RFM Analysis and Customer Segmentation
Overview
RFM (Recency, Frequency, Monetary Value) analysis automatically segments your customers based on their purchase behavior. This powerful tool helps you identify your best customers, those at risk of leaving, and everyone in between—enabling targeted marketing that maximizes your budget and drives customer retention.
What RFM analysis does:
Automatically categorizes customers into behavioral segments
Identifies your most valuable customers (Champions)
Flags customers at risk of leaving (At Risk, Sleeping)
Helps target marketing campaigns effectively
Adapts to your specific business patterns
Updates in real-time as customer behavior changes
Understanding RFM methodology
The three factors
RFM analysis scores customers based on three key behaviors:
Recency (R) How recently did the customer make their last purchase or visit?
Why it matters: Recent customers have your brand fresh in mind and are more likely to purchase again
Measurement: Days since last visit/purchase
Example: A customer who visited yesterday is more engaged than one who visited 60 days ago
Frequency (F) How often does the customer make purchases or visits?
Why it matters: Frequent customers demonstrate loyalty and are more likely to continue
Measurement: Number of visits/purchases within a timeframe
Example: A customer with 10 visits shows stronger loyalty than one with 2 visits
Monetary Value (M) How much does the customer spend?
Why it matters: Reveals spending patterns and customer value
Measurement: Total amount spent within a period
Note: In this system, Monetary value is reflected through visit frequency and tier status
How scoring works
Most businesses use a scale of 1-5 for each factor, though you can customize this:
High scores (4-5): Recent visits, frequent purchases, high spending
Medium scores (2-3): Moderate activity
Low scores (1): Infrequent visits, long time since last purchase
Combined scores create segments: A customer with high Recency (5) + high Frequency (5) = Champion A customer with low Recency (1) + low Frequency (1) = Sleeping
Automatic RFM segmentation
Default segment structure
The system automatically segments customers based on Recency (days since last visit) and Frequency (number of visits):
0-30 days (Recent customers)
1-3 visits: RFM - Beginners
New to your business
Just starting their customer journey
Need nurturing and encouragement
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 engagement and frequent visits
Deserve VIP treatment
31-60 days (Moderately recent)
1-3 visits: RFM - Doubtful
Limited engagement, at risk
Need re-engagement campaigns
May not return without intervention
4-7 visits: RFM - Medium (Borderline)
Previously engaged, now slowing
Target with special offers
Risk of dropping to lower segments
8-12 visits: RFM - Loyal - Regular
Strong history but recent pause
Remind them of your value
Encourage return visits
61-90 days (At risk)
1-3 visits: RFM - Sleeping
Minimal engagement, likely inactive
Need strong win-back campaigns
May require incentives to return
4-7 visits: RFM - At Risk
Good history but fading away
Urgent re-engagement required
High priority for retention efforts
8-12 visits: RFM - Needs Attention
Valuable customers becoming inactive
Priority retention efforts needed
Don't let them slip away
Segment movement patterns
Horizontal movement (through time): Customers move horizontally through segments as time passes without visits:
Champions → Loyal-Regular → Needs Attention
Growths → Medium (Borderline) → At Risk
Beginners → Doubtful → Sleeping
Example progression: Day 1: Customer visits → Beginners (0-30 days, 1-3 visits) Day 35 (no new visit): → Doubtful (31-60 days, 1-3 visits) Day 70 (no new visit): → Sleeping (61-90 days, 1-3 visits)
Vertical movement (through engagement): Customers move vertically when they increase visit frequency:
Beginners → Growths → Champions (within 0-30 day window)
Doubtful → Medium → Loyal-Regular (within 31-60 day window)
Example progression: Visit 1: Beginners (0-30 days, 1-3 visits) Visit 4 (within 30 days): Growths (0-30 days, 4-7 visits) Visit 8 (within 30 days): Champions (0-30 days, 8-12 visits)
Customizing RFM segments
Why customize?
Different business types have different customer behavior patterns:
Cafes: Customers may visit daily
Salons: Customers visit every 4-6 weeks
Car dealerships: Customers buy once every few years
Default settings may not fit your business. Customization ensures accurate segmentation.
