Project Context
There has been increasing online demand for inDrive to introduce a feature enabling riders to travel with specific or favorite drivers. Our capstone team intends to investigate this request thoroughly to identify the underlying “user needs” behind this “user want.”
Through independent user research, we discovered that inDrive users desire more freedom to customize or recreate a memorable ride experience, focusing on the overall journey, the car, the service, and the interaction rather than the specific driver.
This led us to ask, “How might we help inDrive riders recreate an exceptional inDrive experience?”
Solution
We enhanced the riding experience by integrating the Favorite Driver feature, allowing users to create and customize a list of preferred drivers. Riders can also add multiple compliments to drivers, helping them remember and select the best drivers for future journeys based on past experiences.
Success impact
- The feature was incorporated by inDrive and was live at the end of 2022. Till July 2024, over 100K+ users have used this feature.
- This feature is live to 150M users in Pakistan.
- Favorite Driver feature has enabled 1200+ drivers to become favorite drivers and earn more.
- Rider experience is more enjoyable with is feature and 6K users drive daily with their favorite drives.
My role and team
Role: UX/UI Designer
Timeline: Aug 2021 – Feb 2022
Methods & Tool: User Interviews, Competitive Analysis, Usability Study, Affinity Map, Service Blueprint, Figma
Teammates: Salman Asghar (PM) Junaid Khalid (Designer) Shahzaib (Developer) Haider Ali (Developer)
Process
Followed HCD process throughout 6 months
Over a six-month period, we adhered to the Human-Centered Design (HCD) process to explore how inDrive riders might want to customize their ride experiences according to their preferences. Guided by user research, we brainstormed and designed various solutions. Our ideas were then tested through usability tests, leading to the development of a high-fidelity interactive prototype based on our findings.
Discovery
Competitive Analysis: Similar Products Already Existed
To start the research, we analyzed 4 direct competitors in the ride-sharing industry (Uber, Caream, Yango, Bykea).
We learned that:
1. Uber allows users to schedule rides or services with preferred drivers/walkers, letting users choose specific individuals.
2. Most applications enable users to maintain a list of preferred drivers, typically those they have previously ridden with, by marking them as favorites or adding them via driver ID.
3. Yango offers riders the ability to search for drivers with specific amenities and favorite them. Yango’s driver profiles are more detailed than those on inDrive.
Learned from Uber employees: scheduled ride would be a better use case
We conducted 3 subject matter expert (SME) interviews with inDrive employees to gain insights into inDrive’s business and product objectives. These interviews helped us define the project scope and better understand the potential for a favorite driver solution. We discovered that matching with specific drivers or driver types can lead to longer wait times and higher trip costs. However, in the Scheduled Ride scenario, where riders can book trips up to 30 days in advance, it is more feasible for the system to spend additional time matching specific drivers to rider preferences.
User Interviews: wants ≠ needs
Based on suggestions from inDrive employees, we conducted interviews with 8 inDrive Premium riders to gather qualitative insights into both rider and driver experiences. The goal was to determine whether there is a demand for a feature allowing riders to select their favorite drivers.
Use Cases
Identifying high-impact scenarios when customization is needed
While analyzing our findings from user interviews, we identified airport rides and special occasions to be the most common use cases or scenarios where riders stated they would utilize a solution to customize their rides. Therefore, we determined the solution needs to account for:
1. High-stress situations
2. Time sensitivity
3. Quality of service
4. Safety
Design Requirements
People want “the least number of taps”
Thinking through what a rider would need during the use cases identified, we determined design requirements for the solution. We did so to ensure we were holding ourselves accountable to referring back to the data learned in research, and to use these requirements as our guiding principles as we moved onto brainstorming.
Ideation
Brainstormed the possible UX for the new feature
Designing a new feature within the rider experience required us to brainstorm not only the design but how we would introduce this new flow to users. We explored different solutions and sketched out the user flows. Then we discussed and decided the most feasible solution for this new feature.
Solution
Favorite Driver Solution
We identified two possible design solutions. The first, an option for riders to input certain preferences (i.e. a quiet ride, extra luggage, room for pets) for each ride. The other, an option to favorite and request specific drivers that delivered an ideal Uber experience. We chose the latter, as we thought by allowing riders to request specific drivers, they would really be favoriting an entire experience which embodied their preferences, and giving them an opportunity to recreate this experience.
We named the solution Favorite Driver.
Service Design Blueprint: How does it work
To help us identify current gaps in the ride experience, we created a service design blueprint. Through this exercise, we identified new entry points for the favorite driver solution. In addition, we were also able to identify both front end and back end processes needed to support this new feature.
We then created a second service design blueprint to help us identify current gaps in the scheduled ride experience. Coming out of research we heard riders speak to wanting to use this feature in a scheduled context. We identified new entry points for the favorite driver solution, as well as a new workflow between the rider, driver, and backend system.
Usability Tests
Evaluate the mid-fidelity prototypes
We narrowed down on potential ideas and started prototyping Favorite Driver based on the flow identified in the service design blueprints. We created a mid-fidelity prototype and moved on to evaluate on that.
