Conclusive research design

marketing. It is used when the purpose of research is:
a) To make predictions of market and consumer behaviour. For example, a manager will be highly interested in knowing differences in consumption pattern of cola drinks during different seasons and will be able to develop a marketing campaign accordingly for the forthcoming season.
b) To describe characteristics of a certain groups. For example, using its loyalty clubcard scheme Tesco (the largest retailer in the UK) is able to identify who are most profitable and least profitable shoppers by developing their generic socio-demographic profile which includes age, spending in Tesco (number of visits and spend per visit), gender, regularly consumed items and less frequently bought items etc.

way of conducting marketing research. It involves collection of information from any given sample of population elements only once. In simple terms, cross-section studies are just conducted once. For example, the manager of a cola company wants to know the preference of teenagers regarding their cola brand. This kind of study provides a snapshot of the variables of interest at that point in time, as contrasted to the longitudinal study that provides a series of pictures, which, when pieced together, provide a movie of the situation and the changes that are occurring.

design for monitoring changes over time, because it relies less on consumers’ mental capabilities and more frequently monitors events as close to their time of occurrence as feasible. The primary objective of longitudinal design is to monitor change over a period of time. It involves a fixed sample of population elements that is measured repeatedly.

the need to understand the reasons why certain market phenomena happen as they do. In other words, causal research helps in understanding which market variable (for example, packaging change) causes what effect on other market variables (supermarket sales). To measure this however, the data must be gathered under controlled conditions – that is, holding constant, or neutralizing the effect of, all variables other than the causation variable (in the case above packaging change). After neutralizing the effects of other variables researchers manipulate the causation variable and measure the change in the effect variable (in the case above supermarket sales). Manipulation of the presumed causal variable and control of other relevant variables are distinct features of causal design.