Product Analysis— sRide
When I had recently moved to Mumbai, for my first ever job, money constraint was always an issue. This is when a friend suggested I travel to and from office via sRide. When I completed my MBA, I thought of applying my newly acquired product management skills to my favourite app.
sRide carpool app matches riders to car owners based on their location and time preferences. Users post their rides on the mobile app to get multiple options to ride with. Founded by Lakshna Jha, Nitin Chadha & Amit Agrawal in 2015, sRide today has 10 lakh+ users across 9 cities. The founders claim that it is 40–50% cheaper than Ola and Uber while travelling in comfort with their colleagues.
sRide has targeted :
· Working professionals in big cities typically 25–45 years old
· Users are mostly middle income group
· Individuals looking to find cheaper transportation to work
· Individuals looking for environmentally friendly solutions
· Individuals who want to share the cost of taking their own vehicle to office with others
· Colleagues who’d pool rides due to parking spot issues
One big reason for success of the app is the Network Effects. The app partners with big organisations who then conduct awareness campaigns of the benefits of using the app and sometime provide rewards too. They’ve onboarded users from 400+ leading companies like Cagemini, Cognizant, WIpro, Infosys, TCS, Tech Mahindra, Virtusa, Novartis, L&T, HCL, IBM, Cyient, HSBC, Hitachi, Persistent, Qualcomm. More and more users are joining this app because it is innovative, useful and understandable.
It serves the underserved needs of the users of not having a cheap comfortable option of travelling to office on a daily basis.
Feature Benchmarking with Competitors
I’ve enlisted the different features and mapped them to the Kano Model as well as the value that each feature adds to the app.
Having used the app extensively and having talked to other users as well, I came across a few issues with the app, some of them are listed below:
· No realtime location of the car so the riders often do not know when to expect the car at the exit gate. This often leads to the car owner having to wait at the exit and a lot of phone calls to co-ordinate the timings.
· Often the regular car-poolers are on vacation and the others do not know about it. This leaves them without a ride in the morning.
· Sometimes the car owner takes a longer route or a route that is not comfortable for the rider.
· The app crashes often.
· The app has 60% women users but no feature to filter out only female ride givers. Some women do not want to travel with males during the night.
· Some users travel with each other on a daily basis, there is no feature to automatically accept their ride. Users have to manually do it daily.
Based on the importance-satisfaction and value-effort matrices, the following features were shortlisted:
PS. This is a short version of the product case study. For interviews, there are more frameworks and logic explanation required.