Industry overview
What is shaping hospitality
Hotels, restaurants and travel brands are judged on every stay, meal and review. Guest experience, consistency and online reputation drive bookings.
- Online reviews strongly influence bookings
- Consistency across properties builds trust
- Guests expect personalised service
Client background
A boutique hotel group, working in Australia & New Zealand. Client identity is withheld to protect confidentiality.
- Organisation
- A boutique hotel group
- Sector
- Hospitality
- Team engaged
- IT & Development
- Services
- Mobile app development, UI/UX design
Client challenge
Guests at the boutique hotels phoned reception for routine requests such as towels, restaurant bookings and late checkout, keeping staff from personal service. The hotels prided themselves on personal service, but small teams were tied up answering the phone during busy check-in and dinner hours.
Research objectives
- Deliver on the brief: a guest app for a boutique hotel group.
- Define requirements and success criteria the solution would be tested against.
- Deliver a reliable, secure solution the team can run and extend.
Target audience
Scope: Eight hotels.
Audiences we typically reach in hospitality
Guests and dinersCorporate travel buyersFront-line staffTravel agentsOnline reviewers
Geographic coverage
Coverage: Australia & New Zealand. Markets: Australia and New Zealand.
- Australia
- New Zealand
Research methodology
An iterative delivery approach: discovery, design, build and test in short cycles, with the client reviewing each step.
- 1Brief
- 2Guest research
- 3Guest app
- 4Insight
We interviewed guests and staff, then built a simple guest app accessed through a QR code in each room, with requests, local recommendations and booking features. The app worked in any browser without a download, and staff received requests on a tablet at reception with alerts for anything urgent. We tested early versions with guests at one hotel before rollout.
Mobile app developmentUI/UX design
Sampling strategy
- Users and stakeholders from every affected team took part in discovery workshops and acceptance testing.
Data collection
- Requirements were gathered through workshops, process walk-throughs and a review of existing systems and data.
Data quality & validation
- Peer code review on every change
- Automated and manual testing
- User-acceptance testing with the client
- Release checklist and rollback plan
Data analysis
- Usage and performance monitoring after launch
- Defect and support-ticket trends
- Process time before and after
Key findings
- Reception calls fell, requests were handled faster and guests rated the convenience highly.
Self-service for simple requests freed staff for personal attention.
Recommendations
- Build on the core insight: self-service for simple requests freed staff for personal attention.
- Track adoption and support tickets, and plan the next release from real usage.
Business impact
- Staff reported more time for personal recommendations, and guest reviews increasingly mentioned responsiveness.
Impact is described qualitatively.
Deliverables & next steps
- Deployed solution with documentation and handover
- Support and maintenance plan
- Repeat the measure after changes are in place to track progress.
- A natural follow-on question: how do guests rate their stay?
Client identity is withheld to protect confidentiality.