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Profile variable

Digital impact

Age

Age can affect levels of access to technology, computer literacy, and eventually, the extent to which individuals use the Internet as part of their shopping routines. Age can also be linked to where people live and again affect the potential size of the online market; for instance if selling goods and services to China, the majority of online users are under 35.

Household size

Household size has the potential to affect the number of people involved in purchasing decisions and the direction of influence. For example, research has shown that in Europe children and teenagers can have a strong influence on purchasing based on their levels of computing competency.

Household type

Household type has the potential to affect product and service requirements; major shifts towards single person households in the UK (11% increase since 1971 to 29%) has led to a shift in purchasing patterns and times of purchasing. Online, such households can create logistical difficulties when delivering bulky and perishable goods (see Mini Case Study 10.1 for further discussion).

Income

Income affects primarily purchasing power, but also lifestyles and individual expectations of quality and levels of service will vary.

Gender

Generally, Internet populations still have a slight male bias which potentially affects the likelihood of being online and level of computing skills.

Ethnicity

Ethnicity affects access to technology and economic circumstances.

Employment status and work patterns

Employment places time constraints on online shopping behaviour, i.e. when individuals can access online shopping channels.

Mobility

Mobility affects channel access; less mobile targets may be encouraged to shop online. This also applies to macro-populations, which are poorly served by public and private transport.

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