Survey data collection is just as important, if not more so, than the reports generated by that data.
Most market researchers, however, are more concerned about what the results of a given survey are saying rather than the data collection tools used to provide those results. Especially with all of the new web-based, do-it-yourself (DIY) data gathering tools popping up recently, there are many different options one can employ when conducting research. I won’t name any of them here because, while they allow for quick and dirty methods of obtaining data, they don’t do a very good job of trending and reporting.
Let’s first look at the quick and dirty aspect. Using DIY tools allow the researcher to quickly develop and deploy a survey on the internet, but without careful planning and long-range thinking, this may be the beginning of a giant mess. These tools do not restrict or recommend how to setup the underlying single file database. There are no established naming conventions for variables, nor are there any data validation methodologies employed by the software. I’m not trying to say that these tools should have these things built-in, because I think it would be too restrictive and lessen their appeal. Instead, this aspect is not being given enough respect by those responsible for setting up the data collection.
While this strategy works for small one-off surveys, it becomes more problematic when the survey is longer, more complex or is conducted multiple times per year (waves) or multiple years in succession.
If your survey involves more than one data gathering effort, then you will want to make sure that the variable naming and definition remain constant across those efforts. Also, you will want to make sure that the data integrity is intact, or that some validation/verification is being performed to make sure you don’t get invalid data. This can either be done on the front-end (during the data gathering effort) or on the back-end (through scripting or some other verification method).
These aspects of survey reporting are something to consider when employing your next data collection effort for market research. Though DIY survey creation is an exciting step for marketers there are still restrictions on using them for large, trending data sets. Whether or not you choose to use DIY tools or something more robust, planning out the data structure and integrity is critical to gaining key consumer insights.
If you’d like to learn more about how to prepare survey data for analysis, please download our whitepaper Ten Essential Prerequisites for Survey Data Analysis.