The basic premise/purpose of key driver analysis is to determine the attributes that most influence customer attitudes and/or behaviours, be they brand identification, brand choice, purchasing intention, or post-purchase drivers of satisfaction, repurchase intention, or brand advocacy (i.e., customer WOM).  The goal of this type of analysis is to identify the smallest set of attributes that has the greatest impact on overall brand performance or loyalty.

The most common methods used to identify relative importance are importance ratings and trade-off methods (e.g., rank ordering, constant sum). These types of methods, however, require first a survey of customers to collect such data.

Traditional Key Driver Analysis

This example suggests that "the company's ability to deliver on what was sold," "customer service," and several other tertiary attributes tend to drive customers' decision process, while "the account executives depth of knowledge about the market place," and "the company's proactiveness in suggesting new products and services" are relatively less important.

More advanced statistical methods can also be used to identify key drivers and to determine their relative importance, including correlations and multiple regression. These types of methods can often be easily used with existing CRM databases and are minimally intrusive. However, the results are limited to the quality/depth of the information available.