We recruited six inDrive riders via our social channels. Using a screener, we selected participants who use the service at least three times a month and have varying levels of experience with scheduling rides in advance.
Our testing goals included:
1. Evaluating the discoverability of new features like “Add Favorite Driver”
2. Assessing the usability of the updated interaction flow
3. Understanding riders’ behaviors, particularly regarding how and when they rate drivers
Iterations
Based on the key findings we synthesized through conducting affinity diagram, we iterated on the design and upgraded the prototype from mid-fidelity to high-fidelity.
Key Finding #1: Streamlined Post-Ride Experience for Riders, less tap more functions
To enhance the user experience and minimize the number of taps required after a ride, we have introduced a new combined screen. This consolidated interface allows riders to perform multiple actions in one place, including rating their ride, leaving a compliment, adding a tip, and marking the driver as a favorite. This update is designed to make the post-ride process more efficient and user-friendly, ensuring a seamless and quick completion of these important tasks.
Solution – Consolidated interface. Introduced a new combined screen.
Key Finding #2: Enhancing User Experience by Adding “Favorite Rider” Feature to Hamburger Menu
To improve the user experience, we are introducing a new feature that allows users to add riders to their “Favorite Rider” list, which can be easily accessed through the hamburger menu. Users will have the ability to select their preferred riders and add them to their favorites via a simple interface, such as a button next to each rider’s profile or name. Once riders are added to the “Favorite Rider” list, users can quickly access this list from the hamburger menu by selecting the “Favorite Riders” option.
This will lead to a dedicated section displaying all the users’ favorite riders, providing detailed information about each rider and quick access to their profiles and activities. By enabling users to curate and easily access their favorite riders, we significantly enhance the overall user experience, making it easier for users to keep track of their preferred riders and engage with their activities more efficiently. Implementing this feature not only boosts user satisfaction but also encourages greater interaction within the platform.
Solution – Adding “Favorite Rider” Feature to Hamburger Menu
Key Finding #3: Riders want information that can help them remember why they marked drivers as their favorite
To help riders remember why they marked specific drivers as their favorites, we have introduced a system of personalized compliments that highlight the unique qualities of each driver. These compliments, such as “comfort,” “relaxing,” “great music,” and “talkative,” serve as key indicators of the positive experiences riders had during their journeys.
By associating these compliments with individual drivers, riders can easily recall the attributes that made their trips enjoyable and worth favoriting. This approach not only enhances the rider experience but also encourages drivers to maintain high standards and foster a positive atmosphere during rides.
Solution – Personalized Compliments for Memorable Journeys
Key Finding #4: Riders want to schedule the ride with the favorite driver at one tap
When scheduling a ride, the rider is presented with the option to select a driver from their favorite driver list. This list is curated based on the rider’s past positive experiences and preferences, offering a personalized and reliable choice for their journey. If the rider decides not to choose a driver from their favorite list, they can opt for a new driver. This flexibility ensures that riders can either stick with familiar, trusted drivers or explore new options, depending on their current needs and preferences. The system aims to enhance the booking experience by providing these tailored options, ensuring both comfort and convenience for the rider.
Solution – Selecting a Driver: Using the Favorite Driver List or Choosing a New Option
Final Design
Our final design included four main opportunity areas for rider interaction with Favorite Driver within the inDrive application. We updated the existing rating screen by adding a trigger and prompt for Favorite Driver. For the other three areas, we innovated by creating new experiences for during-trip ratings, favorite driver selection in a scheduled ride, and the Favorite Driver list. Additionally, although out of scope, we designed a solution for driver acceptance, developing a mechanism for drivers to opt-in to Favorite Driver.
Reflections
There are several potential risks to consider with this feature. Rider prejudice based on traits such as gender, ethnicity, age, or sexual orientation could influence the frequency of repeat driver requests. Consequently, drivers from certain demographics might receive more business than others.
Moreover, by enabling drivers to learn the habits and routines of repeat riders, there is a risk that unscrupulous drivers could exploit this information. For instance, if a driver knows that a rider regularly travels to the airport, they could deduce when the rider is not home, thereby increasing the vulnerability of the rider’s home and belongings.
Another potential risk is that when a driver consistently drives a rider using the Favorite Driver feature, they might be more inclined to conduct business outside of the inDrive app. In such cases, while both the driver and rider would benefit from their direct relationship, inDrive would lose out on potential profits.
Solution impact
It was thrilling to discover that the “Favorite Driver” feature was launched by inDrive, incorporating many of our designs and ideas. For more details, you can check out this article and the inDrive page.
- The feature was incorporated by inDrive and was live at the end of 2022. Till July 2024, over 100K+ users have used this feature.
- This feature is live to 150M users in Pakistan.
- Favorite Driver feature has enabled 1200+ drivers to become favorite drivers and earn more.
- Rider experience is more enjoyable with is feature and 6K users drive daily with their favorite drives.