predictive-segments-using-rfm-moengage-2

Predictive Segments Using RFM Modeling For Marketing

It goes without saying that serious marketers understand the importance of “know thy customer.” Instead of simply focusing on generating more views or clicks, marketers must follow the paradigm shift from increased marketing to the masses and generating views, opens, and clicks to retention, loyalty, and building customer relationships.

As a marketer, instead of analyzing your entire customer base as a whole, it’s better to segment them into homogeneous groups, understand the traits of each group, and engage each one of them with relevant campaigns rather than segmenting on just customer age or geography.

In other words, in order to deliver relevant, personalized, and timely content to your customers you need to look beyond demographics into behavior across different channels and more importantly you need to be able to do that in real time and of course without having to be a certified IT engineer, after all you are in marketing and not coding.

One of the most popular, easy-to-use, and effective segmentation methods to enable marketers to analyze customer behavior is the RFM analysis.

What Is RFM Analysis?

RFM stands for Recency, Frequency, and Monetary value, each corresponding to some key customer trait. These RFM metrics are important indicators of a customer’s behavior because frequency and monetary value affects a customer’s lifetime value, and recency affects retention, a measure of engagement.

The goal is to predict which clients are more likely to buy again in the future. RFM model is a proven marketing strategy based on customer behavior segmentation. It groups customers based on their purchase history – how recently, with what frequency and of what value did they buy.

RFM analysis helps marketers find answers to the following questions and more:

  • Who are my best customers?
  • Which customer has the potential to buy more?
  • Which customer has been churned out/has lapsed?
  • Which customer can the business afford to ignore to effectively utilize budgets?
  • Which customer can be converted by creating value through promotions?
  • Which of your customers are most likely to respond to engagement campaigns?
  • Who are the customers who buy only discounted items?

Through RFM, businesses can recognize and focus on converting critical customer segments like customers on the verge lapsing or dropping to becoming engaged and active customers. Through effective targeting, RFM helps businesses utilize their marketing budgets wisely and effectively, while also increasing the overall impact of marketing on the business.

How does RFM Work?

Historically, setting up an RFM model required some technical configuration based on some metrics defined by the business.

For example, a business would put the highest value (score) on a customer who shopped recently (say within a month), visited frequently (more than 10 visits per year), and spent a certain amount of money ($10,000 in the past 12 months). Then any customer who falls within that bracket will get the highest score and the business would then label that “segment” of customers (usually the name would be Champions).

The business can define different segments and give them scores so customers would be grouped according to their RFM score. The RFM combination is important because as a business you don’t want to focus only on high spenders who might be casual customers who don’t visit much or did not visit recently. Also you don’t want to ignore small spenders because they might be very regular.

However, as the name implies, the RFM model is about spend and visits but the customer universe is much more complicated than that. A business that is both online and offline needs to setup different criteria for online customers, offline customers, and both. Furthermore, customer demographics and engagement needs to also be included to optimize the marketing spend to target those who are engaged versus those who never respond to campaigns. You add to that product categories and NPS rating (customer feedback) and you get an idea about the different scenarios that a business would be looking at.

Sounds Complicated?

On paper (or on screen), yes all that might sound too much for a marketing team to handle. However, through AI powered segmentation along with simplified UI that is designed mainly for marketing teams, businesses are now able to easily and visually define the different customer groups that is relevant to their business then engage those groups in a personalized, relevant, and timely manner.

Technology should be an enabler not a hindrance. The UrbanBuz team had that in mind when they built the Audience product, which was designed to give the marketers full control over their data without the complexity and the overhead.

With UrbanBuz Audience, which is a standard feature of our CDP, you can create any customer segment you want based on the RFM model and beyond to really optimize your customer engagement and create exceptional customer experiences.

You can visually define your customer segments by easily combining all the different elements to fine tune each segment. You can combine demographics, with RFM, with browsing behavior, abandoned carts and more to create optimized segments.

Once created, the system would automatically keep each segment up to date and in real time so you can engage with the right audience in real time whether through our omni-channel Automated Journey product (where you can create full flows based on each segment), or through our omni-channel Campaign Management product.

You can also use the segments across different dashboards to have a deeper analysis of each segment’s data.

No certification required, all you have to do is click and define you segment and let our system do the rest.

 

 

You want see our platform in action? Book your next demo HERE.

 

Facebooktwitterredditpinterestlinkedinmail

Comments are closed.