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Enterprise · Mobile · Toshiba ELERA

Associate Mobile Redesign

Toshiba ELERA® platform powers unified in-store experiences worldwide. I redesigned the Associate Mobile app, a critical tool store associates rely on during peak-hour checkout.

My role
UX Research & Design
Type
Enterprise mobile
Time
8 weeks
Team
Sr. UX Designer, Engineering
Tools
Figma, Zoom
View product
Associate Mobile Redesign before and after

Improved operational efficiency and boosted checkout speed

Goals

Peak-hour speed

Speed up checkout and reduce walk-aways without adding new hardware

Associate clarity

Make critical actions visible and workflows harder to mess up during rush periods

Minimal disruption

Improve within existing store workflows with no new hardware or major operational changes

Impact

Faster checkout

+43% checkout speed for associates during peak hours

Less abandonment

−58% cart abandonment at mobile POS lanes

Revenue growth

+18% monthly revenue from improved store throughput

Overview

A critical tool during peak-hour checkout

Anywhere checkout

Line-busting, assisted selling, and returns on the floor

Peak-hour pressure

Associates move fast; the app has to keep up

Business stake

Slowdowns mean abandoned carts and lost revenue

Associate holding a Toshiba handheld running ELERA Associate Mobile checkout on the store floor
Peak-hour floor checkout. When the app slows down, customers walk away. Image: Toshiba Global Commerce Solutions

Problem

Peak hours cost retailers revenue and loyalty

Retailers using Toshiba lose revenue during peak hours when carts are abandoned or customers switch to competitors, costing stores millions in lost sales each year.

15–20%

Revenue at risk
Peak-hour loss from cart abandonment & switching

$50–$100M

Retailer scale
Mid-sized annual revenue band

$7.5–$20M

Lost sales annually
Estimated yearly lost sales at mid-sized scale

User research

Interviews, surveys, and usability testing

I needed to understand how associates work during peak hours and why shoppers still walk away, even with mobile and fixed POS on the floor. I conducted an in-store survey with customers and shopper assistants to quantify both sides of the experience.

7 User interviews and usability tests using think-aloud method
In-store Survey with customers and shopper assistants
43.3% Of shoppers still abandon lines despite mobile POS
Customer survey results

Customers express frustration with wait times

Associate survey results

Associates struggle with outdated tools

Associate inefficiencies from outdated systems directly impact the customer experience. Their pain points align with customer frustration about wait times and line abandonment.

What Associates Told Us
"I miss important notifications like 'printer out of paper.' They're hard to notice."
- Shoppers Assistant
"Hidden options slow me down and customers get frustrated waiting."
- Customer Service Lead
"In a rush, the app confuses me and I void items by mistake."
- Cashier Supervisor

Insights

What did we learn from usability testing?

01
Visibility Issues
Critical notifications hidden
02
Navigation Issues
Competing menus break flow
03
Icon Mismatches
Icons don't match meaning
04
Error Prevention
Risky placement of void button

Define

How might we

How might we speed up checkout and prevent walk-aways during peak hours using the resources the store already has, without major changes?

Constraints

Designing within real-world limits

No new hardware
Stores cannot afford another fixed-lane POS.
Legacy system
Improve Associate Mobile within ELERA, no full platform rebuild.
Time pressure
8 weeks from discovery to implementation.

Solution

Redesigning for speed and fewer mistakes

I mapped each usability finding to a specific UI change, then prototyped against peak-hour checkout tasks and validated with think-aloud tests. The goal: reduce cognitive load by making actions scannable, predictable, and harder to trigger by mistake.

Appendix

When mobile POS works best

Mobile POS was expected to reduce queue abandonment, but 43.3% of shoppers still abandon lines. This comparison shows where Associate Mobile fits relative to fixed lanes and self-checkout.

Use Case Associate Mobile Fixed POS Self-Checkout
Peak-hour line-busting ⭐⭐⭐ ⭐ ⭐⭐
Assisted selling ⭐⭐⭐ ⭐ –
Big baskets / complex tenders ⭐ ⭐⭐⭐ ⭐
Returns with verification ⭐⭐⭐ ⭐⭐ –
Small Baskets ⭐⭐⭐ ⭐ ⭐⭐⭐

Key takeaways

What this project proved

  • Associates and customers named the same peak-hour bottleneck.
  • Small UX fixes → +43% speed, −58% abandonment, +18% revenue.
  • Legacy constraints still allow fast, high-impact shipping.

Collaborating closely with my team shaped how I approach complex systems: listen first, prototype against real store constraints, and measure what matters to the business.

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