Causal research
In FMCG for instance, a brand may wish to measure the likely impact of charging for carrier bags on their plastic packaging consumption, or perhaps against consumer sentiment. Alternatively, a clothing retailer may wish to investigate the possible effects on sales when choosing to sell underwear as separates, rather than in multipacks.
Whilst this form of prophetic research can prove to be a vital tool in successfully managing and adapting brand strategy, causal research may also involve the analysis of pre-existing data. Some of the most common causative influences regularly monitored and utilised by brands include the investigation into the effects of weather patterns on levels of consumer footfall, or perhaps, the average number of items per transaction against levels of consumer confidence. This form of research can be particularly helpful for operational planning. For instance, if the level of footfall for a retail park tends to rise dramatically during wet weather conditions, brands can ensure a full staff rota during these forecasted periods in order to cope with the extra levels of demand and maximise potential levels of revenue.
By quantifying the effects of variables, casual research in both forms allows companies to make accurate estimations of both natural business patterns and the results of strategic changes in order to aid both effective and successful operational planning and brand strategy.
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Contact us today to discuss your next market research project and discover how we could become a valuable extension of your team.
Contact usContact us today to discuss your next market research project and discover how we could become a valuable extension of your team.
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