SalonOn

In early 2021, SalonOn contracted our company to create a system architecture and prototype for a service that connected hair stylists to customers and allowed those stylists to use empty salon space to perform appointments on an as-needed basis.

Role

Lead UI/UX Designer

Timeline

February 2021 to
May 2021

Result

Wireframe and prototype
Basic branding guidelines

Product Goals

The current framework

OkaySo is a mobile application that allows users to anonymously ask questions to curated groups of experts, who provide unbiased answers to everyday questions about gender, sexuality, puberty, loneliness, and just about every other topic you can imagine, akin to "the best friend" that never judges. These questions were answered through a "group message" interface, with the asker and the requested team.

At the time, the existing platform was functional on both iOS and Android, serving thousands of users nationwide, but after a rebrand performed by a 3rd party, the client asked that we update their application's UI, helping it conform to the new style guide, and optimize their UX to improve the time from question to answer, and reduce front end workload on their expert teams.

System Architecture

Improving frontend and user experience

The existing system needed a more effective way to serve exponentially more users, without linearly increasing the need for more experts or administrators to communicate with the user base.

Appointment Management

Appointment management interface for stylists to control and prepare their daily schedules. Everything from appointment overviews, requested stylers, approximations of appointment times, and location data for the host salon.

Stylist Calendar

Quick and easy day-to-day appointment management, with an inbuilt Google Maps integration for navigating from one salon to the next.

Optimizing Question Assignment

In order to to tackle the growing user base of the existing application, a method needed to be devised that allowed for linearly scaling expert teams to handle exponentially increasing question submissions, as well as a way to balance the assignment of user's questions to experts.

This was solved through two symbiotic improvments.

Sub-Teams

Sub-teams were created to solve the issue of scale. Acting as secondary segments of teams, these smaller groups of 3 to 5 experts each would allow a single "team" to handle far more questions, and also to balance the question intake among each sub-team.

With this new level of hierarchy, the system could support a new wave of users without a drastic increase in spending or need for new team members.

Question Assignment

With the inclusion of sub-teams came the need for a question assignment methodology that would balance submissions from users amongst all of the expert sub-teams.

The proposed solution (which would later be implemented live, was a simple frequency based assignment, with the team that currently had the least number of active questions, with ties resolved by a simple ordered list.

Customizable Appointments

In the spirit of creating a trusting environment for new and existing users, we helped to create "Shared Conversations", a section of the app where users could share positive experiences with experts in-app.

Scheduling Made Easy

With questions come doubts, and to help ease the growing pains in-app, I built a quick and easy way for users to get to know the expert community. With a simple list of featured experts, anyone can explore the people they can connect with, hopefully facilitating productive conversations and mutual trust.

Complete Salon Details

Understanding how to comfortably end a conversation can be tough, but when experts have answered to the best of their ability, I created a system by which they can end a conversation, and explain, either quickly or in-depth, why the conversation was ended, and their thoughts on the exit.

Automated Salon Payouts

In the end, OkaySo was built for users. Every conversation is started by real people, and one of the goals of the project was to ensure that everyone who came to their experts with a question got an answer that went above and beyond expectations.

With this is mind, nobody is perfect, and to account for that, we wanted feedback from both parties to ensure that both the expert teams and application as a whole could improve over time to better serve people in need.