Score your clients and increase your sales with the RFM method

September 13, 2021
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To prepare an effective email campaign, you not only need a talented chef but also the right ingredients measured in the right proportions. These can be the selection of the right products, prices, content, or shipping time. But what matters the most is who we're cooking our campaign for. After all, everyone is unique and while some users prefer getting the most out of their budget, others will be satisfied only with premium products of their favorite brands.

What’s driving the decision-making process of your customers can sometimes seem like a mystery. According to Salesforce, as many as 52% of consumers change brands due to mismatched marketing communication. Walker consultants, on the other hand, suggest that around  86% of customers are willing to spend more if they are provided with the right experience. The key, then, is to understand the customer's intentions.

For this reason, the best e-marketing chefs are constantly working on creating personas, i.e. profiling customers and segmenting them. This form of art is not only difficult, because it requires experience and understanding of the industry, but also laborious.

In addition, segmentation can be based on the soft and hard characteristics of a person. For instance, a soft characteristic can refer to a client called "collector" as in furniture jargon. It's usually someone from the upper-middle class in their sixties. Hard characteristics, on the other hand, go to the most important demographics—age, earnings, having children, location, etc.

But the more marketers there are, the more ideas of segmentation emerge as well as the number of data you can use.

Thus, preparing a single campaign is related to the working hours of many people from the sales, analytics, eCommerce, and marketing departments.

However, there is a segmentation model that does not require the participation of many people, and, at the same time, always works in eCommerce.

Ladies and gentlemen, please raise your glasses, because on the golden plate appears... scoring segmentation!

What is scoring segmentation and how does RFM taste?

Scoring is a clever and versatile way to segment your customers. But when you are grouping clients based on hard data (time since last purchase, average cart value, etc.), you should always take into consideration the characteristics of your market niche.

For example, if you run an online store with garden supplies, you will have to deal with seasonality. This means that if a customer returns only every six months, it's not a bad indicator. In comparison, if you have an online pet store and your customers don't come back in 2 to 5 weeks, it could mean that they have bought pet food elsewhere.

What a company usually does is build segments based on hard data starting over and over again. But with a proper scoring method, you can take into account the whole context and make the whole process much easier.

In a scoring system, we build benchmarks using the lowest and highest values from a given parameter in our store and assess the score of our customers depending on where they are located between these lines.

There are many scoring segmentation models and one of the most popular is the RFM. This model is nothing more than assessing points in three categories–Recency, Frequency, and Monetary.

Personally, I use a scale of 1-5 taking into account hundredths (e.g. 3.87), but this, in my opinion, really depends on the size of the store and, consequently, how deep we can afford to go.

After all, it makes no sense to divide the score too much if we have several thousand customers in the database. But a more detailed clustering could pay if we have hundreds of thousands of them in our granary.

I build my benchmark on an annual basis, i.e.:

·         For Recency, the rating of 1.00 is the longest period since the last purchase, and 5.00 is the shortest period since the last purchase in store history.

·        For Frequency, the rating of 1.00 represents only 1 purchase per year without return, and 5.00 is the largest number of purchases made in the last year by a single customer.

·         For Monetary, the rating of 1.00 represents the lowest value of customer's orders, and a score of 5.00 represents the highest value of all orders placed by a single customer over the last year.

As a marketer, you now take the role of an arbiter who evaluates each of the customers' characteristics and groups them according to the values of the parameters on the built scale. Below, you can find the description of and samples of scoring segments and advice on how we can deal with them.

Sample segments and how to cook them on a scale of 1-5?

We are going down to the level of my personal experience working with many eCommerce businesses within marketing automation, so please consider the following statement as a mere collection of good practices and not the only legitimate cookbook.

Source: Sample RFM report in the Samba.AI
Source: Sample RFM report in the Samba.AI

The evaluations are mere examples, but given the issue of benchmarks, the good practices and conclusions presented are already as realistic as possible.

Lost – ratings : R1; F1,1; M: 1.3

A group of customers who made purchases a very long time ago and have never returned, while the value of their purchases was not staggering. Such customers can be treated with standard newsletter campaigns, although they will probably significantly underestimate our campaign indicators (they probably do not remember us and do not read the news at all). Therefore, it makes no sense to pay more attention to them.

At risk - ratings: R1,57; F1.05; M: 3.47

A group of customers who made the most common purchase and did not return for a long period of time, although the purchases were of relatively high value.

It's a group of customers who most likely took advantage of our in-store promotion and need extra bait to return to us. The value of their shopping cart indicates that it's a good idea to send them a discounted activation campaign or include them in your audience for all promotions in the store.

Needs attention – R3.05 ratings; F1,56; M3,87;

This is one of the more attractive segments for email marketing. These are customers who made a relatively recent purchase of a high value but have not returned to the store afterward.

A suitable promotional or cross-selling action can help you get the customer back. For this segment, personalization tools (e.g., products recommended based on their browsing history) are very useful features.

New customers – R4.44 ratings; F1,18; M1.55

These buyers did not spend much and have not returned after their first order, but they made the purchase in a very short period of time.

This is the perfect group for upselling and cross-selling campaigns! Send, send, send!  😉

Promising – R4.51; F1,31; M4,23

Customers who have recently made a purchase and placed another order of a significant value.

It's a perfect opportunity to build a relationship as well as for cross-selling activities. Send a thank you message and kick off a campaign for their next purchase. Alternatively, immediately suggest recommended complementary products. Don't be afraid to send even more than in the previous segment!  😉

Champions – R4.72; F4,58; M4.50

Ideal customers – they buy from you often and they're not afraid to spend a lot.

Of course, it's good to keep things going, but the truth is that for these customers, you're already the number one store, and they'll most likely return to you regardless of your marketing activities – unless you alienate them by flooding their inboxes with excessive email campaigns.

Cannot lose!!! R1,41; F4,41; M4.50

A group of Champions who haven't purchased anything from you for an unusually long time.

There always has to be a cause for the change in their behavior. Perhaps, they didn't feel happy about the mood of a customer care representative, or the service provided by the courier didn't fit their needs. Or maybe they found a cheaper variant of products they wanted to purchase elsewhere.

These situations require a highly personal approach. Call them or send them a message and offer them help or assistance. After all, they've made a huge number of high-value purchases, so they represent an important part of the revenues of your eCommerce. It is also worth considering some constant discount for these customers, in order to ensure their recurring visits.

Voilà!

Scoring segmentation is a way for a marketer to take the role of an analyst and, without any additional help, quickly understand what the audience's intentions are and who to focus attention on first when creating a new campaign. Proper planning of communications and adapting them according to the current situation is also important from the perspective of available resources. Time is not inflatable, nor is your budget.

Scoring analysis is also convenient because of its versatility. That's why there are Marketing Automation solutions on the market that perform RFM scoring automatically so that you can save yourself a lot of work and gain a powerful component to make a successful email campaign. That's what I sincerely wish for you (and myself) in the coming years. Bon appetit!

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