FUSS is a mobile app that utilizes a personalized scenario-based search algorithm to quickly connect users with curated leisure activities in London, reducing the average 12 hours spent weekly on entertainment searches to just three minutes. By filtering through various options, FUSS ensures users discover high-quality dining, entertainment, and cultural experiences tailored to their preferences, maximizing their leisure time.
Funding
Funding not disclosed
Founders
Product
Problem
Individuals in London spend a significant amount of time searching for leisure activities, often sifting through numerous options to find experiences that align with their preferences. This time-consuming process can detract from actual leisure time and lead to missed opportunities for high-quality outings.
Solution
FUSS is a mobile application designed to streamline the discovery of curated leisure activities in London. By employing a personalized, scenario-based search algorithm, FUSS quickly connects users with tailored dining, entertainment, and cultural experiences. The app filters through available options, presenting users with high-quality choices that match their specific moods, preferences, and social contexts. FUSS aims to reduce the time spent searching for activities, enabling users to maximize their leisure time and discover new experiences effortlessly. The application also incorporates a group voting feature to simplify planning with friends or coworkers.
Target Audience
The primary target audience includes London residents and visitors who seek curated and personalized leisure activity recommendations, particularly young professionals and students with limited time for planning.
Features
- Personalized recommendations based on user preferences, mood, and social context
- Curated selection of dining, entertainment, and cultural experiences in London
- Scenario-based search algorithm for tailored activity suggestions
- Group voting feature for collaborative planning with friends or coworkers
- Smart filters to refine searches based on specific criteria, such as ambiance and price range
- Integration with map services for location-based discovery
- Option to save favorite locations and share plans with friends