Marketing for shopping malls: Improve your marketing campaigns, more sales and customer engagement

What method can be used to implement segmentation?

RFM marketing is a simple but powerful marketing method to sift through consumer data and categorize customers in segments based on measured behavior.

RFM Analysis is a marketing model that analyzes customer’s purchase behavior and formulates “customer segmentation”. The objective of RFM Analysis is to segment customers according to their purchase history, and turn them into loyal customers by recommending products and services of their choice or preference.

By implementing RFM marketing we can response the following questions:

As we see RFM is a powerful tool that helps understand our customer base better.

RFM - How does it work?

RFM analysis starts by basically asking three questions about each customer:

• 1) How recently have they shopped with you (Recently)?
• 2) How often do they make a purchase (Frequency)?
• 3) How much have they spent (Monetary)?

By having all purchases in the digital platform and customer data, these questions can have their answers. In the case of the Mall is richer the analysis because it sees the big picture of all stores.

In RFM each individual customer is given a score from 1- 5 for each RFM component, with 1 being the lowest and 5 being the highest score. We then combine those scores (not the sum) to create a 3-digit RFM score, then RFM scores range from 111 to 555. Together, these three individual scores give us an accurate snapshot of each customer and help us determine what kind of offer, if any, we should target them with.

Let’s look at the following example to understand how RFM scores work in practice. Ana and Louis are two customers with the RFM scores:

Ana [5 1 2]
Louis [2 4 5]

As we can see in this example, Ana has a high rencetly score (5), but low frequency (1) and monetary (2) scores. It’s likely that she has just made his first purchase. Louis, on the other hand, has high frequency (4) and monetary (5) scores, but a low recency score (2). She has spent a lot of money and bought frequently but it’s been a while since she has made a purchase. The store or Mall may want to take a look at his purchase history and any other known information about her, to send her a relevant and valuable offer to get her re-engaged.

RFM scores for product categories

If a store offers multiple types of products or services, a customer may have an overall RFM score as well as multiple product or category specific RFM scores. For instance, Maria has purchased hats, shoes, and clothing, so her individual product scores are:

Hats [3 1 3]
Shoes [2 2 3]
Clothing [4 3 4]

Product/category scores allow stores to look beyond how often a customer shops with a store and how valuable they are, but also see any patterns related to the types of products they’re buying. This provides valuable insights that can help create very personalized messaging.

For example, if we detect a lapsed customer then we want to enroll them in a win-back campaign. Using their product RFM score, it is straightforward to determine whether that customer is interested in shoes or if we should send them an offer for clothing discounts.

RFM - Standard Customer segments

Here are some standard customer segments:

• Fresh leads – RFM score = 511
• New and promising customers – RFM Score = 514
• Loyal customers – RFM score = 453 (the frequency is what makes them loyal)
• At risk customers – RFM score = 324
• Can not lose – RFM score = 155, 245

Benefits for the Shopping Mall and Stores

The following are some of the benefits that can be achieved if RFM Marketing is implemented in your shopping mall.

Targeting your marketing based on RFM metrics allows you to focus your budget on areas such as retention and acquisition, while still moving customers to more reliable segments. Definitely RFM is a powerful tool which brings value to the Mall and each tenant that is part of it.