So, what should you be measuring about your responses and your respondents to get the most out of your survey data? Here are the metrics it’s vital you include:
The completion rate is, in simple terms, the number of questions answered divided by the total number of questions in your survey. This is important to know for countless reasons.
For instance, if your survey had any questions that your respondents were able to skip (were optional) or if they abandoned the survey, say, halfway through.
If you have a survey of 12 questions but most respondents only answered six of those questions, you have a completion rate of 50%.
Depending on the survey tool you use, the completion rate can indicate many things. For instance, if most respondents were only asked 6 questions out of a total of 12, because half of the questions were not relevant and were skipped, that’s likely a response rate you’ll be happy with.
But what if your 50% response rate results from people skipping questions willfully?
It might suggest that you may need to improve your survey. If you need more help improving your completion rate, we have a great report on best survey practices.
Number of Responses
You need to know exactly how many people answered in order to have enough data to properly analyze your results. Beware – some forms of survey tools may not count individual respondents, instead just their responses to individual questions.
Hence, it’s important that your survey platform allows you to count how many different people responded, so you can determine whether you have a significant sample size.
How do you determine the sample size you need?
This depends on what data you want to analyze, but you can choose whether to analyze data from your entire audience or just those from a chosen segment.
For example, if you are a beauty brand who sells face creams specifically for women over thirty-five, you may find in your survey that you also have younger women who use your products because they want to look as young as possible for as long as possible.
To obtain the data you want or data that may give you interesting insight, you may decide to segment these responses into separate age groups.
So, if you were surveying them on the effectiveness of a new age-defying cream, you may find that the women under thirty had very different responses to those in their sixties. This is the kind of data that you could have overlooked but can help you significantly with your marketing efforts (and will result in a survey report that’s pure gold!).
Date of Last Response
If you’re running a survey for a short and specific time period this may not seem important. Still, if you ask customers to fill out a customer service feedback survey after every ticket is closed, you may have years of data.
A lot can change over time, for your product, team, and customers, so it’s important to know if the data you are analyzing is still relevant.
For example, if you introduce a redesign on your website but have a standard survey you ask all new customers to complete after purchase that isn’t updated with the redesign, the total data may be invalid. This is because it takes into account the feelings expressed before the introduction of the new design.
My advice? Rather than scrapping all the data you have, if you can determine the response time, you can split your data and keep the responses that are relevant to each new implementation.
You need to know the total number of survey views and total of unique survey views (the number of total views versus the number of different people who viewed the survey, as some people may have viewed it more than once).
If there is a large disparity between these two totals, this can point to several things.
First, your survey may be targeted at a large audience and the questions aren’t relevant enough for all your respondents to answer.
Respondents may also view the survey and then decide not to take it because:
- they don’t have the time
- they don’t have the right device (things like open-ended questions can be difficult and tedious to answer on a small phone screen)
- or they see the first questions and decide that taking the survey isn’t for them.
A Breakdown of Answers Per Survey Respondent
You want to see how each person answered all of the questions so you can see how individuals answered all the questions in the survey. This can be helpful for seeing trends in certain respondents’ answers.
If you find a response to one question that is particularly insightful, you can find their other answers, too.
If you don’t have permission from the respondents to do this, then it’s crucial you remember that this data should be anonymous and must abide by GDPR and other privacy policies.
Breakdown of Closed-Ended Questions
When you think of a survey report, you likely picture graphs and pie charts displaying the data attained from closed-ended questions.
This is important for a good survey report because it allows you to take in a large quantity of data at a glance, and can be easily distributed to those who may find the data valuable.
Graphic representation makes survey analysis user-friendly and doesn’t require a lot of time or prior skills to analyze.
In this example, we can see the NPS (Net Promoter Score) at a glance – we know that over 75% of respondents are promoting our brand, 3.2% are detractors (and can and should be addressed as best we can), and that we had 800 overall responses. All of this data is plain to see and easy to interpret.
The best thing is that you don’t need a dedicated team to develop these insights for you. A great survey platform will organize your respondents’ data into an easy-to-read dashboard that saves you a ton of time and helps you start acting on the data you’ve received.
And hey – Survicate does just that, so why not give it a shot!