Managerial Segmentation

build a relevant and actionable customer segmentation

by Mohamed Jendoubi, founder @ uluumy

“Marketing’s future lies in database marketing where we know enough about each customer to make relevant and customized offers to each”. Philip Kotler

The article sums-up the section Segment from our course Become a Citizen Data Scientist
In this article, we’re going to introduce the concept of customer segmentation. Then we will dig into how to do a managerial segmentation.

Definition

“Customer segmentation is the process of diving a customer into groups of individuals who are similar in specific ways relevant to marketing”. SAS

Types of segmentation

The literature about types of segmentation is very diverse.
The best I could find is the one given in the SAS paper “A Marketer’s Guide to Analytics”
It distinguishes between two main types of segmentation:
1-  Foundation segmentation: Core segments. It has these proprieties:
     •    All customers are included
     •    Each customer falls into only one segment
     •    Each segment can be subdivided into clusters.
     •    Attributes: value, profit, attrition, risk, demographics, firmographics, etc.
2- Targeting segmentation: identifies customers with specific needs and preferences. Useful for specific marketing programs and campaigns identifies customers with specific needs and preferences.
It has these features:
   •   Not all customers can be included
   •   Each customer may fall into many different segments
   •   Attributes: behavior, status, usage, etc.

 

A Good segmentation

A good segmentation must have these three features:
   •   Relevant to the business objective
   •    Simple: understandable and easy to characterize
   •   Actionable.

RFM method in a nutshell

RFM is an acronym for Recency, Frequency and Monetary.
Recency: number of days since last purchase/Use/visit
Frequency: number of purchase/use/visit
Monetary: Amount of purchase / time spent
Based on each of these 3 factors, all the customers are ranked and given a score from 1 to 4 (depending on which quartile they are). 1 being the best score.

RFM method has been around for decades. Yet it’s is still very useful

Now for each customer we have a composite score R-F-M.
As each factor could have 4 different values (1,2,3, or 4), We can in theory divide our customer into until 64 segments!!
It’s a good first step, but we cannot stop here because we want to have simple but ACTIONABLE segmentation.
That’s why we have used the term Managerial Segmentation

Managerial Segmentation

As a managerial decision we can decide that we need to have let’s say 9 different segments based on the RFM score we have already computed
Here are the definition for each of the 9 segments:
Best: R (1) AND F (1) AND M (1): it’s simple they have the highest score
Novice: R (1) AND F (3-4)
Active High Value: R (1) AND M (1,2)
Active: R (1)
Warm High Value: R (2) AND M (1)
Warm: R (2)
Win-back: R (3,4) AND {F (1) OR M (1)}
Cold: R (3)
Almost lost: R (4)

Actions

Now that we have our managerial segmentation, what marketing actions can we put in place
Here are some ideas/Examples:
   •   Best Customer: “Thank you” gift, “Exclusive preview” of new service/product
   •   Novice: Personal greeting message, Free shipping.
   •   Warm High-Value: Next best offer “Get $50 in “ZZZZ” $ for every $50 you spend”
   •   Almost Losto: “Last chance” special offer


Take a look to our course Become a Citizen Data Scientist

References:
SAS, “A Marketer’s Guide to Analytics”
Photos Credits:
Cruisers... by micadew CC BY-SA

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