Ridesharing app for commuters | Design Case Study | Task Flipkart

Cover Banner showcasing 3 of the important screens from both ends.

Problem Statement

Design an app for carpooling/bike pooling to help commuters (Ride-seeker & Driver) to discover, connect, route match, coordinate, and cost-share in a seamless manner.

If a user (ride seeker) needs to get somewhere e.g. commuting to work, why not get a ride from someone who is traveling in the same direction, share costs, get a comfortable ride, and be faster compared to buses or metro. On the other side — the app should enable the user (driver) to get co-riders who are traveling on a common route to share his/her personal vehicle with.

Problem Analysis

To design an app for carpooling or bike pooling for two types of users:

  • Drivers (or Ride-offerers): The one who owns the car or bike of their own and is willing to share his ride with co-riders.
  • Riders (or Ride-seekers): The ones who don’t travel with their own vehicle and need a ride from drivers.

The users are referred to as commuters that are daily riders or passengers.

The users should be able to do the following through the app:

  • Discover their rides
  • Connect between drivers and ride seekers
  • Route match
  • Coordinate between themself
  • Cost-sharing accordingly

The app should allow both kinds of users to do any of the following: Ridesharing or Ride seeking from 1 app.

Primary Research

The purpose of this research was to understand + validate user needs and pain points. This would help make necessary assumptions and prioritize user needs.

What do I need to extract from the research?

  • Pain points from both the driver’s end and rider’s end.
  • How ride-sharing scenarios in this case should differ from the current uber pool or ola share scenarios?
  • What factors would one consider while connecting with a particular driver, which might affect their riding experience?
  • Frustrations faced by users while travelling via cab (uber and ola) and public transports (Busses and autos).

I talked to Four users regarding this and followed the below rough questionnaire.

Rough Questionnaire

  1. What places do you travel to frequently?
  2. How do you prefer to travel to those places? (Way of commuting eg. own car, public transport, cabs, friends pickup, etc.)
  3. What are the pain points that you face while using public transport?
  4. How do you choose whether to go via cab or bus or which app to use for cab booking?
  5. Do you always use the same route to go to those places?
  6. Have you ever used any ride-sharing services like uber pool, ola share, or sRide?
  7. How is your overall experience with pooling? Things that you liked and things that you didn’t?
  8. What factors do you think of while booking a pooling service? (like cost, driver, co-passengers, car or bike type, etc.)

User Insights and Pain Points

These are the collective insights that I obtained by interviewing 4 users.

Insights

  • People generally visit — Workplace, Gym, Restaurants and cafes, Weekend Travelling, Health checkups
  • Most people travel via cab or public transport to workplaces but they use their own vehicle for other purposes.
  • Unreliable bus timings, long queues and waiting times at peak hours, and tiresome multi-model travel with no guarantee of getting a seat.
  • Choosing whether to use public transport or go via cab depends on the availability of cabs or public transport, time constraints, cost of cabs, etc.
  • The route to work or somewhere known is generally fixed and kept in mind on the basis of which is shortest, less time taking and comfortable.
  • Most people have used ride-sharing services like Uber Pool or Ola share so they have a decent idea of how they work.
  • Likes of ride-sharing (or pooling)
    — Cost breakdown is cheap and is affordable as compared to cabs.
    — Other co-passengers are picked up from nearby areas, so there is less chances or need of re-routing.
    — Its a good meet and greet type of networking service if you find professional co-passengers working at some good posts.
  • Dislikes of ride-sharing (or pooling)
    — There are always trust issues that arise while booking a pool service as no information about your co-passengers is shared. It's ever harder for women riders.
    — Sometimes, when already there are passengers travelling and your drop is last then journey time increases as the drops are sometimes so off-routes.

User Pain Points

Based on the insights I clubbed from user interviews, I devised certain pain points from both drivers and riders perspectives.

Drivers Perspective

  • Rising fuel costs
    Cuts into their monthly budgets
  • Trust
    Hard to find verified, reliable people for carpooling/ride-sharing
  • Route
    Hard to find cost-effective transport options on their route
  • Traffic congestion and parking woes in urban areas
  • Carbon footprint
    Greater climate-change awareness leads to increasing guilt about driving solo

Riders Perspective

  • Cost
    Private cabs are comfortable but are costly.
  • Safety woes
    Public transport can be unsafe at odd hours, and it’s worse for women.
  • Couldn't trust on co-passengers in the pool and share services.
  • High travel time
    Flaws in ride algorithms lead to pick-ups and drops that aren’t on the route.
  • Public transport issues
    Unreliable bus timings, long queues and waiting times at peak hours, and tiresome multi-modal travel with no guarantee of getting a seat.

User Research

Potential Target Groups

For drivers

  • Age group — 18 to 40 years
  • Tier 1,2 cities
  • Car/Bike Owners

For riders

  • Age group — 16 to 50 years
  • Tier 1,2 cities
  • Either car/bike owners or no vehicle

Use Cases (User Scenarios)

By considering both drivers and riders as customers (users), there are many use cases for which they might use the ride-sharing app. So, I put almost all the cases into 3 buckets:

  1. Commuter use case (Regular users)
    — High frequency on working days
    — Includes people going to workplaces like offices, stations, malls, etc.
    — Generally, trustworthy riders and drivers are found.
    — Service will be used most in the morning and evening time.
  2. Recreational use case (Not regular)
    — Medium frequency
    — Includes people going to Restaurants, Malls, Parks, movies, etc.
    — These cases will occur a maximum of 5–10 times a month.
  3. Intercity Travel use case
    Very low frequency
    — Includes people going on vacations, meeting relatives, attending conferences, etc.
    — 3 to 4 times a year.

