Pro feature: Available on Pro and Ultimate plans.
In app.getfeedback.com, the Key Driver Analysis is a Net Promoter® Score (NPS) follow-up question and dashboard tile.
The Key Driver question is a structured follow-up question that asks, “How would you rate us in these areas?” You can customize the question to include key areas of your business so you can measure their impact on your customer experience.
The Key Driver dashboard tile displays results from your key driver question to help you identify the business areas impacting your score. The tile results can help you proactively make changes to improve customer loyalty.
The NPS Key Driver tile isn't available in Workspaces.
You can create a new NPS survey with a Key Driver question or add it to an existing survey.
When you change a question type, any previous responses to that question are deleted. Consider making a backup of your survey before you change an existing NPS follow-up question (likely multiple choice) to the Key Driver question.
If you’re already using an NPS survey, you can add the Key Driver question to your survey. However, you should keep any existing questions to avoid deleting previous responses. There are two ways to add a Key Driver question without deleting existing questions:
Map your Key Driver responses to a custom Key Driver field in Salesforce or Zendesk.
Learn how to set up Salesforce custom mappings or Zendesk custom mappings
In your app.getfeedback.com dashboard, measure the correlation between your NPS score and key drivers to understand which areas of your business are impacting your customer loyalty. The key driver dashboard tile highlights the areas affecting your business so you can improve customer experience.
In your dashboard, select New Tile. Then, select your survey and the Key Driver question.
Here’s an explanation of the tile results.
We use Spearman's rank correlation on the NPS score and Key Driver question to calculate your correlation score.
Hover over your dashboard tile to highlight the statistical significance of the data (also called the P Score). The statistical significance helps us understand how likely it is that the score is accurate.