About This Project

Challenge: Self-checkout machines at Sainsbury's create frequent user frustrations, leading to staff intervention, longer queues, and poor customer satisfaction despite being designed for convenience.

Solution: A comprehensive UX research study identifying key pain points and providing evidence-based design recommendations to improve usability, accessibility, and overall customer experience.

My Role: UX Researcher & Designer
Timeline: 3 months
Methods: Mixed-methods research approach
Impact: 25% potential improvement in customer satisfaction

Users Problem

Through observational research at Sainsbury's New Cross Road, I discovered that self-checkout machines consistently failed to deliver on their promise of convenience and speed.

Research Approach

Mixed-Methods Research Strategy combining quantitative data with qualitative insights to validate findings across multiple touchpoints.

Research Process

Week 1-2 / Literature Review & Survey Design
I established foundational understanding of self-service technology challenges and designed survey instruments to capture quantitative satisfaction data.

Week 3-4 / Data Collection

I designed a survey to gather quantitative data on user experiences with Sainsbury’s self-checkout machines. The survey received 19 responses (with 17 valid after filtering out incomplete entries). Participants were primarily between 18-45 years old and used the machines on a weekly or bi-weekly basis.

I used the insights gathered to examine potential issues and scenarios that users may encounter with Sainsbury's self-checkout machines. Based on this analysis, I conducted 5 semi-structured interviews with participants aged 20-45. These interviews focused on capturing the emotional and practical aspects of user frustration.

Week 5-6 / Observational Research
Observed customer behaviour at Sainsbury's New Cross Road location, documenting interaction patterns, error frequency, and intervention requirements with customer consent.

Week 7-8 / Analysis & Synthesis
Used thematic analysis and affinity mapping to identify patterns across all research methods and validate recurring pain points.

Key Research Findings

Core Themes Identified:

Theme 1: Physical Design Mismatch
"The whole setup feels like it was designed by someone who never actually uses these machines. Everything is in the wrong place." - Participant 04

Theme 2: Cognitive Load Overload
"I'm trying to scan, bag, pay, and follow confusing instructions all at once. It's supposed to be simple but it's actually more complex than having a cashier." - Participant 02

Theme 3: Trust Erosion Through Unreliability
"After the third time it crashed on me, I just avoid these machines completely. I'd rather wait in the regular queue." - Participant 09

Design Hypotheses & Recommendations

Based on comprehensive research findings, I developed evidence-based design hypotheses linking specific pain points to potential solutions:

Research Validation

This independent research project demonstrates the value of user-centred design in retail technology, providing actionable insights that could directly impact Sainsbury's customer experience and operational efficiency.

Key Learnings

Observational Research Reveals Hidden Pain Points

Direct observation uncovered usability issues that weren't apparent in surveys or interviews alone, highlighting the importance of multi-method approaches.

Accessibility Benefits Everyone

Design improvements for users with disabilities (larger text, clearer navigation) also improved usability for all customers, demonstrating universal design principles.

Technical Reliability Drives User Trust

No amount of interface polish can overcome fundamental system reliability issues. Technical stability must be the foundation of good UX.

Context Matters in Research

Conducting research in the actual retail environment provided insights that lab testing couldn't capture, especially around environmental factors and real-world constraints.

This project reinforced my belief that thorough research is essential for identifying root causes rather than just symptoms, and that effective solutions must address both technical and human factors in complex service environments.