Enhancing rider satisfaction and retention by offering a clear breakdown of their earnings.

What I Did

Background

Airlift Express is a q-commerce service that allows customers to order grocery, pharmacy and electronics items to their doorstep in 30 minutes using its app. Airlift’s rider application is used by people who want to sign-up as riders to deliver orders through Airlift and earn money. After signing up, riders use the app to enrol in shifts, get assigned orders to deliver and track their earnings. Airlift currently operates in Pakistan, so most riders have very low levels of literacy.

Challenge

This case study details the redesign of the wallet feature in the rider app, aimed at delivering a comprehensive earnings summary. Payment issues were the primary source of rider complaints, creating a perception that Airlift was being unfair. This negative view led some riders to stop working with Airlift, contributing to increased churn.

Problem Statement

This was followed by several grooming sessions with the engineering team to finalize requirements. After the initial build, I conducted a thorough design QA to ensure accurate implementation, made final adjustments.

Define the Problem (1/4)

Airlift operates in Pakistan, and most riders come from lower-income backgrounds with lower levels of tech literacy. I began by seeking to understand the rider’s workflow, and what role the Wallet feature plays in it. The best way to do this was to work as a rider myself.


This gave me a good understanding of what the rider does and how the Wallet feature intends to help them. I noticed potential problems with the feature which would be especially exacerbated by the lower tech literacy of riders. I dived deeper into these problems by conducting a thorough usability analysis.

Usability Analysis of Existing Wallet Feature

Daily View

Monthly View

Talking to Stakeholders

Having developed an understanding of what the potential reasons for payment-related complaints could be, I dug deeper to learn more about some of the actual reasons. I talked to delivery operations team members - the people closest to the riders on-ground

  • What they believe could be the cause behind the high volume of payment-related complaints
  • How much riders generally earn and how much Airlift contributes to that
  • What sort of people sign up as riders

User Research

Riders have 3 key characteristics that greatly influence how they interact with the Rider app

  • Low levels of tech literacy Riders cannot use smartphones proficiently. They know how to use specific apps - such as WhatsApp and Facebook - which they learned over time, often from friends and family.
  • Average monthly household income between PKR 30,000-50,000 and find little avenues to save money, so their job at Airlift is vital to them.
  • Their maximum education level varies between 5th and 8th grade

Research Objectives

Consolidating learnings

I transcribed all the raw data of the interviews, then grouped them into themes so that I could present them to the team in a manner that is easy to understand.

Rider's pain points

  • They want to know how much they have earned at the end of a ride, shift, or month, but have to manually calculate this. The Wallet does not clearly tell them this.
  • Riders place complaints to ask for clarity around their earnings. They want to understand how they are calculated, but are unable to do so through the Wallet.
  • Unless riders settle their dues with Airlift, they see a negative amount as their earnings for the shift. This is very confusing for the riders - some did not even know what the negative sign meant.
  • When looking at a specific payment on the app, they are unable to understand which trip or shift it is from.

Design the Solution (2/4)

Based on the rider pain points, I came up with the following How Might We (HMW) statements

Mrket Analysis

I took a look at some local applications that were solving this problem, although for a different user group - they helped small merchants maintain ledgers with their suppliers and customers.

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Digi Khata

My Khata

Wireframing & Prototyping

With an existing design system, I moved directly to high-fidelity mockups. First, I consulted the engineering team to understand the various transactions riders see and their triggers.

High Fidelity Mockups

Clearly communicates Wallet status to the rider. Balance from previous day’ transaction ensures that the rider does not get confused when clearing his dues that were accumulated from previous days. ach transaction has a description and time

Riders can use a 'monthly' filter to view aggregated values for each transaction over the entire month, eliminating the need for manual calculations. Additionally, the 'amount earned' filter totals daily earnings, providing a clear daily summary.

Test & Refine (3/4)

Testing Goals

I conducted testing sessions with 6 riders overall. 3 sessions were in-person, and 3 sessions were remote with riders from another city. This was done to ensure that our results are fully representative of the user base.

Consolidating Learnings

  • All participants felt it was a massive improvement over the old design in terms of the clarity they got about their finances
  • They understood the overall ledger-based design
  • They liked that they could view each transaction’s details to see where it came from

Deliver & Assess Impact (4/4)

After testing and iterating, I finalized the design and gave the engineering team 3 deliverables

  • An exhaustive set of screens covering different user journeys and all states (tool used: Figma)
  • An interactive prototype for different user journeys to help them understand the flow (tool used: Figma)
  • A design spec document that covered the updated architecture + information design of the feature
This was followed by multiple grooming sessions to lock the requirements with the engineering team. Once an initial build had been developed, I conducted a thorough design QA as a final check to ensure the design was translated as intended to the final, developed feature. After a couple of tweaks, the feature was rolled out to all riders.

Impact

Over the next 3 months, the following was observed