Google Voice
Challenge: Create a Voice Over IP (VoIP) solution for enterprise users.
Impact: Launched the Google Voice Software as a Service (SaaS) product in 2019. Google Voice is considered by Forbes magazine to be one of the most user friendly Cloud-based phone systems in the world.
Role: UX Research Assistant
Process
Understand the competition
For the Voice launch to be a success, the team needed to know how our competition were solving for our user journeys. I conducted a series of competitive analyses that were critical in shaping the feature set of Voice.
User interviews
I executed 30 interviews with potential Voice users to learn about their workflows, pain points, and tooling needs. I specialized in the small and medium sized business (SMB) market (<100 employees). This user group is one of the largest Voice customers.
Targeted surveys
I sent targeted surveys to our users asking about their feature needs, device use, and distinct workflows. I learned many things. For example, SMBs wear many hats at any given time, so needed user friendly admin experiences as well as easy to use core experiences.
In-app surveys
I also fielded pop-up, in-app surveys, meeting users where they were - in the tool. This provided the team real time feedback on user satisfaction.
Remote usability tests
To know if the team was headed in the right direction, I tested design concepts and prototypes with users in remote, unmoderated settings. My findings influences Voice’s feature build roadmap.
User empathy
To foster more user empathy with the product team, I organized CUJ watch parties where I invited the team to watch curated recordings from user interviews. I gave party-goers observation worksheets to note their impressions and grade the interactions. This way, they saw first hand users’ experiences, and saw where improvements were needed in the user journey.
Benchmarking
Nearing its launch date, I tested Google Voice against its competition directly with users through a competitive benchmark. Insights gathered from these sessions informed the post-launch fast follow prioritization.