- What is a "Intelligent Question Sampling"?
- Why use it?
- How does it work?
What is "Intelligent Question Sampling"?
At the beginning of each survey/pulse round, Perked! distributes all your survey questions amongst your employees. Each person receives a personalized subset of questions that is small, manageable and takes only a few minutes to complete. Our algorithms assign these questions so that you receive representative feedback from all aspects of your organization in the most efficient manner. Over a series of surveys, every employee will complete the full set of questions in a way that isn’t overwhelming.
Why use Intelligent Questions Sampling?
1. Better quality insights
The Intelligent Question Sampling methodology is designed to gather feedback on every aspect of your company’s culture as quickly as possible - while considering the need for quality feedback. By covering all of the drivers at the same time, instead of only certain drivers in each survey (or having themes in each survey), you will be able to:
- View trends faster. This is especially important when you’re trying to figure out the impact of an event or action you’ve recently taken that affects multiple facets of your company’s culture.
- Prevent you from missing out on the important issues influencing the engagement of your employees.
2. Reduce survey fatigue
Keeps surveys short. Adds variety to each survey round.
Imagine doing a weekly, bi-weekly or monthly survey where you are asked the same questions over and over again. Over time, you’ll get tired and bored of answering the same questions. Our sampling methodology allows us to keep your surveys short, because you do not need to ask all questions to all employees at the same time to gain insight into how your company culture is doing.
How does it work? How are questions distributed?
The intelligent question algorithm takes into account each employee’s personal survey history. We prioritize the questions an employee hasn’t answered recently. Over a series of surveys, every employee will complete the full set of questions in a way that is not overwhelming.
More technically speaking: For each employee, our algorithm picks questions based on weighted probabilities among the question set. The weights are inversely related to the last time the question was last answered by an employee – the longer it has been, the higher the probability of picking that specific question.