In the era of digital transformation, artificial intelligence systems, especially reinforcement learning, play a vital role in improving marketing processes and enhancing customer experience. Reinforcement learning allows systems to self-learn through continuous interactions with customers and respond more accurately to their changing needs and behaviors. Focusing on reinforcement learning mechanisms, this research analyzes its impact on customer experience in the field of marketing.
Self-learning systems are able to provide personalized offers tailored to the specific needs of each customer by analyzing customer behavior, which leads to increased satisfaction and enhanced individual interactions. Also, using big data and advanced algorithms, these systems have the ability to predict the future needs of customers and enable marketers to continuously improve their strategies.
This research shows that the application of reinforcement learning in marketing not only improves the customer experience, but also leads to a significant competitive advantage by reducing the costs of customer acquisition and retention and increasing the efficiency of marketing campaigns. However, there are challenges such as managing huge amounts of data, algorithmic complexities, and protecting users' privacy, which require innovative solutions. This research examines these challenges and provides solutions to fully exploit the potential of reinforcement learning in marketing and provides a new perspective for the future of this field.