What you can customize
Recency intervals: Define time periods that match your business cycle:
Retail: 0-10, 11-20, 21-30 days
Salons: 0-15, 16-30, 31-45 days
Professional services: 0-25, 26-50, 51-75 days
Frequency ranges: Set visit counts appropriate for your industry:
Cafes: 8-12 (high), 4-7 (medium), 1-3 (low)
Healthcare: 4-6 (high), 2-3 (medium), 1 (low)
Hotels: 5-7 (high), 3-4 (medium), 1-2 (low)
How to customize RFM settings
Step 1: Access RFM settings
Navigate to: https://app.perkstar.co.uk/settings/rfm-segments
Or: Go to Settings → RFM tab
Step 2: Adjust recency periods
Set high activity range (e.g., 0-15 days)
Set medium activity range (e.g., 16-30 days)
Set low activity range (e.g., 31-45 days)
Step 3: Adjust frequency ranges
Set high frequency range (e.g., 8-12 visits)
Set medium frequency range (e.g., 4-7 visits)
Set low frequency range (e.g., 1-3 visits)
Step 4: Save changes
Changes take effect immediately
All customers are automatically recalculated
Customers receive push notifications about segment changes (if enabled)
Important: When you change RFM settings, customer segments recalculate immediately. Customers may move to different segments based on new criteria.
Industry-specific RFM examples
Food and Beverage (Cafes, Restaurants)
Recency:
High: 0-10 days
Medium: 11-20 days
Low: 21-30 days
Frequency:
High: 8-12 visits
Medium: 4-7 visits
Low: 1-3 visits
Why these settings: Customers visit frequently, often daily or weekly. Short recency periods capture rapid behavior changes.
Health and Wellness (Salons, Gyms, Spas)
Recency:
High: 0-15 days
Medium: 16-30 days
Low: 31-45 days
Frequency:
High: 6-9 visits
Medium: 3-5 visits
Low: 1-2 visits
Why these settings: Service appointments are typically monthly. Longer recency periods account for natural service cycles.
Medicine (Clinics, Pharmacies)
Recency:
High: 0-20 days
Medium: 21-40 days
Low: 41-60 days
Frequency:
High: 4-6 visits
Medium: 2-3 visits
Low: 1 visit
Why these settings: Healthcare visits are less frequent. Lower frequency ranges reflect medical visit patterns.
Professional Services (Lawyers, Consultants)
Recency:
High: 0-25 days
Medium: 26-50 days
Low: 51-75 days
Frequency:
High: 3-5 visits
Medium: 2 visits
Low: 1 visit
Why these settings: Services are project-based with longer cycles. Extended recency periods accommodate business engagement patterns.
Retail (Stores, E-commerce)
Recency:
High: 0-10 days
Medium: 11-20 days
Low: 21-30 days
Frequency:
High: 10-15 visits
Medium: 5-9 visits
Low: 1-4 visits
Why these settings: Shopping can be frequent. Higher frequency ranges capture active retail customers.
Hospitality (Hotels, Tourism)
Recency:
High: 0-20 days
Medium: 21-40 days
Low: 41-60 days
Frequency:
High: 5-7 visits
Medium: 3-4 visits
Low: 1-2 visits
Why these settings: Travel is periodic. Moderate ranges account for seasonal and vacation patterns.
Customer journey examples
Example 1: New customer journey
Timeline:
Day 1: Customer installs card and makes first visit
Segment: Beginners (Recency: 0-30 days, Frequency: 1-3 visits)
Day 35 (no additional visits):
Segment: Doubtful (Recency: 31-60 days, Frequency: 1-3 visits)
Moves horizontally due to time passing
Day 70 (still no visits):
Segment: Sleeping (Recency: 61-90 days, Frequency: 1-3 visits)
Customer is now inactive, needs win-back campaign
Action: Send re-engagement offer before customer reaches Sleeping segment.
Example 2: Growing engagement
Timeline:
Visit 1: Customer installs card
Segment: Beginners (Recency: 0-30 days, Frequency: 1-3 visits)
Visit 4 (within 15 days):
Segment: Growths (Recency: 0-30 days, Frequency: 4-7 visits)
Moves vertically due to increased frequency
Customer receives push notification (if enabled)
Visit 8 (within 30 days):
Segment: Champions (Recency: 0-30 days, Frequency: 8-12 visits)
Customer is now highly engaged
Action: Reward Champions with VIP perks and exclusive offers.
Example 3: Declining engagement
Timeline:
Current status: Champions (Recency: 0-30 days, Frequency: 8-12 visits)
Customer was visiting frequently
35 days without visit:
Segment: Loyal-Regular (Recency: 31-60 days, Frequency: 8-12 visits)
Horizontal movement due to time
70 days without visit:
Segment: Needs Attention (Recency: 61-90 days, Frequency: 8-12 visits)
Valuable customer at risk
Action: Priority outreach to prevent loss of valuable customer.
Example 4: RFM settings change
Scenario: You change RFM settings to better match your business:
Old: Recency 0-30 days
New: Recency 0-15 days
What happens:
All customers immediately recalculated
Customer with last visit 20 days ago moves from "Recent" to "Medium recency"
Segment reassignments happen automatically
Customers receive push notifications about new status (if enabled)
Using RFM segments for marketing
Segment-specific strategies
Champions (0-30 days, 8-12 visits)
Action: Reward and retain
Tactics: VIP perks, early access, referral programs
Message: "You're our VIP! Here's an exclusive reward..."
