What Is the Key Driver Analysis?

Note: we recommend at least 30 responses for a statistically meaningful Key Driver Analysis (KDA). If your organization size is smaller than 30, please send your KDA-supported survey to "All Company” when creating the survey.

The Limeade Listening Key Driver Analysis (KDA) is an advanced statistical analysis that identifies which elements of a survey’s results have the most impact on the primary outcome that the survey is intended to achieve. The KDA will then recommend areas for your organization to prioritize so you know where to invest your time and energy to get the most return on your investment.

Want to learn about how to use our KDA? Click here!

Want a quick overview of some of our KDA best practices? Click here!

Why is Key Driver Analysis important?

  • It helps you invest in the right things. Each decision your organization makes to improve engagement is an investment. Since these decisions take time, effort, and money, you would expect to see a return from them. The Limeade Listening KDA helps you invest in the areas that will potentially give you the highest return on your investment.
  • It presents important takeaways - in real time! Just seeing high and low scores on a survey tells you what your strengths and weaknesses are, but it may not help you pinpoint the noteworthy results. Our KDA does this for you as soon as you have data for it to analyze.
  • It saves you time and money on analysis. With our KDA-supported surveys, you no longer need to pay hundreds of thousands of dollars for an external consultant or an in-house Data Science team. With the KDA, you can confidently present your data-driven proposals to your leadership team and colleagues. Your organization can move quickly with instant actionable insights and focus its time on action planning rather than analyzing data.

How does the Key Driver Analysis work?

In our Content Library, there is a list of Limeade Listening templates that are scientifically designed and statistically validated to be supported with the KDA. These templates have a "KDA supported" label next to them. You can also find them in the templates list when creating a survey to be sent out from the Manage Surveys page.

Each template has outcome questions that specifically measure the primary topic the survey is about. For example, our Engagement Survey has engagement outcome questions and our Benefits Satisfaction Survey has benefits satisfaction outcome questions. These outcome questions represent your users’ feelings and perceptions around a particular topic. 

Each template also has driver questions that measure more defined areas within the survey’s topic that can potentially impact the overall outcome. Driver questions are actionable and give you exact items to focus on. 

When is the Key Driver Analysis available?

While we recommend that you send KDA-supported surveys to your entire organization so your initiatives will have a company-wide impact, you can still send a KDA-supported template survey to any group of your Limeade Listening users as long as that group has at least 30 employees.

Our KDA works the best with a larger audience - the bigger the audience, the stronger the analysis will be.

On the reporting side, anyone who has super admin or admin permissions for Engage will have access to KDA. And, if you send out a survey to attributes or saved groups with more than 30 users in them and collect at least 30 responses, you will also be able to view KDA that are attribute or custom group-specific that admins and the group admins or viewers of these groups can view, too. 

Need help interpreting our Key Driver Analysis?



When you use a KDA-supported survey template and qualify for all the conditions to have the KDA, your analysis will include an Engagement, the Improvement Areas for Outcome, the driver Scores, the driver Impacts, and the Recommendations.


Outcome Score is computed using the average of the outcome questions. If the survey has only one outcome question, the outcome score is the score of that one outcome question. 

Improvement Areas for Outcome has from one to three driver questions that our KDA determined to have the most potential impact on your organization and that we recommend you focus on.

Driver Score is the average score of the question that makes up a driver.

Driver Impact tells you the predictive impact that a driver has on the outcome score - if you improve the driver’s score, it could potentially improve the outcome score. The driver’s impact has a scale of Extremely High, Very High, High, Medium, Low, Very Low, and Non-Significant.


  • Extremely High, Very High, High Impact - if you work on this driver, your outcome score will likely improve
  • Medium Impact - if you work on this driver, your outcome score could potentially improve
  • Low, Very Low Impact - if you work on this driver, there is a small chance that your outcome score will improve
  • Non-Significant - there is too much random data to determine a meaningful pattern or trend for this driver’s impact (this usually happens when the survey audience size is small)
  • Interested in learning more about the math behind how the driver impact is calculated? Read more here!


Recommendation is the action we recommend for each driver by combining driver’s two dimensions - Score and Impact. 


  • Prioritize: These drivers have low scores but high impact. You are not doing well in these crucial areas and will want to focus on these items so that you can have the highest return on investment (ROI) for your initiatives. 
  • Celebrate: These drivers have high scores and high impact. You are doing very well in these important areas and should commend your efforts to produce these strengths. 
  • Maintain: These drivers have high scores but low impact. You are doing well in these essential areas and should continue to sustain them even though they are not as impactful in comparison to other drivers. 
  • Review: These drivers have low scores and low impact. You are not doing well in these areas, but since they have less effect on your organization, you should look into making small improvements on these and divert most of your resources to more impactful items.


For a better understanding of how the driver impact and driver score interact, you can toggle between the Key Driver Quadrant view and the Key Driver Details view of your KDA by clicking on the three dots or the lines in the top-right corner of the All Key Drivers section of the analysis.



How is Key Driver Analysis calculated?

  • The Outcome Score is calculated using the average of the outcome questions. 
  • The driver Impact is calculated using Kendall’s tau-c, a statistical technique that measures the strength and direction of association that exists between two variables. Kendall’s tau-c evaluates the relationship between the outcome index and every other driver question in the survey. We then rank all the evaluations calculated. This technique involves looking at all comparisons between the outcome and each of the drivers for each of the responses then comparing the data trending with every other response's trending. Though the statistics are intuitive and simple, it is an intense calculation and evaluation with this many comparisons to find the trend. 

  • To determine the strength of a driver Impact on the outcome (x), we use the rules below from Kendall's tau-c calculation: 

    Extremely High: x > 0.6

    Very High: 0.5 < x <= 0.6

    High: 0.4 < x <= 0.5

    Medium: 0.3 < x <= 0.4

    Low: 0.2 < x <= 0.3

    Very Low: x <= 0.2

    Non-Significant: anything with p-value > 0.05

  • We use the average for all driver Scores as the score reference. Plotting all the drivers on the Key Driver Quadrant will give you the Recommendation as below. 

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