Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Recency, Frequency, Monetary (RFM) Analysis in Magento BI

819 views

Published on

Thought leaders in the commerce industry, across all channels, are emphasizing the importance of RFM analysis for identifying your business's best customers. What can RFM can do for you?

Magento BI analysts Sal Calvo and Kerri Nunnamaker will spend time on March 22 walking through each valuable component of recency, frequency, and monetary analysis. What you’ll learn:

• Exactly how valuable a recently acquired customer is in the long run
• How to use seasonality trends to predict repeat purchasing frequency
• How our Professional Services team can identify and rank the most valuable customers in your dataset

Published in: Data & Analytics
  • Be the first to comment

  • Be the first to like this

Recency, Frequency, Monetary (RFM) Analysis in Magento BI

  1. 1. © 2016 Magento, Inc. Page | 1 Recency, Frequency, Monetary (RFM) Analysis in Magento BI Presented by Salvatore Calvo and Kerri Nunnamaker March 22, 2017
  2. 2. © 2016 Magento, Inc. Page | 2 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
  3. 3. © 2016 Magento, Inc. Page | 3 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...
  4. 4. © 2016 Magento, Inc. Page | 4 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
  5. 5. © 2016 Magento, Inc. Page | 5 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?
  6. 6. © 2016 Magento, Inc. Page | 6 Recency in Magento BI
  7. 7. © 2016 Magento, Inc. Page | 7 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...
  8. 8. © 2016 Magento, Inc. Page | 8 Frequency in Magento BI
  9. 9. © 2016 Magento, Inc. Page | 9 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?
  10. 10. © 2016 Magento, Inc. Page | 10 Monetary in Magento BI
  11. 11. © 2016 Magento, Inc. Page | 11 The road so far... RFM 1. Recency 2. Frequency 3. Monetary Extensions 1. Assigning RFM scores to create unique customer groups 2. Use cases for assigning scores
  12. 12. © 2016 Magento, Inc. Page | 12 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...
  13. 13. © 2016 Magento, Inc. Page | 13 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
  14. 14. © 2016 Magento, Inc. Page | 14 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
  15. 15. © 2016 Magento, Inc. Page | 15 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
  16. 16. © 2016 Magento, Inc. Page | 16 Targeting email lists New Customers Churned Customers
  17. 17. © 2016 Magento, Inc. Page | 17 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.
  18. 18. © 2016 Magento, Inc. Page | 18 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
  19. 19. © 2016 Magento, Inc. Page | 19 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 support@rjmetrics.com today!
  20. 20. © 2016 Magento, Inc. Page | 20 Questions

×