RFM Customer Segmentation for D2C — Sheets Template
What Is RFM Analysis?
Here's what RFM stands for, the way I use it:
- Recency — how recently they bought (last week versus 6 months ago)
- Frequency — how often they buy (once versus 5 times)
- Monetary — how much they've spent overall (₹500 total versus ₹15,000 total)
I score every customer on these three dimensions, then group and market to each group differently.
The 6 Customer Segments
| Segment | RFM Profile | % of Customers | Marketing Strategy |
|---|---|---|---|
| Champions | Recent, frequent, high spend | 5-10% | VIP treatment, early access, referral program |
| Loyal Customers | Frequent, good spend | 10-15% | Loyalty rewards, cross-sell, upsell |
| Potential Loyalists | Recent, moderate frequency | 15-20% | Nurture to increase frequency. Second purchase incentive. |
| At-Risk | Used to buy frequently, not recently | 10-15% | Win-back campaign. ‘We miss you’ + discount. |
| Can’t Lose Them | High spend historically, inactive now | 5-10% | Aggressive win-back. Personal outreach from founder. |
| Lost | Long time ago, infrequent, low spend | 30-40% | Low-priority. Occasional re-engagement email only. |
Step-by-Step: RFM in Google Sheets
Step 1: Export Customer Data from Shopify
- I start in Shopify Admin → Customers → Export all customers
- I need four columns: customer email, last order date, total orders, total spent
- I open the file in Google Sheets
Step 2: Score Recency (1-5)
- I sort the sheet by last order date
- I divide the list into 5 equal groups (quintiles)
- I score 5 for the most recent group (ordered in last 30 days)
- I score 1 for the least recent group (ordered 6+ months ago)
Step 3: Score Frequency (1-5)
- I sort by total orders next
- I divide into 5 equal groups again
- I score 5 for the highest frequency (5+ orders)
- I score 1 for the lowest frequency (1 order)
Step 4: Score Monetary (1-5)
- I sort by total spent
- I divide into 5 equal groups
- I score 5 for the highest spend (top 20%)
- I score 1 for the lowest spend (bottom 20%)
Step 5: Combine Scores and Segment
- I concatenate R, F, M scores: a customer with R=5, F=4, M=5 is ‘545’
- I map that to a segment using the table above
- My Champions are scores like 555, 545, 554
- My Lost bucket is scores like 111, 112, 121
What to Do With Each Segment
Champions (5-10% of customers, 25-40% of revenue)
- I get the founder to send a personal thank-you
- I give this group early access to new products, before anyone else
- I add them to an exclusive WhatsApp group for feedback and previews
- I run a referral program with real incentives
- I never send discount offers to champions — they buy at full price
At-Risk Customers (10-15%, declining engagement)
- I run a win-back email sequence: ‘We noticed you haven’t shopped with us recently’
- I offer a 15-20% ‘come back’ discount
- I show them what’s new since their last purchase
- For high-value ones here, I send a WhatsApp from a real person — never automated
Lost Customers (30-40%, long inactive)
- I keep re-engagement low-effort here: a quarterly email with best-sellers
- I don’t spend heavily trying to win this segment back
- I clean them off the active email list after 6 months of no engagement — improves deliverability
Need Help With Customer Segmentation?
At Growww Tech, my team and I run this segmentation and retention playbook for D2C brands. Let’s open up your customer data.
Related reading:
From the founders
Want this applied to your brand?
A 30-minute call — we'll map what works for your store, not a generic playbook. No sales pitch.