UBER
Situation
Same cars, same app, same price points. The functional delivery that had once set Uber apart had become the baseline, and rivals were meeting it comfortably.
The harder problem was loyalty. Riders used Uber out of habit and convenience, not connection. When the experience worked, it was forgotten. When it failed, it was remembered. Teams had behavioural data in quantity, but no shared understanding of what riders actually felt, or where in the journey those feelings determined whether someone came back. Decisions defaulted to feature fixes and short-term interventions. Nobody was designing around the emotions that actually drive retention.
"A car is more than just a car. It's a magic carpet, a beauty salon, a mobile office, a safe haven, a karaoke carpool…"
From rider fieldwork,
Project MUNDI
Approach
The brief was not to produce a research report. The aim was to build something that Uber's EMEA teams across Ops, Product, Marketing, and Support could actually use, without each function commissioning its own version of the same question.
Working as an integrated team of researchers, designers, and strategists alongside Uber's client team, we engaged 4,443 riders across London, Cairo, Madrid, and Johannesburg over nine months. Ride-alongs, an online community, acquisition experiments with first-time riders, co-creative workshops, and a quantitative survey fed into a regression analysis that identified the moments disproportionately driving satisfaction and predicting repeat use. Those became the 11 Moments That Matter.
My role was to lead the experience system design throughout: from how the research was framed and what it needed to produce, to the designed system that made it actionable. The question I was answering was not what mattered to riders. It was how to make that knowledge usable at scale, across functions, within Uber's existing ways of working, without creating new process overhead. The design challenge was adoption, not just insight.
System
From a brand experience perspective, the work reanchored how Uber expressed itself around trust and emotional meaning. The insight was stark: riders did not choose Uber for its functionality. They chose it when it felt like it was on their side. That shift shaped brand language and tone across the moments the regression had flagged as highest-stakes.
On the customer experience side, the 11 moments were mapped into 8 Experience Platforms, each one a specific opportunity space where investment in emotional quality would most affect loyalty. These replaced ad hoc briefs as the shared planning foundation across functions. For the first time, Ops, Product, Marketing, and Support were working from the same picture of the rider, with the same language for what mattered.
The service design work translated everything into a deployable digital toolkit: a Rider Experience Map covering 8 phases and 26 steps, 11 Moments That Matter cards, the 8 Platform documents, an activation playbook, and a data dashboard. All of it was built into Uber's own microsite and workflows. Teams could reach the tools inside their existing planning cycles. The system was stress-tested across 10 co-creation workshops before the platform went live.
"The impact of this work could really have only been realised through a strong strategic partnership and C Space understood early on that more than a detailed map of our customer experience, what we really needed were the tools to activate and embed this in the business."
Daniela Nortjé
Customer Experience
Insights & Innovation
Uber EMEA
Outcomes
Experience Systems gave the work its coherence: brand experience reframed what loyalty meant for Uber, customer experience pinpointed where it was being won and lost, and service design ensured the tools for acting on that knowledge were embedded where teams already worked.
4,443 riders across 4 markets, validated by regression analysis, gave Uber its first evidence-based view of the emotional drivers of rider loyalty.
11 Moments That Matter and 8 Experience Platforms replaced siloed briefs as the shared planning language across Ops, Product, Marketing, and Support.
Planning cycle effort reduced by an estimated 20–30% as teams used the ready-built toolkit rather than commissioning bespoke research per initiative.