This paper elaborates on a novel concept to orchestrate tourism networks. In particular, each actor optimizes his service (touchpoint n) while seamlessly transferring the customer information from the previous (touchpoint n-1) to the following service (touchpoint n+1). To implement such a theory, we leveraged on chatbot technology, which interfacing directly with the user eased the transition from the point of interaction (touchpoint) n-1 to n+1. Moreover, the chatbot entails the connection between the nodes of the customer's journey, enabling user profiling, personalization, and knowledge transfer. The deployment of a chatbot implementing the "n-1 n+1 touchpoints" model would significantly benefit actors operating in a fragmented touristic economy (i.e., Switzerland). Hence, we tested the first prototype in the heart of the Canton Valais, where, in collaboration with students in tourism, we based the scenario on counterfactual thinking. In particular, we identified all the possible situations a grandmother and her grandson might face arriving at the Sierre train station to spend a day in Crans-Montana. In turn, using reenactment theatre techniques, tourism professionals played the worst-case scenario (without chatbot) and the best case (with the chatbot) to elicit the different clients' perceptions on those diametral situations. Such a feasibility study paved the way to a more holistic view, employing artificial intelligence techniques to enhance the chatbot and smoothen the "n-1 n+1 touchpoints" dynamics.