Key driver analysis (KDA)

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Key driver analysis (KDA)

Key driver analysis is used to determine the relationship between the dependent and independent variables. Often using a questionnaire, businesses will use it to understand the changes in customer behaviours, such as: recommendations, likelihood to buy a product and satisfaction.

The business will be hoping for positive correlations (independent variables positively effecting the dependent variable) but they would also wish to know how to improve their product if the effect was negative. Key driver analysis is also used to help establish target populations, which allow businesses to better assess their market places. 

For example, if it is found that there is a positive correlation between customer services and the likelihood of a recommendation, then customer services can have a beneficial impact on the chance of a customer advising other possible buyers to purchase the product. However, it can also work in the opposite direction. It could be found that there is a negative correlation between the branding and the probability of a customer buying the product, meaning the business would have to look at their marketing in order to sell more.

Key driver analysis is effective when used within surveys to discover links between two key bits of data. It is also efficient, cost-effective and easy to implement into a standard questionnaire.

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