Increased Retention Rate of WashPay

UX Case Study

Project Overview

About WashPay

WashPay is a mobile payment application for laundry. It helps the users pay for their laundry with the help of a mobile app instead of using coins or cards.

My Role

UX Research | UI Design

Timeline

4 weeks

Team

Individual

Business Problem

WashPay was losing users since the mobile app was not engaging thus leading to decreased adoption of the mobile payment application that negatively impacted the ROI.

Goal

The aim of the project's to identify the limitations of the mobile payment application and provide feasible and scalable solutions to increase the retention rate.

Quick glimpse of my design process

User Research

I wanted to understand the user's perspective of the application including their pain points. Hence, I started analysing the reviews from Google and App Store to gather insights.

From the reviews I understood most users faced difficulties to complete a workflow that resulted in poor ratings to the application.

Secondary Research (Play Store Reviews)

I collected poorly rated reviews from Play and App Store and identified all the possible issues reported.

Note: Reviews were collected since the last update of the app (Last update: November 04, 2022)

Primary Research (User Research Survey)

To verify if the user reported issues were real, I conducted a survey using Google Forms with the actual users of the WasPay app.

Surveyed 15 participants and found the following :

COUNT OF USERS ADDRESSING AN ISSUE

Usability Testing

Once the user survey was done, the existing application was tested with 5 participants. Usability testing was conducted to understand the impact of each issue identified during the survey and also to know whether these issues were actual issues to the users or not.

Participants were given 3 scenarios and 3 tasks under each scenario to understand users’ opinions and feedback on the website.

Usability Test Insights

User Journey Mapping

5 participants' behaviors were analysed while performing the task of starting a machine from start till end. Their behaviors and emotions were tracked to understand their pain points as they perform the actual task.

Issues that had severe impact in users:

Competitor Analysis

Competitor Analysis was done to identify what distinguishable features are being provided. Identifying these distinguishable feature and implementing them into the WashPay app will help in increasing the retention rate.

Criteria to choose competitors

- Number of downloads (To know the popularity of the app) (With the help of PENDO tool)
- App Store & Play Store Ratings (To know the performance of the app)

Major Competitors

Number of Downloads: 13,456
Play Store Ratings: 4.4 stars
App Store Ratings: 4.7 stars
Number of Downloads: 9,224
Play Store Ratings: 4.3 stars
App Store Ratings: 4.7 stars

Features

Real-time status of the machine
Availability of machines
“Scan to Pay” payment option
Notification on completion of machine
Transaction history
Simple problem reporting process
Points and rewards

Insights

Persona (Target Audience)

With the insights from the survey, personas were created. Personas were classified into 2 categories based on the frequency of doing laundry. This is because users doing laundry weekly once had different pain points compared to those who do laundry bi-weekly.

Note: Personas were classified into 2 categories based on the frequency of doing laundry.

Frequent LAUNDRY User

Occasional LAUNDRY User

Classification of Issues

Sketches

User Flow

Sketches (Possible Solutions)

Prototype

High Fidelity Design

Solution #1 - Differentiate Washers and Dryers

Solution #2 - Custom "Add to funds" section

Solution #3 - Available machines

Design iteration based on user feedback

Once the initial high fidelity designs were created, it was once again tested with 5 participants. Participants were given 3 scenarios and 3 tasks under each scenario which were the same as the previous usability test.

User behaviours and feedback were collected. With the help of feedback collected, necessary design iterations were made to make the product desirable and user-friendly for the users.

Conclusion

Users felt difficulty to identify the available machines while being at home which was a serious issue that made users get frustrated easily. This was a major cause of poor retention rate.

Quick QR code scan to start a machine, providing option for adding custom funds to wallet and letting users know the available machines while being at home helped users in completing the laundry process easily and eventually helped to improve the retention rate of the application.

What did I learn?

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Thank you for reading!

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