DayDeskr

DayDeskr connects two very different users who don't think about each other much:

• Bookers (desk seekers): hybrid workers, freelancers, contractors and remote employees who don't fit a traditional serviced-office model. They want a professional place to work by the hour — a quiet deep-work desk today, a meeting room for an afternoon, a call booth before a client call — without a membership they'll never use enough.
• Hosts (workspace providers): cafés, restaurants, hotels and underused commercial spaces sitting empty between breakfast and dinner, or mid-week, while still paying heating, lighting and staff. A desk sold in the quiet hours is pure margin — but only if hosting doesn't add labour, risk or complexity to a business already running on thin margins.

The platform only works if both sides transact. That made this a two-sided research problem from day one: demand research alone (would people book?) would have produced a marketplace with no supply; supply research alone would have produced venues with no one in them. The research design had to balance the needs, economics and fears of both sides — and find the point where a booking is genuinely good for the booker and the host.

The broader context made the timing sharp: hybrid work had normalised, employees were pushing back on rigid office mandates, and flexible workspace demand was growing fast — but most supply still sat in expensive, membership-heavy serviced offices, leaving a gap for hyper-flexible, pay-as-you-go workspace in the places people actually live and travel through.

Design and lead a dual-sided research programme that would ground the DayDeskr business model in evidence before more was built. Specifically:

For the booker side:

• Validate that a real, underserved need exists for hourly, hyper-flexible workspace — and find the "jobs" people hire a workspace to do (escape a distracting home, take a professional call, collaborate face-to-face, beat a commute).
• Understand what drives people out of home and office on any given day, what they can't live without (WiFi, power, ergonomic seating, quiet), and how they decide where to go.

For the host side:

• Understand the micro-economics of underused space: which venue types have genuinely sellable dead time, what occupancy or spend threshold makes hosting worth it, and what operational burden venues can absorb.
• Define what a host needs to say yes: low-friction setup, automated check-in, no extra staffing, clear revenue.

For the marketplace:

• Build personas for both sides, benchmark early booking and hosting flows for usability, and set the KPIs that would tell the team whether the marketplace was healthy — for bookers, hosts and the platform itself.

The research ran on two parallel tracks that were deliberately designed to be read together.

Booker-side research:

• Jobs-to-be-Done interviews (n≈20): hybrid workers, freelancers and remote managers across the UK, recruited to span the range from casual "third place" users to corporate employees under hybrid mandates. Each interview mapped the trigger, the functional job (focus, meeting, calls) and the emotional job (feeling professional, escaping isolation) behind seeking a workspace.
• Contextual shadowing: observed a sample of participants through a real "workday on the go" to see where they actually chose to sit, what made a space usable (or not), and what they paid attention to — power, noise, tables, WiFi.
• Quantitative follow-up survey: sized the needs and willingness-to-pay across segments (solo desks, meeting rooms, day passes), and tested which amenities were non-negotiable.

Host-side research:

• Venue operational audits: worked with café, restaurant and hotel operators to map their dead-time windows, staffing costs per hour, and the minimum occupancy or food-and-beverage spend that would make a hosted desk profitable during off-peak periods.
• Host interviews (n≈20): owners and managers on their margins, their fears (extra labour, brand damage, rowdy "coworkers", liability) and the conditions under which they'd list space — automated check-in, self-serve coffee, clear house rules, and no new staff.
• Feasibility modelling: translated the interviews into a simple threshold model for each venue type — the desk price, hours and utilisation that turn "dead time" into revenue without cannibalising the core business.

Marketplace synthesis:

• Persona Atlas: produced from the combined data — three booker personas (the freelancer escaping home isolation, the corporate satellite worker avoiding a long commute, the high-earning professional trading up to premium space) and the host persona (the hospitality owner diversifying revenue from an existing asset), each with behavioural triggers and non-negotiables.
• Competitive and market analysis: mapped large flexible-space networks, curated workspace platforms and hospitality aggregators to find genuine differentiation — hourly flexibility, neighbourhood coverage and a price point well below membership models.
• Usability benchmarking of the booking and hosting flows: tested early prototypes with both sides. Bookers were set tasks like find a quiet desk near a station, understand the true price, and book in two clicks; hosts were timed setting up a listing (photos, rules, desk counts, availability) and handling a booking. Measured task completion, time-on-task and errors against industry-style targets — then prioritised the issues into a build queue.
• Trust architecture work: because two strangers transacting around a physical space is riskier than a normal booking, I researched what reassurance each side needed — verified profiles, clear photos and descriptions, secure WiFi expectations, cancellation and no-show rules — and fed it into the product's trust features.
• KPI framework: defined the metrics that would tell us the marketplace was healthy after launch — activation, booking completion, host utilisation of listed hours, churn on both sides, and NPS — rather than vanity signup counts.

Working practice: I worked embedded with the product, design, marketing and engineering teams, running the full lifecycle — study design, recruitment, moderation, analysis, synthesis and stakeholder presentation — and pairing every booker insight with its host-side counterpart before it reached the roadmap.

• Evidence-based problem–solution fit: the research validated the core hypothesis — real demand for hourly, hyper-flexible workspace and real, monetisable dead time on the supply side — and, just as importantly, showed where the two sides' needs collide (e.g. price expectations vs. host viability), so product decisions were made with both sides visible.
• A usable blueprint: the Persona Atlas, venue feasibility thresholds, prioritised usability issue log, and KPI framework gave product, design and engineering a shared reference for what to build first, and marketing a research-backed story for each audience.
• Product decisions grounded in dual evidence: booking flows, host onboarding, pricing transparency and trust features were shaped by what both sides actually needed — the check-in loop, no-show handling and host setup speed all trace back to specific findings.
• Foundation for launch: the research converted the concept from a "build it and they will come" assumption into a defensible, data-backed model ready for real-world validation — and gave the team the metrics to read the launch honestly.

Two-sided research changed how I think about "the user". On a normal project the user is one person; on a marketplace there are two, and they pull in opposite directions — bookers want cheap, plentiful, flexible space; hosts need enough revenue per hour to make hosting worth it. The most valuable skill turned out to be holding both perspectives in tension and designing every study so its output could be read on both sides of the marketplace. I'd also flag the classic marketplace trap my research kept steering us away from: optimising the demand side first, because demand is easy to measure, while the supply side — the hosts — is where two-sided marketplaces actually live or die.