RFM - Analyzing your Customer Data in a different way!
There is a lot of buzz in the wine business world right now about “RFM”. All of your customers (from the “Best Customers” to the “Lost Customers”) have different needs and will respond to marketing campaigns in different ways.
Being able to segment your customers will allow you to make your campaigns more relevant to your customers and therefore improves the likelihood of your customers responding to your marketing, and in turn increasing your sales.
What is RFM analysis?
Recency-Frequency-Monetary (RFM) analysis is a relatively simple technique that allows you to use past purchasing behavior to segment your customers, which can dramatically improve your marketing effectiveness:
Recency (R) - Days since last purchase
Frequency (F) - Total number of wine orders
Monetary value (M) - Total monetary value
Customer segmentation with RFM Analysis
VinDashboard scores your customers on a 1- 5 scale against each of the RFM definitions (5 being the highest score).
For example, one of your “Best Customers” who has purchased Recently, Frequently and spends a lot of Money on those purchases would score a 5 in each category, whereas a “Lost Customer”, who has not purchased Recently or Frequently and spends little Money, would score a 1 for each category:
Please note the following important points with respect to VinDashboard’s approach to RFM:
We use two year’s worth of wine purchase history and only orders containing one or more bottles of wine are counted
Customers are included in the analysis if they have made at least two wine order purchases in the last two years or if they are an Active/Canceled WC member with one or more wine orders.
Only wine revenue is included in the M amount
Wine orders with a value of zero $ or less are excluded (examples of these could be wine club exchanges/refunds, replacement for corked/damaged bottles, complimentary wine club memberships).
Where a customer score fits into more than one segment, the first on the list will be where the customer is placed.
We ignore club status when performing the analysis, so you could find, for example, a Canceled club member in the “Best Customer” segment.
Below is a table showing each of VinDashboards RFM segments and detailed scorings for each.
Bought recently, buy often and spend the most!
Reward them. Offer early release of new vintages. Will promote your brand.
Potential Best Customers
Made a few big purchases - need to keep them engaged
Keep them sweet via special offers, don’t lose them to competition, talk to them.
Best Customers at Risk
Spent big money and purchased often, but haven’t purchased for a few months. Need to ensure they stay!
Call them or send personalized emails to reconnect, offer incentives, provide helpful resources.
Spend good money with us often. Responsive to promotions.
Upsell higher value wines. Ask for reviews. Engage them.
Potential Loyal Customers
Recent customers, bought a few times
Offer club membership / loyalty program, recommend other wines they might like.
Loyal Customers at Risk
Above average frequency and monetary values. Not purchased for a few months though.
Make limited time offers, Recommend new wines based on past purchases. Reactivate them.
Regular shoppers, but don’t spend much.
Create brand awareness, try to upsell to higher value wines.
Recent shoppers, but not frequent purchasers
Provide on-boarding support, give them early success, capture wine preferences, start building relationship.
Last purchase was several months ago; unremarkable frequency and monetary scores
Offer other relevant wines and limited time discounts. Recreate brand value. Focus on high LTV customers.
Lowest recency scores - haven't seen them all year.
Revive interest with reach out campaign, especially high LTV, ignore otherwise.
Now you can work on ideas for your marketing campaigns for each type of Customer Segment!
Use the following two reports to identify your customers and click here to see instructions on downloading customer data for import to WineDirect allowing you to create a targeted marketing campaign using contact types.
07- Customer Analysis > 06- RFM Analysis
07- Customer Analysis > 07- RFM Customer Data