Every BFCM email list contains a mix of very different customers. Some are loyal shoppers waiting for early access. Others haven’t purchased in months and may need a reason to return. And some are unlikely to respond, no matter how many reminders you send.

Most merchants still treat them as one audience. They send the same BFCM campaign to a brand-new member, a high-value VIP, and a lapsed customer, then wonder why all that holiday activity fails to produce lasting retention in January.

Here’s what makes that especially frustrating. New loyalty member enrollment increases by 132% over BFCM weekend compared with a typical week, and 81% of shoppers say a loyalty program influences whether they purchase again, according to BON Loyalty data from 2025. That creates a huge retention opportunity, but only if you know what each customer needs next.

This is where an RFM audit becomes useful. RFM looks at three signals: how recently someone purchased, how often they buy, and how much they spend. Add loyalty data such as points balance and VIP tier status, and you get a much clearer picture of who should receive VIP early access, who needs a win-back message, and who should be left out of the campaign altogether.

In this post, I’ll walk you through the three data inputs to collect before scoring your customers, how to turn those numbers into RFM segments you can actually use, and the specific BFCM move I’d recommend for each one.

TL;DR

• New loyalty sign-ups jump 132% during BFCM weekend, and 81% of shoppers say a loyalty program shapes whether they repeat-purchase, which is exactly why this audit needs to happen before the surge, not after (BON Loyalty data, 2025)
• RFM analysis is well covered everywhere, but almost none of it connects to Black Friday/Cyber Monday timing or loyalty program mechanics
• Most “at risk” members aren’t gone, they’re dormant, and the right reward can bring them back if you catch them early
• Layer points balance, tier, and last redemption on top of standard RFM scoring, then use it to find your top 20% VIPs for early BFCM access
• Each RFM segment should map to one specific move: VIP early access, a win-back nudge, an onboarding push, or no send at all
• Run the audit again after BFCM. The wave of new deal-seekers you just acquired needs its own triage before you build a January campaign around them

A quick terminology note: this post calls groups like Champions and At Risk “RFM segments,” not “tiers.” The term “tier” usually refers to VIP levels (Bronze, Silver, Gold, Platinum), so keeping the two terms separate avoids mixing them up.

What is a RFM audit?

RFM stands for recency, frequency, and monetary value. In simple terms, it helps you understand how recently each customer purchased, how often they return, and how much they spend when they do. An RFM audit scores customers across these three areas and groups together people with similar buying behavior.

You can think of it this way: two customers may have spent the same amount with your store, but one purchased last week while the other hasn’t returned in six months. Treating them as equally valuable would miss an important part of the picture. The first may be ready for a VIP offer, while the second needs a reason to re-engage.

For loyalty programs, I’d take the audit one step further by adding signals such as points balance and tier status. These details reveal whether someone is close to a reward, actively progressing through the program, or sitting on unused points. The result is a more useful customer segment and a much better starting point for deciding what to send before BFCM.

Why building RFM segments before BFCM actually matters

BFCM is the one time of year your customer list changes shape overnight. A wave of new, mostly untested shoppers lands on top of the base you already had. But if you treat the whole list the same way, one blanket campaign, one discount code for everyone, and you’ll spend your best budget on people who were never coming back, while your actual best customers get nothing that makes them feel like it.

Picture two customers receiving the same 20% discount. One has purchased five times this year and is close to reaching your highest VIP tier. The other ordered once last BFCM and hasn’t returned since. Sending them the same offer may be easier, but it ignores everything their behavior is telling you.

An RFM audit helps you make those differences useful before the busiest shopping period begins. It shows you which loyal customers have earned VIP early access, which inactive members may respond to a well-timed win-back offer, and which contacts are unlikely to justify another paid send.

BFCM also brings a sudden wave of new loyalty members. Having your segments ready beforehand gives you a framework for handling that growth. Instead of mixing new sign-ups with established customers, you can place them into the right journey as their purchase and loyalty data develops.

And that’s the real value of RFM. The goal isn’t to produce a spreadsheet full of scores. It’s to decide who should receive what, and when, before every brand starts competing for the same inbox.

Most RFM guides explain the scoring process well, but then stop at broad recommendations like “send a win-back email.” They rarely explain when to send it for BFCM or how to use the loyalty metrics you should already be tracking to shape the offer. This guide starts where those explanations usually end.

Gather your data first: what you need before you can score anyone

Before you can build useful RFM segments, you need a clean picture of how each customer has behaved. Let’s start with the three signals at the center of the model:

• Recency: How long it has been since the customer’s last purchase
• Frequency: How many times the customer purchased during your chosen period
• Monetary value: How much the customer spent during that period

You can pull all three directly from your Shopify order history. Together, they tell you who purchased recently, who returns consistently, and who contributes the most revenue.

But if you stop there, you’re only doing a standard RFM analysis. Your loyalty program knows things that order history can’t tell you, such as how many points a member has, which VIP tier they’ve reached, and when they last redeemed a reward.

That extra context can completely change how you interpret a customer. Someone who hasn’t purchased recently but still has 800 unredeemed points may only need a reminder that a reward is within reach. Another customer with the same purchase history and no points balance may need a stronger reason to return.

I’d also include recent email engagement where it’s available. Opens and clicks won’t change the core RFM score, but they can help you judge whether a quiet customer is still paying attention before you send another campaign.

Before scoring anyone, take a little time to clean the data. Match guest orders to existing customer profiles where possible, decide how to handle duplicate accounts, and choose a consistent analysis window. Twelve months is a practical starting point for most stores. If your program is newer, use the full history you have and revisit the scores as more data comes in.

