How to scale business with the use of the RFM analysis - step by step!
The aim of this article is primarily to show you a new perspective on your clients and to inspire you to perform more precise marketing activities so that you can earn more money - are you interested? Let's go!
You have probably segmented your customers more than once in terms of their demographics, interests, problems, and needs. After all, this is one of the basic assumptions of marketing and we should carry out such segmentation when working in favour of our business. But think about what it really gives you. What you can use such conclusions for? Hmmm… To target advertising better, to create better tailored advertising messages, to adjust your offer - so to effectively attract new customers?
What about your current clients?
I mean, who really is a client? We can define a client as a user who made a purchase from you in the past and, please note, is ready to make such a purchase again (otherwise we can't really call that person a "client", but rather a "former" or "lost" client).
So I'd like to ask you a few questions, okay?
How many users do you really have? Ones who placed an order with you, any order really, during your store's lifetime?
How many of these users placed an order with you only once and never returned?
And those who placed more orders, how often did they do so? And how much money did they leave in total?
Which customers are most valuable for you? Do know that? Or perhaps you treat all your customers exactly the same - the same emails, the same campaigns, the same marketing activities?
How much do you pay for acquiring a client? How much do you pay to keep that client? Does it pay off?
Don't worry. I'm pretty sure you can't answer most of these questions. And even if you can, it would require hours of analyses, for example, using Excel, right? Fortunately, there is a system that can help you find this information and then use it in practice. Just a reminder - so that you can earn more money. But first things first.
So what does RFM analysis mean?
The RFM analysis is one of the marketing analysis tools used to segment clients on the basis of their purchasing behaviour (not characteristics) in a given period.
The RFM abbreviation includes the following terms:
R as RECENCY - a characteristic describing the time from the last transaction (or other activity considered to be a conversion depending on the type of business we analyze). Let's consider whether a client who placed an order in your store 2 months ago is "more important" than a client who placed such an order over a year ago? Yes, I suppose so. The "fresher" the client, the greater his value for our business will be (of course, in most cases, because every rule has exceptions).
F as FREQUENCY - a characteristic describing the frequency (in terms of quantity) of a given user's transactions. A client who has already placed 3 orders with us has a higher "frequency" and is "more important" than one who has only placed 1 order.
M as MONETARY ("value") - an evaluation of the total value of a user's orders. As you can guess, a client who has already spent PLN 3,500 with you is probably "more important" than one who has only spent PLN 100.
As a standard, according to this methodology, all clients are divided into 5 equal groups in each of these 3 characteristics, assigning them numbers from 1 to 5, where 5 is the "least valuable" and 1 is the "most valuable".
This can also be simplified to a 3-degree scale: high (best 20%), medium (middle 60%), and low (worst 20%).
With such segmented clients, you can easily find various groups of clients and adjust marketing activities to them, for example:
the best clients (those who performed purchases recently, made a lot of purchases, of a great value in total)
clients with a high potential (those who made one order recently, but with a lot of value),
valuable but lost clients (those who made more orders, of high value, but did not perform any transactions for a long time),
and many more...
So how to perform an RFM analysis and how to use it in terms of business?
First, let's look at the practical application - we want to show its great potential.
(Before we go any further, I would just like to mention that we won't perform this analysis using the well-known Google Analytics tool, because we need complete business and client data for this).
- Example one: In search of fat cats
Having a segment of the best customers, you can export a list of their e-mail addresses and upload them to the Facebook Ads tool, and then create an advertising campaign for similar users - basing on the behaviour of your fat cats, the Facebook system will find those who also fit the segment and it is going to show your advertisement to them.
- Example Two: Tailored e-mail marketing
Having your client lists, you can send a given messages to customers who made their first order, but haven't returned for a long time, encouraging them to do so with a discount code.
Whereas, it is not worth sending a discount code to your regular clients (because they are regular clients, they love you, so they will place an order with you anyway - don't waste your profit on meaningless discounts). However, you can send them information about pre-sales, a unique offer and news, because that's what they're waiting for.
Example three: Analysis of marketing activities
You perform various marketing campaigns, you acquire customers - but which ones? Do you catch "fat cats" or just "strays" (whatever you call them - each store probably has its own term for it)? It would be good to know, right? Having an RFM analysis, you can easily find it out and manoeuvre your activities in such a manner to acquire entire clowders of the most valuable clients who will stay with you for a long time, performing regular purchases.
Example four: Does Black Friday work?
During the year, we have many opportunities to acquire many new customers, but at an additional cost, whether via advertising or promotions and discounts, e.g. Black Friday or Christmas.
Do clients who bought something from you during a promotion come back? Does such marketing action and reducing your margin make sense? By analyzing RFM you can very easily find out!
Example five: et cetera et cetera…
I hope that these few examples have properly inspired you and you can already imagine what you can do with such data concerning your clients :)
But how do we perform such an analysis if we already know that we will not see such data in Google Analytics?
We can do it manually, e.g. in a spreadsheet (because who doesn't love Excel)
How to prepare an RFM analysis in a spreadsheet?
Having your client data downloaded (date of the last transaction, number of transactions, value of transactions), you must segment it.
You can do this using a spreadsheet in the following steps:
- Sort columns with variables
- For each variable create ranges and assign them given values on a scale (e.g. 1 - 5)
- Assign each record with a corresponding value from the scale for the variables R, F, and M.
- Assign values from 1 to 5 to clients from each group.
- In a separate column, calculate the sum of values R, F, M for each record, and then sort the entire column.
- Depending on the total result, assign companies to separate groups (segments).
However, let's be honest, we can make such calculations once to see the condition of our store and the structure of customers. However, if we want to take advantage of the RFM analysis in practice, we should collect such data on an ongoing basis.
Fortunately, we do not have to hire a staff of new employees, or spend huge amounts of money and waste a lot of time - we live in the 21st century and, attention, we don't have to reinvent the wheel!
RFM analysis with WitCloud!
If you want to save time and minimize the risk of error, use our automatic WitCloud solution and enjoy the ready data!
This is very simple and takes just a few steps:
Create an account in Google Cloud (your data will be safely stored there)
Create a WitCloud account (14 days free trial)
Connect your data from the store - (hmmm… 4 clicks are probably enough)
Create an RMF report (also a few clicks)
Analyze the data in the report (you get to know your clients - a lot of things may surprise you, so prepare to spend more time on this)
Explore e-mail addresses of your customers matching a given segment
It's really very simple and in a situation when Google Cloud and WitCloud initially do not cost you a thing, it would be a crime not to try and get to know the structure of your clients and not take advantage of it in terms of business.