When building a segment in the side menu, sellers will be able to select the countries their customers reside in, and then compare those segments with revenue metrics such as:

• Growth rate

• Retention

• Churn

• LTV

• ARPU

• Revenue composition

This location data can be “stacked” with other properties, such as age of account and MRR, to create more detailed segments. In turn, this provides:

Improved analyses: Provides sellers with the ability to understand their subscription revenue more deeply, and compare the effect of different locations on their revenue.

Improved strategy: Enables sellers to determine the regions that have the largest impact (or the largest opportunities for improvement) on their subscription revenue goals, so they can focus their resources on these regions, and grow more efficiently.

Improved positioning: Enables sellers to understand the geographies that they are strongest in, and effectively position themselves against competitors who may have a larger market share in other regions.

Looking to get started with Paddle Billing? Get started here.

Instructions to Segment by Location

Step 1: Enter the Metrics platform, and in the Segmentation Comparison page, click “How does my LTV vary by geographical location?”

Step 2: Once the default countries are loaded, click the small downward arrow on any of the countries to open configuration options. 

Step 3: Click “Remove Segment” and click “Add Another Segment” to select another “Location”.

Step 4: Select the countries that you want to have included in your Segment Comparison (up to 5 countries allowed). 

Step 5: Dive deeper into your data by “stacking” different segment traits together (i.e. company size, company industry, etc). 

*In order to add these traits to the platform for richer customer data, you can do so by following the instructions here. The uploading of custom traits will lead to more meaningful segmentation and more granular views into your customer data.*