Process Mining-Driven Optimization of Digital Customer Journeys Based on Audience Intervention Using the AI-DATA Model

Heidrun Mühle, Daniel Danter, Simone Sandler, Oliver Krauss, Andreas Stöckl

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

In a case study, we aimed to explore AI-based e-commerce optimization based on process mining by introducing the AI-DATA model, a human-centered approach to customer journey optimization in the context of trustworthy AI. The AI-DATA model, which stands for Awareness, Interest, Desire, Action, Trust, and Again, is a phase model. It is an extension of the traditional AIDA model, emphasizing a human-centered customer journey, that includes post-transaction activities and a cycle of repeat patronage. In our case study, the AI-DATA model was implemented at an e-commerce online shop specializing in nutrition supplements. The objective of employing this model through process mining was to increase conversion rates, such as clicks and purchases, through phase interventions.
Original languageEnglish
Title of host publicationInternational Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2024
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9798350391183
ISBN (Print)979-8-3503-9119-0
DOIs
Publication statusPublished - 6 Nov 2024
Event2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) - Male, Maldives
Duration: 4 Nov 20246 Nov 2024

Publication series

NameInternational Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2024

Conference

Conference2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
Period04.11.202406.11.2024

Keywords

  • Artificial Intelligence
  • Big Data
  • Customer Journey
  • Data Mining
  • Digital communication systems
  • Large Language Models
  • Process Mining
  • Trustworthy AI

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