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Rover Rush Pickup app
Introduction

As a UX/UI Designer at Coles, I had the opportunity to work on the “Rover Rush Pickup App” project, aimed at optimizing the order picking and packing process for Coles’ online orders. Coles’ dark stores serve as fulfilment centres where orders are picked and packed by Coles order pickers. The Rover Rush Pickup App, pre-loaded on Zebra PDT devices, plays a pivotal role in guiding order pickers through the fulfilment process, ensuring accuracy and efficiency.

… New Rover Rush app is such a time saver. I am able to find the item Isle location quickly ... 

I did end-to-end journey mapping along with pickup store visits and getting to pick and pack orders to help understand the current pain points and areas of opportunities for this project.

Domain

Domain:
e-Commerce
Team member experience
Pickup and delivery service
Notify real-time experience

Areas:
Shopping experience
Order pickup experience
Multi device integration

Skill and Expertise:
Competitor research
Usability Audits
Low-Hi Fi prototypes
Service Design
In-store experience
TM interviews and testing
User flows & Empathy maps
Qual and Quan research

UX PROCESS INVOLVED
Data Analysis & User Research
80%
Complex UI and interaction design
85%
Project lead and management
80%
Stakeholder facilitation
75%
Workshops
75%
Low-Fi and Hi Fi Prototypes
85%
Dev support
65%
Post implementation analysis
70%
Project Overview:

The Rover Rush Pickup App was designed to streamline the order picking and packing process by providing order pickers with real-time information on product locations, aisle numbers, and item types. Additionally, the app facilitated the classification of items based on temperature requirements and allowed for customization preferences such as bagged or non-bagged items. The project aimed to address various challenges, including technology limitations, PDT constraints, aisle location discrepancies, out-of-stock items, substitute items, and optimizing pick rates by staff.

Challenges faced:

Technology Limitations:
Working within the constraints of the Zebra PDT devices posed challenges in terms of screen size, processing power, and usability.

Aisle Location Discrepancies:
Inaccurate aisle locations or aisle congestion could lead to delays and inefficiencies in the picking process.

Out-of-Stock Items:
Unavailable items posed a challenge in fulfilling orders accurately, requiring efficient substitution processes.

Substitute Items:
Selecting appropriate substitute items in the absence of requested items required clear communication and decision-making by order pickers.

Pickup Time and Pick Rate:
Ensuring orders were picked and packed within the designated timeframes while maintaining a high pick rate by staff was crucial for meeting customer expectations.

METHODOLOGY:

User Research:
Conducted user interviews and observations to understand the pain points and preferences of order pickers.

Iterative Design:
Utilized an iterative design process, incorporating feedback from stakeholders and end-users to refine the app’s interface and functionality.

Usability Testing:
Conducted usability testing sessions to evaluate the app’s effectiveness in real-world scenarios and identify areas for improvement.

Collaboration:
Collaborated closely with cross-functional teams, including developers, product managers, and operations staff, to ensure alignment and successful implementation of the app.

KEY FEATURES AND SOLUTIONS:

Real-time Product Location:
Implemented a feature to provide real-time updates on product locations and aisle numbers, reducing search time and improving efficiency.

Temperature Classification:
Integrated functionality to classify items based on temperature requirements, ensuring proper handling and storage during the picking process.

Customization Preferences:
Incorporated options for bagged or non-bagged items based on customer preferences, improving order accuracy and customer satisfaction.

Delivery Notes:
Included detailed delivery instructions for drivers to ensure seamless order delivery and customer experience.

OUTCOMES:

Improved Efficiency:
The Rover Rush Pickup App contributed to significant improvements in order fulfillment efficiency, reducing picking time and error rates.

Enhanced User Experience:
User feedback indicated a positive response to the app’s intuitive interface and helpful features, resulting in increased user satisfaction and engagement.

Reduced Errors:
The app’s real-time updates and classification features helped reduce errors related to product location, temperature handling, and substitution.

Streamlined Operations:
By addressing challenges such as out-of-stock items and aisle location discrepancies, the app helped streamline operations and improve overall productivity in Coles’ dark stores.

CONCLUSION:

Improved Efficiency: The Rover Rush Pickup App contributed to significant improvements in order fulfilment efficiency, reducing picking time and error rates.

Enhanced User Experience: User feedback indicated a positive response to the app’s intuitive interface and helpful features, resulting in increased user satisfaction and engagement.

Reduced Errors: The app’s real-time updates and classification features helped reduce errors related to product location, temperature handling, and substitution.

Streamlined Operations: By addressing challenges such as out-of-stock items and aisle location discrepancies, the app helped streamline operations and improve overall productivity in Coles’ dark stores.