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PRACA POGLĄDOWA
Advanced methods for target audience identification: enhancing marketing strategies through machine learning and data analytics
 
Więcej
Ukryj
1
WSEI University
 
2
Netrix S.A.
 
3
Wyższa Szkoła Biznesu - National Louis University
 
 
Data nadesłania: 28-05-2024
 
 
Data akceptacji: 13-07-2024
 
 
Data publikacji: 20-08-2024
 
 
JoMS 2024;57(Numer specjalny 3):417-435
 
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
Purpose: This article presents a novel approach that leverages advanced data analytics and machine learning techniques to enhance marketing strategies. By precisely targeting and segmenting audience groups based on their descriptive profiles, the study aims to significantly improve the efficacy of marketing campaigns. Methods: The study employs several clustering and community detection algorithms, including Louvain Community, Greedy Modularity, and Label Propagation. These methods are applied to diverse datasets to identify distinct groups within the audience that exhibit specific behavioral and preference patterns. The approach emphasizes data-driven decision-making, which involves making decisions based on the analysis of data rather than intuition or observation, to optimize marketing outcomes. Results demonstrate that employing advanced clustering techniques can significantly refine the segmentation process, leading to more targeted marketing efforts. These methods successfully identified nuanced sub-groups within the datasets, which corresponded closely with customer behaviors and preferences variations, thereby allowing for more tailored marketing strategies. Discussion: The study's findings underscore the imperative for marketers to embrace sophisticated analytical techniques. Machine learning has the potential to transform marketing strategies by providing deeper insights into customer segmentation. This research highlights the importance of staying ahead of the curve in the face of the complexities of consumer markets and evolving business environments.
 
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ISSN:1734-2031
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