Summary

This chapter underscored the importance of sentiment analysis in modern marketing strategies. It introduced sentiment analysis as a key tool to interpret vast quantities of unstructured text data, such as social media conversations, to refine marketing strategies, brand messaging, or customer experience. By utilizing the Twitter Airline dataset, we covered the end-to-end process needed to classify sentiment as positive or negative, using both traditional NLP and more advanced GenAI methods involving pre-trained LLMs. We then covered an array of tools for the visualization and interpretation of these results to derive actionable marketing insights. This chapter should leave you equipped with the necessary skills to harness sentiment analysis effectively, for applications ranging from brand reputation monitoring to aligning marketing messages with customer preferences.

Looking ahead to the next chapter, we will progress from understanding customer sentiment to actively shaping...