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What is a metropolitan statistical area (MSA?)

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MSA (Metropolitan Statistical Area) Definition

A free-standing metropolitan area surrounded by non-metropolitan counties and not closely associated with other metropolitan areas. Each MSA is grouped by population size and coded using government FIP codes.

A metropolitan statistical area (MSA) is a geographic region defined by the U.S. Office of Management and Budget that represents an urban core and its economically connected surrounding areas. In market research, MSAs are used to analyze population trends, demographics and consumer behavior within specific urban markets.

Who relies on an MSA in market research?   

Market researchers, businesses, urban planners and government agencies rely on MSAs to understand urban populations. Companies aiming to target specific metro areas, such as retail chains, real estate firms and advertising agencies, often use MSA data to optimize their strategies.

What are key aspects of an MSA in market research?             

Key aspects of MSA in market research include:

  • Defined boundaries: MSAs are standardized, making data comparable across regions.
  • Demographic detail: Provides granular demographic, economic and social data.
  • Economic connectivity: Reflects areas with strong commuting and business ties to a central city.
  • Targeted analysis: Allows for focused research in specific urban regions.

Why are MSAs important in market research?    

MSAs are important because they help researchers analyze consumer behavior within defined urban regions, allowing for targeted insights. By focusing on economically connected regions, MSAs provide a realistic picture of market demand, preferences and economic conditions, supporting more effective decision-making.

How do market researchers use MSAs?          

Market researchers use MSA data to segment urban markets, analyze consumer demographics and identify regional trends. By focusing on specific MSAs, researchers can tailor marketing strategies, assess market potential and make data-driven recommendations tailored to each metro area's unique characteristics.