This is the second post in our series about marketing success metrics. The first post covered Return on Marketing Investment, which is used to measure the financial return of any money spent on marketing efforts. This post is about a method for evaluating and prioritizing existing customers, called “Recency, Frequency, and Monetary Value” or RFM for short.
RFM is built upon the idea that it’s always cheaper for a company to sell more to its existing customers than it is to attract new ones. But how do you make sure that when you reach out to existing customers you do so in a way that’s effective? Performing an RFM analysis is a great place to begin.
The RFM analysis ranks three aspects of your company’s customers in the same table, but independently of each other. Each customer winds up with three scores, one for each metric, not a single combined score that takes into account all three. So a customer could score well on Frequency, but poorly on Recency and Monetary Value.
Here is how you define each part of the RFM analysis:
- Recency: How long has it been since the customer’s last purchase?
- Frequency: On average, how often do they purchase?
- Monetary Value: On average, how much is each purchase?
Companies rank customers on each of these attributes in one of two ways. One way is to enter the actual values for each one, but in a comparable scale and with a restricted range. So if you chose a scale of 1-10, you could say that the score in Recency would be the number of months since the last purchase, up to a maximum of 10. Frequency would be the number of purchases in the past year, again capped at 10. And finally, Monetary Value could be the average order size in thousands of dollars, up to the maximum of $10,000.
Another way is to create your own scale, based on your business and its individual situation, and define the scores yourself. So if you wanted to use a scale of 1-5, you could say that for the Recency measure a customer who purchased in the past 3 months is a 5, one who purchased in 3-6 months is a 4, and so on until you reach 0 for customers who haven’t purchased in more than 15 months. Do the same for the other two metrics and score your customers that way.
If you have a particularly large customer base, you can perform a RFM analysis on a representative sample instead of all of your customers to determine your key segments. Once you’ve completed your RFM analysis, it will help you target special offers and promotions to different audiences and demographic groups more effectively.
Let’s say your RFM analysis shows a particular customer segment has a high Monetary Value score, because they make large purchases every time they visit your store, but low Frequency score because they only come once a year. You now know you need a strategy that gets these “high rollers” to visit your store more often each year, and you could target this audience segment with an offer to buy a special premium coupon book that gives them a notable discount once a quarter, for example.
Since these customers are probably aware that whenever they come to your store they make large purchases, they would see the value in paying a small amount of money up front in order to reap significant savings in the future. The benefit to you is that now they have a reason to come to the store and purchase 4 times a year, instead of just one, which should dramatically boost your profits from these customers. And even if they don’t visit, then you’ve made money on their purchase of the coupons and haven’t had to give them any discounts on merchandise.
For another example, let’s say you find a different customer segment that has a low Monetary Value rating, but a high Recency and Frequency rating. These customers are loyal. They come in and purchase from you frequently and have done so recently as well. But they don’t spend a lot of money each trip. This intelligence lets you know that the most valuable offer to these customers would not be something that encourages them to shop with you more, since they already come more often than any of your other customers, but instead to try to get them to buy more during each visit.
Because you know the average purchase amount of these customers from the RFM analysis, you could once again use a discount as your strategy and give them 10% off if they spend a certain amount above that average. So if their average purchase is $50, you offer them 10% off if they spend more than $75. This encourages your regular shoppers to increase their Monetary Value, which increases their RFM rating as well as your company’s profits. You could even make this a “customer loyalty program” and give a special card to these customers, so that whenever they shop with you and spend more than $75 they need to show the card to get an additional 10% off. This makes them feel like you are doing a favor for them, when in reality if it gets them to make larger purchases it’s also a favor for you!
One final use of the RFM analysis is to figure out who your most valuable customers are so you can communicate with them and make sure that they are as satisfied as possible. If you find customers with high scores across all three categories, you don’t need to market to them to try to improve any one of their attributes since they’re already at the top of all of them. What you need to do is make sure that they continue to stay the same level of customer that they currently are. This is where it makes sense to invest in customer loyalty and happiness, whether that’s giving them a special line to customer service that doesn’t have a wait, or an extended warranty or return policy on your products, whatever you can do to show these customers that you value their business to keep them purchasing from you early, often, and in large orders is a smart investment.
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