Optimizing the Funding Funnel for TV Shows
Brief
Rivit TV launched its MVP web product with one funding show. The goal was to test core features, usability, and gather feedback for further improvements.
Here are some key things we wanted to learn from the show page:
- Did users watch the pilot?
- Did people understand how to pledge for a show?
- Discover challenging touching points.
My Role
The task was a team effort with everyone in the design and product team working together to quickly come up with solutions. My main contribution was designing the new pricing panel flow.Credits
Director of Product Design: Megan O’Toole
Product Designer: Tina Maleki
Research
I dug into the analytics, collected insight from cross functional teams, and noted user feedback. I gathered all this information and discovered there were two key issues people were having trouble with to accomplish their next task in the funnel:
I took my findings and presented my hypothesis to the team for next steps.
- From the data, we found most people were engaging only on the first and last button of the five price buttons. Was having too many options upfront causing decision anxiety and preventing users from taking actions?
- From customer interviews, we found that some people simply wanted to donate money without participating in the auction, but the beta version didn’t allow them to.
Explore Solutions
The solution needed to simplify the current pledging flow and also provide the ability to donate money without participating in the reverse auction. The task was not going to be easy since we wanted to simplify, yet we were considering adding another feature which could result in more complexity.
I initiated a workshop to brainstorm some ideas to explore and test:
Validate Initial Ideas
I created a rough prototype from the sketches to validate our initial ideas and make sure we were on the right path. When building the prototype I thought of a fourth option (Illustration D) where there would only be a single CTA on the show page.
I conducted a low-fi test with people at the office and random people who worked in the same building. I first asked participants if they really enjoyed watching TV shows. If they did, I set up the scenario and their tasks. From there, I handed them the phone with a randomly selected screen and ask them to go ahead and begin.
The results were surprising, most of the participants initiated an action about half a second faster on option D (Single CTA options) than the rest of the options. Option B came in second. This told me that if a user was interested in participating, the single call to action resonated to them to get started in the funnel.
I reported my finding to the team and stakeholders for review. We agreed to remove any pricing options on the show page and move it down the user’s pledging journey.
Next Task
My next task was to figure out the rest of the user’s journey and to explore how to separate a regular pledge user from one who just wants to donate. We explored possible solutions in a meeting, and an interesting idea surfaced up: What if we gave these type of pledgers a fun name along with a more exciting visual treatment when communicating to them? We ended calling this type of user a Super Fan pledger. With this new inspiration, I began to explore different user flows and built a higher fidelity prototype to conduct a similar test as the first one.
The winner
Results from the test showed option v3 generating the highest engagement and lowest learning curve. In this version, users were able to toggle between the two types of pledges by tapping on a card. Throughout the test, users would usually tap between the cards to see them animate again. The card style design also helped keep the UI to a minimum and the pledger focused on their task.
Wireframes and Behavior
I presented the final version to stakeholders for approval and moved forward on fleshing out the final flow, and behavior for all screens.
Visual Design
Once done with all the flows, I began the visual design phase where I tweaked a few minor things in the animations.
Conclusion
At launch we tracked the same metrics and saw increase of 12% higher engagement.
