Two Things That Improve Accuracy With Survey Analysis Software

Analyzing survey data can be one of the highlights of a project, and you may be tempted to jump right into it as rapidly as possible. Don’t. Before you move forward analyzing data, you need to ensure the data is accurate. This can be done by first reviewing and then editing your data.

Reviewing Your Data

Giving your data a quick review may seem like an obvious task, but some people still skip it and dive right into the analysis stage. Taking the time to review your data can uncover essential information about your project, including any weaknesses in your response population or questionnaire design, which you may want to address before moving forward (read more: 7 Things You Need to Know About Survey Analysis Software).

While conducting your review, take a look at each question to make sure the results appear to make sense. Most people already have a general idea of what the collected data is expected to look like, and the review process allows you to spot any glaring inconsistencies or obvious errors.

The review also lets you see if the respondents are evenly distributed throughout your response population. Let’s say you launched a survey of your employees and you knew that 15 percent were in sales, 15 percent were in marketing, 40 percent were in manufacturing, 10 percent were in management and 10 percent were in finance or research.

If your survey responses are similar to the existing distribution, you’re good. However, if 80 percent your survey responses came from your marketing department, you would know that the results don’t accurately reflect a representative sample of all the departments throughout your firm.

Problems with the survey itself can also come to light during your data review. If a notable percentage of respondents skipped a specific question, or didn’t complete the survey at all, there may be flaws that prevent questions from being answered. Low response rates can indicate your survey invitation was poorly worded or poorly timed, and a follow-up reminder may be in order.

One more benefit of a quick review is its ability to point you in a direction for your analysis. You already had an idea of the types of responses you expected to get, but the review can reveal the unexpected.

Editing Your Data

The editing process is essential to consolidate information, and it’s best done once all survey responses are received. While you may end up changing or eliminating some responses, you want to make sure any of those changes don’t end up biasing your final results.

Eliminate responses if the respondent didn’t fill out enough of the survey information to make the response meaningful. If your survey was trying to track buying habits across demographic groups, for instance, and a respondent didn’t fill in any demographic information, the response needs to go.

Duplicate responses also need to be eliminated. You can typically pinpoint these by examining the answers to open-ended questions. When you find two open-ended responses that match exactly, review the remainder of the questions. If they, too, are an exact match, delete one version of the duplicate response.

Another issue you need to address are responses where people chose the “other, please specify” option, but then filled in an answer that was one of the choices listed above.  Here you want to adjust the answer as needed, changing it to the response that should have been initially selected.

An example might be if a person answered “other” and wrote “professor” when asked about their position at a university, even though “teacher, faculty or student” was a choice on the response list. Changing their answer helps ensure the “other” category doesn’t become overstated and the listed responses understated.

Reviewing and editing your data before diving into the analysis process can save you time and headaches down the road. It also ensures your survey analysis software is equipped with the most accurate data so it can provide the most accurate results.