  This document serves as a technical report for the analysis of on-demand
transport dataset. Moreover we show how the dataset can be used to develop a
market formation algorithm based on machine learning. Data used in this work
comes from Liftago, a Prague based company which connects taxi drivers and
customers through a smartphone app. The dataset is analysed from the
machine-learning perspective: we give an overview of features available as well
as results of feature ranking. Later we propose the SImple Data-driven MArket
Formation (SIDMAF) algorithm which aims to improve a relevance while connecting
customers with relevant drivers. We compare the heuristics currently used by
Liftago with SIDMAF using two key performance indicators.