Here’s where to find each group of data:

• Recency, frequency, monetary value: Shopify admin order history
• Points balance, tier status, last redemption date: your loyalty app dashboard
• Email engagement (opens, clicks on recent sends): your email platform

Turn that data into segments you can actually act on

Once your data is clean, the scoring itself is fairly straightforward. The traditional RFM method gives each customer a score from 1 to 5 for recency, frequency, and monetary value. If you divide your list into five equal groups, customers in the top 20% receive a 5, while those in the bottom 20% receive a 1.

Combine those three scores and you get 125 possible customer profiles. That may sound precise, but honestly, it’s far more detail than most teams can use. If every segment needs its own campaign, offer, and timing, the system becomes difficult to manage before it delivers any value.

For a first audit, I’d keep it to six practical groups: Champions, Regulars, Potential Loyalists, New Customers, At Risk or Dormant customers, and Lost customers. That gives you enough separation to make meaningful decisions without creating a spreadsheet nobody wants to open. You can always build a more detailed model once the first version is running.

This is also where loyalty data changes the story. Imagine two customers who both purchased several months ago and received the same RFM score. One has 800 unused points and is close to a reward. The other has no points, no recent redemption, and no email engagement. Their purchase history may look similar, but they shouldn’t receive the same message. The first customer may respond to a simple points reminder, while the second may genuinely be lost.

And you don’t need specialized software to begin. A spreadsheet is usually enough for a smaller customer list. Larger merchants may already have RFM tools inside their email platform or customer data platform. Once your segments are live, it’s also worth comparing them with your loyalty program’s VIP tier thresholds. RFM segments describe current customer behavior, while VIP tiers give members something to work toward. Used together, they tell you both where a customer stands and what might motivate them next.

Mapping each segment to a specific BFCM action

Champions score high on recency, frequency, and monetary value, and show strong points or tier engagement. They’re your top 20% VIPs, the exact group BON’s own 2026 BFCM Loyalty Calendar tells merchants to identify in this audit. Give them VIP early access to the BFCM sale, a day or two before the public launch. BON’s own BFCM playbook recommends exactly this move, to lock in revenue from core fans before competitors’ deals even begin.

At Risk / Dormant customers show low recency but decent historical frequency or monetary value, or carry a meaningful unredeemed points balance. Antavo’s 2026 Global Customer Loyalty Report found this group is usually just dormant, not gone, and that catching them early with the right reward is what brings them back. Send the win-back nudge before BFCM, not after.

New Customers have a recent first order and no frequency history yet. They need an onboarding push, not a discount. Confirm the points they earned, show them what a second purchase unlocks, and use a streak-bonus mechanic to catch them before they drift into the Lost segment.

Lost customers and one-time deal-seekers show no engagement signal at all. Don’t spend BFCM budget chasing them. The Alia BFCM Playbook calls this the churn and burn problem: acquiring a wave of low-LTV deal-seekers can make Black Friday performance look great while doing nothing for long-term retention.

Segment	Signal	BFCM action
Champions	High recency, frequency, monetary, strong points/tier engagement	VIP early access, 1-2 days before public launch
At Risk / Dormant	Low recency, decent history, or a real points balance sitting unused	Win-back nudge before BFCM, not after
New Customers	Recent first order, no frequency history yet	Onboarding push: confirm points, show what’s next
Lost	No frequency, no monetary depth, no engagement signal	Leave alone, don’t spend the budget here

Audit mistakes that quietly wreck your BFCM targeting

• Scoring on order data alone. Ignore points balance, tier, and redemption history and a genuinely dormant-but-recoverable member ends up in the same bucket as someone who’s actually gone.

• Running the audit once and never again. BFCM itself creates a new wave of one-time buyers who need their own triage in December or January, not a repeat of the pre-BFCM segmentation.

• Treating every At Risk customer the same. A former high-spender who’s gone quiet deserves a different offer than someone who only ever bought once at a steep discount.

• Skipping tier thresholds after the acquisition wave. A flood of new, low-engagement sign-ups can quietly dilute what “VIP” means in your program if thresholds aren’t checked afterward, which makes turning a one-time BFCM buyer into a repeat customer that much harder in January.

FAQ

What is RFM analysis?

RFM stands for recency, frequency, and monetary value, a method for scoring customers based on how recently they purchased, how often, and how much they’ve spent, then grouping them into segments like Champions, At Risk, or Lost. It’s a standard customer segmentation framework used well beyond loyalty programs.

How is RFM analysis different for a loyalty program versus a general ecommerce store?

A loyalty program gives you extra signals that standard RFM doesn’t have access to: current points balance, tier status, and last redemption date. Those signals help distinguish a genuinely dormant-but-recoverable customer from one who’s actually gone, which order history alone can’t tell you.

When should I run an RFM audit before BFCM?

Run it early enough to act on it, at least three to four weeks before your BFCM campaigns launch. That gives you time to build a win-back sequence for At Risk customers and set up VIP early access for Champions before the sale starts.

Do I need special software to do RFM analysis?

No. A spreadsheet with an order export is enough for a first pass on smaller lists.

Should I run the audit again after BFCM?

Yes. BFCM brings in a wave of new, mostly untested customers, and re-running the segmentation in December or January tells you who’s worth nurturing into a repeat customer versus who was a one-time deal-seeker.

The audit is the budget decision

An RFM audit isn’t a box to check before BFCM. It’s the difference between spending your BFCM budget on VIP treatment for people who’ll actually respond to it, win-back nudges for people who are dormant but recoverable, and nothing at all on people who were never going to stick around. The segments themselves are well documented. What’s missing from most guides is what to actually do with each one during the one season where your customer file changes shape the fastest.

P.S. BON surfaces points balance, tier status, and redemption history right alongside your order data, so this audit doesn’t require stitching together two separate systems. BON’s VIP early-access and streak-bonus mechanics are ready to route each segment into the moment you’re done.