metroSNAP

Or why the current online trade will soon reach its limits and new business models will have to be implemented.

Machine learning only insights: The top-selling positions in the city

When planning a location, the retail trade always asks itself the question of the optimal location. The opportunities offered by continuously changing locations have not yet been recognized - but they are extremely promising. The challenge of predicting the right position in the urban area to set down the POD and optimizing it throughout the day can only be solved in a meaningful way through machine learning. Cognizant Mobility has therefore developed a recommender system that predicts precisely these optimal locations. At the heart of the process is Deep-Reinforcement Learning, which uses the monetary turnover of the PODs across the entire fleet network as a target figure. Our approach does not require any existing data sets at the start and thus enables new business models to go live immediately.

A.I. based suggestion system directly integrated into metroSNAP fleet management

In the future, operators should be able to control and manage all necessary functions of their business model and thus PODS with a clearly structured fleet management tool. We make a distinction between operators of any business model and the Mobility Service Platform, which provides all technical functions. Business models such as the example of the convenience food store can thus be implemented in a timely manner, the operator uses the platform and can thus take mobility for granted. Along the intelligent suggestion system, which is constantly learning, not only can the loading of suitable products be managed, but also the performance of the entire system - and thus the turnover - can be managed.

No longer waiting for autonomous driving thanks to metroSNAP

Hardly any other area of technology has experienced such a strong phase of disillusionment in recent years as autonomous driving. Level 5 autonomy is being pushed further into the future by experts in the industry. The financial resources of corporations are slowly but steadily becoming thinner and thinner. Reason enough to work on solutions that are not completely dependent on it.

For the business case of metroSNAP, it is in fact irrelevant in the first step whether the skateboards ride completely autonomously or whether a version with a driver is used first. The mobility platform achieves its great potential not only through autonomy, but especially through the fact that a truly digital business model is created from previous point of sale (POS)-bound business. A model in which the usage and consumption behavior of customers can be read, optimized and precisely predicted. All purchasing via metroSNAP is done digitally and thus generates customer data with high value.

Together with Rinspeed's partners, Cognizant Mobility is working on a continuation of this concept. Perhaps the cityscape of the future will soon be shaped by PODS with high recognition value. It would be desirable in any case, because it not only addresses the problem of the last mile - it also reduces disruptive traffic in the cities' road network. Perhaps it is time not only for the uncomplicated fulfilment of people's everyday problems, but also for an end to the truck convoys in the cities.