Response Labs helps brands Make Every Message Matter™ by employing the RFM data model for improved targeted marketing.
We deliver greater return on your investment in customer data with the RFM data model
What is RFM?
The RFM Analysis is a data modeling technique that helps to determine customer value at a point in time. RFM stands for:
- Recency: Date of last transaction
- Frequency: Number of times transacted in a time period
- Monetary: Total amount spent in a time period): three key indicators of customer value.
The resulting RFM Analysis divides the data into a group of segments with associated attributes allowing marketers to quickly sort customers.
Put Your Customer Data to Work
By working with Response Labs you will not only get a full RFM Data Analysis of your customers, but a marketing plan informed by the results of the report. The marketing plan will focus on the following key areas:
- Loyal Customer Advocacy: Target your best customers to keep coming back and empower them to be ambassadors of your brand.
- Customer Retention: More quickly identify patterns of customers that drop from higher value loyalty groups and prevent them from defecting with win-back and lapsed campaigns.
- New Customer Acquisition: Create lookalike audiences of your top customers and target advertising in places.
- Segment Marketing Messaging: Dynamically get the most relevant messaging in front of customers based on their RFM group in email, SMS, push marketing campaigns.
Get Started With Response Labs
Complete the form on this page to connect with us and get started on your RFM Data Analysis. Our experience working with top brands in grocery, dining, and retail allows our team to customize a program just for you based on the needs of your business.
Talk to Our Experts
Discover how we can help your business get the most value from your customer data using the RFM data model.
“Working with the team at Response Labs to unlock new customer segments in our data has informed personalized messaging in email. We’re driving significant lift within key sub-segments and uncovering new ways to build relationships with top customers.”