SERVICES

Tablet Design


CATEGORY

Retail


REALIZED

May 2024


Computer Vision Based
Self-checkout

to enhance convenience by streamlining the process and reducing wait times.

The system has been deployed in 2,000 stores to date.

to enhance convenience by streamlining the process and reducing wait times.

The system has been deployed in 2,000 stores to date.

BACKGROUND

Shaping the future of convenience

7-Eleven is a global convenience store chain known for its wide range of products and innovative shopping experiences. With a presence in over 17 countries, it aims to provide quick and easy solutions for customers' daily needs.

QCO

A quick self-checkout system to reduce wait times and streamline the checkout process.

Impact of Design

2,000

Stores with Self-Checkout

$47 million

Sales Generated

$48 million

$48

million

Saved in Annual Labor Costs

7 Million

Transactions Processed

My Role

As part of the 7-Eleven R&D team, I partnered with two project managers and one other UX designer to transform concepts into features that meet customer behaviors and motivations.

As part of the 7-Eleven R&D team, I partnered with two project managers and one other UX designer to transform concepts into features that meet customer behaviors and motivations.

Planning & Scope

Defined the product with PM partners, balancing customer and business goals.

User Flows

Developed detailed user flows for a smooth and intuitive user experience.

Visual Execution

Created high-fidelity mockups and final visual designs.

Prototypes

Built interactive prototypes for testing and validation.

User Testing

Conducted sessions and iterated based on feedback.

Research

70%

customers say checkout lines are their biggest pain point.

See More Research

Why do customers use checkout?

Insights

Why do customers dislike self checkout?

85% had issues with item scanning, like items not scanning correctly or needing multiple attempts.

54% of users found the self-checkout interface confusing, leading to errors and delays

67% faced problems with the payment process.

User Journey

Challenges

Accuracy and Reliability

Ensuring the computer vision system accurately identifies and classifies items is crucial. To mitigate recognition errors, we need to provide users with clear guidance on using the system correctly, like how to position items.

Problem Reporting

Since the algorithm isn't fully accurate, issues like unrecognized or similar items may arise. We aim to provide simple, user-friendly solutions to help users quickly resolve these problems.

Effective Item Searches

When users manually input items, they often face challenges with search results that do not match their terms accurately. Common issues include misspellings, similar item names, and insufficient suggestions. We need to enhance search functionality to improve accuracy and relevance of search results.

Ideation

In our ideation process, we began with group brainstorming sessions to collaboratively generate and conceptualize ideas. These sessions fostered creativity and allowed us to explore a wide range of possibilities. After narrowing down the best concepts, we created low-fidelity prototypes to test and validate these ideas. These prototypes were essential in identifying potential issues and gathering initial feedback, which informed subsequent iterations and refinements.

Happy Path

"What's this?"

In addition to the main user flow, a key feature is the "What's This?" option.


If the algorithm fails to recognize similar items or items within a container, users are prompted with "What's This?" to allow them to manually identify the items.

We've developed dedicated flows to address these edge cases.

A/B Test

Methods

Moderated usability tests – 10 self-checkout customers

Data collected: January 24-26th

Goals

Understand delights, pain points and opportunities

Understand the usability of QCO unrecognized item flow

1

A

B

A/B TEST

Summary

Summary

01

CTA hierarchy is important.

If Finalize & Pay is primary action, then that CTA should be prioritized or highlighted.

02

Customers prefer clear instructional prompts. A full-screen experience for adding items is favored as it reduces distractions and has clear guidance.

03

Users mentioned that the graphics displayed provided instructional information and they were pleased with the look & feel.

Final Design

Usability Study

Observe store customers as they use the QCO and note any technical or usability issues they encounter, using a pilot QCO at the Sound 7-Eleven Store in Coppel, TX.

60+

Store customers

6 hours

Conducted during 6 hours

Summary

Almost everyone was willing to try the QCO

Associates were able to spend more time cleaning, stocking shelves, and preparing fresh food when customers were willing to use self-checkout without assistance.

However, a few customers stated an overall preference to bechecked out by an Associate.

"That's as easy as it gets"

"Wow that's phenomenal"

"Amazing"

"How awesome"

"Pretty easy"

47 store customers who used the QCO rated its ease of use

/10

9.6

Key Metrics

Following the usability study, we established specific metrics to measure the success and impact of the self-checkout system.

Transaction Goal:

15%

eligible transactions to be processed through the self-checkout system.

Customer Retention:

50%

of customers who use the self-checkout system for the first time return to use it again.

Search Efficiency:

80%

success rate for customers using the search function for items

Transaction Fit:

<40%

of transactions that are suitable for self-checkout are diverted to traditional registers when the self-checkout system could have met their needs.

By setting these metrics, we aimed to ensure that the self-checkout system not only met usability standards but also achieved business goals related to customer satisfaction. Monitoring these KPIs allowed us to make data-driven decisions and further refine the system based on real-world usage and feedback.

Key Metrics

Following the usability study, we established specific metrics to measure the success and impact of the self-checkout system.

Transaction Goal:

15%

eligible transactions to be processed through the self-checkout system.

Customer Retention:

50%

of customers who use the self-checkout system for the first time return to use it again.

Search Efficiency:

80%

success rate for customers using the search function for items

Transaction Fit:

<40%

of transactions that are suitable for self-checkout are diverted to traditional registers when the self-checkout system could have met their needs.

By setting these metrics, we aimed to ensure that the self-checkout system not only met usability standards but also achieved business goals related to customer satisfaction. Monitoring these KPIs allowed us to make data-driven decisions and further refine the system based on real-world usage and feedback.

Other Explorations

This is an un-used alternative exploration of how to navigate lists and search for items.

Other Explorations

This is an un-used alternative exploration of how to navigate lists and search for items.

Other Works

Internal Platform

2022

Internal Platform

2022