Social media management tools have come a long way from just scheduling posts.
Nowadays, they’re equipped with deep analytics that offer a gold mine of information for data-driven decisions. For example, Sprout Social
has introduced AI tools that use sentiment analysis so customers can better understand their audience, determine optimal campaign targets, and gauge customer feedback.
Sentiment analysis is allowing social media tools to help their users build stronger brand loyalty, capture deeper audience insights, and more thoroughly track campaign analytics. That enables businesses to more effectively analyze their online brand reputation, improve their calls to action, and generate more engaging content. Simply put: investing in sentiment analysis helps social media management platforms better serve their users.
Of course, this is all easier said than done.
Building an effective sentiment analysis tool requires extensive fine-tuning of a foundation model in order for it to make relevant and accurate analytics. Usually, this requires a lot of work by data scientists and machine learning engineers to meticulously collect, and prepare the right data to fine-tune their large language models (LLMs).