Whatever people do – whether it is offering a product or service, creating a video game, writing a book, or running a marketing campaign –
The world is a vast and dynamic place. Any business that wants to succeed needs to fill that gap and market a product or service to as many people as possible. Awareness will eventually trickle into conversion.
While marketing to more people is ideal, sometimes it just isn’t the ideal thing to do. The assumption that everyone will be interested in a product or service may often lead to a strategy that has no effect and will just end up wasting your time and money.
In most cases, the term “one size fits all” is a myth that many people wish to be true, but just isn’t. This is especially true with marketing.
The solution? Instead of trying to blast out marketing efforts like buckshot and praying it will hit as many people as it can, the best move is to narrow one’s sights via customer segmentation.
Customer segmentation is a way to group customers into groups that share similar qualities and characteristics. When it comes to effective marketing, customer segmentation helps drastically.
In fact, a study by Harvard Business School found that of 30,000 product launches, at least 95% fail each year due to the failure of segmentation.
One of the most effective segmentation categories is via RFM. Effective RFM analysis can pave the way for an effective customer segmentation. Throughout this article, we’ll learn more about customer segmentation as well as how RFM can help achieve successful segmentation.
As stated previously, customer segmentation is a way to identify customers and place them in groups that have distinct shared characteristics.
If a business looks at their target customers, one of the obvious things that they have in common is the need for the product or service. However, there are many other characteristics and demographic information that can be effectively utilized by an organization.
There are many types of data that can be used for segmentation. These include things like:
Furthermore, companies can utilize the checkout process to obtain even more information that can help more with the segmentation process. These include things like why they decided to purchase the product, the age of the customer, their job, their gender, what they intend to use the product for, and their company industry segment.
Customer segmentation has many benefits. The first one we mentioned was improved marketing efforts and strategies.
When it comes to marketing, information is key. With enough of the right information, it can help companies target the right market, with campaigns launched towards the right people. This increases the chance of the message being effective to these specific people.
Apart from that, the information gathered can help craft a more informed and effective marketing strategy and message. It also helps point out which channels are the most effective and should be used to reach the target customers.
Finally, the gathered information can also help with the content of your marketing efforts. When it comes to marketing, personalized communications versus general ones usually lead to improved relationships along the way.
This relationship can result in customer loyalty that can help the company stay afloat for years to come.
Like all companies, budget is not an infinite resource. Whether it is for operation or marketing, companies operate on a limited budget.
Customer segmentation allows for companies to have a precise picture as to who and where they spend their resources on.
When a company has segmented their customers, they also obtain a clearer picture of which customers will most likely convert or those who will provide a return for your company’s marketing efforts.
Ensure that every penny you spend on marketing is invested toward the right group. This makes sure that the budget is well spent and generates additional budget to help push the company towards success.
When companies have a better idea of the customers they are servicing, this can open a lot of doors towards improvement and increased revenue.
The feedback of the customer is very important. With more customers under your wings, the more input you can get regarding what features they like, what improvements they want to see, and which segment of customers provide the most value.
There could be times where the additional features added to the product are best offered to a higher value segment of customer.
In addition, different customer segments have different purchasing behaviors. Having insight into their purchasing habits and levels of income can become a good signal towards upselling your company’s other products.
One of the most basic customer segmentation models is grouping customers via their demographics. These include things like age, gender, and even marital status of the customers.
Understanding the predominant gender of your customers allows for the customization of the content being developed. Similarly, even the understanding of a customer’s marital or parental status can help with how the message is developed and delivered.
Another good segmentation model is psychographic. This has to do with the beliefs, attitudes, and personality traits of the customers. These points usually match closer to what the company or business represents or stands for.
Additional psychographic information can help provide for a narrower and more focused picture of customers.
For instance, a demographic segment of customers aged 21 to 30 would yield a million. However, when paired with the psychographic groupings, companies can then see that only half of the million identify closely with the message or belief of your company.
As the name suggests, the RFM customer segment looks at how recent a customer’s purchase was, how frequently they purchase, and how much they have spent for their purchases.
Let’s learn more RFM in the next section.
