Example Concept: One effective strategy is to use session-based memory, where the chatbot maintains a session object that stores relevant user data and conversation context throughout the interaction. This session data can include user preferences, previous questions, and any other pertinent information that helps the bot provide coherent and contextually aware responses. Additionally, integrating advanced NLP models that support context tracking can further enhance the bot's ability to maintain continuity over multiple turns.