Editor’s note: Chris Handford is the director and co-founder of Waveform Insight. This is an edited version of an article that originally appeared under the title, “10 ways to ensure your online surveys deliver quality data.” 

Surveys remain an invaluable tool in helping brands understand their audiences and find new opportunities. As creating online surveys becomes more democratized, there is an increasing danger of poor question design and UX leading to bad data. Bad data can lead to bad decision-making and costly misdirected choices. 

In this post I’ll look at 10 common pitfalls that I see regularly, and increasingly, see in survey design. 

In the early 2000s, creating and launching online surveys was typically the preserve of highly trained researchers. Starting out in one of the big research agencies of the day, you would put in months of extensive training before being let loose on launching a live survey. Extensive training in different question types and their purpose (categorical, dichotomous, ordinal, Likert, semantic differential, conjoint, etc.), question psychology, sampling techniques, survey UX, cleaning and processing of data were all the norm. Good survey design was both a science and art that needed years to master. 

Today, anyone can launch a survey. No data science training is needed. No survey craft to learn. Just a credit card and your choice of many self-serve survey platforms. But as great as removing barriers to research is, with more surveys comes more bad surveys. And more bad data. Ask the wrong type of question – or ask a question in the wrong way – and the resulting data will lead to poorly informed (and potentially costly) decisions. 

But many survey errors are easy to spot and avoid if you know what to look for. In this article, I’ll share a list of 10 survey design tips for delivering good data. 

Watch out for fuzzy answer lists, including numbered ...