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Survey responses are a valuable source of insights that can form a key driver for growth in a business. You must get results that are unbiased and accurate. Bias can be from respondents to your surveys or from the survey creators. It can be tempting to create surveys that confirm your theory, but in the end, you need results that can provide actionable insights that can help meet your goals for the long term.
Response bias is the systemic conditions and biases that can impact the responses your surveys get. Bias can be intentional as well unintentional and be an issue in self-reporting surveys. Bias is important because it directly influences the quality of your data. Bias can come from the researchers’ side as well, which is why it’s important to create surveys that are fair and balanced.
This form of response bias occurs when your participants change their behavior and their responses because of their participation in the survey. Some participants change their answers in their desire to conform to the survey’s findings. Demand bias can be triggered by:
All humans have biases that impact how they interact with the world. Researchers need to consider personal bias when creating surveys and when analyzing their responses. While it is impossible to avoid personal bias entirely, it can be contained to an extent. You can read more about avoiding survey bias here.
This is a tricky one. Think about the last time you were faced with a difficult question about life, society, or politics. Did you give an answer that was truthful or one which you felt was morally correct? You can avoid this by framing questions in a way that doesn’t put the respondent on the spot.
Acquiescence is when a respondent chooses to respond positively to your survey questions, with dissent being when a respondent chooses no for your questions. This can be dealt with by mixing up the style of your questions, forcing respondents to pause and think.
Take a Likert scale question for example. Your respondents can typically choose from some variation of “Strongly disagree” to “Strongly agree”. Respondents who select options at either end of the scale can be said to have an extreme response bias.
A neutral bias, on the other hand, is when a respondent selects neutral answers more often than not. This is a sign of disinterest.
How you word your questions is crucial for soliciting unbiased answers. Your survey as a whole needs to be balanced with negative and positive responses. You should also avoid asking questions that could trigger an emotional response from your respondents.
If you need to ask open-ended questions, then be certain about framing your question as neutrally as possible – You don’t want to lead your customers to an answer.
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Every demographic can have its own type of bias. While framing your questions you need to keep your demographic firmly in mind. You need to ask yourself a few questions:
CATI surveys are an excellent way to conduct large-scale research studies. They can allow researchers to target demographics that would otherwise not be interesting in taking part in a survey on other channels. However, you will require skilled interviewers to conduct CATI surveys. Your interviewers need to pick up on tics exhibited by respondents and be able to convince them to share their opinion on sensitive topics from time to time.
Unfinished surveys can often give misleading insights that resemble bias. Survey software like Voxco’s research cloud can integrate rewards in surveys. This can help encourage people to participate in your surveys, and most importantly complete the surveys.
Survey fatigue can make respondents click on random answers – just because they want to get the survey over with. Survey fatigue can contribute to response bias and affect the quality of insights you can expect.
Using multiple question types (audio and video survey questions are an option!) can break up the monotony in your survey and ensure respondents put more thought into their answers. If possible, ask questions about multiple topics in your survey.
Whether it’s a Likert scale questionnaire or a simple yes/no survey, you need to give the possibility of a negative or neutral. Sometimes a respondent may not see an option that best describes their response which forces them to choose the wrong answer, thus tainting your survey with bias. The ‘don’t’ know’ option in a survey can be a valuable source of data by itself, too.