Sales Analysis by Customer Attributes

Analysis > Sales > Customer

Summary

The report breaks down key metric performance based on specific customer attributes such as customer type (new or report), locations, and more.

Questions the report answers

• How is the business performing across different customer attributes, such as customer type (new or report), locations, and more?

How to read the report

Switching Between Customer Attributes

The report lets you switch between different customer attributes which helps you analyze how various dimension type such as customer type (new or report), locations and more attributes contribute to overall sales performance. The attributes you can switch between are as following:

• New or Repeat
• Marketing Consent
• Percent Orders has GWP
• Percent Orders has Sample
• Percent Orders has Discount
• Percent Orders has Shipping
• Percent Orders has Return
• Percent Orders has Subscription
• Country, State, City
• New or Returning Users
• Device Category
• Browser
• Operating System

Select the specific customer attribute you want to analyze based on your goals. For instance,if you want to assess customer acquisition or retention, focus on the New or Repeat attribute. If you’re targeting specific geographical areas for a campaign, switch to the Country or City attribute.

Customizing Metrics on the table

The report allows you to customize the metrics you want to analyze, which means you can choose the specific data points that matter most to your business. By default, key metrics like Sales Amount, Number of Orders, and Average Order Value (AOV) are selected, but you can add or remove metrics depending on their focus.

You can use the YoY Variance and YoY Variance % to compare performance with the previous year and determine whether your strategies are more effective.

You can leverage the KPI Tree structure to understand how all the metrics are related to each other. By understanding the relationship between the metrics you can use the supporting metrics to answer why behind the change of a specific high-level metric. Let’s say you notice a significant drop in Sales Amount YoY Variance %.

You can use the First-level KPIs such as the Number of Order and AOV to answer why the Sales Amount has dropped. If you see that the drop in Sales is because of the drop in the Number of Orders, you can the Second-Level KPIs such as Sessions, Conversion Rate, Number of Customers, and Order per Customer to further understand why the Number of Orders has dropped. This step-by-step approach helps you quickly identify which areas of your business need attention.