Nourish Co-design: Capturing the full end-to-end micro-mobility journey across London

The Challenge

Micro-mobility is having a moment. E-bikes, e-scooters and ride-share services are reshaping how people move around cities, and the way cities are being planned around them. But the actual user experience is genuinely complicated. A single ride-share trip touches a physical vehicle, at least one mobile app, parking signage, cycle infrastructure, payment systems and city-borough rules. Each of those is built and managed by a different organisation, and most user research only looks at one piece at a time.

These are complex, multi-faceted experiences built from a combination of physical vehicles, mobile apps, city infrastructure. And often user research focuses on one channel like the app, or just the signage, but it doesn't see the bigger picture.

For Nourish Co-Design, a research and service innovation consultancy run by James Sunderland, that bigger-picture view was the whole point. The team set out to look at micro-mobility across the experience, find the biggest unmet user needs and pain points end-to-end, and identify where new users' confidence breaks down on first use.

‍

The Approach

Nourish Co-Design built the Micro-Machines London study around a three-week digital diary study with 12 participants, deliberately mixing experienced ride-share users, people building confidence for the first time, and people who own their own e-bikes. Some used e-bikes, some used e-scooters, all moved around London.

End-to-end trip capture. Every stage of every trip, from planning a journey to picking up a vehicle to making the journey itself to paying to reflecting at the end. The study was designed to see the seams between the parts, not just the parts in isolation.

Multi-touchpoint capture via Indeemo. Selfie videos in the moment, screen recordings of provider apps mid-trip, photos of bike racks and parking signage. Whatever caught the actual experience.

A deliberate mix of user types. Three segments, experienced ride-share users, new users, and e-bike owners, so the team could see what was shared across very different starting points.

Three weeks of field time. Long enough to see the same user across multiple journeys in multiple conditions, with the consistency to spot patterns rather than one-off frustrations.

The diary study format mattered for one specific reason: it kept the data anchored in real journeys rather than what people remembered or predicted afterwards. Someone walking through their actual provider-app experience while standing next to the bike caught details that wouldn't survive a focus-group recall.

I always envisaged this project would be built around a digital diary study because I know they can be this really powerful method to capture participants' in-the-moment reflections and just report from the frontline of real service experiences.

‍

The Results

The richest finding wasn't about any one touchpoint. It was about what happened in the gaps between them.

Trip navigation is fragmented and distracting. At the time of the study, the major provider apps didn't support in-trip navigation. Users had to load the provider app to find a vehicle, switch to Google Maps or Citymapper to navigate, then switch back to the provider app to find a legal parking spot. The app-switching created friction at every transition.

Personal smartphones are doing too much heavy lifting. Bikes and scooters typically rely on flimsy silicon mounts for the rider's personal phone, and phone theft in London is high and rising. Participants felt visibly vulnerable, which opened up genuine conversations about alternatives: smartwatches, bike-mounted navigation, anything that took the expensive phone off the handlebars.

Infrastructure isn't fit for the vehicles people are actually using. One participant, a busy mother of three on an e-cargo bike, summarised it directly.

I don't feel like it fits in the cycle lanes, and I also don't feel that the parking spaces, the traditional bike parking spaces can fit it either.

For city planners trying to design around carless futures, that mismatch is a structural problem.

Borough-level parking rules push the burden onto riders. Parking regulations differ between London boroughs. One participant on a Lime bike had to backtrack half a kilometre after meeting friends at a pub before finding a spot the app would accept. The cost of inconsistent rules ends up sitting with the user, not the operator.

The confidence gap is bigger than it looks. Recruiting experienced ride-share users with three or four years of experience was easy. Recruiting people considering it for the first time was hard, and that's the cohort cities will need to convert if they're going to go carless at scale.

The study generated what James calls a gold mine, a treasure trove of insight, that Nourish Co-Design is now turning into a custom AI model. The idea: let people inside ride-share operators and city planning teams query the research findings in plain English, with answers grounded in real participants and real journeys rather than synthetic users. That work is in prototype.

Often change doesn't happen without data that supports that change. I hope that rich exploratory research methods like digital diary studies can give that really deep and powerful user perspective that will help build an evidence case and persuade people of the need for change.