Analyzing Customer Journey with Process Mining: From Discovery to Recommendations

2018 ◽  
Author(s):  
Alessandro Terragni ◽  
Marwan Hassani
Keyword(s):  
Process Mining ◽  
Customer Journey

scholarly journals Mapping the Patient’s Journey in Healthcare through Process Mining

2020 ◽  
Vol 17 (18) ◽  
pp. 6586
Author(s):  
Michael Arias ◽  
Eric Rojas ◽  
Santiago Aguirre ◽  
Felipe Cornejo ◽  
Jorge Munoz-Gama ◽  
...  
Keyword(s):  
Life Cycle ◽  
Process Mining ◽  
Customer Experience ◽  
Customer Journey ◽  
Customer Life Cycle ◽  
Patient’S Experience ◽  
Healthcare Process ◽  
Or Organization ◽  
A Company

Nowadays, assessing and improving customer experience has become a priority, and has emerged as a key differentiator for business and organizations worldwide. A customer journey (CJ) is a strategic tool, a map of the steps customers follow when engaging with a company or organization to obtain a product or service. The increase of the need to obtain knowledge about customers’ perceptions and feelings when interacting with participants, touchpoints, and channels through different stages of the customer life cycle. This study aims to describe the application of process mining techniques in healthcare as a tool to asses customer journeys. The appropriateness of the approach presented is illustrated through a case study of a key healthcare process. Results depict how a healthcare process can be mapped through the CJ components, and its analysis can serve to understand and improve the patient’s experience.

Predicting Next Touch Point In A Customer Journey: A Use Case In Telecommunication

2021 ◽  
Author(s):  
Marwan Hassani ◽  
Stefan Habets
Keyword(s):  
Historical Data ◽  
Process Mining ◽  
Use Case ◽  
Customer Journey ◽  
Contact Type ◽  
Touch Point ◽  
The Future ◽  
Telecommunication Company

Customer journey analysis is rapidly increasing in popularity, as it is essential for companies to understand how their customers think and behave. Recent studies investigate how customers traverse their journeys and how they can be improved for the future. However, those researches only focus on improving the process for future customers by analyzing the historical data. This research focuses on helping the current customer immediately, by analyzing if it is possible to predict what the customer will do next and accordingly take proactive steps. We propose a model to predict the customer's next contact type (touch point). At first we will analyze the customer journey data by applying process mining techniques. We will use these insights then together with the historical data of accumulated customer journeys to train several classifiers. The winning of those classifiers, namely XGBoost, is used to perform a prediction on a customer's journey while the journey is still active. We show on three different real datasets coming from interactions between a telecommunication company and its customers that we always beat a baseline classifier thanks to our thorough pre-processing of the data.

A Big-data Study of YouTube Comments to Classify Customer Journey Decisions - Proposing a New Exploratory Analysis Method -

2019 ◽  
Vol 16 ◽  
pp. 57-89
Author(s):  
Seonwoo Kim ◽  
Heewoong Ahn ◽  
Yoona Jang ◽  
Minye Hong ◽  
Minji Seo ◽  
...  
Keyword(s):  
Big Data ◽  
Exploratory Analysis ◽  
Analysis Method ◽  
Customer Journey

Process Mining - A Comprehensive Review

2018 ◽  
Vol 6 (7) ◽  
pp. 1108-1113
Author(s):  
S. Vijayarani ◽  
A. Sakila ◽  
R. Ramya
Keyword(s):  
Process Mining ◽  
Comprehensive Review

Process Mining im Prototypenbau

2019 ◽  
Vol 114 (11) ◽  
pp. 707-710
Author(s):  
Günther Schuh ◽  
Jan-Philipp Prote ◽  
Andreas Gützlaff ◽  
Sven Cremer ◽  
Seth Schmitz
Keyword(s):  
Process Mining
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