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Home > Blog > Digital Marketing > PPC >

Improving Customer Segmentation With RFM Marketing Analysis

Smart business owners understand the importance of knowing their customers. And that goes beyond measuring regular metrics like clickthrough rate (CTR) to focusing more on things like loyalty, retention, and healthy relationship with the customers. To focus on these things, you must have a good grasp of RFM marketing.

RFM marketing

With RFM analysis, you get to segment the customers into groups and analyze customer traits within these groups. After that, you get to launch relevant campaigns that will resonate with each of the customer groups.

That’s a more effective marketing model than segmenting the customers using metrics like geography and age.

RFM analysis is an effective and easy-to-use segmentation model that helps business owners analyze their customer behavior and get the most out of their business advertising.

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What is RFM Marketing?

RFM marketing stands for recency, frequency, and monetary value. It’s a marketing analysis model that helps in segmenting the company’s customers based on their purchasing habits and patterns. It works by evaluating how long a customer has made a purchase (recency), how often a customer makes purchases (frequency), and how much money a customer spends (monetary value).

The RFM marketing model is arguably one of the best ways of analyzing and measuring the spending habits of your customers. In the long run, you’d easily identify your best customers. It also helps in maintaining high-scoring customers even as you improve the low-scoring customers.

If you’re still unsure of what RFM marketing is, here are easy tips to help you understand it.

  • Recency, frequency, and monetary value is a marketing analysis model that helps you identify who your best customers are by keeping a close eye on their spending habits.
  • With the RFM marketing model, you get to assign a score to your customers. The score range could be from 1 to 5, with 1 being the worst and 5 being the best.
  • The RFM marketing analysis monitors your customers and scores them using these three categories: how recently they bought your products, how often they buy, and their purchase size.
  • RFM marketing can help you easily pinpoint three types of customers. Customers who will most likely buy again from you, the amount of revenue that comes in from new customers (versus repeat customers), and how to convert skeptical buyers into loyal paying customers.

Calculating RFM Scores:

To adequately calculate the RFM scores, you need to know this data.

  1. Customer’s most recent purchase data
  2. The amount of transactions within a period (usually a year)
  3. Total (or average) sales generated from the customer.

What are Recency, Frequency, and Monetary?

Here is an easy explanation of the terms recency, frequency, and monetary.

Recency:

If a customer has bought your products in recent times, they’ll likely buy from you again. However, a customer who has not bought from you in recent months or years, will likely not buy from your company. With these kinds of data, you can reach out to recent customers and encourage them to spend more on your product or service offering.

Customers who have not reached out in recent times can also be encouraged to engage with your brand. One of the ways of doing that is by offering them some incentives.

Frequency:

The frequency of a customer’s interaction with your brand can be affected by several factors. These factors could be the product type, the price point of the product, and the need for replacement. If you can predict buyer behavior, then it would be much easier to market to them.

For instance, let’s say you manage a grocery store, and can easily predict when your customers need to replenish their product stock. Marketing to them when they need to replenish their stock is a sure way to drive more sales.

Monetary Value:

The monetary value boils down to the amount of money the customer spends. Customers who spend money are to be encouraged to spend more. Although this method is sure to generate better ROI, you may end up alienating loyal customers who may not be spending much.

How Does RFM Analysis Work?

Now you’ve figured out what RFM marketing is, and how the recency, frequency, and monetary metrics are determined, the next step is to figure out how it works. With the RFM marketing model, the customers are scored on three primary factors.

And the scoring ranges from 1 to 5. With 1 being the lowest score while 5 is the highest. The rules are not set in stone as there is another RFM marketing analysis model that uses different values.

An analysis is performed on each customer, and the three values are collected. These three values make up the RFM cell. There are organizations where the average of these values is taken, and customers are categorized based on how valuable they are to the company.

Customers are typically sorted from the highest to the lowest in value. However, there are other organizations where each of these three values is weighed separately.

For instance, a business person who sells outdoor running shoes may notice that a customer will not buy running shoes in a few months.

