Survey Design is the large process of designing all aspects of a survey, from the targeting to the format. For non-researchers, it can be a daunting task to start designing a survey, therefore, here at Bounce, our Account Managers are here to offer you a helping hand when it comes to designing your survey. Our team will ensure that you are asking the right questions to help meet your research objective. In this blog, we cover the many steps involved in perfecting the art of survey design, helping researchers to get the most out of their surveys.
Survey Goals & Objectives:
Before you start to writing your questions or deciding on which audience you want, it is good practice to set your survey objectives and goals. You should always ask yourself why are we doing this research? What do I/we want to obtain from the data? You shouldn’t stray from your survey objectives, otherwise you risk getting responses back that don’t actually provide you with the information you need to achieve your research goal. Your goal will inform your survey objectives, so for example, if your goal is to understand what drives customer loyalty, my objectives would be:
- To determine the percentage of the current customer base that are likely to purchase our product again over the next 6 months.
- To assess the level of customer loyalty towards your competitors.
- To describe what unique need our products are filling that leads to increased customer loyalty
- To explore marketing factors that influence customer loyalty.
Having the right audience means that you can get the right answers and ultimately, get the most out of your research. By understanding your targeting tools and having a real targeting strategy you can do more with less. For targeting, on the Bounce platform, you can target based on the basic demographics such age, gender, & region. We also however offer a more specific behavioural targeting, such as coffee or alcohol drinkers.
It is a researcher’s responsibility to minimise the effect of the response bias as much as possible in a survey. Understanding bias is crucial in identifying weaknesses in your survey design. There are many different types of response bias when it comes to research but there are certain tips we can give you to help avoid these as much as possible.
Often connected to bias, ambiguous questions are a leading cause of frustration among survey respondents, reducing the quality of the data you are collecting, as well as your response rate. An ambiguous question is one that a respondent will struggle to answer, not because they are a bad respondent but because it is a bad question. Generally, ambiguous questions are too broad and leave room for interpretation by the respondents. An example of an ambiguous question could be “Please rate the speed and quality of our customer service”. This question would be confusing for a respondent as it is asking to rate on two different things, one of which they could rate well, the other not as good. To help avoid ambiguous questions, we always recommend testing your survey before giving it the final go ahead. You should go through the survey as if you are a respondent – are the questions easy for you to answer? How would you answer this question? Are all the possible options there for me to answer honestly?
Discover the basic question types that are used in surveys and find out the best practices to employ. There are many question types in survey design, but having a wide and diverse range of question types at your disposal allows you to customise your survey to get the best design possible. Having a variety of different question types makes it a more intuitive experience for the respondents, rather than answer the same question type each time.
Open Ended Questions
Open ended questions can empower the respondents, providing comprehensive data to researchers. However, knowing when to use open-ended questions can puzzle even the best researchers. Before setting any open-ended question, you should brainstorm possible close-ended questions that could replace that question. Open-end questions work well as an addition to a previous closed question to allow the respondent to explain their reasoning behind an answer. Having too many open-text questions can frustrate a respondent so you should only ask open-text questions for only the questions that you absolutely need to.
Conditional Logic is one of the most advanced features in survey designs, allowing researchers to customise the question path depending on their respondent’s responses. There are massive benefits to utilising conditional logic, pleasing both respondents and researchers alike. Using Conditional Logic will mean that you are always asking the right people the right questions and allows for a better respondent experience. Researchers should constantly be looking for ways to improve their survey design.
Survey design, more so than anything else, can make or break research and this process should not be rushed. Take your time and follow best practices. And remember, we are always on hand to help you out if you are still learning those best practices! For any questions or queries around your own research project, please feel free to contact our Account Management team.