Dealing with Lazy Survey Respondents — Drop Them or Keep Them?
It might seem obvious that inattentive survey respondents should deleted from your data. Think again. Here’s why a “light touch” during data quality review is best.
It might seem obvious that inattentive survey respondents should deleted from your data. Think again. Here’s why a “light touch” during data quality review is best.
One luxury of doing primary research is that you can get data perfectly tailored to the problem you need to solve. Primary research allows you to design how data will be elicited, and how, exactly, attitudes and behaviors are measured. Hence, you get the insight you need. If you don’t have perfectly tailored data, you…
Like most researchers who take data visualization seriously, I am not a fan of pie charts. But yesterday I came across a pair of pie charts that display data in a striking and visually compelling way. Indeed, they tell a story with data better than other alternative types of charts. The story here is obvious,…
Contrary to some widely held beliefs that mobile devices are a barrier to survey participation, a majority of survey respondents nowadays fill them out on phones, rather than on desktops, laptops, or tablets. Research has amply documented that the quality and reliability of data collected via mobile devices is comparable to data collected on desktops.…
Whether you’re a seasoned research professional, a newbie, or whether you dabble in research for other job responsibilities (like marketing or strategy) you will probably find something you don’t yet know in our winter newsletter with a feature article on 25 Things You Might Not Know About Research. It covers topics from stats, to charts,…
In our company we nearly always try to keep data collection “anonymous.” This means that for most of our surveys we intentionally do not know the identity of who participates (though our sample providers do). We rarely ask for any type of identifying information, not even a first name. If for some reason we have…
Customizing MaxDiff exercises by piping in text from previous survey answers might seem like a good idea, but analyst beware: if you are estimating individual-level scores using hierarchical Bayes or latent class analysis, you must split the data into subsets before you calculate the scores. Your results will be nonsense otherwise. Here is the scenario…
Surveys run the gamut from silly to serious, and from sloppy to scientific. Occasionally we do something silly if a client insists (though we generally advise against it). But we never do sloppy surveys, and we hope you never do them either. Lean as far as possible towards rigor and science within reasonable constraints of…
Nobody gets really good at market research by taking classes. It comes from learning on the job and in the field from other researchers. That is because researchers are always solving new problems and answering new questions that have never been asked before. That inspired us to make our summer newsletter The Big “How To”…
The problem with most business approaches to “analytics” is that they rely on automated, unthinking algorithms. The algorithms scan boatloads of data and generate correlations that are surprising and, therefore, presumably deeply insightful. But in most cases the correlations are not insightful. They are random coincidences, which unfortunately does not stop humans from sharing with…