The RFM segmentation model allows for marketers to more accurately target groups of customers with messages and content that are more relevant to them. This increased relevance results in better responses, more loyalty, and prolonged value from customers.
While there are many segmentation models, with the three above only a few out of the whole list, the RFM has its own set of unique benefits.
For starters, RFM uses objective data. This objective data is able to paint a clearer picture of the customers.
Despite the fact that it utilizes data, it is still a very simple and easy model to use. There is no need for any data scientists or specialized software to put RFM in play. Along with the simplicity, marketers will also see that the RFM is an intuitive model that can be done and interpreted easily.
RFM’s factors can be found in its name: Recency, Frequency, and Monetary.
Recency takes a look at when the customer last made a purchase with the brand. How recent was it? Apart from purchases, marketers can also look at how recent customers have visited a website or used an app.
In understanding the recency of customer’s activities, it creates a point of target for customers. The people who recently interacted with a company via purchases or visits are the ones most likely to respond to communications sent out.
For Frequency, marketers take a look at how often customers purchase or interact with a certain brand. Increased frequency points to customers who are engaged and loyal. Thus, they become prime targets for marketing communications.
The final factor of RFM is Monetary. This factor looks at how much a customer spends on the product or brand in a specific period of time.
Customers who end up spending way more than others are more likely to be treated differently than those who don’t spend as much.
In addition, the average purchase amount of customers can be discovered when the Monetary factor is divided by the Frequency factor.
The first step to crafting effective customer segmentation through RFM analysis is by collecting the necessary data and assigning it to the customers. This data can be taken from the company’s CRM and can be put together in an Excel spreadsheet.
Assign each Relevancy, Frequency, and Monetary values to each customer.
The next step is to apply tiers to the data you have compiled. These tiers should be applied to each factor and are usually “most” to “least”. The recommendation is to split up the data into four tiers for each factor. This means there will be four tiers for Recency, four for Frequency, and four for Monetary.
The example here is that Recenecy will have a Tier 1 (for most) to Tier 4 (for least). The other factors will have the same.
The four tiers for each factor will create a total of 64 possible segments, as the customers will be assigned to specific tiers per factor.
It is possible to go for three tiers instead of four. This creates a total of 27 possible segments. It must be noted though that it is not recommended to have more than four tiers.
With the data and tiers in place, it is time to assign certain customers into groups based on specific tier combinations.
One example is if a customer belongs to the highest tiers for Recency, Frequency, and Monetary, then this group can be named the best customer group.
Consequently, if certain customers have interacted recently and frequently, but do not spend a lot, these customers can be put in a group that is loyal but low spending.
These groups are the segmentations that will help you craft better and more targeted marketing messages.
Bear in mind that the group names are all up to the practitioners. It should follow the data from the customer’s assigned RFM tiers.
There you have, the step by step RFM Analysis Guide for effective customer segmentation. After these first three steps, you’ll want to use the information that you have brought together and start making it work for you by crafting RFM-group specific communications.
The RFM analysis is a great way to better craft and understand the customers that are purchasing from your brand. The result can be anywhere from increasing customers to increasing revenue.
Let’s take a look at a couple of cast studies that will show the effects of RFM Analysis.
The first RFM case study looked at its effect on a company called SilverMinds Direct. The nature of this company’s business was marketing special interest music like jazz, country, classical, and many more.
At the time, the company had a quarter of a million customers. With the help of RFM Analysis, they were able to better segment their customers.
The segmentation improved their mailing strategies. Furthermore, the data from their RFM groups revealed several opportunities that they didn’t know were there.
The result was a 5% increase to their revenue.
Another case study saw various improvements for a company that include: active customers growing by more than 500, total purchase volume increase by 279%, and total consumption amount increased by 101.97%.
RFM is a very potent and useful analysis tool. The different pieces of data are individual bricks that help pave the road towards understanding the various groups of customers that are interacting with your brand.
RFM is simple, intuitive, and easily interpreted. Any marketers can analyze brands via RFM. Get the RFM segmentation model in your arsenal and start to discover different opportunities to push brands to succeeding.