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Understanding RFMT Score
RFMT scoring is like giving each customer a report card that tells you exactly how engaged they are with your brand—and more importantly, who's about to ghost you.
Think of it as a relationship status indicator. Just like you can tell when a friend is drifting away (they text less, skip hangouts, seem less invested), RFMT spots these patterns in your customer data.
The model looks at four key 'vital signs' of customer health:
Recency: How fresh is the relationship? A customer who bought yesterday is more engaged than one who purchased 6 months ago.
Frequency: Are they a regular or a one-hit wonder? Someone who buys monthly is more valuable than a once-a-year shopper.
Monetary: How much have they invested? Big spenders often indicate strong brand affinity.
Tenure: How long have they been around? Long-term customers have proven loyalty.
By scoring each factor and adding them up, you get a single number that instantly tells you who needs attention. Low scores = red alert. High scores = your brand champions.
How RFMT Scoring Works
RFMT Score = R + F + M + T
Where each component is scored 1-5 based on quintiles:
Recency (R): Days since last purchase
• Top 20% of recent buyers = 5 points
• Bottom 20% = 1 point
Frequency (F): Number of purchases in last year
• Top 20% most frequent = 5 points
• Bottom 20% = 1 point
Monetary (M): Total lifetime spend
• Top 20% highest spenders = 5 points
• Bottom 20% = 1 point
Tenure (T): Days since first purchase
• Top 20% longest relationships = 5 points
• Bottom 20% = 1 point
Data sources: Shopify order history, Customer profiles
Total Score Range: 4-20
• 16-20: Champions
• 11-15: Loyal Customers
• 6-10: At Risk
• 4-5: High Churn Risk
Example
Imagine you run a sustainable fashion brand. Your RFMT scoring reveals three distinct customer groups:
High Scorers (7-10): Sarah last purchased 15 days ago (high recency), buys every season (high frequency), has spent $1,200 lifetime (high monetary), and has been a customer for 2 years (high tenure). She's your VIP—loyal and engaged.
Mid Scorers (4-6): Jake bought 60 days ago, made 3 purchases last year, spent $400 total, customer for 8 months. He's engaged but needs nurturing to move up.
Low Scorers (1-3): Emma hasn't purchased in 180 days, only bought once, spent $75, been a customer for 7 months. She's at high risk of churning.
You create three automated campaigns: VIPs get early access to new collections, mid-tier gets personalized style recommendations, and at-risk customers receive a 'we miss you' campaign with their favorited items. Result? 40% of at-risk customers reactivate, saving $85K in potentially lost revenue.
Takeaway
RFMT scoring is like a health checkup for your customer relationships. Just as doctors check vital signs (blood pressure, heart rate, temperature) to assess overall health, RFMT checks the vital signs of customer engagement.
The beauty of RFMT is its simplicity and effectiveness. While fancy AI models have their place, sometimes you need a quick, reliable way to spot who needs attention RIGHT NOW. RFMT gives you that.
It's particularly powerful because it balances multiple factors. A customer might have purchased recently (good!) but only bought once with a low value (concerning!). RFMT catches these nuances that single metrics miss.
Bottom line: RFMT scoring turns your customer list from a confusing spreadsheet into a prioritized action plan. You'll know exactly who to reward, who to re-engage, and who needs immediate attention to prevent churn.
Ready to level up your learning?
Read more about RFMT Score
Implementing RFMT scoring for your brand
Start with basic segmentation
Break your customers into four core groups based on RFMT scores:
- Champions (16-20): Your best customers. Reward them with VIP perks, early access, and exclusive offers.
- Loyal Customers (11-15): Engaged but could spend more. Focus on upselling and cross-selling.
- At Risk (6-10): Showing warning signs. Time for re-engagement campaigns and personalized outreach.
- Lost Causes (4-5): Nearly churned. Try aggressive win-back offers, but don't overspend.
Automate your workflows
Set up triggered campaigns based on score changes:
- Score drops by 3+ points → Trigger 'Is everything OK?' check-in email
- Score increases to 16+ → Send VIP welcome package
- Score stays at 6-10 for 30 days → Launch personalized win-back series
Tools like Tydo can calculate RFMT scores automatically and sync them to your email platform for instant action.
Advanced RFMT strategies
Weight scores by business model
Not all RFMT factors are equal for every business:
- Consumables (supplements, beauty): Weight Recency and Frequency higher—you need regular repurchases
- High-ticket items (furniture, electronics): Weight Monetary and Tenure higher—purchase frequency naturally lower
- Fashion/Seasonal: Balance all four equally—all factors matter
Combine with predictive analytics
RFMT is powerful alone but unstoppable when combined with AI:
- Use RFMT to identify at-risk segments
- Apply predictive analytics to understand WHY they're at risk
- Create hyper-targeted campaigns addressing specific issues
Track score migration
Monitor how customers move between score brackets:
- Upward movement: What campaigns or actions caused improvement?
- Downward movement: What triggered the decline?
- Stable scores: Are these customers actually stable or slowly declining?
Use these insights to refine your retention strategies and prevent future churn.
