Market Segmentation
Market segmentation is the process of classifying a market into distinct subsets (segments) that behave in similar ways or have similar needs. The segmentation process consists of segment identification, segment characterization, segment evaluation and target segment selection.

If each segment is fairly homogeneous in its needs and attitudes, it is likely to respond similarly to a given marketing strategy.

The purpose for segmenting a market is to allow your marketing/sales program to focus on the subset of prospects that are “most likely” to purchase your offering. If done properly this will help to ensure the highest return for your marketing/sales expenditures.

Multivariate Solutions is an acknowledged leader in market segmentation, and we continue to advance the art by ensuring that the tools are agile and usefully applied. Our flexible, approach to market segmentation research enables us to design creative yet pragmatic segmentation frameworks for a wide array of market applications and industries in consumer market segmentation, business market segmentation, and healthcare market segmentation.

Market Segmentation Articles

Canonical Multiphase Segmentation, published in ADMAP, discusses segmentation as a vital tool in determining the effectiveness of ad spend.

Using open-source software to make sense of small big data, published in Quirk’s Media, describes how to use new capabilities with traditional marketing research deliverables.
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The premium market research statistical software offers and excellent introduction to segmentation, SPSS Tutorial-Cluster Analysis.

Coke Brand Differentiation Example shows how to differentiate between coca-cola consumption groups in order to plan targeting which will move Weekly drinkers into the Daily category and Monthly drinkers into the Weekly category.

After creating an add-value presentation with existing multi-wave data, Multivariate Solutions presented Mining Traffic Opportunities jointly with McCann-Erickson, New York.

Two-Step Segmentation utilizes first a traditional cluster analysis across several dimensions of attitudes or behaviors, then binds them in a second step based on a business rule, such as money spent or propensity to purchase a product.

Four A’s Model Segment Presentation examines four key measures in the study to determine key segments, Satisfaction with The Company, Would Recommend The Company, Likelihood to Remain with The Company, Magazine Purchase Intent and to determine key discriminators for each.

Small Data Visualization by Michael Lieberman presents two examples for examining primary research – a two-step cluster analysis and a data-mining example that takes existing consumer purchase data and reports the items in which the client should specialize to connect to the greatest number of other products.

The Power of Segmentation examines the price differences various segments of drivers are willing to pay for gasoline.