Evolution of Customer Segmentation
What?
The practice of dividing a customer market into sub groups based on shared characteristics relevant to marketing.
How?
By identifying key differentiators such as customers' demographics, geography and psycho-graphic and behavioral tendencies.
Why?
Every customer is different. Effective marketing will increase return on investment and reduce cost. Marketing efforts are better served if we target specific, smaller groups with messages that consumers find relevant. When we send personalized messages that are designed around customers’ needs, they tend to be more valued and appreciated by the customer as opposed to impersonal brand messaging that doesn't acknowledge purchase history or any kind of customer relationship.
Evolution
The earliest form of marketing was carried out with no data about customers in mind and an undifferentiated segmentation strategy - Mass Marketing
“Any customer can have a car painted any color that he wants so long as it is black”
Henry Ford
With advent of data storage concepts, marketing was carried out using limited internally recorded data.
Demographic/Geographic Segmentation
Based on data that is relatively constant over time.
- Demographic data: Age, race, religion, gender, family size, ethnicity, income, education level, etc. Based on Income Demographic, Car manufactures marketed versions of the car to customers from various economic backgrounds. I.e. the entry-level model to customers from lower income groups and the featured luxury edition to prospective buyers from higher income groups.
- Geographic data: Country, region, city size, population density, climatic zone, etc. Geo-cluster segmentation is widely used by Governments and public sector departments such as urban planning, health authorities, police, criminal justice departments, telecommunications and public utility organizations. For example, due to the large numbers of Japanese visitors Melbourne erected Japanese signage in all of its tourist precincts.
Over a period of time, market segmentation was carried out using transactional and behavioral data of customer accumulated over time. This too is using only internal data.
Transactional Segmentation
Based on purchase data of customers, we can classify them into segments with varied engagement with the merchant. Using KPIs like number of purchases, products purchased, value of purchase, AOV (Average Order Volume), CLV (Customer Lifetime Value), cost of acquisition, acquisition source, etc. we can categorize customers into Highly Engaged, Moderate Engaged, Light Engaged, Never Active, Dormant segments.
A more recent segmentation technique is the RFM, which is a refined version of transactional segmentation.
- Recency - How recent did the customer purchase?
- Frequency - How frequent does he purchase?
- Monetary - How much does he spend?
Each customer is given a score out of a scale (say 1 to 10, 10 being the maximum value) for each of the three categories. The combined result from the three scores gives the customer a value (commonly known as the RFM score) based on which he can be categorized into the desired engagement segments.
Behavioral Segmentation
Based on observed customer behavior patterns in purchase data, we can classify him into segments with varied purchase intent towards the merchant. The behavioral variables and descriptors used to segment customers must be customized for the audience, application and special conditions.
Let us say we are marketing an energy drink to a customer market. We can use the following variables
- Purchase/Usage Occasion: This refers to the consistency of product purchase. We can categorize customers into daily purchasers, weekly purchasers, monthly purchasers and only during special occasions.
- Usage Rate/Purchase Frequency: This refers to the frequency of product purchase. We can categorize customers into light users, moderate users and heavy users.
The difference between the two is that, a customer can buy the drink every month in bulk, but still use it every day.
Nowadays, market segmentation is carried out using both internally and externally recorded data. External data can be from social media, surveys, blogs, web activity etc. These types of marketing are one-to-one marketing where we employ hyper segmentation strategy to segment customer market.
Need Based Segmentation
Leonardo DiCaprio says, “Sell me this ****** pen right here” and gives the pen to Jon Bernthal. Jon asks Leo, “Why don’t you do me a favor? Write your name down on that napkin for me?” Leo replies, “I don’t have a pen.” Jon says, “Exactly. Supply and demand, my friend” and tosses the pen to Leo.
Wolf of Wall Street (Diner scene)
By understanding the want and need of customers we can effectively target specific segments with relevant product marketing. Below are a few common segments created using customer needs and their corresponding optimal product marketing:
- College Students: Market college supplies and affordable living essentials to cater to this segment.
- With kid/baby on the way: Market budget friendly baby related products, organic products, educational toys, etc.
- New Residents/Home owners: We can market furniture, appliances and home décor to customers who moved recently.
Attitudinal Segmentation
By understanding the mindset of customers and perceptions of the brand or product we can classify them into niche marketing segments.
- Loyalty: We can segment customers based on brand perception into loyalists, non-loyalists, switchers and lapsed segments.
- Stage of customer: Based on his duration of exposure or usage of product we can categorize customers into specific segments. For example, as a cell phone manufacturer, we must target customers who are using their first smart phone and customers who have been using our product for many years differently.
Take Home
“Data! Data! Data! I can’t make bricks without clay.”
Sherlock Holmes
With the amount of data recorded every day, it would be a crime if we didn’t analyze it to the best our abilities and use it to target customers with utmost customization possible.
