Lyft

Quantitative UX Research Intern

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Internship Overview

I spent the summer conducting quantitative UX research on a number of projects that touched both the driver and passenger side of Lyft’s two-sided marketplace. I created reports and presented findings directly to product teams. I provided strategical and tactical insights to assist in decision making during the company’s hyper-growth phase.

Project DELIVERABLEs

  • Research Brief

  • Survey Design

  • Survey Data & Analysis

  • Presentations

  • Reports

Background

As one of two quantitative researchers at the company I was able to conduct and plan studies for a number of product teams. In addition to the studies I ran myself, I facilitated 3rd party vendor management for more specialized quantitative studies. The studies that I worked on influenced the driver acquisition strategy for the Express Drive program as well as the design and implementation of in-app driver tools.

Me and my mentor, Emma, in front of the Amp Wall!

Me and my mentor, Emma, in front of the Amp Wall!

Surveying

The bulk of my personal development with surveys can be broken into three parts: sampling, questionnaire design and analysis. At Lyft I gained a strong understanding of the limitations and implications of various sampling methodologies — most importantly I learned the best practices to ensure high quality data. I reviewed SQL queries to specify our target audience and later ran queries in our database again to validate results from the surveys. Having the ability to work on a number of projects gave me a chance to strengthen my questionnaire design skills, in particular I became adept and translating stakeholder needs into research questions and then figuring out not only what we needed to ask users, but how. Finally, I gained exposure to data analysis in both Excel and SPSS. During analysis I used significance testing, correlation analysis and other techniques to derive answers to our research questions.

Mixed-Methods Approaches

One of the greatest aspects of my experience was the collaborative nature of the research team at Lyft. This made it easy for me as a quantitative intern to start taking a mixed-methods approach on my studies. Being able to build off of prior qualitative work to measure the prevalence of various phenomenon led to the validation of proposed design concepts. This was a rewarding experience and one that I hope to have more of in the future!