tl;dr
Customer Segments let you define any subset of customers using over 100 dimensions — across ordered products, marketing source, activity state, value metrics, and more
Segments go beyond built-in report filters — you can combine multiple conditions with AND/OR logic to build precise, reusable cohorts
Once created, segments can be applied across reports in Klar to drill down into a specific customer group
Value Metric filters support two modes: Absolute (exact values, e.g. lifetime revenue > €200) or Percentile (e.g. top 10% by net revenue)
What is the Customer Segment builder?
Most reports in Klar have built-in filtering options, but these are limited in scope. Customer Segments extend that — they let you create reusable, complex filters using over 100 dimensions, which you can then apply across reports to drill down into any customer cohort.
Dimension Groups
Dimensions are organised into six groups. Each group has two classifiers — the first selects the dimension to filter on, the second sets the condition. Like the Channel Builder, conditions can be combined with AND/OR logic to build precise rules.
The six groups are:
Customers Who Ordered Product
Customers By Most Bought Product
Customers With Revenue Of Product
Customers By Marketing Source
Customers By Activity State
Customers By Value Metric
Customers Who Ordered Product
Filter on customers who have (or have not) ordered a specific product.
First classifier — select the product dimension (Title, Type, SKU, etc.) and the product(s) to filter on. If you select multiple products in a single condition, a customer only needs to have bought one of them. To require both, create separate conditions and link them with AND.
Second classifier — define which order the product should appear in:
Specific Order Count — their first, second, third order, etc.
Any Order — any order they have placed
Last Order — their most recent order, regardless of order count
Operator — define the match logic:
Equals — customer placed an order with the product in the specified order position
Not Equals — customer did not place an order with the product in the specified order position
Less than — customer placed an order with the product at an order count lower than the value you select (only relevant for Specific Order Count)
Greater than — customer placed an order with the product at an order count higher than the value you select (only relevant for Specific Order Count)
Customers By Most Bought Product
Filter on customers based on the product they have bought the most. The first classifier defines how "most bought" is measured:
First classifier — value metric:
Net Revenue
Contribution Margin 1
Contribution Margin 2
Order Count — orders that contain the product at least once
Unit Count
Second classifier — the product dimension to filter on:
Product Type
Product Title
Product Variant
Product SKU
Product Brand
Customers With Revenue Of Product
Filter on customers who have spent a specific amount on a product.
First classifier — product dimension level (same options as above: Type, Title, Variant, SKU, Brand).
Second classifier — the revenue metric to filter by:
Gross Revenue
Net Revenue
Contribution Margin 1
Contribution Margin 2
Customers By Marketing Source
Filter on customers based on the marketing source that drove their order.
First classifier — the marketing source dimension. 17 dimensions are available:
Sales Channel
Marketing Channel Name, Group & Category — based on the channels you built in Klar
UTM Parameters — Source, Medium, Campaign, Term, Content
Landing Page
Device Category
Discount Code & Discount Code Type
⚠️ Note: The marketing source refers to the session in which the customer placed the order.
Second classifier — the order count to filter on. Same options as above: Specific Order Count, Any Order, or Last Order.
Customers By Activity State
Filter on the activity state of customers.
First classifier — the type of activity state:
Customer Frequency State — One-time Buyers, Repeat Customers, Loyal Customers, Evangelists
Customer Recency State — Active, At-risk, Defected, Reactivated
Second classifier — the point in time:
Any — was the customer ever in this state
Current — is the customer currently in this state
Previous — was the customer in this state immediately before their current state
Customers By Value Metric
Filter on customers based on their overall spending and purchasing behaviour.
First classifier — the metric that defines their behaviour:
Net Items / Gross Items
Net Revenue — First Order, 90 Days, Lifetime
CM2/Lifetime Value — First Order, 90 Days, Lifetime
90-Day Net Revenue Extension — how much net revenue increased in the first 90 days after his their first purchase
90-Day CM2 Extension — how much CM2 increased in the first 90 days after their first purchase
Average Order Value — average net AOV across all their orders
Average Discount Rate — average discount rate across all their orders
Average Voucher Rate — average voucher rate across all their orders
Average Return Rate — average return rate across all their orders
Second classifier — the filter mode:
Absolute — filter based on an exact value
Percentile — filter based on a percentile bracket
Example — Absolute: Customers who have spent more than €200 lifetime:
Classifier 1: Lifetime Net Revenue
Classifier 2: Absolute · greater than · €200
Example — Percentile: Top 10% of customers by net revenue:
Classifier 1: Lifetime Net Revenue
Classifier 2: Percentile · in · 90th Percentile + 95th