UK subscription service that rents physical board games to customers on monthly plans. Games are delivered by post and returned using prepaid labels, enabling reuse and reducing the need to buy and store new games.
Circularity Relevance
Core
Primary purpose is renting board games for reuse rather than sale, directly supporting circular reuse of physical products. Source: Love Board Games, 2025
Circular Role
DirectEnabler
Directly provides and manages the rental service and logistics (delivering and collecting games), functioning as a direct enabler of reuse.
Circular Type
CircularRetailer
• Products
• C2C
• B2C
Primary activity is rental of physical board games, service includes circular logistics.
R Strategy
R3 - Reuse, R1 - Rethink, R2 - Reduce
Primary strategies: R3 (Reuse) via renting/redistribution and R1 (Rethink) via access/subscription model. Secondary: R2 (Reduce) as renting reduces need to purchase. Evidence: subscription plans and return flow. Source: Love Board Games, 2025
Circular Business Model
Rental / Leasing, Product-as-a-Service (PaaS)
Operates a subscription rental (monthly plans) for physical games - identified as Rental/Leasing and an access-based PaaS model. Source: Love Board Games, 2025
Platform offers paid rental/subscription of physical consumer board games - a retail rental model. Evidence: homepage and plans pages describing monthly plans and delivery. Source: Love Board Games, 2025
Geographical Reach
National
• United Kingdom
Site cites free UK postage both ways and prices in GBP, indicating primary operation within the UK. Source: Love Board Games, 2025
Hardware Component
None
Service delivers physical goods by post and uses prepaid return labels; there is no evidence the provider supplies or requires specialised hardware to deliver the service.
Tech Map Relevance
Service operates a subscription rental model for physical board games (reduces ownership and encourages reuse), meeting inclusion criteria for the Circular Tech Map. Source: Love Board Games, 2025.
Enablers are initially categorised by an AI agent, then verified by a real human. Suggestions or corrections are most welcome.
