Create An Intuitive Dashboard To Increase Engagement For New/Old Users
The original product of Laughly is an audio-based comedy streaming app — the Spotify for comedy. The platform provides access to an exclusive selection of streaming comedies through its unique channels of albums, playlists, podcasts and radio stations.
The client approached us to help them integrate video content to the audio-only app and explore solutions to boost the community engagement. This involved redesigning the architecture of the existing app and envisioning how to generate greater user conversions online. Within a 10-week timeline, we focused on identifying the fundamental problem and iterating solutions under changing scopes.
I was on a team of 12 designers. I was responsible for researching streaming app products, interviewing product users, carrying out design solutions from low-fi to hi-fi with validations and iterations. My design focus was on the channel page and the micro-transaction features.
At the outset, my fellow researchers and I studied several existing products that have cracked similar challenges. User Interviews were carried out in parallel to understand the effectiveness and relevance of potential solutions. I was responsible for researching the product of YY.com (a key product to study as advised by the client), interviewing their users, and condensing the insights from those users.
After the team presented the research findings, the essential concern of the client was revealed — the focus on community engagement for Laughly app was on its monetization and micro-transactions. The fundamental problem of this project was how to use the app to transform free users to paying customers. Integrating video contents with an optimized discovery was also one of the strategies to pitch the product for customers to pay.
We quickly pivoted our efforts to explore different interactions that would be conducive to micro-transactions. To generate a multitude of design ideas to get our team forward, we ran a design studio session within which we diverged by creating many ideas and converged on a few (shown as below).
The whole team together voted for best approaches of integrating video contents and promoting internal monetization. The option with the easiest switch between video and audio without disrupting the existing discovery flow won the rate. Based on the feedback from user interviews and the probability that all primary contents types (album, playlist, & podcast) could be video streaming, we chose to structure contents by the filter of ALL / AUDIO / VIDEO.
Aside from subscription tiers for revenue generation, we sketched a flow of clapping with tipping — Laughly users from initial interviews showed interests that they would like to tip their favorite comedians. Previous product research also provided proof that micro-transactions happened mostly when users tried to show appreciation.
From the usability testings we were surprised by the confusion of clapping along with tipping. The three most debated areas related to:
• How much a clap is worth
• How the clapping works with tipping
• How much the tipping goes to the artist
We considered a few ways of how users would interact with the content and when they would be inclined to show appreciation through clapping and tipping:
• Direct monetization of claps
• Bundle claps with subscription tiers
• Claps not associated with tipping but as a rating system
However, testings with 8 participants revealed that:
• User disliked the idea of tipping when they were already presented with paying more to subscribe to new content.
• Users got confused of "claps" with "likes". Since the clap icon is more readily available versus the “like” embedded within Comments, users thought clicking the clap icon would indicate that they liked the content.
• Users felt adding tipping and subscription tiers at the same time would be too much for users to digest.
“ ... If you make people buy CLAPS, you’re losing a lot of valuable data because I'm not going to use it. If Laughly offers a lot of things for free, then it's easier to start building a profile of what the users like.
Compared to music, people have a more particular taste for comedy. It would be cool to use machine learning to make recommendations." — A Laughly User & Software Engineer
Based on those insights we decided to promote the like/dislike feature as the one and only rating system across the platform and eliminate the clapping features. Users favored subscription more than tipping, therefore in the high-fidelity phase, our focus was shifted to how to structure and adapt the subscription tiers.
In the low-fidelity testings we also found out that 4 out of 8 users didn't know what the roman numerals were upon the first glance. After replacing them with annotations and texts, positive feedbacks were received of telling the differences between subscriptions.
The team and I identified the essential problem for Laughly and provided a well-adapted UX to existing users. We iterated the solutions under changing scopes and balanced between users needs and the business vision. Furthermore, I am glad to know that the client rated the team with positive feedback and the design is currently in development phase. Feel free to go through the prototype below and share your thoughts and comments.
VIEW PROTOTYPETo comply with the non-disclosure agreement, in this case study I have omitted the dashboard page for persona Maritza, the expanded view of containers, and pages with confidential information.
© 2021 TINGRAN LIU