BACKGROUND
According to data from statista, between the years of 2019 to 2021 there has been an increase in the number of people that read books. However, only 23% percent of the U.S. population read ebooks while 44.6% are sticking to printed books. So it is now more important than ever to help make sure that ebook readers can easily find a book that suits not just their taste, but their personality. Finding and reading an ebook should be effortless. We want readers to not feel as if it's a chore to find a book that they may be interested in.
WHAT PROBLEM DID I TRY TO SOLVE?
There are many book recommendation apps available. However, common frustrations that readers have with book recommendation apps include:
- Inaccurate recommendations
- Overwhelming options
-Difficulty syncing information between different devices
- Occasional technical issues
- Outdated design
- Difficulty navigating the app.
PROCESS DELIVERABLES
- Defining the problem
- Understanding the user
- Early Ideation
- Solution
- Next steps
DEFINING THE PROBLEM
In order to get a better understanding of user needs, I conducted a survey with 12 participants.
With the data I then went on to do competitive analysis which helped me discover common features and lack of certain features. My discoveries include:
- The majority of these services include native mobile apps.
- Some competitors had spot on recommendations while others did not have a recommendation feature at all.
- Only a minority of the apps have a camera search function to take a picture of the book cover or barcode number.
UNDERSTANDING USERS
In the next step I used what i've gathered in the research so far to create a user person named Debra. Debra is a highschool teacher that uses book suggestion apps . She wants an easy way to keep track of her books, better book suggestions, and a way to keep track of books she lent to others.
EARLY IDEATION
With the research completed, I decided to address some of the issues by making the following:
-A smooth onboarding flow where users can input their personality traits and book genres they are interested in so that when the onboarding is completed, the user will immediately be suggested books based on the data they shared.
- Both a mobile app and desktop site
- Book ratings
- Easy way to add books to a "shelf"
I went on to create A sitemap of how I would like the navigation to be organized.
I created a taskflow to demonstrate the steps of onboarding
And below is the userflow showing more in depth what its like to go through the onboarding process.
Sketches were also drawn to demonstrate some of the onboarding interest selection screens and book details. I wanted this to be similar to Tinder but instead of matching users with people, they are matched with books.
SOLUTION
Shown here are some of the screens for onboarding
Below are the finalized screens I designed to show the onboarding, book matching screen. users can swipe left or right to reject a book suggestion and move onto the next suggestion This can also be accomplished by pressing the "X" or heart buttons. The trey shows a preview of the book synopsis along with ratings and genres. The user can swipe up on the tray to see the full information of the book.
Dropdown menu allows users to mark the book as read, now reading, or want to read.
User can also purchase the book from the book details screen
The desktop site allows users to see their shelf on the right side while looking at book suggestions in the middle. The user can user the keyboard to press the left key to rejet or the right key to accept. This can also be done by clicking the "X" or heart icons.
The screens were put through user testing with 9 participants and ended with overall positive results.
