The more effort you put into the planning a survey, the better the data it will yield. Start by contemplating your goals and target audience so you can ask the best questions.
To begin, give some thought to the overall structure of the survey, starting with your goals and perceptions about the extent to which your audience might feel engaged. Use those two things to guide the number of questions you ask and in what order. Customers who are more engaged with your product and have already provided some form of feedback — through help tickets or something similar — might be more likely to want to share their thoughts on your product with you. For that audience you might be able to create a longer and more in-depth survey that will generate good insights.
How you deliver your questions can make a big difference in the number of responses and the quality of responses you get. If you’re looking for quantitative data, a survey will serve you well. But for more qualitative feedback consider in person surveys — so customers can give feedback in their own words with a longer response.
Aside from format of your overall survey, pay attention to the kinds of questions you include. Instead of asking yes-or-no questions, consider including a like scale for more information on sentiment. Multiple-choice questions might generate more responses than open-ended one in online surveys. And certain topics might merit allowing people to choose more than one response.
A third and final point on your survey: include pages or question numbers in a progress bar. SurveyMonkey does a great job of numbering pages of questions or displaying how many questions a respondent has left. This assurance to the respondent will provide a higher completion rate for you and your company.
In general, try to make survey questions as simple as possible. Avoid jargon unless you’re surveying within a specific industry in which everyone speaks the same language. Also don’t ask more than one thing at a time. Take, for instance: “Were you satisfied with your experience and the representatives at our services department?” This question asks about two different aspects of the services department — the experience and the representatives. To get accurate data that you can really base decisions on, break this out into separate questions. If it makes the survey longer than you want, cut somewhere else.
Steer clear of absolute language that might yield skewed responses. For example, “Do you ever bike in the snow?” is an absolute. An individual who bikes once or twice a year in the snow may answer “no.” Consider rephrasing it and inlcuding a scale of frequency, as in “How frequently do you bike in the snow?”
Leading questions might steer your data away from objectivity, even when phrased more subtly than what attorneys object to in courtroom dramas. For instance, instead of asking, “Would you be more likely to purchase healthier food if it were cheaper” try “If fruits and vegetables were cheaper than they currently are, would you buy more or the same amount of them?”
By no means are the suggestions in this post a comprehensive list, but they’re a great start toward generating more precise data analysis and better-informed decision making — especially if you conduct the survey in SurveyMonkey, and then connect the resulting data into DataHero. The app categorizes it and suggests charts that will help you uncover the relationships between certain variables, filter responses to certain questions and share all the information in a dashboard. If you’re ready to give it a go, just click here to start analyzing your survey data in DataHero.
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