How to get useful survey results
Employee surveys with algorithms & AI can aid in increasing the participation rates and accuracy of answers in survey results.
We all know what it’s like: you get surveys in your e-mail inbox, requesting you to evaluate a service or your own employer. The questions and answers you can select are often the same. So, most people just sign off.
A low response rate is not only irritating. If the rate is too low, the responses are not particularly informative either. So how can we prevent a certain lethargy from the side of the user?
In classic employee surveys, a response rate of 60 to 80 percent is considered very good. Oftentimes participants will drop out while completing a survey or not even want to begin due to tedious user journeys. 70 to 90 percent of those who drop out do so on the first set of questions – if they even get that far. It is important to avoid overloading the first set of questions, as well as enabling a user journey that does not present any breaking points. In this case people usually think of single sign-on or modern survey solutions in which surveys can be answered directly in the e-mail.
Advanced technology for more accurate survey results
This is where algorithms and artificial intelligence (AI) can be implemented to help. Our database continuously stores new questions while surveys are being completed. Consequently, follow-up questions that are unexpected are produced. Depending on the answers that an individual gives, their survey will be structed differently from all others. Nevertheless, the end results can be compared and evaluated.
Our software for measuring and fostering employee engagement in companies adapts each survey individually. The software stores hundreds of scientifically based questions in the employee engagement category alone. There are also numerous additional questions on topics such as employee life cycle and employee experience. Together with the Zurich University of Applied Sciences, we are also continuously developing additional questions. So, when employees voice critique, they are asked pertinent questions so that constructive criticism is derived that can be taken into account and learned from. The tool is also interconnected: it interacts between topics and accesses the respective surveys in the various topical categories. Thus, the employee survey is never monotonous, but develops through continuously new content managed by the company.
It also depends on the industry: What works for engineers may not work for a financial institution. Therefore, the algorithm suggests different measures depending on the industry or employees. Generally, all tools are customer-specific and customizable.
Based on how often a pulse check is conducted, the number of questions also varies. After all, a person who completes a survey monthly or weekly should be able to complete it more quickly than someone who only does it three times a year.
What comes after the survey results?
Ensuring that employees feel their needs are being taken into account means processing survey results quickly. However, very few companies succeed in making the results of employee survey available immediately to those involved, as well as deriving specific measures. If employees don’t hear anything for months after a survey, they are less likely to participate again. A good idea is to give employees the option of making their answers “public”, i.e. to share them directly with their manager and at the same time initiate dialogue and an exchange of information.
Our software provides results in real-time. This ensures high participation rates for future surveys. AI is applied to take the user experience to the next level. Machine learning is applied to identify tendencies in answering surveys. If, for example, the participation rate on Monday and Friday is significantly higher than on Wednesdays, or people more often answer surveys in the morning rather than afternoon, the software learns and adapts accordingly.