Overview
Customer filters allow you to segment your customer base using specific criteria. Find customers who meet certain conditions, create targeted marketing campaigns, and analyse customer behaviour patterns. Combine multiple filters to create precise customer segments for personalised communication.
Key benefits:
Target specific customer groups with relevant offers
Identify at-risk customers who need re-engagement
Find your most valuable customers for VIP treatment
Analyze customer behavior patterns
Clean your database by finding incomplete profiles
Accessing Customer Filters
Navigate to the left-hand menu, click the Customers icon, and select the My Filters tab at the top of the screen.
Available Filter Parameters
Customer Information Filters
Name - Filter by customer's first or last name. Use Equal to / Not equal to specific name, or Contains specific text to find specific customers or name patterns.
Email - Filter by email address. Use Equal to / Not equal to specific email, or Contains specific domain (e.g., @gmail.com) to find customers from specific email providers.
Phone - Filter by phone number. Use Equal to / Not equal to specific number, or Contains specific digits or area code to identify customers by region or phone pattern.
Gender - Filter by customer gender (Male / Female / Other / Unknown). Target gender-specific promotions or identify profiles with missing gender data.
Customer birthday - Filter by birth date or birth month. Use specific date range, birth month (e.g., all January birthdays), or age ranges to create birthday campaigns or age-targeted offers.
Registration date - Filter by when customer profiles were created. Use date range (from date to date) or specific period (e.g., last 30 days) to find new vs. long-time customers and analyze acquisition trends.
Card-Related Filters
Card balance - Filter by points, stamps, or monetary balance on customer cards. Use Equal to / Not equal to, Greater than / Less than, or Range of values (e.g., 50-100 points) to find customers close to rewards or with high balances.
Card serial number - Filter by specific card identifier using Equal to specific serial number. Useful for tracking specific card batches or issues.
Card status - Filter by card installation status (Installed: active cards on devices; Not installed: issued but not activated; Deleted: removed from devices). Identify customers who need installation assistance.
Current number of uses - Filter by how many times cards have been used. Use Equal to / Greater than / Less than, or Range of values to find frequent users or inactive cardholders.
Number of stamps - Filter by stamp count on stamp cards. Use Equal to / Greater than / Less than, or Range of values to identify customers close to rewards.
Unused rewards - Filter by available rewards customers haven't redeemed. Use Has unused rewards or Number of unused rewards to encourage redemption with targeted reminders.
Technical Filters
Device type - Filter by platform customers use (iOS (iPhone/iPad), Android, Unknown). Send platform-specific instructions or offers.
UTM tag - Filter by acquisition source or campaign. Use Equal to specific UTM tag or Multiple UTM tags to analyze which marketing channels work best and target customers from specific campaigns.
Filter Operators and Logic
Comparison Operators
Equal to - Exact match to specified value (Example: Card balance equal to 100).
Not equal to - Any value except the specified one (Example: Gender not equal to Unknown).
Greater than / Less than - Numerical comparisons (Example: Card balance greater than 50; Number of uses less than 3).
Range of values - Between two values (inclusive) (Example: Registration date from 2024-01-01 to 2024-12-31; Card balance from 50 to 100).
Contains - Text contains specified string (Example: Email contains "@gmail.com"; Name contains "Smith").
Array of values - Equal to one from a list (Example: UTM tag equals one of: facebook, instagram, twitter).
Combining Filters
AND condition - Customers must meet ALL specified criteria.
Example: Card balance > 100 AND Device type = iOS. Result: iOS users with more than 100 points.
OR condition - Customers meet ANY of the specified criteria.
Example: Card balance > 100 OR Number of uses > 10. Result: Customers with high balance or high usage.
Complex combinations - Mix AND/OR conditions for precise targeting.
Example: (Card balance > 50 AND Device = iOS) OR (Card balance > 100 AND Device = Android).
Pre-Built Filter Groups
Info: Filter groups are ready-to-use presets that combine multiple filters for common use cases. Apply entire groups with one click or use individual filters from the group.
RFM Segments
RFM (Recency, Frequency, Monetary) analysis segments customers based on visit timing and frequency. The system automatically categorizes customers into segments based on their behavior.
How RFM works:
Recency: How recently customers visited (days since last visit)
Frequency: How often customers visit (number of visits)
Segments: Automatic classification based on these metrics
RFM segment definitions:
Last visit: 0-30 days (Recent customers)
0-3 visits: RFM - Beginners - New customers just starting their journey. Need nurturing and welcome engagement.
4-7 visits: RFM - Growths - Developing loyalty, showing consistent interest. Ready for rewards and incentives.
8-12 visits: RFM - Champions - Your best active customers. High value, frequent visitors.
Last visit: 31-60 days (Moderately recent)
0-3 visits: RFM - Doubtful - Limited engagement, risk of leaving. Need re-engagement campaigns.
4-7 visits: RFM - Medium (Borderline) - Previously engaged, now slowing down. Target with special offers to retain.