As the commuters fall under the Work Use case bucket, I am majorly focussing on solving for them. This might eventually work for other use cases too.

User Personas

Keeping the use cases and users involved with the solutions in mind, I created 3 user personas for covering multiple pain points and solving for wider audience.

Driver

Aman Sethi (Age 30 years)

  • Married for 2 years now
  • Product manager
  • Lives in Aashraya Enclave, Kormangala, Bangalore (22 km from his workplace)
  • Honda Amaze owner (Goes to office solo, daily, using his car)
  • Spends roughly 10% of his income on fuel costs.
  • Pain Points
    — So expensive to drive cars these days and that too for a single person.
    — Driving solo for 22 km is again so boring to follow regularly, Can't use your phone too.
    — How can I give a lift to someone like that? How can I trust that person?

Rider 1

Rashi Singh (Age 25 years)

  • Unmarried
  • Works at Restaurant in Bangalore
  • Lives in a rented complex at Akash Vihar, Bangalore
  • Usually takes public transport like city busses or auto-rikshaws.
  • Waits at the bus stand for almost half an hour sometimes. Also, the bus stand is quite far from the apartment.
  • Faced unusual and strange incidents with strangers sometimes.
  • Cabs are unaffordable on a regular basis.
  • Pain Points
    — If you choose comfortable rides (cabs) then it's costly, if you choose budget-friendly rides (public busses)then they are not comfortable. Isn't there any option which is comfortable and less costly?
    — But even if it exists (solution), what about your security. Being a girl its so hard to travel with strangers these days.

Rider 2

E.M. Rao (38 years)

  • Senior Engineer at an MNC, Bangalore
  • Lives in Whitefield Bangalore (18 km from Bosch)
  • Owns Creta (SUV) but generally prefers public transport
  • Takes 1.5 hours to travel on a usual 45 min route
  • Health issues as the body is growing old.
  • Pain Points
    — A lot of time is wasted by traveling by public transport.
    — Uncomfortability
    — Cost at some point
    — Environment issues with lots of vehicles.

These user personas are used in designing the app screens and features.

Ideation

After clearing out some blockers and understanding the important pain points, the assumptions and key features of the app are now striking in my mind. Followed many processes like creating user journeys and user stories for different personas which I dint feel mentioning because those points will covered here.

Assumptions

Many of the assumptions are mentioned wherever necessary in the documentation. These are 2 important ones I thought to mention.

  • To avoid the extra step of bidding cost and agreeing on a number. I assumed that the cost breakup of a ride is estimated by the app itself using an algorithm similar to Uber Pool one.
  • Assuming the KYC of users is done in the onboarding step which will build at least a little amount of trust.

Prioritized pain points to solve for

  • To share cost breaking among the users in such a way that it's cheaper for riders to take services and it's more effective for drivers to give rides to them.
  • To reduce the fear of trusting unknowns.
  • To reduce the traveling time overall (from finding transport to the rerouting of cab drivers).
  • To reduce the efforts of interaction, whether it's with an app's interface or with cab drivers not getting correct locations.
  • To reduce the environmental issues (it will be a very small change but it can be the start of something big).

Key Features

  • The user can choose between whether to offer ride or request ride on the home screen. Also on the next screen while inputting start and destination location.
  • The app is map view based, i.e most of the interactions are while viewing route or navigating.
  • A side menu is given to quickly go to various screens like messages, Previous rides, Payments, settings etc.
  • The rider can choose how many seats he/she requires and the results are displayed accordingly.
  • Similarly, a driver can choose the seating capacity and waiting time he/she can devote for riders.
  • Listing the ride information for riders allows them to see who the driver is, rating, vehicle details, waiting time, drop time, seat capacity etc. The rider can also click the driver photo to view his/her full profile.
  • The rider is also provided with the details of their co-riders to gain a pinch of trust and assure safety.
  • For safety, emergency buttons and ride-sharing options will be given.
  • Similarly, the driver can accept or reject any request according to his/her will.
  • The driver will be given the option to call or message (via app) if the rider takes time.

Information Architecture

Information architecture covering both rider and driver flow.

User Workflow (interaction with app)

User Workflow of Rider end (Green) and Driver end (Blue)

Wireframes

Wireframes — Rider Screens
Wireframes — Driver Screen

Designed Screens

Designs — Rider Screens
Designs — Driver Screens

Future Scope

Ride Scheduling

It is not always possible that the driver finds a rider once he/she has started his/her journey. so, in order to fetch more riders, the driver can schedule the ride for later.

Women-centric user experience

With increasing concerns of women security in the current commuting ways. We have decided to incorporate a feature for women which connects them only with women drivers in the subsequent versions.

Subscribe to another user

Why book the same driver for the same time and same destination daily, when you can subscribe to him/her for the upcoming week/month and save more?

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Vaibhav Khandelwal

Vaibhav Khandelwal

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I am a self taught product designer from IIT Roorkee. Enjoy searching and designing solutions for real problems.