Impact
Design Process
Understand
Conduct the user interview to understand existing user workflow and needs.
Ideate
Hypothesize the user workflow and lead to the potential solution that meets user’s needs.
Validate
Execute the user testing under diverse context. Observe the process and collect user feedbacks.
User interview
How did users complete management tasks?
After the online meeting with APO and Users, we gained some insights below.
Here are the existing steps to manage stream setting:
1.Receive the stream list.
2. Import stream data by each manually.
3.Set the Language data for each stream.
4.Set the specific display site for each language.
5.Set the streamer supplier and channel for each language.
And some other details:
Stream list usually comes with diverse sports and language setting for each stream.
Stream List might ordered by date or League.
The management task happened about once a month and editing about 200 data each time.
Requirements Analysis
User Story
And It would be great if the user can:
Set stream data and language in quick steps.
Avoid edit errors.
Starting design after clarify the needs.
Ideate
Hypothesize User flow
Before we dive into the UI design, I outline the possible path to achieve user goals first. In this way, we get to know the frames and features needed to connect all steps.
Check stream list.
Filter out the data by language or sports.
Select streams and set the language data.
Save changes.
Double confirm changes.
Design Solutions
After brainstorming, I scoped out what feature should this new page have and what data needs to be displayed. Here are the initiatives I followed.
This new feature allows the data of multiple streams can be edited simultaneously and avoid mis-editing. It’s a new thing to the platform, so the UI should be distinct difference for these two state.
Assume that user will repeatedly edit stream data for the same time period, the highlight allows user to contrast current edited item with the last edited item by the background color and makes the checking easier.
The feature is developed based on user habits and the presentation style of stream Lists. In certain context where users need to edit specific stream data, they can utilize filters and one-click selection to execute the edit more efficiently.
The regular stream editing tasks usually involve over 100 pieces of stream, the confirmation popup should show the data changes clearly. Using distinct color label for different data state make it easier to view the streams.
Time to involve AI and streamline our works.
User Testing
At this stage, I use ChatGPT as a assistance to generate possible user testing paths and identify key details.
Then I sketched out the prototypes and the testing scripts based on possible context. Therefore, we get to observe how users interact with the prototype, how they complete the missions and how they feel about the new feature.
After this, we decided to cut off some complex design and simplify the components' state as well.
Testing Conclusion
Based on the testing and interview results, I decided to launch feature 01, 03, 04.
With this iteration, regular stream management has been streamlined from five steps to three, reducing work time by 85% compared to before.
I kicked off the project with a 30-minute online meeting, which was a total game-changer. It helped me move beyond the initial requirements document to really understand our users' context and their specific pain points. The experience solidified my belief that involving real people early on—even for a short time—is key to building a truly professional product. It's an investment that pays off in both usability and personal growth.