Overview

The Customers section includes powerful filtering tools that let you narrow down your customer list by a wide range of parameters. You can build custom filters, combine them with AND/OR conditions, and use pre-built filter groups to quickly identify key customer segments.

How to use filters

Navigate to Customers in the left-hand menu.
Click the Filters option to open the filter panel.
Select a parameter and configure the filter condition.

Available filter parameters

Card balance
Device type
Card serial number
Card status
UTM tag
Current number of uses
Registration date
Email
Gender
Name
Phone
Unused rewards
Number of stamps
Customer birthday

Filter conditions

Each filter supports different condition types depending on the parameter:

Comparison to a specific value — Equal, not equal, greater than, less than, etc.
Range of values — For example, a date range from one date to another
Array of values — Equal to one from a list of options

For example, the "Card balance" filter lets you find customers whose balance is greater than, less than, or equal to a specific number.

Combining filters

Filters can be combined using AND or OR conditions. This lets you build precise queries — for example, "Card status is Installed AND Device type is Apple Wallet AND Registration date is within the last 30 days."

Filter groups

Filter groups are ready-to-use presets that apply one or more filters automatically. Each filter within a group can be applied individually or combined.

RFM segments

RFM analysis segments your customers based on two variables: how recently they visited and how frequently they visit. This helps you identify your most valuable customers and those at risk of churning.

0 to 30 days since last visit:

0–3 visits: Beginners
4–7 visits: Growths
8–12 visits: Champions

31 to 60 days since last visit:

0–3 visits: Doubtful
4–7 visits: Medium (borderline)
8–12 visits: Loyal — Regular

61 to 90 days since last visit:

0–3 visits: Sleeping
4–7 visits: At risk
8–12 visits: Needs attention

Health

The Health group helps you identify customers with missing data or incomplete profiles:

Card status not installed
Unknown gender
Empty birthday

Use this group to clean up your customer data and follow up with customers who haven't completed their card installation.

Loyalty

The Loyalty group filters customers by card installation status and device type:

Card status installed
Apple Wallet
Wallet Passes
Google Pay
PWA

Use this group to understand how your customers are accessing their loyalty cards and which platforms are most popular.

FAQs

Can I combine filters from different groups?

Yes. You can apply filters from different groups and combine them with AND/OR conditions to create precise queries.

What's the difference between a filter and a filter group?

A filter is a single parameter with a condition (e.g., "Card balance greater than 50"). A filter group is a pre-built set of filters designed for common use cases like RFM analysis, data health, or loyalty tracking.

How do RFM segments help my business?

RFM segments automatically categorize your customers by visit recency and frequency. This helps you identify your best customers (Champions), those who need re-engagement (At risk, Sleeping), and new customers who are just getting started (Beginners). You can then target each segment with tailored push notifications or campaigns.