However, when the customer chooses to buy, the customer usually opts for bulk purchase – and that’s a clear sign of a high-monetary customer. As a business person, you may choose to put more weight on the value of the monetary score.

Charities and nonprofit organizations may also take advantage of the RFM marketing strategy. This way, they get to pinpoint their largest donors and also keep a close eye on donors who have donated in the past. After all, donors who have donated in the past will most likely donate again.

Finally, businesses that do not prioritize direct payment may opt for a different analysis model. For instance, apps and websites tend to pay more attention to interaction, number of views, or readership.

Direct payment is not prioritized in these businesses. And as such, these businesses are better off performing an RFE (recency, frequency, engagement) analysis and not the regular RFM marketing analysis.

What is the RFM Analysis for Customer Segmentation?

Instead of having a single customer database, segmenting your customers and putting them into various categories is much preferable. And when it comes to segmenting your customers, you can do that using characteristics like geography or age.

After that, you get to create separate campaigns for each of these categories. These campaigns will most likely be personalized and well-tailored to meet the needs of the customer.

The RFM marketing model applies to real-life situations. But to get the most out of it, you need some advanced math skills or top-tier analytical expertise. Furthermore, the RFM model varies in complexity and sophistication.

A typical RFM scale ranges from 1 to 10, and each customer is ranked in the recency score, monetary score, and frequency score categories. A score of 10 is the highest and makes up the top 10% in each category.

In other words, a score of 10 pretty much shows the most frequent transaction, the most recent transaction, and the customers with the highest purchase. A score of 1 is the lowest score on the scale.

An RFM scoring system is a sure way to create a more robust marketing strategy and effectively categorize your customers. Speaking of categorizing your customers, the RFM marketing model will help you identify:

1. Your Best Customers:

Customers who fall into this category are loyal, generous spenders, and you’re more likely to have repeat sales from them. These customers are top scorers on the scale.

And you have to target them with your loyalty programs or any new product (or service) offering. Since these customers are loyal to your brand, offering them discount pricing will be a wrong business move.

However, you should aim to boost your profit potential by using their purchase history to recommend more products. Also, you can recommend some big-ticket items to these customers.

2. Your Big Spenders:

These customers rank high on the monetary value scale. If you have top-tier subscriptions or luxury offers, then these are the categories of customers to target. Furthermore, you’ve got the option of upselling these types of customers. It doesn’t make business sense to offer discount sales to this customer type.

3. Your Loyal Customers:

These customers rank high on the frequency scale. Although they make regular purchases from your brand, that doesn’t translate to big spending. You should consider offering them some rewards. And these rewards could be in the form of free shipping or other incentives you come up with.

4. Your At-Risk Customers:

These are customers who have ranked well as big spenders or loyal customers but have a recent low ranking in the recency and frequency scale. You can rekindle their interest by offering exclusive offers, discount pricing, or targeting them with new product launches.

There is the option of creating a specific customer journey that is aimed at retaining or re-engaging these customers.

Steps to Performing RFM Analysis

Here is an overview of how to perform an RFM analysis.

1. Build RFM Model:

You can get started by assigning a recency score, frequency score, and monetary score to all your customers. Getting this data is easy. All you have to do is look through your previous transactions with your customers. After that, you have to compile your data in a database or spreadsheet.

2. Divide the Customer Segment:

Separate your RFM database into various group tiers. And the separation should be dependent on the score of the customers. For instance, tier five could be made up of high spenders, while tier one could be made up of small spenders.

3. Select the Targeted Customer Group(s):

You should choose the group segment with the most customer value. You can start by naming your preferred customer segments. For instance, your faithful customers, biggest spenders, at-risk customers, and best customers.

4. Craft a Personalized Marketing Strategy:

You can tailor a marketing message for each of these customer tier groups. And you can use their behavioral pattern to tailor your messages. The RFM marketing strategy helps you craft compelling messages that resonate with your customers.

What are the Limitations of RFM Analysis?

