Survey Analysis Pro Tips To Give You Better Insights

Survey Analysis: Pro Tips To Give You Better Insights

Have you collected your online survey data? If yes, great! Now is the time to analyze the survey results.

Survey analysis is defined as the process of analyzing the results of the surveys that you have sent to your customers to gain business insights.

If you have ever stuck in the middle of your excel sheet filled with rows of survey data and confused about what to do next, you are not alone. This post will help you execute the best practice survey analysis.

Data alone means nothing if you don’t analyze it. You must ensure your survey analysis provides meaningful results that help make better decisions about your business. Whether it’s been a few days or weeks since you last visited the survey, it’s a good idea to recall your purpose and survey’s goals.

Moreover, if your survey has been created and analyzed perfectly having the results delivered to the right decision-makers, will open doors to new opportunities to your goals.

Here’s how you can analyze your survey and look at the results of your survey goals to crunching the numbers and making conclusions.

What Top Research Questions Say?

How would you go about calculating survey results?

Ask yourself about what type of questions you have featured in the top research. Remember to outline your top research questions when you set your survey goal.

For instance, if you held a conference and provided attendees with the post-event feedback, one of your first survey questions might be, “How did the audience rate conference overall?”

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You can follow this above question by asking, “Do you plan to attend this conference next year?” having answer choices:

Yes

No

Not sure

The percentage you receive will give you an idea about how many people will be attending your conference. Once you have collected the basic results in your online survey software, you can analyze them to find trends, correlations, and other comparisons.

Filter the Results

Look back at your survey goal, recall the different subgroups you want to analyze, and compare to delve into conclusions. For instance, if you want to look at how people of different job professions like doctors, teachers, administrators, etc. respond to answering a certain question. For that, you need to look at response rates using “cross-tabulation”, where you can show the feedback of the questions by subgroup.

Cross-tabulation will help you with insights into how subgroups respond to specific questions. Once you gather the data, you can then think about how you can make improvements.

Filtering means viewing one specific subgroup’s result. Also, you can combine cross-tabulation and filter to compare different subgroups to each other. Remember that your sample size changes every time you add or eliminate a group from filter, so keep that in mind when making conclusions.

Compare Your Data

Let’s say you are pretty happy with the feedback currently. But don’t you want something to compare it against? Whether it is better or worse than the previous year?

You can ask in your feedback about last year’s conference to make a trend comparison. If the satisfaction rate has increased, you know what enables this rise.

Make sure you start collecting feedback after every event- this is called “benchmarking.”

This way, you establish a baseline number, and you can see how this has changed. You can track the attendees’ responses year after year- This is known as “longitudinal data analysis.”

You can also track the data for different subgroups and look at the responses to the survey to gain insight and improve accordingly.

Making Conclusions

The data of your survey results tell the story. Let’s say, your conference got mediocre ratings; you can dig deeper to find what aspects people didn’t like. For instance, they liked your sessions and classes, but they disliked the location because of the cold weather. This is the story right here- a tremendous overall conference, the wrong decision about the place. So, next time, you would choose the time and location when the weather is pleasant.

Now that you know the steps involved in survey data analysis, you can not only analyze it, but also implement strategies to improve it.

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