How Sentiment Analysis Changes the Way Brands Analyze Social Media
Social media analytics provide a foundation on which brands build successful marketing strategies. To reach its target audience, a brand needs to know where, when, and why it is a part of the conversation on social media. Social media analytics helps organize this information, tracking which platforms and events tend to generate brand-relevant discussion. But another central component of modern branding strategy is social media sentiment analysis, which helps brands answer the all-important question: How do consumers feel about the brand?
What Is Social Media Sentiment Analysis?
Social media sentiment analysis involves using AI methods such as natural language processing (NLP) and image analysis to identify the emotions and opinions motivating social media posts.
This process may involve identifying keywords and phrases that indicate positive or negative reactions, or that indicate specific emotions such as surprise or excitement. It can also involve image recognition techniques that analyze the emotional content of facial expressions, emojis, and GIFs, or that identify when a brand’s logo or product appears in a post, even when the brand is not tagged.
Because AI can process large data sets that would be impossible to process by manually sifting through the massive amount of social media content available, sentiment analysis can spot subtle brand-relevant trends and information that would otherwise remain hidden.
How Do Brands Use Social Media Sentiment Analysis for Consumer Research?
Consumer research is about more than just gathering data on consumer behavior. To drive actionable marketing strategies, a brand needs to organize and visualize data such that consumer insights rise to the surface.
This means that sentiment analysis technology should involve data analytics and visualization capabilities that can translate large amounts of data into digestible, yet informative packages.
For example, NetBase Quid AI provides a Brand Passion rating of consumer sentiment on a scale from -100 to +100 based on two key metrics: whether emotions are positive or negative (Net Sentiment) and the strength of emotion expressed (Passion Intensity).
Users can analyze these ratings in relation to competitors’ ratings and can create audience segments to track how ratings differ across various demographic characteristics such as age, gender, and location. Other useful segments to target could include those who have more social media influence, or those who share interests with the audience whose posts tend to have a high Brand Passion rating.
The key is that brands can use sentiment analysis to identify unseen market gaps with high potential. This might involve text analysis to determine that a certain feature of a competitor’s product is receiving negative sentiment. A brand could then highlight this feature of their own product to position it as a better alternative. Or, using image analysis, a brand could identify events or social media platforms where their logo or products tend to be featured in positive posts and target these events and platforms in future campaigns.
Managing a Social Media Crisis
While social media sentiment analysis has emerged as a foundational tool for building marketing strategies, it has also become essential for crisis management. In a world where any brand is vulnerable to a social media crisis caused by a viral post, it is imperative to identify and proactively address a potential social media crisis.
Brands can use sentiment analysis as a social listening tool to identify when a post expresses negative sentiment and dedicate customer service attention to that post. The goal is to address a customer’s concern and show dedication to customer support, rather than let an unresolved negative post drive the conversation.
When it is not possible to immediately contain a crisis, sentiment analysis helps brands track whether their crisis management strategies are successful. A brand can identify which of their posts had the most success in shifting negative sentiment, or identify which platforms saw the highest volume of responses. This information is helpful for directing an ongoing crisis management project and for targeting similar posts and platforms in the future.
Analysis That Builds Connection
Social media analytics is an invaluable tool to help brands understand their audience. But with sentiment analysis, social media analytics is able to move beyond mere understanding and foster connection, helping brands develop strategies and address concerns that speak directly to how consumers feel.