8-12 visits: RFM - Loyal - Regular - Strong history but recent pause. Remind them of your value.
Last visit: 61-90 days (At risk)
0-3 visits: RFM - Sleeping - Minimal engagement, likely inactive. Win-back campaigns needed.
4-7 visits: RFM - At Risk - Good history but fading away. Urgent re-engagement required.
8-12 visits: RFM - Needs Attention - Valuable customers becoming inactive. Priority retention efforts.
Using RFM segments:
Target Champions with VIP rewards
Re-engage At Risk customers with special offers
Welcome Beginners with onboarding campaigns
Win back Sleeping customers with incentives
Health Group
The Health group identifies customers with incomplete data or inactive cards. Use these filters to clean your database and improve data quality.
Available Health filters:
Card status not installed - Customers issued cards but haven't activated them. Send installation reminders and provide setup assistance.
Unknown gender - Customers with missing gender information. Request profile completion and update records for better targeting.
Empty birthday - Customers without birth dates recorded. Collect birthday data for campaigns and improve personalization opportunities.
Using Health filters:
Identify incomplete profiles
Send data completion requests
Improve targeting accuracy
Clean your customer database
Loyalty Group
The Loyalty group identifies active, engaged customers based on card installation and platform usage.
Available Loyalty filters:
Card status installed - Active customers with cards on their devices. Your engaged customer base and prime targets for promotions.
Apple Wallet - Customers using iOS/Apple Wallet. Send iOS-specific communications and optimize for Apple platform features.
Wallet Passes - Customers using generic wallet apps. Platform-agnostic card holders.
Google Pay - Customers using Android/Google Wallet. Send Android-specific communications and optimize for Google platform features.
PWA (Progressive Web App) - Customers using home screen installation. Web-based card access.
Using Loyalty filters:
Target active users with new offers
Send platform-specific instructions
Reward engaged customers
Analyze platform preferences
Creating Custom Filters
Step-by-Step Filter Creation
Step 1: Choose your parameter
Select the customer attribute you want to filter by (balance, device, date, etc.).
Step 2: Select operator
Choose how to compare (equal to, greater than, contains, etc.).
Step 3: Enter value
Specify the comparison value, range, or list.
Step 4: Add more filters (optional)
Combine multiple filters with AND/OR logic.
Step 5: Save filter
Save your custom filter for future use.
Filter Examples
High-value customers:
Card balance > 100
Number of uses > 10
Card status = Installed
Re-engagement campaign:
Last visit 60-90 days ago
Number of uses > 5
Unused rewards > 0
Birthday campaign:
Birthday month = Current month
Card status = Installed
Installation follow-up:
Card status = Not installed
Registration date = Last 7 days
Platform-specific:
Device type = iOS
Card balance > 50
Using Filters Effectively
Marketing Campaigns
Targeted promotions:
Create customer segments and send relevant offers including VIP rewards for Champions, win-back offers for At Risk customers, and welcome bonuses for Beginners.
Timing campaigns:
Use date and recency filters for birthday specials, anniversary rewards, and re-engagement after 60 days.
Platform optimization:
Send platform-appropriate content such as iOS users receiving Apple Wallet features and Android users receiving Google Pay benefits.
Database Maintenance
Data quality:
Find incomplete profiles using the Health group, request missing information, and update customer records.
Inactive customers:
Identify not-installed cards, send installation reminders, and clean up old records.
Engagement analysis:
Compare RFM segments over time, track customer lifecycle stages, and measure retention effectiveness.
Best Practices
Tip: Start simple by beginning with pre-built groups before creating complex custom filters. Always test filters by reviewing filtered results before sending campaigns to ensure accuracy.
Document filters: Name custom filters clearly and note their purpose.
Regular review: Update filters as your business needs change.
Combine strategically: Use AND/OR logic thoughtfully to avoid overly narrow segments.
Frequently Asked Questions
How many filters can I combine?
You can combine multiple filters. The system supports complex filter combinations with AND/OR logic.
Can I save custom filters?
Yes, save frequently used filter combinations for quick access in future campaigns.
Do filters update in real-time?
Yes, filters reflect current customer data when applied.
Can I export filtered customer lists?
Yes, apply filters then use the export function to download the filtered list.
What's the difference between RFM segments and custom filters?
RFM segments are automatic classifications based on visit patterns. Custom filters let you create any criteria combination.
How often are RFM segments updated?
RFM segments update automatically based on current customer visit data.
Can I edit pre-built filter groups?
Pre-built groups are fixed, but you can use them as templates and modify individual filters to create custom versions.
What happens if no customers match my filters?
The system returns an empty result. Try adjusting filter criteria to broaden the search.
Can I see how many customers match before applying?
Yes, the system typically shows the count of matching customers when you create or apply filters.
Should I use AND or OR for multiple filters?
Use AND when customers must meet all criteria (narrower results). Use OR when customers can meet any criteria (broader results).