Analyzing Customer Journey with Process Mining: From Discovery to Recommendations

Alessandro Terragni · Marwan Hassani

66 citations0/0 files storedIEEE International Conference on Future Internet of Things and Cloud (FiCloud)

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Business Process Modeling and Analysis Recommender Systems and Techniques Web Data Mining and Analysis

Abstract

Customer journey analysis is a hot topic in marketing. Understanding how the customers behave is crucial and is considered as one of the key drivers of business success. To the best of our knowledge, a data-driven approach to analyze the customer journey is still missing. For instance, web analytics tools like Google Analytics provide an oversimplified version of the user behavior, focusing more on the frequency of page visits rather than discovering the process of the visit itself. On the other hand, customer journey maps have shown their usefulness, but they need to be created manually by domain experts. This paper contributes a novel approach for applying process mining techniques to web log customer journey analysis. Through process mining we are able to (i) discover the process that better describes the user behavior, (ii) find useful insights, (iii) compare the processes of different clusters of users, and then (iv) use this analysis to improve the journey by optimizing some KPIs (Key Performance Indicators) via personalized recommendations based on the user behavior. We show through a real-life case study a proof of the correctness of the introduced concept by improving the recommender accuracy when incorporating additional context information about the journey as extracted from the process model.

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References

2016Understanding Customer Experience Throughout the Customer Journey 2016Process Mining 2007Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective Metrics 2005Discovering Social Networks from Event Logs 2009Trace Clustering in Process Mining 2016Improving service quality through customer journey analysis 2008Supporting Flexible Processes through Recommendations Based on History 2014Mapping customer journeys in multichannel decision-making

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2020Mapping the Patient’s Journey in Healthcare through Process Mining 2019Optimizing customer journey using process mining and sequence-aware recommendation 2021Deep customer segmentation with applications to a Vietnamese supermarkets’ data 2024A hybrid machine learning with process analytics for predicting customer experience in online insurance services industry 2019Speaking with Actions - Learning Customer Journey Behavior

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