Introduction

When surveying customers or employees, understanding which aspects of your business truly drive satisfaction and engagement is essential – and this is where key driver analysis becomes invaluable. While many companies gather feedback on various touchpoints, such as product quality, customer service, or employee development, knowing which factors have the greatest impact allows you to prioritise areas that will make the biggest difference to your business goals.

Key driver analysis enables you to determine which elements of the customer or employee experience most influence satisfaction. For example, in a customer survey, statements might cover products, service, and brand, which are core touchpoints in the customer journey. In an employee survey, you might explore aspects like leadership, training, and rewards. By analysing these areas, you can focus on what matters most, using data to make decisions that lead to higher satisfaction and engagement. This guide will walk you through the role of key driver analysis and how it can drive impactful actions.

1. Designing Your Survey for Effective Key Driver Analysis

Before you can perform key driver analysis, you need to design your survey with this analysis in mind. Start by identifying which statements or attributes are most relevant to your organisation’s goals. For instance, a customer experience survey for a supermarket might include statements about product range, staff friendliness, and ease of finding items in-store.

Selecting Key Touchpoints for Maximum Insight

Choose statements that reflect the essential elements of the customer or employee experience. Customer surveys often include touchpoints like “value for money,” “product quality,” and “staff knowledge.” In an employee survey, key touchpoints might focus on aspects like “opportunities for career growth” or “support from management.” These statements are rated on a Likert scale to capture satisfaction levels, making it easier to perform key driver analysis once the data is collected.

2. Understanding Key Driver Analysis: Linear Regression for Market Research

Key driver analysis is often conducted using linear regression, a statistical process that estimates relationships between variables. Linear regression allows you to see how changes in one (independent) variable, such as “staff friendliness,” impact a dependent variable, like “overall satisfaction.” Variables with a significant impact are identified as key drivers, providing clear direction on where to focus improvements.

Example of Key Driver Variables

To illustrate, let’s consider a supermarket customer survey. Independent variables might include:

• Product range
• Staff friendliness
• Product quality
• Convenient location
• Waiting times
• After-sales service

Dependent variables, on the other hand, could include:

• Overall satisfaction
• Likelihood to recommend the store
• Likelihood to shop there again

By running a regression model, key driver analysis identifies which independent variables (e.g., staff friendliness, product quality) have the strongest influence on the dependent variables. This insight is critical for prioritising actions.

3. Prioritising Actions Based on Key Driver Analysis Results

Once you’ve identified the key drivers of satisfaction or engagement, you can use these results to prioritise actions effectively. Often, a survey might cover a wide range of factors, but key driver analysis will reveal which ones are most important, allowing you to allocate resources more strategically.

Identifying Quick Wins and Long-Term Improvements

One of the main advantages of driver analysis is that it helps organisations identify both quick wins and areas that require more time or resources to improve. For example, suppose your analysis shows that “waiting times” is a significant driver of satisfaction but currently scores low. In this case, introducing a queue management system might lead to a swift improvement in satisfaction scores.

Plotting performance and importance on an impact matrix can further clarify which drivers are underperforming relative to others. Areas with high impact but low performance represent “low-hanging fruit” where improvements can have a substantial effect on overall satisfaction.

4. Enhancing Key Driver Analysis with Qualitative Feedback

While key driver analysis offers valuable quantitative insights, adding qualitative data can deepen your understanding of priority areas. After identifying key drivers, consider reviewing relevant customer comments or running focus groups on those topics. This qualitative approach provides context that can help you develop targeted strategies and understand the specific factors behind satisfaction scores.

Using Focus Groups and Customer Comments

For example, if “product range” is a key driver, but feedback indicates a lack of variety in specific categories, focus groups can help identify which products to add. Similarly, if “staff attentiveness” is a key driver of employee satisfaction, qualitative data might reveal specific actions managers can take to improve attentiveness.

Conclusion: Turning Key Driver Analysis Into Actionable Insights

Key driver analysis is a powerful tool for prioritising actions and ensuring your organisation focuses on the elements that matter most to customers or employees. By understanding which factors have the strongest impact on satisfaction or engagement, you can make targeted improvements that yield the greatest results. Whether you’re working to enhance customer experience or boost employee morale, focusing on key drivers ensures that your resources are invested where they will have the most impact.

Implementing actions based on robust analysis increases management’s confidence in decision-making, as priorities are data-driven and focused. By leveraging both quantitative and qualitative insights, organisations can create more effective strategies that lead to sustainable business growth and improved satisfaction.

For expert assistance with key driver analysis and prioritising actions for your market research, contact us at Robust Insight. We specialise in helping organisations gain clarity on their most impactful drivers for informed decision-making.

Robust Insight adheres to the Market Research Society (MRS) guidelines, ensuring that all our research practices meet the highest standards of quality, ethics, and professionalism. This commitment helps us deliver trustworthy and actionable insights for our clients.