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Lifestyle Segmentation Profiles

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Title: Lifestyle Segmentation Profiles


1
Lifestyle Segmentation Profiles
  • Nicholas H. Campiz
  • Department of Geography

2
ACORN Type 3a High Rise Renters
  • Median age 37.9 years
  • Mixed ethnicity
  • Surprisingly affluent 50,000 median income,
    with many holding degrees
  • Prefer investing over saving
  • Found predominately in NYC, Chicago, Los Angeles
    and DC
  • Join health clubs and environmental groups
  • Engage in racquet sports, bicycling and jogging
  • Buy expensive clothing and frequent bars,
    theaters and museums
  • Read metro, fashion, and gourmet magazines, as
    well as a daily newspaper or two

3
Why Segmentation?
  • Imperfect competition the classical single
    demand schedule was inadequate.
  • The market is fragmented, and each sub-market or
    segment behaves differently.
  • Each customer also behaves and reacts
    differently.
  • Market segmentations goal is to strike a balance
    between the population as a whole and the
    individual

4
(No Transcript)
5
Segmentation
  • All segments are arbitrary
  • Segment is viewed as valid if it is measurable,
    accessible, sustainable, stable, and unique
    (Baker 2000)
  • Lifestyle segmentation A mix of geographic,
    demographic, and psychographic segmentation

6
Methodology
  • Most of the companies employ a similar, though
    far from identical, methodology to come up with
    their cluster assignments
  • These assignments are usually based around Census
    data
  • A host of other household and personal
    information is factored in, such as credit card
    statements, shopping habits, lifestyle surveys,
    etc.
  • Key characteristics are selected and run through
    statistical analysis to generate segments
  • Number of segments and groupings is up to the the
    company. Some say there is statistical
    significance behind the number of clusters, some
    say that it is half science-half art
  • Validation techniques usually include comparing
    the new clusters to characteristics that were not
    originally used in the formulation of the segments

7
Experians MOSAIC
  • 13 groups (worldwide) split into 62 subgroup
    classifications
  • Currently exports at the zip, census tract, and
    block group levels
  • New release to have data at the block level
  • Experian has been developing MOSAIC for almost 20
    years

8
MOSAIC
9
Global MOSAIC
  • Global MOSAICs are LSP databases that can be
    found in more than 17 countries around the
    developed world
  • These are Australia, Belgium, Finland, France,
    Germany, Great Britain, Greece, Italy, Japan, New
    Zealand, the Netherlands, Northern Ireland,
    Norway, Republic of Ireland, South Africa, Spain
    and Sweden

10
ESRI Tapestry
  • Formerly CACI ACORN LSPs
  • 11 Urban groups, 12 LifeMode groups
  • 65 segments
  • Data on the ZIP4 level
  • CACI is the grand daddy of LSPs. Development
    started in the 1960s

11
Claritas PRIZM
  • 15 Groups
  • 62 Segments
  • Data on the block-group level
  • Introduced in 1974
  • Works closely with MapInfo

12
Comparison Matrix
13
Examples of Possible Use
  • Pro Sport Teams

14
Expansion Moved Teams
15
Draws of the South
  • Fast growing population
  • A lot of new money
  • More likely to attend sporting events, especially
    football, hockey, basketball
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