Overview

As a frequent traveller, I have seen long-distance relationships experience difficulties staying connected. Pace is a client-based project with the aim to help friends and family who live in different timezones more conveniently connect. The client seeks to implement a machine learning feature that groups messages by topic ("topic grouping") and plans to develop this product in December 2022.

I was tasked with addressing the client's and users' needs through branding and an end-to-end mobile app with the business goals of attracting and retaining users.

My contribution

Product strategy User research Product design

The team

1 × product designer 1 × engineer

Year

2022

Process

Discover

In a project brief, the client and I determined the business goals, potential user goals, and a schedule to complete the MVP within the 80 hour timeframe.

To qualify these user goals, I interviewed 5 people who have been in long-distance relationships and developed insights using an empathy map.

As this is a new product with many competitors that cater to a broad audience (i.e. Facebook Messenger, Whatsapp, and etc.), I analyzed these competitors to find product differentiators that would attract and retain the general audience while helping long-distance relationships. These features are scheduling calls and organizing chat messages for easier navigation.

Define

From user research insights, I formed HMW questions to brainstorm and define the most user-relevant problem to be solved:

Based on research, two key flows were identified to be the most valuable for staying in touch in a long-distance relationship: call scheduling and finding relevant messages. User flows were developed to map out the screens to be designed, taking care of the default user actions as informed by user research.

Develop

With the users' needs in mind, many rounds of iterations culminated in the hi-fidelity designs that would be prototyped for usability testing.

Testing

5 usability tests were conducted to understand the design's discoverability and learnability; affinity mapping was used to distill insights.

Although all tasks were completed, discoverability and learnability could have been improved, with users unsure about how to use the "topic grouping" feature and how it works.

Iterations were prioritized based on "fixes" and "improvements". "Fixes" disable users from harnessing features, and "improvements" enhance usability of these features.

Deliver

The iterations were implemented, and designs were handed off to the developer. A design system was created for scalability, consistency, and brand identity; this included typography, components, icons, and color palette.

Outcome

After one iteration, I was able to decrease the time to schedule a call by 15 seconds and navigate a conversation by 6 seconds. All 5 users were satisfied with the experience and were intrigued by the technology. The foundation was in place to continue gathering valuable data and enhance the user journey.