Audible App
Role: UX/UI Designer
Duration: Aug 2024 - Nov 2024
Toolkit: Figma, Figjam, Maze
Overview
This project is part of my studies with Designlab, where I chose an existing app and designed a new feature. The feature is an onboarding quiz designed to enhance the user experience by personalizing audiobook recommendations. Integrated into the app's onboarding process, or accessible from the Account section for existing users, the quiz gathers users' preferences in genres, favorite authors, and specific interests. This ensures that the recommendations displayed on their homepage or in the Discovery section are highly relevant and engaging.
Problem
Many Audible users struggle to find personalized audiobook recommendations, leading to frustration and wasted time browsing irrelevant content. This issue is especially prominent among time-conscious users who prefer quick solutions, users with diverse or niche tastes who have difficulty discovering content aligned with their interests, and new users who may feel overwhelmed by the vast library. The lack of personalized suggestions can lead to a disengaging experience, making it harder for users to fully enjoy the app and discover books that suit their preferences.
Solution
The personalized audiobook quiz addresses the issue by providing a quick, user-friendly way to tailor audiobook recommendations. By asking users about their preferred genres, authors, and interests, it ensures the content displayed on their homepage or in the Discovery section is relevant and engaging. This personalized experience helps users save time, discover books they truly enjoy, and enhances overall satisfaction with the app, ultimately driving increased user engagement and enjoyment.
Research
After identifying Audible as the app I wanted to work with, I explored it to find areas of frustration. While Audible offers a vast library of audiobooks, the "Discover" section lacks advanced filtering options like author search, star ratings, and alphabetical sorting. This forces users to scroll through long lists, making it difficult and frustrating to find specific titles, ultimately impacting the user experience. Compeptive analysis and user interveiws were conducted to better understand how other platforms handle content discovery and to gather insights on user needs and preferences.
Competitive Analysis
The competitive analysis showed that Audible stands out with its large library and useful features like notetaking, bookmarking, and car mode. However, it could improve by adding better filtering options, similar to Audiobooks.com, which allows sorting by genre, length, and author. While Audible offers more content, it is generally more expensive than competitors, with higher subscription costs and extra fees for certain books. Apps like Libro and Chirp have fewer features and are limited in availability, with Libro only in the US and Canada. Despite these points, Audible remains popular due to its wider catalog and global reach.
User Interviews
The goal of this research is to understand how users interact with Audible’s "Discover" section, identify ways to improve it, and explore how they discover new books. We interviewed five users, aged late 20s to 40s, three of whom are regular audiobook listeners.
User Interview Key Insights
Define
Now that user research has been complted and the problem has been identified it was time too look at user personas and POVs and HMWs.
User Personas
I created 2 personas. Lisa is a marketing manager from San Francisco who loves diverse audiobooks but finds the Discover section lacks personalization and offers repetitive suggestions. She seeks engaging, tailored recommendations to explore new titles easily. Jason is a busy software engineer from Seattle who values quick access to audiobooks but feels overwhelmed by the Discover section. He wants intuitive navigation and personalized, curated content to save time.
POV and HMW
To address their challenges, the guiding question becomes:
How might we build a recommendation system that learns what users like to read so that they get a more personalized experiences that allows them to discover new authors and stories without feeling overwhelmed?
Ideate
During the ideation process, I refer back to my personas and HMW to determine the main feature I want to design and how to create the user flows.
Feature Set
While developing my feature set, several ideas emerged, but one in particular stood out: a personalized recommendation quiz. Inspired by an onboarding quiz I encountered in another app, I saw an opportunity to apply this concept to Audible, creating a tailored quiz for personalized audiobook recommendations. This feature aims to simplify the process of discovering new books, ensuring the recommendations are tailored to the user's preferences.
Main Priority
-
Users would have the ability to complete a quiz that enhance their discovery section list or home page
Why a priority?
This feature aims to address the issue that Audible does not provide personalized book recommendations, making it frustrating for users to discover books they are genuinely interested in.
User Flows
After deciding on the feature I would be developing, I began designing the user flows. These flows helped outline the quiz's placement, the main topics and questions to include, and the overall flow when the user completes the quiz.
Design
After creating the user flows, I began designing the wireframes.
Low Fidelity Wireframes
Once the user flows were established, I moved on to creating the low-fidelity wireframes. The goal was to visualize the basic layout and user flow. A few iterations were made to refine the designs, which are shown below. I focused on maintaining consistency with Audible’s current design patterns while ensuring the layout was intuitive and wouldn’t confuse users.
Testing Low Fidelity Wireframes
Early usability testing was conducted to identify potential pain points in the design and flow. Participants were assigned four tasks: reviewing four different home screen options, navigating through the website, locating company services, and searching for resources. This approach aimed to evaluate the site's usability, organization, and ease of access, ensuring alignment with user expectations and goals.
Key insights include:
All users (5/5) were able to complete all tasks.
