The expansion of Internet-based services has increased the need to ensure a good quality on them. In this context, a preliminary work we developed exposes a Quality of Experience (QoE) evaluation framework based on the mathematical formalism of EFSMs, which includes business-related variables into the prediction analysis. In this paper, we present an implementation of this QoE evaluation framework using the Montimage Monitoring Tool (MMT). The implementation presented in this paper is based on three main algorithms: (1) generation of the traces of a given length of the EFSM-based OTT model, (2) computation of the QoE for each trace using a suitable QoE model, and (3) computation of the number of configurations reachable from the initial state of the EFSM. We use this implementation to calculate the amount of configurations captured by the model of a real OTT service, analyzing how this value varies with respect to the depth (trace length) of the analysis and which is the distribution of the QoE values of the computed configurations. This information will enable the service provider to characterize the QoE of all possible scenarios and to introduce changes if required, in order to maximize the revenues provided by the chosen business model and the QoE of end-users