Relationship surveys need to collect data about both key touchpoints along the customer journey and brand expectations, in addition to the overall relationship. Transactional surveys need to be focused on a few topics that are relevant to the specific experience or event.

Both relational and transactional formats need to begin with the appropriate primary metric and continue with a combination of open ended and driver questions to maximize both quantitative and qualitative analytics.

Regardless of feedback type, question flow needs to be smooth and logical, beginning with broad, top of mind feedback and continuing to specifics. Great questions lead to great responses which lead to great analytics.

Here are a few other considerations in crafting your survey questions:

• Relevance of questions by segment and role
• Clarity of language
• Globally appropriate native language
• Avoid question redundancy
• Avoid asking what you should already know about your customer
• Avoid asking about more than one thing in a driver question
• Consider how well questions enable analytics
• Consider whether questions address areas you are actually capable of taking action on
• Survey length should be measured in minutes to complete.

When considering survey length, keep in mind that business clients have a lot invested in you and are willing to spend more time providing feedback than consumers. In a B2B scenario we recommend a relationship survey should be able to be completed in 5 minutes or less. For a B2B transactional survey, 3 minutes or less. For consumer relationship surveys respondents should be able to complete in 3 minutes or less. For consumer transactional surveys, completion should be possible in 1 minute.

Far too many programs stop at the foundational step of collecting NPS scores through surveys. Even those programs that follow the demonstrated best practices in this guide by building out additional sources of attitudinal data usually stop before they take the transformative step of including operational data, which is a critical building block for predictive scoring. A complete, connected, and continuous set of data is a prerequisite for predictive scoring and a visionary NPS program. To get there, download our guide, take our comprehensive training course, or read about the future of NPS.