Case study 06

A two-sided marketplace for amateur sport

Venue owners lose revenue to no-shows and manual double-bookings. Players can’t find an open court, and can’t find opponents at their level. Game On is a concept pitch for the platform that serves both sides at once.

Context: Audencia Nantes · Customer Experience & Branding (exchange term)
Year: 2025
Contribution: Team project
Frameworks: Personas · pain mapping · competitive matrix · monetization · go-to-market

What this is: academic coursework — a concept pitch for a hypothetical venture, not a shipped product. Market figures below are as cited in the deck from third-party market research; they have not been independently verified here.

Team project — individual contribution detail to be added.

Two users, six pains

Persona — supply side

Benji, the venue owner

Manual booking — leads to double bookings, scheduling conflicts and inefficiency.
High no-show rates — wasted slot time, lost revenue, unpredictability.
Lack of data — hard to estimate demand, plan maintenance or optimize pricing.

Persona — demand side

Speed, the player

Finding a venue — difficulty finding open slots, causing last-minute cancellations or overpaying.
Fragmented systems — multiple platforms, confusing and inconvenient.
Finding teammates — no way to find like-minded players at a similar skill level.

“There’s no integrated platform for both venues and players that handles bookings, payments, community and analytics cohesively.”

Slide 4 — the gap

The market, as cited

Figures reproduced from the deck’s cited market research. Not independently verified.
Market	Base	Projected	CAGR
Global sports app market	USD 3.66 B (2022)	USD 8.03 B (2030)	~10.9%
Court-booking software	USD 635 M (2024)	~USD 1.91 B (2033)	~14.2%

Target segments: recreational and student players (casual players, hobbyists, amateur enthusiasts), and venue owners or managers of small-to-medium sports facilities and community halls.

Five things the product does

Automated booking & payment — real-time availability, instant confirmation, secure payments, fewer no-shows.

AI performance feedback — post-match summaries and progress tracking, so improvement doesn’t require paid coaching.

Community & matchmaking — find players, create or join group matches; skill grouping via k-means clustering.

Venue analytics dashboard — occupancy, peak hours, booking trends, cancellation patterns.

Trust & verification — verified profiles lower risk for venues and raise user confidence.

The two journeys. Owner: log in to dashboard → manage bookings → monitor analytics → access verified users → plan operations. Player: open Game On → filter & book → join or create a match → performance feedback → connect & rebook.

Why this instead of the incumbents

Dimension	Game On	Existing tools
Integrated solution	Full stack: booking, payments, community, analytics, feedback	Often manual or partial; focused on one aspect
AI performance feedback	AI-powered insights for player improvement	None, or very basic tracking
Data-driven venue management	Actionable insights for optimisation and revenue	None / manual reporting
Trust & verification	Verified users, lower cancellation risk	High risk, unreliable bookings
Affordable & accessible	Freemium plus commission — low entry barrier	Often higher cost or limited features

Making money, and getting the first users

Monetization

Three revenue lines

Booking commission on every transaction
Venue SaaS subscription for the management and analytics layer
Freemium → premium upsell for players

Go-to-market

Supply first, then demand

Venue partnerships — onboard existing facilities, offering immediate value
Digital marketing — target amateur players via social
Referral program — reward users for inviting friends or new venues
Local collaborations — universities, colleges, sports societies

The deck closes as an investment ask: funding to build the MVP and scale, plus partnerships with venues, coaches and early adopters for a beta programme. No funding was raised and no product was built — this is coursework.