Translating sentiment into actionable insights

So far in this chapter, we have explored the tools and strategies needed to understand and apply sentiment analysis to your data, from the foundational techniques of data preparation and prediction using traditional NLP methods to the advanced capabilities of GenAI. In this final part of the chapter, we will discuss how these insights can be analyzed to generate actionable strategies that can guide a brand to success across all stages of a marketing campaign.

Creating your own dataset

Before applying this analysis to your use case, we need an approach to collecting the data that captures the underlying customer sentiment related to your brand. While this chapter utilizes the Twitter Airline dataset as an example, the techniques we’ve explored are applicable regardless of the industry or data source. This section will present the general steps you can take to curate your own proprietary dataset for analysis, whether it be...