Social media analytics, including sentiment analysis, is essential for effectively managing your social media presence. Gathering and analyzing performance data is a common aspect of making informed social media marketing decisions, whether it’s on Facebook, Instagram, or Twitter.
It may be challenging to keep up with the amount of information shared on social media every day. You want to know not only what’s being said about your own brand but also what’s being said about your competitors, your industry, and emerging customer trends. You’re hoping to get in.
Therefore, Sentiment analysis is critical for determining how your audience views you, your products, and your position in the marketplace.
What Exactly Is Social Media Sentiment Analysis?
The process of interpreting and determining whether social media collected text data is positive, negative, or neutral is known as sentiment analysis. It entails more than simply gathering and counting the number of mentions, comments, and hashtags.
Sentiment analysis provides a deeper understanding of the attitudes, opinions, and emotions expressed in the text. It will tell you whether that gathered Facebook post mentioned you positively or negatively. It puts your number of mentions in context.
Importance Of Sentiment Analysis For Businesses
Analyzing a customer’s sentiments was not taken seriously until a few years ago. Sentiment analysis is becoming a viable tool today, thanks to advancements in technology and business thinking. What makes it interesting and distinct from other types of data analytics is that it deals with emotions.
Sentiment analysis is an algorithm-driven process that uses a dictionary of words with a positive, negative, or neutral sentiment. Sentiment analysis tells a company or a brand how the rest of the world or its customers feel about it. Positive, negative, or even neutral feelings could be expressed. For instance, happy, sad, irritating, rewarding, lovely, wonderful, creative, and so on.
However, to conduct such an analysis, a company must have the necessary tools and a clear understanding of using them.
How To Conduct Social Media Sentiment Analysis?
Although sentiment analysis can provide brands with helpful information, it also comes with its own set of challenges.
A few ways of conducting sentiment analysis and analyzing social media sentiment are as follows:
- Find out where people are mentioning your brand
As previously stated, consumers are voicing their opinions on brands like never before. This is true both on and off social media.
Your on-site reviews are precious if you’re in the e-commerce business. Customers addressing you directly on Twitter or Instagram require firms to pay close attention to their social mentions. This is a great way to capitalize on compliments and address criticism quickly. Don’t overlook the opinions of your most loyal customers, who are arguably the most important to your company.
Manually monitoring all of these platforms can be time-consuming. However, social listening tools like Sprout can be useful for monitoring brand mentions and tracking keywords related to your brand even if customers don’t directly tag you.
- Choose your terms for sentiment analysis
Sentiment analysis is only useful if you can distinguish between positive and negative mentions. This entails looking for keywords that highlight customer sentiment. Some sentiment terms are relatively straightforward, while others may be industry-specific. You must divide your sentiment terms into positive and negative words in either case.
Here’s a quick example of how some of those terms might appear in a sentiment search:
Positive words- “best,” “love,” “high-five,” “amazing,” “perfect,” and “thank you.”
Negative words and phrases- Worst, despise, ugh, disappointment, bad, and avoid.
- Put your mentions into context
This is where sentiment analysis becomes challenging. The number of sentiment-related terms in your searches does not always reflect how your customers feel. It’s critical to double-check your references and leave some room for error in your analysis.
For example, take a look at Netflix’s Facebook page. Fans are singing the show’s praises, but they’re also using words like “ugly,” “cry,” and “depressed” in the process. It’s cause for concern if you see those terms in your mentions without context.
Although sentiment analysis is generally accurate, these types of outliers will always exist. Therefore, a combination of manual listening and Lachine Learning is ideal for the most “complete” sentiment analysis.
Conclusion:
Customers’ opinions and feelings about your company are too important to overlook. Thanks to sentiment analysis, there’s no speculating regarding where people stand on your brand.
Analyzing their sentiments enables you to make actionable decisions on behalf of your company by monitoring the conversations on social media. Therefore, modern businesses need to conduct social media sentiment analysis in order to gain a competitive advantage, especially in this digital era.
