Uncover which variables impact on customers and drive satisfaction and change
Driver analysis is a statistical technique that aims to quantify the importance and influence of various factors on a particular outcome such as customer satisfaction or net promoter score (NPS). It allows you to uncover the underlying drivers behind consumer preferences, satisfaction, or behaviour.
Traditional methods of understanding importance involving asking survey respondents how important various factors are to them. While stated importance can be useful, driver analysis produces derived importance that reflect actual customer preferences and intentions.
At Lonergan Research, we employ advanced driver analysis techniques to produce actionable insights that drive decision making.
HOW DRIVER ANALYSIS WORKS
Our driver analysis methodology:
- Data Collection: Rating (Likert) scales are the most common questionnaire format for collecting driver analysis data through surveys. We also can conduct driver analysis on more custom performance measures.
- Statistical Modelling: We employ a host of advanced regression techniques (linear, ordered logit, negative binomial, Poisson) applied to a range of algorithms, (Shapley regression, Johnson’s relative weights) tailored to the question and relevant statistical assumptions.
- Insights & Recommendations: We interpret the results of the driver analysis, providing you with actionable insights and strategic recommendations.
- Customer preferences: Identify the factors that significantly influence customer preferences, enabling you to tailor your products and services to meet their needs effectively.
- Customer experience: Understand what really drives delight amongst your customers, so you can focus on the areas that will drive the greatest improvements in satisfaction, loyalty and advocacy.
- Brand loyalty: Uncover the drivers behind brand loyalty or perceptions, enabling you to optimise your marketing campaigns and messaging.
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