Growths (0-30 days, 4-7 visits)
Action: Encourage progression to Champions
Tactics: Milestone rewards, progress tracking
Message: "You're just 2 visits away from VIP status!"
Beginners (0-30 days, 1-3 visits)
Action: Welcome and nurture
Tactics: Welcome offers, education, onboarding
Message: "Welcome! Here's 20% off your next visit..."
Loyal-Regular (31-60 days, 8-12 visits)
Action: Re-engage before they drift further
Tactics: "We miss you" campaigns, special offers
Message: "It's been a while! Come back for..."
Medium/Borderline (31-60 days, 4-7 visits)
Action: Prevent further decline
Tactics: Incentives, reminders of benefits
Message: "Special offer just for you! Return within 7 days for..."
Doubtful (31-60 days, 1-3 visits)
Action: Strong re-engagement
Tactics: Significant discounts, surveys to understand why
Message: "We want you back! Here's 30% off..."
Needs Attention (61-90 days, 8-12 visits)
Action: Priority retention effort
Tactics: Personal outreach, exclusive win-back offers
Message: "You're valued! Let's reconnect with this special offer..."
At Risk (61-90 days, 4-7 visits)
Action: Urgent win-back campaign
Tactics: Strong incentives, ask for feedback
Message: "We haven't seen you! Here's 40% off to come back..."
Sleeping (61-90 days, 1-3 visits)
Action: Last-chance win-back or let go
Tactics: Maximum discount, survey, or accept churn
Message: "One last offer: 50% off if you return this month..."
Campaign timing
Regular communication:
Champions: Weekly updates, exclusive offers
Growths: Bi-weekly encouragement
Beginners: Follow-up after first visit
Intervention points:
Day 25 for Beginners → Send offer before moving to Doubtful
Day 55 for Champions → Urgent outreach before Needs Attention
Day 85 for At Risk → Final win-back before considering lost
Important notes
Lifetime visits don't affect segments
Key point: Total visits over the customer's entire lifetime do NOT affect RFM segments.
Why? RFM focuses on recent behavior, not historical totals:
Customer with 100 total visits but none in 70 days = Needs Attention
Customer with 10 total visits but 8 in last month = Champions
What matters:
Visits within the recent time windows (0-30, 31-60, 61-90 days)
Not cumulative visits since card installation
Real-time updates
Automatic recalculation:
Segments update automatically as customer behavior changes
No manual refresh needed
Changes happen immediately after visits or time passing
Push notifications:
Customers can receive notifications when moving to new segments
Configure in push notification settings
Use strategically (congratulate Champions, re-engage Sleeping customers)
Best practices
Setting up RFM for your business
Analyze your business cycle:
How often do customers typically visit?
What's a normal gap between visits?
When does a customer become "inactive"?
Start with industry standards:
Use examples above as starting points
Adjust based on your specific business
Monitor and refine:
Review segment distributions after 2-4 weeks
Adjust if too many customers in one segment
Ensure spread across segments
Using segments effectively
Segment-based campaigns:
Create different messages for each segment
Target by segment in bulk communications
Use filters to isolate specific segments
Monitor segment flow:
Track how customers move between segments
Identify problem patterns (too many moving to Sleeping)
Celebrate successes (Beginners → Champions)
Combine with other data:
Use RFM with UTM tags for acquisition analysis
Combine with custom fields for deeper insights
Layer with product preferences
Frequently asked questions
How often do RFM segments update? Segments update in real-time. When a customer makes a visit or time passes, their segment changes immediately.
Can I create custom segment names? No, segment names are predefined. However, you can customize the recency and frequency values that determine segment assignment.
What if my business doesn't fit the 0-90 day window? Customize the recency periods to match your business cycle. Set longer or shorter time windows based on your industry.
Will changing RFM settings affect my existing data? No, historical visit data remains intact. Only segment classifications recalculate based on new criteria.
How do I know if my RFM settings are working? Monitor segment distribution. You should see customers spread across multiple segments, not clustered in just one or two.
Can customers see their RFM segment? No, RFM segments are internal for your marketing use. Customers don't see their segment classification.
Should I notify customers when they move to a new segment? Selectively. Congratulate Champions, encourage Growths, but don't highlight negative segments like Sleeping.
What's more important: Recency or Frequency? Both matter. Recency shows current engagement, Frequency shows loyalty. Together, they paint a complete picture.
Can I export customers by RFM segment? Yes, use customer filters to select specific RFM segments, then export that filtered list.
How many customers should be Champions? Typically 10-20% of your active customer base. If much higher or lower, adjust your frequency ranges.