Customer Segmentation and Predictive Modeling Improve the Results of Marketing Campaigns

There’s an important concept in marketing that you’re probably already familiar with called Customer Segmentation.
Here’s why it’s important:

• The more you segment your target market, the more you can customize your marketing materials;
• The more you customize your marketing materials, the more meaningful they become to your prospects;
• The more meaningful they become to your prospects, the more stuff you’ll sell. 

The more you know about Customer Segmentation and Predictive Modeling, the more stuff you'll sell. And that would be a good thing.

The bottom line — Customer Segmentation is an important concept because it can help you sell more stuff to more people. And that would be a good thing.
What are the different kinds of Customer Segmentation? Glad you asked. Here’s a summary of how Dr. George Belch and Dr. Michael Belch break things down in Advertising and Promotion.

Demographic Segmentation: This is pretty straightforward and something you’re probably doing already. Essentially, it’s dividing your target market on the basis of demographic variables such as age, sex, family size, education, income and social class.
You want to focus attention on the specific demographic groups that drive large chunks of your revenue. For example, when Ikea found out that 70% of their shoppers were women, they enhanced their store environment to be more “women friendly.” The results speak for themselves.

Psychographic Segmentation: Dividing your target market on the basis of personality and/or lifestyles is called psychographic segmentation. There is some disagreement as to whether a personality is a useful basis for segmentation, but lifestyle has been used effectively by the majority of sophisticated marketers.
The determination of lifestyles is usually based on an analysis of the activities, interests and opinions of consumers. These lifestyles are then correlated with the consumers’ product, brand and/or media usage. For many products or services, lifestyles may be the best discriminator between use and non-use, accounting for differences in food, clothing and car selections among numerous other consumer behaviors.

Behavioral Segmentation: Dividing customers into groups according to their usage, loyalties or buying responses to a product is called behavioral segmentation. For example, product or brand usage, degree of use (heavy vs. light), and/or brand loyalty are combined with demographic and/or psychographic criteria to develop profiles of market segments.
In the case of usage, the marketer assumes that non-purchasers of a brand or product who have the same characteristics as purchasers hold greater potential for adoption than non-users with different characteristics.

Benefit Segmentation: In purchasing products, consumers are generally trying to satisfy specific needs and/or wants. They’re looking for products that provide specific benefits to satisfy these needs. The grouping of consumers on the basis of attributes sought in a product is known as benefit segmentation.
Consider the purchase of a wristwatch. While you might buy a watch for particular benefits such as accuracy and water resistance, others may see a different set of benefits relating to style and prestige. Those different customer groups would be broken out using benefit segmentation.

Going Deeper with Predictive Modeling Customer Segmentation was just the starting point for marketing analytics. Demographic, Psychographic, Behavioral and Benefit Segmentation are important foundations, but they’re just the beginning. If you’re really going to get deep into this kind of stuff, you’ll want to get into  Predictive Modeling.
Predictive Modeling is used to describe the likelihood that a customer will take a particular action, usually in the form of a purchase. For example, a large telecommunications company will have a set of predictive models for product cross-selling, product deep-selling and churn.

Data, or different criteria, is used to analyze and predict how certain customer segments would respond to the marketing initiatives. The starting point might be to use Segmentation to develop your overall strategy and to use Predictive Modeling as a way to analyze transactional and other data to predict the likelihood that customer segments will respond to marketing messages.

Action Steps for You:

• At a minimum, you should have a good grasp of your different customer segments.
• You should also be customizing your marketing materials based on which customer segments will be receiving them.
• Ideally, you’ll also use sophisticated techniques like Predictive Modeling to super-charge your efforts and to improve the efficiency of your marketing programs.