All users (5/5) found navigation easy, rating it a 5 (1 being hard, 5 being easy).
Most users were able to easily navigate to the correct location to reaccess the quiz.
3 out of 5 users selected more than three genres, despite being asked to choose up to three.
Many users expressed dissatisfaction with the "Add Favorite Book" section, feeling it limited their options and raised questions about how books would be chosen.
Most users appreciated the ability to input their favorite authors.
Based on the feedback, certain design adjustments were considered when creating the high-fidelity mockups. These included redesigning the favorite book section to align more closely with the favorite author section to reduce frustration, adding icons for improved visuals, and ensuring appropriate scaling and sizing for clarity and ease of use.
High Fidelity Wireframes
High-fidelity mockups were created based on feedback from low-fidelity user testing. The background and all UI elements were color-matched to align with Audible's existing color scheme and design patterns.
Users feel recommendations are not tailored to their preferences.
Broad categories without sufficient subcategories make browsing difficult.
Users struggle to find content quickly due to a lack of filtering features.
All users prefer using the search bar over browsing the "Discover" section.
Users want faster and more effective ways to search for specific audiobooks.
Personalized suggestions based on users’ preferences and reading history are desired.
Users want filters like subcategories, ratings, and availability.
A dedicated section for free content is desired.
Users want integration with social platforms like Goodreads and social recommendations.
Some users need filters specifically for academic content.
Those who are active audiobook readers use other audiobook platforms such as Libby
Affinity Map
To uncover broader patterns and themes, I synthesized these insights using an affinity map. The affinity mapping process highlighted the following key themes:
100%
Low Priority
-
Users can filter by genre, author, mood, book length, etc
Why a low priority?
Though users suggest filtered options, they do not directly contribute to personalized recommendations.
-
Organizes the Discover section alphabetically or popularity with visual clarity
Why a low priority?
During user interviews, some users mentioned the lack of organization, but it wasn't a major concern for most.
Testing/Prototype
Desktop and mobile designs were tested by 5 users. Key insights are:
Users liked the visuals and colors, but identified some typos.
One user struggled to locate the "Next" button.
Users found the quiz easy to complete
Average time to complete the quiz: 267.8 seconds (close to 5 minutes)
Users were frustrated with not being able to input authors and books manually due to a testing oversight.
Success Metrics
Iterations
Although the user testing feedback was positive, further refinements were made to enhance the designs and improve the overall user experience.
Format Selection Screen
Changes were made to sliding bar to make it more visually pleasing. It seemed fitting based on current and modern designs for quizzes.
Number 1 is highlighted to showcase what question they are on
"Select 1" was added to clarify the number of choices allowed, as users were previously selecting more than one option. This helps ensure users understand the selection limit.
Changed the direction of the icons on the "both" card to align with the style of other icons for consistency.
Before
Genre Preference Screen
The number of selection was reduced to reduce the time of completion of quiz
“# out of # were selected was added” so users know how many they have selected. According to usability testing, users were selecting more than 3.
Before
Conclusion
The redesign of the Audible app, specifically the introduction of a personalized audiobook recommendation quiz, effectively addressed users' need for more tailored content discovery. User testing revealed that the feature was well-received, with most users finding it easy to navigate and helpful in discovering new books. The design also adhered to Audible's existing visual style, ensuring seamless integration with the app’s current user interface.
Additionally, follow-up user testing showed a significant improvement in completion time, with the average time to complete the quiz reducing to 125 seconds (around 2 minutes), a decrease of 3 minutes. This reduction in time not only enhances user engagement but also benefits busy users by making the quiz quicker and more convenient to use.
Key Insights for Completing This Project
Of users found the quiz easy and simple to use.
Users felt the time allotted to complete the quiz was sufficient
Before
Before
100%
100%
Of users successfully found an alternative way to access the quiz.
Other Iterations
Several other iterations were created to refine the design further such as: Questions are now bold with helper text 8px below for better clarity. Text remains centered, matching Audible’s design style and user poll preferences. Additional screens were added to improve prototype flow, visible on the "Final Hi-Fi Page" in Figma. Selection options were reduced to prevent overwhelm and speed up completion time.
Final Designs
This project has been an invaluable learning experience that helped me grow as a UX designer, particularly in flexibility, user-centered design, and simplifying complex concepts. I enjoyed designing a feature for an existing app, balancing the integration of Audible's design elements with user needs for personalization. While the process was challenging—especially in narrowing the focus to personalization and adjusting designs based on feedback—it taught me the importance of listening to users and iterating quickly. Despite difficulties in recruiting participants and time constraints, I learned the significance of adapting my approach, which will guide my future projects in creating more user-focused, effective designs.
After
After
Favorite Author Screen
After
After
The labels "Authors added" and "Select up to 3" were removed.
Users now select only one favorite book or author instead of three to streamline the quiz, reduce completion time, and avoid overwhelming them with multiple choices.
The trash can icon was removed since the selection count was reduced from three to one, rendering the icon unnecessary.