Drops is the fastest growing language app in the world specializing in vocabulary building. They take pride in their beautifully designed word games to make language learning fun and easy. In this conceptual case, Drops wants to improve user engagement and retention by implementing new features to help users reach their goals.
Drops is praised for its beautiful visual design with its colorful gradient backgrounds, simplistic look and illustrations for each word. Integrating new features must be done seamlessly without overcrowding and breaking the user-friendliness of the already minimal look of Drops.
• Implement a scheduling and reminder system
• Recommend daily mindfulness reminders to meditate
• Create a mindful product that puts users at ease upon use
To understand what features to implement, the problem space needs to be explored further through market research and empathizing with our target demographic. The scope will include desk research on learning a second language in both tradition and non-traditional methods along with an analysis on Drops’s competitors and taking a deep dive into the users of these apps.
Market Research was carried out to gain insights of the target markets of language learning mobile apps and to uncover trends and opportunities within the market.
A Competitive analysis was conducted to unmask the strengths and weaknesses of the main players in the productivity and wellness mobile app industries as well as study their commonalities.
With the findings from desk research, I created provisional personas to identify possible target users of language learning apps and their needs.
User Interview participants with the below criteria were recruited online for user interviews:
After talking with the participants, some painpoints were brought to my attention:
It was now time to condense our research data with empathy to understand the end-user’s common goals, needs and behaviors.
Konnichiwa!* This is Sara! She will be representing our user interview participants. Sara has a goal of learning Japanese for her grandmother. Sara will guide us through the design process so our decisions throughout the process are aligned with the end-user’s goals and solves their problems.
*Konnichiwa is a Japanese greeting meaning Hello/ Good Afternoon
To further empathize from Sara's point of view, a user journey map was created to explore opportunities within each stage to improve her learning experience and bring Sara closer to her goals.
Some opportunities were identified for the current state of the app based on user data including:
Using the insights from our research data, I used the “How Might We” method to create the basis needed to tackle the right problems. Over Zoom and Miro, 2 designers, a developer and I brainstormed as many possible solutions within a short timeframe, presented our ideas, and voted on the best idea using the red dots as shown below.
Thanks to the brainstorming session, I was able to narrow down the main features.
With the help of a real developer, the features were determined by their ability to provide the highest value with the least effort:
Due to the limited time frame of the project, the following features were decided for implementation:
To get started, I went through a couple of language learning mobile apps that offered a podcast feature and took screenshots to study the nature of how they work for each one.
It was now time to hit the drawing board and come up with ways to bring these features to life.
Because the test out function directly correlates to the topic screen, this was our starting point. As I was sketching out the flows, I wanted to be mindful about Drop’s minimal design and avoid cluttering the app with unnecessary elements so I kept the topic screen as is and instead used the existing elements on the screen.
What I had in mind from the flow was that once an element within the topic card is selected, it directs the users to that specific topic screen with a test out button. From there, the user would test out in the same way as they would practice but will need to avoid making too many mistakes in order to pass.
If the user passes, they will no longer need to review it unless they intentionally wish to by visiting that specific topic card. If the users fail, they will be prompted to either practice more and retry.
The task creation screen (left) shows the basic functions of scheduling a reminder by entering a title and selecting a specific date and time.
Although it isn’t part of the Must-Have Features, the Notes screen (right) was roughly sketched because I was inspired at the time and wanted to keep it for a future iteration.
For the podcast feature, I decided to add it as an item in to the bottom navigation item. I then sketched out additional screens such as the list of audio lesson topics, the audio screen and a screen filled with helpful transcripts or a summary of the lesson.
The podcast feature screens were inspired by music mobile apps such as spotify and apple music.
Shown below is the limited UI kit specific to the new features that were implemented for this project. Creating the nonexistent podcast item and screen was interesting because working with gradient colors is not the ideal choice when it comes to accessibility so I had to be careful that the elements and contents communicate well to the majority.
Since this is a brand new product, prototyping sooner will reveal any assumptions and creates the chance to fail fast and fail forward without over-investing time and effort on the first iteration.
Check out the prototype here.
In order to determine whether the new features work well with the app, it was time to put it in front of real people and test to understand what works well or what can be improved. The test was conducted with 4 drops users over a recorded Zoom call where they were given scenarios to complete specific tasks.
Task 1: Test out of a specific topic (users will meet the success screen)
Task 2: Test out of a different topic (users will meet the “did not pass” screen)
Task 3: Look for the podcast feature and how you would use it
Once the usability test was over, I created an affinity map to organize related information and observations into distinct clusters. In doing so, the data is easier to synthesize and leads to meaningful insights.
There are still things that can be tested and improved on, including but not limited to:
Doing this project was research intensive as there are many existing features that can solve similar problems and the brainstorming helped with bouncing off ideas and identifying biased assumptions.
What I enjoyed 😁
The group brainstorming session was fun as it helped me generate as many ideas in a short amount of time and challenged me to think about tackling problems from different angles.
My favorite moments 😊
As a lover of all things cute and illustrations, my favorite moments include creating the cute smileys from the user journey map and the podcast icon in the bottom navigation menu.
My least favorite moment 😭
I am not very fond of mundane tasks such as having to document the recorded zoom sessions in detail... but it was definitely worth it as I like getting the key insights and feeling a sense of accomplishment!
Room for Improvement 🤔
One thing I do want to improve on moving forward would be to get feedback on deliverables as soon as possible such as the user journey map so I can avoid spending too much time on one deliverable.
