Using Google Surveys, we included a survey for users on a university website. After 148 completed responses and over 500 partial responses were collected, I imported the excel sheet into Airtable. Using Google algorithms provided useful and valuable data we wouldn't have had access to otherwise such as urban density, age groups, and other demographics Google pulls into platforms like Google Analytics.
​
Going through the survey, I used Airtable to create unique views to see the responses one by one. I added Frustration as a tag and later related it to another sheet. This was so I could roll the frustration up to see which instance was most common. I also made User Goal and **User Goal - Specific, **which are what the user was trying to accomplish on the site. These two are a parent/child relationship, seen in the User Goal view with multiple groupings.
​
Airtable gave me the ability to change the values of the satisfaction scale into numbers.
​
​
Now that I understand this numbering sequence, I can group frustrations together and take the average of the numerical satisfaction. Now I can see, for example, that "Navigation / IA" as a frustration averages about 1.2, which is just above Very Dissatisfied. This then allows me to compare frustrations not just by instances, but by user satisfaction.