Pop Up City - strengthening urban retail through AI

As a result of the structural change in retail and the shortening of the utilization cycles of retail real estate, the market for the brokerage of pop-up stores is a pronounced growth segment in a stagnating retail real estate market struggling with vacancies.
In the Pop Up City project, an algorithm is being developed that uses a self-learning recommender system to match supply (retail space) and demand (retailers) for pop up stores (temporary store concepts). The more effective the matching, the higher the benefit for space owners, store operators and cities in the fight against trading down (downward spiral of loss of attractiveness and pedestrian frequency). For this purpose, suitable patterns are identified on the basis of the determinant characteristics of the locations and the implementation motives of the retailers. The monetization of the customer value created for real estate owners and retailers is the future basis of the business model and the unique selling proposition of the Swiss start-up PopUpShops.com (POS) in the race for the dominant marketplace for temporary (store) use concepts. The algorithm-based matching technology is embedded in an ecosystem of supporting services for providers and consumers, enabling unique customer experiences.
The algorithm is developed and tested through acquisition, implementation support and evaluation of pop-up stores in Zurich and St. Gallen. Both cities benefit from the embedding of the algorithm into a holistic process model (5M), which effectively reduces transaction costs and barriers of pop up stores and thus leads to vacancy avoidance, attractiveness increase (trading up) and reduction of municipal (administrative) costs and lead times (DLZ). 5M ensures efficiency for implementers (DLZ time-critical) and serves as an enabler of the RS, since the number of real implementations (use cases) is a prerequisite for its development.