Smart Relationship Development in Community Based Marketing using Machine Learning

Abstract

Business world competition has compelled customer relationships to become a critical success factor. As new and advanced technologies drive digital transformation in many industries, there is an opportunity to leverage machine learning methods for customer relationship areas. The opportunity also covers the implementation for community-based marketing. The purpose of this research is to solve relationship problems between company and targeted segments or community. The quality and quantity of relationships are analyzed by using machine learning methods. The analysis is performed to customer interaction data collected cumulatively from event to event. The specific problems range from customer profiling to customer prediction, then to customer understanding categories. Finally, the research results in several optimal models for the identified problems such as: profiling model with agglomerative clustering, prediction model with artificial neural networks, and understanding model with simple RNN (Recurrent Neural Network). The novelty of this research includes the combination of 3 (three) things, namely: “relationship development”, “community-based marketing”, and “machine learning usage”. The research also confirms technology's role in supporting businesses.