While the power to read people’s minds is confined to comic books and superhero movies for now, Sentiment Analysis software might just be the next best thing. Marketers, SMEs or entrepreneurs are taking advantage of machine learning advancements which give more and more accurate impressions of how customers are feeling when they interact with or mention brands, services, and products online.
Sentiment analysis uses a kind of Artificial Intelligence called NLP (Natural Language Processing) to ‘read’ text and then categorize the meaning or feeling behind it and assigning a positive, neutral, or negative sentiment. This allows us to do many things that were previously very difficult or impossible. Imagine reading through thousands and thousands of social media mentions to determine what the sentiment behind each one is, and then tagging them. You would need a team working around the clock, just for this one task! Platforms like Mandala Analytics (which includes Sentiment Analytics on certain packages) can collect and analyze hundreds of thousands of social media mentions, perform sentiment analysis, and then organize and present this data in almost real-time. Mandala Analytics’ dashboard presents this sentiment data in clear, understandable metrics with plenty of easy-to-access functions.
Sentiment Analytics isn’t Perfect (But Neither are you!)
As we learned, Sentiment Analytics depends on Natural Language Processing, the branch of Artificial Intelligence in which computers basically ‘read’ written language and interpret the writer’s emotional intent. This can be a very difficult task for a computer because sometimes a word or phrase has multiple different meanings, sentences may be poorly written, or people use sarcasm. Languages are complex, even humans have a difficult time identifying the true sentiment of the writer and two people reading the same text often disagree on whether the sentiment is positive, negative, or neutral. For this reason, Sentiment Analytics platforms like Mandala allow the human user to review mentions and manually adjust the sentiment. Additionally, these machine learning algorithms are constantly improving as they learn, they can never be perfect, but they get closer every day.
Now we understand what Sentiment Analytics works and what it can do, let’s look at what it’s used for and what impact it can have for users. There are a wide range of applications, but here are five main areas that Sentiment Analytics benefits businesses and organizations:
- Improved Customer Service
- Brand and Campaign Monitoring
- Content Insights
- Product and Campaign Planning
- Finance, Stock and Crypto Monitoring
- Market and Competitor Research
- Avoiding PR Crises
Happy customers are repeat customers and, better yet, they will tell their friends too! People love to discuss their buyer experiences on social media. It might be something small like the way they were treated by staff, or it could be something more serious. In any case, it’s vital to respond quickly when a customer expresses something negative and to address the cause of the complaint too- around 50% of surveyed customers said they would switch to a competitor after just one bad experience, 80% would switch if it happened a second time. Responding to positive feedback is also and great way to build rapport and loyalty. After all, it’s much easier (and cheaper!) to keep your existing customers satisfied and spreading the word than it is to find and win over new ones. Sentiment analysis is an invaluable tool for understanding customers’ mood and identifying issues, you can ensure you don’t miss any of important mentions and you can follow up immediately.
With any campaign there’s going to be discussion and feedback on social media, it can be difficult to sort through all those comments or page posts to determine which ones are supportive, and which are not, especially if those posts or comments don’t appear in your own channels. Sentiment analysis give priceless insights on how people feel about your brand, products, and services in real time - whether positive, negative, or neutral. Rather than just looking at the standard metrics of likes, shares or comments, you can identify the emotions behind people’s interactions with your brand. Sentiment analytics automatically categorizes mentions for you, giving you an overview of how well something was received across social platforms, while also allowing you to ‘zoom in’ on those comments that are negative and examine them further to find out why people had a negative reaction, and then use that feedback to plan your future brand strategy.
Content’s ‘success’ is usually measured by reach and engagement, but the third metric of sentiment is equally important, especially if you’re using content for sales or brand awareness. When we factor in sentiment, we get a much clearer understanding of why certain content may have greater reach and engagement. As we know, social media posts that cause outrage or anger often attract high levels of engagement, but these are likely not kind of posts that we would want to be associated with.
The best content will score highly on all three metrics with plenty of positive sentiment.
