UX Testing and Feedback: The Feedback
So I decided to publish my UX Testing form on my website and as a class we decided to test each other's websites to further improve our websites. As you see above, I filled up the above UX testing forms but the ones that are blank did not have UX testing forms (at the time of creating this post) on their websites which is why they are blank.
After completing the forms, I decided to look at data of that my form collected. Here are the results:
The Data above shows that People use Phones more than PCs, but they used PCs to access my website and will continue do so and in this regard all changes need to be focused to towards Computer view rather than Mobiles view. Also, this Data also shows me that the next type of feedback is based on what type of device, so it helps that regard.
This section of Data is referred to as Quantitative Data. Data in this section is more represented by numbers. Feedback in this section would pose a question and feedback would be given in a scale of 1 to 4 from 1 being bad to 4 being very good. From this data we gather that people have a mixed response. While no one has rated elements of the website as 1, Some elements are rated 2 as they are between the 37% to 25% of the feedback. This means some elements do need a bit more polishing but overall, a good 75 to 63% of people like my website.
This part of the Feedback is referred as Qualitative Data. I created some questions and let them answer as they wanted. From this form we gather the following, The overall impression of the website is good, but one person said that images need spacing (I'll look into that), they thought that overall final project was good, but some people couldn't access it (I'll have to change my flipbook software) and their overall experience was good. I also asked on the form itself but the feedback with that is that people found the form a bit long while some actually understood the need for an Indepth form.
Overall, this UX testing has helped me realize what could be made better and what can be approved.
Please delete the first screenshot to keep data anonymous. Explain each graph. What did you learn from the findings? What would you do differently?
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