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How to interpret survey results

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How to interpret survey results survey
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After following all the necessary steps to create and conduct a survey, you deploy it to the target audience. And once the respondents submit their responses, the data starts flooding in. Now it is time to analyze the survey data. Data that comes in is always raw and random. To organize it and make sense out of it, survey data analysis is done to derive quality insights and results from it.  

In this article we will take a deeper look into how survey data is analyzed and how you can reach your survey goals.

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How to interpret survey results?

  • Pay attention to top survey questions 

When you set a goal for your survey, you probably have jotted down the top questions which directly serve the purpose of the survey topic and its results. While starting to analyze survey results, the first data to look at is that of these top questions. You get direct results through such questions. 

For example, the goal of your survey was to collect contact information of potential customers. This survey will have its top questions like contact number, email address, home address, etc. By directly looking at responses to these questions, you will get what you were looking for in the survey results.  

  • Sample size  

Sample size is another factor that affects the accuracy and effectiveness of your survey results. Sample size is nothing but the number of people that take your survey and complete it so that their responses add to final results.   

Determining the right sample size for your survey is a task. Although various online survey software does the work for you by predicting and understanding the complexity of the process. The survey results and their reliability are highly dependent on the sample size that took the survey.  

  • Filtering results  

When the survey results are ready and your analysis plan is ready, it is time to analyze and compare the subgroups. In filtering survey results, the same group analysis and comparison will be helpful.  

For example, you conduct a seminar on digital marketing. Everyone from the college, like students, teachers and administrators, attends the seminar. For a feedback survey that was conducted for the seminar performance, these subgroups and their responses and put against each other to see which group had to say what. 

  • Visual representations  

You might have seen various statistical data being represented visually for a better understanding. Well, survey results need just that. With a lot of close-ended quantitative questions, data is mostly numeric in nature, and this makes it easier to represent on a graph or charts. 

Another way of putting and representing your survey results can be using cross-tabulation or crosstab reports. It organizes your data into a table like the one above, which is far easier to look at and understand right away. You can compare the groups based on what their response is and how they differ. This helps you understand each group deeply and determine how survey results differ for each one of them. 

  • Benchmarking and comparative data analysis 

Let’s say you conducted a seminar feedback survey and the results came out saying 60% of the attendees enjoyed the experience. Although it does sound like a nice percentage, how do you say that your seminars are doing overall well with every take?  

This is where benchmarking and comparing comes in. It is nothing but marking your progress as you move forward with every survey, recording the responses and what respondents had to say and comparing the new one with the previous one. How will it help though? Well, when you have a frame of reference to compare your result with, you can make an instant decision whether you did good or bad this time. As in the seminar feedback survey case, 60% is compared to the last seminar which had 75% satisfied respondents. This result indicates that the current performance is rather not very good. 

  • Concluding the survey 

Survey result analysis is nothing but converting raw data into meaningful information. What your respondents have to say will only reach you in a proper way if survey results are analyzed in the right way. After decoding the top questions, dig deep into the other questions to know what are the reasons behind specific responses and what can be done to make them better.  

Concluding the survey is probably the last step of survey result interpretation where you now have all the insights and information you need and you just have to make a decision in the right direction regarding the respondents’ opinions and views. 

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Tips for survey result interpretation

Here are some extra tips and prerequisites that you might need to have a look at before you sit down to analyze your survey results. 

  • Asking the right questions – for the quality data to be collected, asking quality questions is but obvious. Effective interpretation starts with the survey quality itself. Short, simple and direct questions play an important role in giving as much accurate data as possible.  
  • Grouping for open-ended questions – if your survey has more open-ended questions, prefer to group the answers based on their intentions and further dig more into their situational meanings. 
  • Key phrases – for open-ended answers where there are lots of words and sentences, pick out the commonly used words or phrases and put them together to get the sense of the survey result. Word cloud is also one of the best options when it comes to visualizing words that were used by the respondents. 
  • Don’t lose sight of your goals – it is best advised to interpret survey results through the lens of your goals. Keep in mind what you want to learn from survey data and keep digging in until the purpose is satisfied.

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