Making sure your product fills a space in the market is critical. There might be product that already offer similar features and sentiment analysis let’s you see what people like or dislike about it. This can help to eliminate unnecessary features, to innovate new ones, and to make sure it’s suitably priced.
“An investment in knowledge pays the best interest” – Benjamin Franklin
Sentiment Analysis has become a buzz word in the crypto scene, and there’s good reason for this. Trading crypto currency might be a new and exciting way to grow your money, but it’s essentially no different from any other kind of trading. In the stock trading world, Sentiment Analysis has been around for a long time, traders know that mood and sentiment are crucial factors, and understanding them in real time gives you the upper hand. This is especially true in the volatile world of crypto currency. With so many new tokens or coins launching all the time and values fluctuating wildly, which one should you bet on? Sure, it’s important to have the statistics and the historical data but knowing how other people are feeling about a coin allows you to jump on the next big thing before it takes off. Sentiment analysis is the most accurate, most real-time method for understanding how people feel.
Stock market or crypto, investing for the future, or playing for a quick win, a good trader never stops reading, learning, and gathering information. Sentiment Analysis is now an essential part of any good investor’s knowledge assets.
When planning a new campaign or product, the last thing you want to do is go in blind without taking the time to properly understand the market. Sentiment Analysis lets you understand what works and what fails so you can make sure you’re hitting the right messages, responding to real demand, and potentially avoid costly mistakes.
Competitors: As Picasso said, “good artists copy, great artists steal”. By analyzing competitors’ social channels and sentiment, you can see what kind of products are popular, well regarded, and generate the most positive feedback and use this information when planning your own products. You can also study the mistakes your competitors and others have made by tracking negative mentions and engagement learn from their blunders.
New Markets: It’s important to have a clear understanding of how your new product or service is going to fit into the market because getting it wrong can be a disaster. Sentiment Analysis is great for identifying customer pain points and gaps in the market by tracking keywords and analyzing related sentiment, while keyword and hashtag clouds in the Mandala Analytics’ sentiment dashboard introduce terms that you might not have considered to be associated with your brand, opening doors to new potential customer groups.
Even the best marketing professionals will at some time find themselves dealing with a crisis. It may be caused by poor planning, incorrect messaging, or it may be nobody’s fault at all, simple bad luck. On social media negative posts and sentiment spread fast, and the most important thing is to spot the problem early so that it can be dealt with quickly to avoid too much harm to a brand’s image and reputation.
In March 2021, the team at Burger King UK decided to tweet out a message for International Women’s Day that they believed would “draw attention to a huge lack of female representation in our industry”. It sounds like a nice idea, however the message they chose didn’t end up creating the reaction they had wanted. “Women belong in the kitchen” was the first in series of tweets that went on, explaining “only 20% of Chefs are women. We’re on a mission to change that in the restaurant industry by empowering female employees with the opportunity to pursue a culinary career." While the follow-up tweets clearly showed that the first tweet was meant to be taken with humor, social media users didn’t get the joke. The tweet received a wave of negative backlash and even some competitors, like KFC took the opportunity to take a shot at Burger King.
The original tweet was deleted, an apology was issued, and while it’s unclear whether this kind of crises had any lasting impact on the Burger King brand, it shows the importance of monitoring sentiment on social media. For the Burger King, it was important to respond quickly once they realized that the tweet had gone viral (in a bad way), and for KFC it presented an opportunity for some positive PR of their own. Sentiment Analytics let’s businesses large and small spot problems or opportunities as they arise on social media.
Sentiment Analytics will keep playing a bigger part in the way brands find, connect, and build relationships with their customers. Fortunately for the smaller players, the barriers to entry for this technology continue to fall, and platforms like Mandala Analytics now offer big data capabilities that were previously out of reach for the average small business or those just starting out.
With Mandala’s personal package, users have access to advanced Sentiment Analysis along with all the functionality and data gathering capacity of the full Social Media Analytics platform. Aspiring mind-readers can start a free 7-day trial and there are great in-depth tutorials to get new users up and running.
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