David Randall PhD 👋
A Passionate User Research Specialist with 15 years of Experience conducting research in academia and business.
Vehicle Search Redesign and Beta Rollout
Overview
BCA set out to overhaul its core vehicle search, a high-traffic feature critical to buyer conversion. I led significant discovery and usability research to shape the new design and algorithm, ensuring it addressed real customer needs before moving into rollout. My role then shifted to guiding the live release strategy, making sure adoption was evidence-based, low risk and strategically aligned.
Research Goals: 🎯 Validate usability and relevance of the new search in real-world conditions 🎯 Capture behavioural and attitudinal feedback to guide refinements 🎯 Detect and resolve issues that only emerge at scale 🎯 Monitor adoption and satisfaction to support rollout decisions
Beta Testing
To safeguard revenue and user trust, I designed a staged beta release beginning with 10 percent of users and gradually scaling to 100 percent. This phased approach enabled me to monitor adoption, uncover issues invisible in lab testing and make data-driven decisions about when to progress. The strategy blended intercept feedback, pulse surveys and behavioural analytics to create a continuous loop of evidence for leadership.
Process:
- ⚙️ Beta Rollout: Initial release to 10 percent of users, gradually increasing to full coverage
- ⚙️ Intercept Feedback: Qualtrics intercepts captured feedback at key interaction points
- ⚙️ Pulse Surveys: Surveys were triggered following major rollout stages
- ⚙️ Issue Resolution: Several critical bugs were caught during rollout and resolved promptly thanks to user reports
Methodology:
- 🧪 Discovery and Testing: Foundational research and iterative lab tests shaped the new design
- 🧪 Real-time Intercepts: Users gave contextual feedback without leaving the search experience
- 🧪 Behavioural Analytics: Adobe Analytics tracked usage patterns and drop-offs, identifying issues early
- 🧪 Pause and Resume: Approach allowed for rapid identifcation and resolution of significant bugs.
Outcomes
The staged beta allowed BCA to identify and resolve high-impact issues before full release, minimising risk and protecting client experience. Once the rollout reached 100 percent, adoption remained strong with minimal resistance. The new search increased vehicle purchases and reduced average search time, validating the investment in both algorithm and design improvements.
