Rate Your Lyft
Project Overview
Lyft is one of the fastest growing companies in the sharing or gig economy. One of the most important mechanisms that enable the gig economy is qualified and accurate ratings from users, which allow companies to keep track of the contractors' performance and provide a high-level services for people.
RESEARCH
Methods: Secondary Research, Affinity Diagramming, Competitive Matrixes, Interview, Personas and Scenarios
Research Findings:
Rating systems are commonly used on sharing platforms as a tool to regulate employee performance and provide safe and high-quality services to customers. However, the existing five-star rating system used by Lyft does not provide accurate and trustworthy information about the ride.
Personas & Scenarios
Click on personas for full profile and stories
Stephanie Roberts, 21 - The Needy Passenger
Studious, reserved, caring, patient.
Charles Schneider, 33 - The Dedicated Driver
Passionate, energetic, cautious, curious.
PROBLEM SCOPE
User group: riders with specific preferences
Pain point: mismatch between expectations and reality
Context: scheduling a Lyft
Scope: When requesting a Lyft, riders with specific preferences experience a mismatch between expectations and reality because star ratings are ambiguous and open to interpretation.
DESIGN
Methods: Sketches, paper prototypes, usability testing, iteration
After thorough discussion, we decided to eliminate the star-based system and replaced it with the new features to the rider’s rating experience, and one new feature to the driver’s page
Visual representation of the driver’s performance for each rating criteria
The goal of this screen is to encourage drivers to quickly identify which criteria they need to improve upon to fill those bars with more green. The criteria can be quickly identified by the symbols in front of each bar.
Watch the new way to rate your Lyft !
Final Design
Methods: Sketches, paper prototypes, usability testing, iteration