recency, frequency, monetary (rfm) analysis in magento bi

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Recency, Frequency, Monetary (RFM) Analysis in Magento BIPresented by Salvatore Calvo and Kerri NunnamakerMarch 22, 2017


What's RFM analysis?

• A new industry standard for identifying your top customers, and who you can expect to become top customers

• A way to benchmark your business's success in retaining customers and revenue

• A technique you can use with the commerce data you already own


A walkthrough of the three cornerstones: • Customer recency habits• Buyer frequency behaviors• Monetary (LTV) analysis

A case study on how to score customers based on RFM activity, and predict LTV growth in Magento Business Intelligence

Today's Agenda...


A brief history – where did RFM come from?

• Origins in the brick-and-mortar retail industry, where customers couldn't be identified with certainty

• Based on assumption that a valuable customer had a combo of recent, frequent, and expensive purchases

• Effective jumping off point for developing a marketing strategy

• Incredibly powerful in the ecommerce age with your data


Step 1: Understanding customer recency

Recency implies that a client who has recently interacted with your business, all else equal, is more valuable than one you hasn't. • What % of your customer base

has made a purchase in the last 60 days?

• How many of your recent purchasers are 1st-time buyers, vs. Repeat buyers?

• What are popular products or trends in recent purchases?


Recency in Magento BI


Step 2: Understanding buyer frequency

Frequency assumes that a repeat buyer is inherently more valuable than a new buyer.• What is your business's cost of

acquisition (in $)?• What is your business's churn

rate? Its retention rate? • How long does the average

buyer wait before returning?

Actions to accelerate customer frequency...


Frequency in Magento BI


Step 3: Drilling into monetary activity

Monetary = the assumption that valuable customers will continue to be valuable. • What's your current average

lifetime LTV? • How does average LTV grow?

First 30 days, 90 days? • Are there segments of

customers (demo, products bought, location) with different LTV profiles?


Monetary in Magento BI


The road so far...

RFM1. Recency2. Frequency3. Monetary

Extensions1. Assigning RFM scores to create unique customer groups2. Use cases for assigning scores


How to assign individual scores

Let's consider monetary score.

Out of all customers, assign the top 20% of customers who have spent the most revenue a score of 5.

Assign the next top 20% of customers who have spent the most a score of 4.

And so on...


How to assign RFM scores

Concatenate the scores for all 3 attributes

Customer A:• Recency: 5• Frequency: 1• Monetary: 1

Customer B:• Recency: 1• Frequency: 4• Monetary: 5

Overall score: 511 Overall score: 145

New Customer Churned Customer


What are the use cases?

1. Targeted email lists

2. Identifying actions within certain customer groups that may be causing this behavior

3. A/B testing within groups


Targeting email lists

Customer A:• Recency: 5• Frequency: 1• Monetary: 1

Overall score: 511

Customer B:• Recency: 1• Frequency: 4• Monetary: 5

Overall score: 145

New Customer Churned Customer


Targeting email lists

New Customers

Churned Customers


Investigating customer groups

1. Are there any common trends for how these customers were acquired?– Season of year– Sale– Promotional campaign

2. Are there any common products these customers purchased?

3. Are there any common events these customers participated in?– Sales– Product reviews– Surveys– Support requests

Consider the best customer group, RFM scores of 555.


A/B testing within groups

A/B testing within groups which have similar behaviors allows better conclusions on whether the action you're testing worked.

Consider the "shopper" group, RFM scores such as 342 or 452.

Can you get these shoppers to engage without providing a large discount? Do they engage just the fact that there is a discount available?

• Test an email campaign– Test A: 10% coupon code– Test B: 5% coupon code


To sum it all up

• Defining RFM• How you can create RFM analyses in your account today• Assigning RFM scores• Using scores and customer groups to create targeted email lists,

identify common behaviors within groups, and perform A/B testing

Reach out to [email protected] today!

mailto:[email protected]


Questions

recency, frequency, monetary (rfm) analysis in magento bi

Data & Analytics