Mastering Product Management: Insights from a PM Interview Case Study
Last year, while interviewing for a product management role at a leading tech firm, I was presented with an intriguing case study: to reimagine Uber's approach for large events. This challenge not only tested my problem-solving skills but also sparked a deep dive into the complexities of event-based transportation. I worked on preparing a detailed solution encompassing a PRD document, a presentation, and a prototype. Now I am sharing this knowledge with the broader product management community. This article is my way of giving back, opening a dialogue, and connecting with fellow PMs, by sharing insights and learnings from this unique project.
Here is the case prompt that I received as part of the interview: "Uber is built primarily for a core use case of pickups and drop-offs in urban and suburban environments (e.g. home/work). That means it doesn’t always work well at events such as concerts, sporting events, and festivals. Imagine you are running a new team focused on making Uber to/from large events (10,000+ attendees) a magical experience for riders and drivers."
Here is how I prepared for this case study response.
Title: A Case Study on Uber's Approach to Large Events
This document proposes a magical experience for Uber riders and drivers at large events such as sporting events, concerts, festivals and trade shows, which usually witness 10,000+ attendees. This aligns well with Uber's mission to reimagine the way the world moves for the better. This also serves as a step towards fulfilling the long term vision for Uber to be a one stop shop solution for mobility worldwide.
Introduction
Imagine attending a large-scale event, like CES in Las Vegas, and facing the usual transportation woes: crowded public transport, long waits, or the struggle of finding parking. Now, envision a seamless, efficient, and enjoyable journey to and from these events. This is the future Uber envisions, and through a comprehensive case study, we explore how this can be achieved.
Identifying the Customers & Core Problems
Uber's traditional model faces unique challenges at large events, including logistical hurdles, high demand, and varied user needs. This proposal delves into these issues, understanding the specific needs of event-goers and drivers alike, and proposes innovative solutions.
Who is the customer and what job are they hiring Uber for?
Uber Rides is a two sided marketplace with riders and drivers as the key target customers. There are multiple ways to show this segmentation as captured below:
What are the circumstances in which customers are trying to choose (hire) Uber, and the reasons why they might avoid (fire) Uber?
What is the expected impact of meeting customer needs focusing on large events?
The Events* industry market size was valued at USD 886.99 Billion in 2020 and is projected to reach USD 2,194.40 Billion by 2028, growing at a CAGR of 13.48% from 2021 to 2028.
As you can observe in the table below, there are several large events taking place all year round across the United States. With thousands of attendees, this is undoubtedly a huge target market segment that presents a great opportunity for Uber Rides business.
Why should Uber enter this segment:
Proposed Solution
The proposed solution involves a partnership with event organizers, integrating event schedules into the Uber app, and offering advanced ride-booking features. This plan ensures a personalized and hassle-free experience for both riders and drivers. However, it does not make sense to target all these large event types at the same time. Where should we start? Let us look at how I prioritized one event type to start thinking about the solution.
Prioritization Framework
Assess different types of events for high, medium and low variability across different factors such as frequency of occurrence, location (venue) including traffic conditions and attendance. Top priority will be given to events that have a fixed frequency of occurrence, same or similar location (venue) and lastly low attendance variability.
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LV = Low Variability, changes rarely.
MV = Medium Variability, changes sometimes.
HV = High Variability, changes often.
I identified Trade Shows in the USA as the top large event category for the MVP, and then I focused on further segmenting the customers based on their behavior or demography or region.
Here is a customer segment tree to understand the target customer segment better. The boxes highlighted in green showcase key customer segments that would serve as a priority for the MVP.
Consumer Electronics Show (CES)* is one of the largest Trade Shows that takes place in Las Vegas every year in January and witnesses more than 180,000 attendees from across the world. For the Uber Rides MVP, I determined that I would focus on U.S. based attendees at the CES Trade Show in Las Vegas.
65% U.S. based attendees at CES = 117k. They are most likely high income, college graduates, tech savvy professionals with smartphones, could be frequent travelers, less price sensitive.
The MVP and Beyond:
My proposal suggested to introduce a concept – Uber Events – tailored for large-scale events. Starting with the MVP focused on trade shows like CES, the proposal outlines a phased approach, eventually expanding to cover various types of large events nationwide.
I used screenshots of my own Uber App and prepared a prototype using Google Slides for the MVP and Long Term vision as shown below:
MVP Vision Statement: Create a magical experience for Uber riders and drivers at the CES Trade Show starting with their journey at the Las Vegas airport.
MVP Feature Milestones:
Long Term Vision Statement: Create a magical experience for Uber rides and drivers at large events with 10,000+ attendees across the United States. (Expand this vision to global marketplace after succeeding in the USA)
Measuring Success
The success of this initiative is tied to specific KPIs, including user adoption rates, satisfaction scores, and efficiency metrics. The goal is to significantly enhance the event transportation experience, contributing positively to Uber's overall service offerings.
Lessons and Call to Action
I developed a comprehensive solution, including a PRD, presentation, and a prototype. Despite the depth of my proposal, the interview didn't lead to a job offer. However, the experience was invaluable, offering rich lessons in strategy, user experience, and the dynamic nature of product management. Reflecting on the product management case study experience, here are some key lessons learned:
I invite the PM community to provide their insights and feedback on this approach. If you're interested in a more detailed look at the PRD and the Presentation Slides, please leave a message in the post, and I'll share my PRD and slides directly with you. Should there be substantial interest, I'm considering developing a program to share more such case studies.
DGM - Products @Paytm | Ex VP Global Digital Products @ HSBC | IIM Graduate
1 年Abhishek Agarwal enjoyed the case study and approach solution that you have provided, can u pls share PRD and presentation on my email id :[email protected]. would like this to understand the end to end approach and framework for case solution.
Senior Software Engineer at GoDaddy
1 年Its a good read Abhishek Agarwal. Very thoughtfully envisioned and covered with some good initial planning. However, I also feel we are not covering the solutions to address the known challenges such as traffic conditions, event delays, last-minute changes, or cancellations, or enough drivers availability. which you already mentioned in start may affect user (both rider and driver) experience for this offering. A section on risk mitigation is missing which may include solutions like complimentary vouchers, incentive programs, capacity planning, flexible scheduling options, alternate routing, real-time traffic data to make informed decisions and so on. We only discussed about the offerings and its launch, but we must cover cases of potential disruptions also and how those can be avoided and regularly tracked with user satisfaction scores and number of trips happened and not happened, etc.