The RFM marketing model helps you gain insight into your customers. But it’s not an all-in-one solution to your customer analysis. You would need more than the RFM marketing model to discover a whole lot about your customer.

There are marketing tools that will help you discover things like the ethnicity, sex, and age of your customers. And when it comes to predicting your customer’s behavior in the future, the RFM marketing model may fall short.

RFM in PPC (Pay-per-Click) Marketing:

Recency, Frequency, and Monetary (RFM) are valuable metrics to consider in PPC (Pay-per-Click) marketing for better audience targeting and campaign optimization.

Recency measures the time elapsed since a user’s last interaction with your ad, frequency measures the number of times a user has interacted with your ad, and monetary value measures the amount of money a user has spent on your product or service.

By combining these metrics, you can identify your most valuable customers and target them with personalized and relevant ads, maximizing return on investment.

Additionally, RFM can help you segment your audience and create tailored campaigns for different customer groups, leading to higher engagement and conversion rates by using leading platforms like Google Ads.

How RFM Can be Analyzed on Google Ads Campaigns Data?

Recency in Google Ads can be measured using conversion tracking, which allows you to see when a user last interacted with your ad and made a purchase. Frequency can be measured by tracking the number of times a user has clicked on your ad, visited your website, or taken a specific action.

You can understand the monetary value of your campaigns by knowing the conversion value, and the CLV (customer life time value).

To get the most out of your PPC analytics, you’ve got to use the RFM marketing model with another tool like the PPC Signal. The PPC Signal helps you detect any anomaly and other unexpected scenarios in Google Ads campaigns so that you can take action to correct it on time.

With this tool you can easily get an alarm if there is some scenario occur that customers are interacting with your ad but still there is no significant positive change is coming in conversions and monetary values.

Here’s what the PPC Signal dashboard looks like.

The PPC Signal uses a data-driven approach to offer insights about the anomaly of your campaign. This way, you get to take quick action. Information is displayed in the form of signals, and there are filter options on the left side of your dashboard.

For instance, let’s say you’re using the metric filter, you get to analyze the information as shown below.

You can explore the anomaly as shown below.

The signal above shows you that something is wrong, and you can correct it by taking the necessary actions. There is also the option of displaying the information in a graphical format. To do that, click on the Explore button.

From the image above, the yellow lines represent clicks, while the blue lines represent conversions.

Both have started to in opposite direct from the last 7 of days, which is showing that customers are engaging with your ad but getting difficulty in getting convert.

In result your cost on this campaign will definitely be increasing as your clicks are consuming budget. You need to have quick focus on your conversion flow in your landing page to fix this scenario. So that you can generate more customers without wasting much budget on acquiring them.

FAQs:

What Is Recency in the RFM Model?

The recency factor argues that customers who have recently bought your product will likely buy again. The data can help you tailor a message to your recent customers to prompt them to keep buying from you.

What Is Frequency in the RFM Model?

A customer’s frequency is dependent on factors like price point, product type, and the need for replacement. A good grasp of these factors will help you tailor the right messages to the right customers. It also helps in the delivery of the right message at the right time.

What Is Monetary Value in the RFM Model?

The monetary value focuses on the amount of money the customer spends. With the RFM marketing model, you get to encourage the heavy spenders to keep spending.

What Is Customer RFM Analysis?

RFM marketing analysis helps in grouping and ranking customers based on their recency, frequency, and monetary value. This way, you get to pinpoint the best customers and focus your marketing campaigns on them.

Wrap Up:

The RFM marketing model helps you identify your best and most loyal customers. This way, you get to target them with the right messaging to boost their customer lifetime value. Data generated during the RFM marketing is solely based on the customer’s history.

That means RFM marketing is not the right choice for business persons who are looking to predict their customer’s behavior in the future.

To get the most out of your marketing campaigns, you need to consider using RFM marketing with other tools like PPC Signal. This way, you get to generate your desired result without wasting your time and resources.

The PPC Signal helps you monitor your campaign and quickly correct any anomaly you may see.

Now you know what RFM marketing is, how will you determine your most valued customers?

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