It’s one thing to collect feedback about your product, but quite another to read between the lines and understand how users actually feel about your brand. Not to mention figuring out what your customers are thinking as they interact with your website or digital product.
That’s why user sentiment analysis is such a powerful technique to truly understand your customers.
User sentiment analysis uses tools and algorithms to process and interpret unstructured data—such as feedback forms, interviews, customer reviews, and social media comments.
This analysis helps you understand customer thoughts and feelings at various stages of the buyer journey and beyond. By segmenting users and addressing issues, businesses can enhance their products, boost customer loyalty, and increase overall satisfaction.
This guide walks you through the fundamentals of user sentiment analysis—what it is, why it matters, how to analyze sentiment, and the challenges that come with it—to improve your product and reach your business and customer goals.
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Summary
- User sentiment is the positive, negative, or neutral feelings people have for your brand or products
- You can collect user sentiment through things like surveys, online review sites, social media platforms, customer support tickets, and more
- Some benefits of user sentiment analysis include being able to uncover customer emotions and motivations, gauge users’ emotional connection to your product, and monitor your brand’s reputation
- You can perform user sentiment analysis in five steps:
- 1. Gather your data
- 2. Sort, process, and clean your data
- 3. Analyze your data using user sentiment analysis software
- 4. Visualize and share your insights
- 5. Put your findings into practice
- Common challenges of user sentiment analysis include developing hypotheses, collecting data, understanding context within your datasets, and achieving a large enough data sample size