Process mining

Process mining turns traditional, manual process analysis on its head by analyzing the transactional records from the IT systems to automatically visualize the processes that actually take place. It aggregates all processes in a single graph that is easy to understand and delivers actionable insights.

Understanding the customer journey

Process mining can be used to understand how customers are experiencing the interaction with an organization, and how they are using their products. For example, you may want to see how your customers are navigating your website or are interacting with your web application. This perspective in process analysis is often called customer journey.

With our Process Mining support, mining web visitor processes and journeys becomes really easy and insightful.

How it works

All data collected with our services is process mining-ready. That means you can, at any moment, export your data to a proecss mining tool of choice. We support common export formats that embed already all available structural and contextual data. This means, we will export session information, some broser details and also any form of labeling that you have created using our visual flow processing. This enhanced process data helps you max out the feature set of your process mining tool.

We also offer a special integration with Fluxicon’s AirLift technology. This allows to access collected data from within Fluxicon’s Disco tool, where you can select dataset, timeframe, and other import parameters.

To give you an idea of what is possible with session and process mining, we have integrated a simplified session mining view into our tools. It shows process views that can be filtered and adjusted to visualize the essentials of the customer journey. As you can imagine, using the extended dataset with a full process mining tool will only amplify what’s possible.


According to Wikipedia, process mining is a family of techniques relating the fields of data science and process management to support the analysis of operational processes based on event logs. The goal of process mining is to turn event data into insights and actions. Process mining is an integral part of data science, fueled by the availability of event data and the desire to improve processes. Process mining techniques use event data to show what people, machines, and organizations are really doing. Process mining provides novel insights that can be used to identify the executional path taken by operational processes and address their performance and compliance problems.

Process mining starts from event data. Input for process mining is an event log. An event log views a process from a particular angle. Each event in the log should contain (1) a unique identifier for a particular process instance (called case id), (2) an activity (description of the event that is occurring), and (3) a timestamp. There may be additional event attributes referring to resources, costs, etc., but these are optional. With some effort, such data can be extracted from any information system supporting operational processes. Process mining uses these event data to answer a variety of process-related questions.

We hope you got interested. You can test-drive our solution at or contact us about a custom plan.