🔍 New Dimensions Added: "Country," "Sales Channel," "Product Type," "Average Order Value"

Feb 20, 2024


We're excited to announce the addition of "Country," "Sales Channel," "Product Type," and "Average Order Value" to the data available for segment creation within ECPower.


We've expanded the customer attribute dimensions to include "Country." This enhancement is ideal for users interested in understanding their customer base on a country-by-country basis, such as those engaged in cross-border e-commerce.

Usage Example: Create customer segments by country and needs to analyze trends and characteristics in purchasing behavior.


Sales Channel

The "Sales Channel" dimension has been added to orders, allowing you to differentiate customers across various channels, including online stores, physical store POS systems, Shopify's "Shop" mall, and others. This is a significant step forward in planning and executing omnichannel strategies.

Usage Example: Segment customers based on the sales channel used for their first purchase to tailor omnichannel strategies.


Product Type

Many merchants manage their product categories through "Product Type" data. We encourage you to explore creating customer segments at the category level, especially for those categories that were previously challenging to pinpoint using products or product tags.

Usage Example: Segment customers based on purchase activity by product type to enhance cross-selling initiatives.


Average Order Value

This new dimension enables you to filter customers based on their average purchase amount within a specified range. Additionally, it's possible to set a time period for this filter, such as the past year, to refine your analysis further.

Usage Example: Consider upselling campaign to customers who’s AOV is lower than $50 and track AOV metric after the campaign.


From the Product Team
We have received numerous requests for additional dimensions in segment creation, and in this update, we focused on integrating those with the highest demand. The use of customer-level aggregate data, such as segments based on average repurchase intervals, has been a popular request, and we plan to continuously enhance this feature. If you have any suggestions or needs, we're all ears!