I finished my first project with GA this week regarding a research application. I was given the topic of to formulate a solution around. After my first interview I found that people have difficulty finding specific information they are looking for. So I developed a hypothesis based on this:

“People seem to have difficulty finding good information on music and artists they listen to. People would like to do better research for their music needs. How can I help make a resource that provides good music information?”

After this I developed a screener asking them questions like: Do you listen to music a lot? What kinds of things do you research for in music? Why?

The screener helped me focus on the target audience who would be having problems with music research. I screened out one person who wasn’t into music research and another who doesn’t like music. There was one lady who failed the screener initially but after I dug in for a few seconds more, she started speaking about how she likes to read about the music bio and the story behind it. She went into much depth about her likes and needs regarding music research. Its interesting to see what a little bit of digging can find.

As I went about the interviewing process I asked several open ended questions to people such as: When was the last time you used a service for music research? What was the result? Why? or How/why does your current music research service meet your needs?

I voice recorded my observations so I could easily refer back to them later for pulling out relevant information and insights. After all my interviews I started putting together all the information on sticky notes to create an affinity map. I initially organized it by users.

I then rearranged them into 4 grouping, wants, likes, dislikes, and needs. This helped me better understand the people and users.

I finally started looking for common trends and grouping them. This was based more on eyeballing and meditating on the insights I had gathered onto the sticky notes

During the initial stage of affinity mapping and from my user interviews I thought the problem I would be solving for was going to be a centralization problem where people would just want all the their music info in one place. However from the affinity mapping synthesis I was fascinated to find that most users simply wanted to know more about the artists. It was interesting as to how the process gave me the problem.

This lead straight into the problem statement. I was able to set the context and ‘how might I?’ based on the information from the user interviews.

When New Yorkers listen to music they like to read information on the artists. John wants to be able to read more on the artists and their background stories. How can I help him access more information on the artists?

I decided to develop a persona to assist me in solving the problem and also to make it more personable and add empathy to the process. I used behaviors from my user interview to put together John Cross:

John wants access to popular snippets of the ’s information but also wants to see if their musician’s story has depth. He wondered: ‘How did they come to this point in their career?’ ‘Do they share they have interests similar to mine?’

So I developed the ‘KNOW YOUR ARTIST’ app for John. It took me a couple of rounds of wire-framing before I felt it was good enough for putting in Marvel. John would open the app and see the home page where he can type in the keyword. This would then take him to the latest picture of the artist and a short bio. John would be able to scroll down if he wanted to see what other information is available. He could click on something like photos to get more details. John could also go back to the search through the magnifying glass.

I took pictures of my paper prototype and fed it into Marvel to make it digital. You can play with the prototype at: https://marvelapp.com/cac588j

In order to see how well the app actually worked I had to test it with people. I decided to do at-least 4 tests since research has shown that 4–6 tests gives the optimal amount of data. I gave my users scenarios and tasks such as “You are listening to Celine Dion on your phone and decide you want to see her latest photos. Please use the app to find her photos”. As they went about completing the task I made notes of what they seemed to like and dislike. I asked them why they clicked in a certain spot or what they thought about something on the app.

As I collected my insights, I was happy to know that most of the users found the experience intuitive and straight-forward. On average, they gave it a rating of 4 out 5 for pleasantness. However people mentioned other wants such as ‘How do I search for something specific about the artist if it’s not
in the info?’ or ‘I want to know what my friends think”. So on my next iterations I’ll be adding in features to address these wants while also clearing out some navigation bugs I found during my testing.

All in all it was a fun project that taught me a lot about the process.

Source link https://uxplanet.org/i-just-started-the-ux-immersive-at-general-assembly-2-weeks-ago-65e2827e5052?source=rss—-819cc2aaeee0—4


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