October 14, 2022
When working with a customer database, how can you find the data of those who buy regularly? How do you track when a loyal customer makes orders less or more rarely, and how do you correct the situation? These challenges can be solved by RFM analysis.
RFM analysis is suitable for better understanding customer needs, offering them what they really want, developing effective marketing strategies, increasing their coverage and ROI, and segmenting customers. In this article, we show you what RFM analysis is, how to create and customize segments for mailings based on the RFM model, and how you can use it to increase conversion into orders.
So, what is RFM? RFM (Recency, Frequency, Monetary) analysis is a method of customer segmentation. RFM meaning is to divide customers into non-intersecting groups, as well as to understand who among customers buys a lot and often, who buys a lot but rarely, and who hasn't bought anything for a long time.
RFM segmentation is important for effective interaction with customers, increasing ROI and LTV. Based on the results of the RFM analysis, you will know which ads to show, which email marketing to plan and which bonuses to offer.
For example, you can send letters to loyal customers with information about new products and services of the company and give motivating discounts to customers who haven't made orders for a long time.
RFM analysis is based on three indicators:
A business that divides customers into different segments, optimizes advertising costs, and successfully launches new products has better contact with consumers because it knows how and which tools to use.
The key benefits of RFM modeling are:
The RFM in marketing is suitable for e-commerce, direct sales, and non-commercial interactions. It is used if the need for the product is not one-time but recurring and therefore satisfied customers make purchases on a regular basis. In particular, this type of customer analysis allows us to answer a number of essential questions:
The results of the RFM scoring will show the most loyal group of customers, which brings the most profit. The company can adjust the assortment or the advertising display for this group.
After the analysis, you get segments of new customers and those who buy frequently but a little bit at a time. To move these customers to the group of regulars, the company develops attractive offers for them, such as a loyalty program.
If the company divides customers into groups and studies their needs and interests through RFM analysis, it can create helpful and interesting content for those people. The content will generate a response and lead to the target action: make a purchase, register for a personal account, or subscribe to the newsletter.
Customers who have lost activity are likely to leave. But if the company conducts analysis and discovers such customers in time, it can take measures to retain them.
Now you know what RFM stands for and other important info apart from the definition. Let's get down to use cases and explore what RFM segmentation is and how to perform it.
Start with the collection of data and determine the analysis period. There is no strict framework, but it all depends on the organization's characteristics (including the direction of the work — B2B or B2C). Usually, you have to gather RFM data for the last year.
There are some obligatory requirements for the source data. They should contain the following information:
If you are going to create a table manually, it will take much time. To speed up the process, use a CRM or analytics system that automates the exporting of the necessary information.
Create groups based on time of purchase (R), frequency of purchases (F), and money spent (M). Each group is assigned a value from 1 to 5, where 1 is the best and 5 is the worst.
We estimate the date of purchase, select the group of customers with the highest Recency, and assign it position 1. The rest are evenly split into segments, depending on activity.
A scale of 1 to 5 separates new and loyal customers from those who are almost lost. Customers from segments 1 and 2 will always be fewer than those from 3, 4, and 5.
We determine how many purchases we can consider profitable for the company.
Customers who spend the most money are divided into a separate RFM segment. They play an important role, even if they are not regular customers.
Then we number clients by each parameter. For example, a customer made two purchases 40 days ago for $5,000. In this case, his value will be 243.
Based on these values, the so-called "triples" are formed, i.e., values 111, 333, 232, and so on. For example, "333" — is a recent customer who rarely shops and spends an average budget. This customer isn't bad, but customers from value 111 would still be the best, since they constantly come and invest more money in the product.
You can further divide your customers into specific groups:
Based on the information in the table, you can develop a strategy for each group separately.
You can notify them about current promotions, sales, and discounts. However, you shouldn't put a lot of effort and time into returning your long-time customers, as the outflow is inevitable. If there is no response, remove them from the database.
This group deserves attention because previously these people have bought many times for large sums. To get customers back, you should offer a personal selection of products, discounts, and bonuses, and inform them about the sale. Get them interested in useful content (an article or video). Find out the reason customers stopped buying.
It is recommended to remind them of the benefits of the company, the purchase, and the product/service. Tell them about your fortes that your competitors don't have.
It's important to move customers from newcomers to loyal. Offer educational text or video content, advise on products (how to choose, what to look for), provide background information, congratulate them on their purchase, etc.
Consumers who regularly buy for a small amount or have recently bought for a large amount may become ideal clients in the long run. Your job is to hold their interest and increase user engagement.
It is essential to convince this segment of their importance to the company. Ask your ideal customers to leave a review and offer a form of personalized service. Encourage customers to order regularly, and provide customized product selections. Don't be overly intrusive, as unnecessary communication is tiring. Give only helpful information so as not to annoy people.
RFM segmentation is a great tool for a company's marketing analytics, with the help of which you can separate your audience and achieve effective sales. Above, we looked at how to work with it and when it's best to use it. Finally, we'd like to add that RFM analysis is much more convenient to carry out with the help of special automated tools such as Reteno. Reteno is a no-code platform for gathering information and setting up marketing campaigns. The platform allows marketers to take full control of customer-centric communication and avoid routine. In Reteno, RFM is created automatically based on the activity of contacts. Contact us now, and we will make your marketing truly effective.
August 30, 2022
Find out how to improve your marketing results with the behavioral segmentation feature in Reteno
September 14, 2022
Common features or similar actions – choose your approach for effective audience segmentation