Towards an Ontology and Process Mining-based System for Targeted E-Commerce Marketing Strategy Suggestions

This paper presents an ontology and process mining-based system that employs semantic technologies for targeted e-commerce marketing strategy suggestions. The proposed approach utilizes ontologies as a knowledge representation formalism to capture the domain knowledge, product descriptions, and website texts in the e-commerce domain. The ontology is populated with relevant attributes and corresponding values, allowing for a structured and standardized representation of users and content.To suggest targeted marketing strategies, the system employs interest and intensity calculation techniques that utilize the concept of scroll depth and others to measure the interest in different contents and customer preferences.Process mining techniques identify moments of truth along the customer journey and happy paths a customer usually goes through. Once the ontology is combined with the process mining results, it can be identified in which phase of the customer journey a user is, and it can be determined what marketing actions to employ to get them to enter the next phase of a marketing model.Overall, the proposed approach is a promising approach to address the challenges of personalized e-commerce marketing strategy suggestions by utilizing ontology-based knowledge representation and intensity calculation techniques. The system has the potential to provide personalized and targeted marketing strategies for e-commerce businesses, leading to increased customer engagement, loyalty, and sales.