You’re conducting a customer survey, and you want to ask your customers about their experiences at your store.  Aside from testing their satisfaction and asking for feedback, you also include questions like: what products they are buying, when did they visit the store, etc.  When developing a survey you might want to reconsider the questions you decide to ask.  Before adding a question, ask yourself – can this data be found internally from your customer database? 

While basic questions about your customers, including products they’ve purchased and when, can be great for giving you a little more insight on who is responding to your survey or for confirming that respondent data is proportionate to your customer base, they should only be asked if you need the data.  Focus your survey questions on finding out the “why’s” or any type of information you cannot gather at the point of purchase.  Using the question to strictly conduct a simple analysis might end up being a waste, (i.e.: 20 percent of our customers are buying Product X) – this is what your internal database should be for (assuming you feel comfortable with the quality of your data).  Running an analysis on your customer records/database will give you an answer to that question with a much greater representation of your customers. 

Another solution would be to connect and merge survey data with customer data (when possible).  This will eliminate the need to ask questions of respondents that you already can find the answer to and open up opportunities for conducting in-depth analysis on the back-end.  There are all sorts of cross-tabulations that can be done between survey data and existing information.  One example of this would be matching data from a college student survey with student record data to explore the relationship between satisfaction with the college (survey data) and how long they’ve been enrolled (student record data).  By using a unique identifier, survey data can be compared with the in-depth records, which ultimately will be reported anonymously and in the aggregate.

The survey design process can sometimes be tricky.  There are always so many questions that need to be asked, but in many situations it’s important to keep the survey to the point.  A concise survey can make all the difference for factors such as data quality (more questions, more respondent fatigue) and budget restraints. 

Ultimately, it’s important to consider and reconsider the purpose behind each question asked.  If you’re stuck cutting questions, you have to realize that the end goal of your market research should be to learn new and/or difficult to find information that you know you are going to use.  This will allow you to get the most bang for your buck when conducting market research.