If you crave a deep understanding of why your customers choose one product, concept, or message over another, you might be thinking that deep-dive qualitative research is best. Possibly it is, but you should also be considering a research method at the opposite end of the spectrum: conjoint analysis. Conjoint analysis is one of the…
Telling stories is a natural human behavior, but also highly complex and difficult to imitate or automate. This means that, happily, trolls can’t tell stories. And asking survey respondents for an extremely brief story (even just a few words) about their experience related to a survey topic can help you differentiate real respondents from fake…
Market research isn’t dead. It just keeps moving around and re-inventing itself as organizational needs for primary research change. Some of it has moved to operations groups, and now focuses exclusively on Customer Experience (CX). Some of it has moved to User Experience (UX) groups, as we have noted in a few recent articles (6…
A survey platform we have been using launched a new service promising an “expert review” of our surveys before we send them out for data collection. Unfortunately, it is a gimmick. It turns out that there are no experts reviewing our surveys. An artificial intelligence robot reviews them. It was interesting to see which best…
The online customer satisfaction survey I received today had me noticing an unfortunate side-effect of the NPS (Net Promoter Score) schema and visual imagery. For those of you unfamiliar with NPS as a way to measure and track customer satisfaction, here is how it goes. In your survey ask: “How likely are to recommend Acme…
Conducting surveys with your own customers is surprisingly difficult anymore. Phone options are dead, and online surveys are tough, because nobody answers or responds anymore. So what’s a researcher, strategist, or marketing professional to do? How about conducting a paper-based mail survey. It sounds crazy, but we just did it, and it succeeded beyond what…
While it is tempting to use advanced programming to “force” good answers and good behavior out of survey respondents, don’t do it. Let respondents make mistakes. Let them mess up, and then review who messes up. This is one of the best ways to assess data quality in a survey, and trust me you will…
If you make your survey questions hard, it turns out that people will make a good faith effort to answer them. But they will make mistakes, and you will end up with bad data that lacks reliability and validity. What I find so interesting is that most people will actually try to answer your hard…
Here is a sly little test I recommend giving the next researcher who offers up their help on your next quantitative survey. Ask if they have ever used a DIY survey tool, and what advice they would give you about sample size based on this selection tool you looked at from one of the largest…
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…