Alexey Mitsyuk -Analyst, International Laboratory of Process-Aware information Systems (PAIS Lab.), National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: amitsyuk@hse.ru

Anna Kalenkova - Research Fellow, International Laboratory of Process-Aware information Systems (PAIS Lab.), National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: akalenkova@hse.ru

Sergey A. Shershakov - Research Fellow, International Laboratory of Process-Aware information Systems (PAIS Lab.), National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: sshershakov@hse.ru

Wil van der Aalst - Academic Supervisor, International Laboratory of Process-Aware information Systems (PAIS Lab.), National Research University Higher School of Economics; Full Professor, Department of Mathematics & Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands.
Address: P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands
E-mail: w.m.p.v.d.aalst@tue.nl

     E-trade systems are widely used to automate sales processes. Inefficiencies and bottlenecks in the sales processes lead to business losses. Conventional approaches to identifying problems require much time and result in subjective conclusions. This paper proposes an approach for the analysis of e-trade system processes based on the application of process mining techniques. Process mining aims to discover, analyze, repair and improve real business processes on the basis of behavior of an information system recorded in an event log. Using process mining techniques, we have analyzed process running in an online ticket booking information system. This work has shown that process mining can give insight into the e-trade processes and can produce information for their improvement. The case study carried out allows formulating appropriate recommendations. The article also presents the real outcome of using process mining techniques. We have generalized the applied approach and showed how it could be used to the investigation of a wide spectrum of e-trade information systems. During the case study we mostly used a software framework named ProM, which includes a substantial number of plug-ins implementing process mining methods. Using software for automatic process analysis and discovery, one should be careful with the interpretation of particular methods’ output. Pitfalls and difficulties of applying process mining techniques to the logs of e-trade systems have also been shown.