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5 Strategies To Increase LTV Using RFM

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RFM is the secret to customer lifetime value because it helps brands understand how customers make purchasing decisions. RFM is a data-driven customer behavior segmentation technique. Almost all brands use an RFM framework for omni channel messaging to segment their customers. Most of them use RFM without knowing it. 

Example: A customer receives an email 30 days after her last purchase event with a Free Shipping offer. If she did not make a purchase, the same customer will receive an email 60 days after her last purchase event with a 10% Off + Free Shipping offer. 

The example above uses a 2 x 1 x 1 RFM framework. Customers are segmented into 2 groups based on the recency of purchase: 30 days, 60 days. Since customers are not segmented based on Frequency of Purchase or Monetary Value of Purchase, both Recency and Monetary are treated as 1 segment each. The RFM math results in 2 segments.

RFM Matrix by Customer List Size

For early stage brands, basic RFM segmentation can positively impact lifetime value. As a brand grows, especially when crossing over 100k customers, a mature 5 x 5 x 5 RFM framework can dramatically impact the five key strategies for increasing customer lifetime value.  Our Shopify App automatically layers an RFM Framework onto a store and instantly enables a brand to execute the following five strategies to increase LTV.

5 LTV Strategies

The five LTV strategies are listed in decreasing difficulty of implementation and execution.

  1. Reduce Churn
  2. Improve profit margin
  3. Increase Repeat Purchase
  4. Increase AOV
  5. Value Based Acquisition

1 Reducing Churn

Most brands manage churn by focusing on reactivating Lost Customers, customers who last purchased Y (eg 180) days ago. An effective growth framework enables leading and lagging indicators / segments.  “Lost Customers” is a lagging segment. In our RFM Framework, we enable brands to iterate strategies on leading segments, Slipping Customers and Slipping VIPs, in addition to managing lagging segments. “Slipping” signal can be simply defined as customers who last purchased X (eg 60) days ago. Or it can be scored based on multiple data points: days since last purchase, frequency of purchase, and average days to N purchase.

GP RFM Personas - Lost Customers, Lost VIPs, Slipping Customers, Slipping VIPs

2 Improve Profit Margin

The most common promotional strategy is a blast email campaign. It is designed to maximize conversion opportunities by reaching every customer. Here’s the rub: blast campaigns reduce profit margin. A simple tactic to instantly improve campaign profit margin using our RFM framework is to design unique incentives for each of the RFM personas. Another tactic is to simply exclude VIPs. 

GP RFM Personas - VIPs, Regulars

3 Increase Repeat Purchase

RFM’s simplicity masks the ability for marketing strategists to apply the Pareto Principle and focus on which RFM Persona matters most for a specific strategy.  In the absence of RFM, a brand creates generic strategies to increase repeat purchase. Generic strategies statistically result in mediocre outcomes. Our RFM framework identifies “Potential VIPs” and “Potential Regulars”. In addition to frequency and recency, we look at LTV velocity to predictably identify purchasing behaviors that correlates with VIPs and Regulars. “Potential” segment is the best opportunity for brands to increase their Repeat Purchase Rate. This is especially true for mission driven brands where brand mission is often included only in the welcome series or onboarding series.

GP RFM Personas - Potential VIPs, Potential Regulars

4 Increase AOV

RFM increases eCommerce sales by enabling brands to create specific, relevant offers to the right groups of customers. In our RFM framework, we enrich RFM persona targeting by providing additional data points such as Favorite Product, Favorite Category, Product LTV, and purchase correlation to enable one-to-one personalized messaging. 

GP RFM Personas - All

5 Value-Based Acquisition

In an effective growth framework, retention powers growth by increasing recurring revenues, increasing lifetime value, and enhancing acquisition targeting. In addition to impacting retention, our RFM facilitates targeting by injecting customer value audiences on Facebook. By helping Facebook understand the value of each customer, we supercharge lookalike targeting. This results in capturing new customers that will potentially model your VIPs LTV curve at a higher rate. Typically this strategy results in higher CAC, higher AOV, and steeper 6 month LTV curves due to the improved quality of customers a brand is acquiring. We leverage our app to help our clients visualize these metrics.

GP RFM Personas - All, VIPs, Lost

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Some Data Points On Me

I've led e-commerce operations, built growth teams, and scaled three consumer brands from seed to over $100M in revenues. My insights on growth stems from my experience as an investment banker, front end engineer, UI/UX designer, CxO, and investor. Growth is an exercise in navigating uncertainty through decisions. Hopefully my experience will help you make better decisions for your business.

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