- Sentiment analysis is the scanning of words written or said by a person to determine the emotions they’re most likely feeling at the time.
- You can monitor real-time conversations about your company and its products or services to measure consumer sentiment.
- You can use the data from sentiment analysis to determine which products and services your customers want or how they’re feeling about a brand.
- This article is for business owners who want to better understand how their customers are feeling and what they need.
Find out what your target customers want and think about your company and its products or services in real time by conducting a sentiment analysis. Although they’re still a developing technology, sentiment analytics apps have the potential to revolutionize the relationship between brands and their consumers by creating greater understanding. Businesses can use the data from a sentiment analysis to drive revenue and guide marketing efforts.
What is sentiment analysis?
Sentiment analysis is the scanning of words written or spoken by a person to determine the emotions they’re most likely feeling at the time. If the person spoke verbally, sentiment analysis technology can analyze a transcription of the conversation for that purpose. The results of the analysis give businesses a better read on their customers.
Companies can use sentiment analysis to analyze direct communications – i.e., conversations and interactions between you and your clients via email, phone, WhatsApp, chatbots and other channels. They can also analyze online communications such as comments made by consumers on social media, in blog posts, in news articles and on online review sites.
How does sentiment analysis work?
Sentiment analysis examines text mined from a wide variety of sources, including online forums, social media platforms (including Twitter, Facebook and LinkedIn), chatbot conversations, support tickets, blog posts, emails and third-party websites.
Artificial intelligence and machine learning run natural language processing algorithms to analyze the text. Sentiment analysis software attempts to understand the emotional content of the text from a human point of view. [Related article: What’s the Difference Between Machine Learning and Automation?]
Did you know? Sentiment analysis is used by companies like KFC, Apple, Google, TripAdvisor, Intel and Twitter.
What are the different types of sentiment analysis?
There are five main types of sentiment analysis.
- Graded analysis: This is one of the simplest forms of sentiment analysis. An example would be people scoring a business out of 5, like rating a business on Yelp. Sometimes, numbers are replaced by choices like “excellent,” “satisfactory” or “below average.”
- Emotion-detection analysis: Analytics tools assign feelings like sadness, anger, frustration and happiness by matching text to a list of words tagged with one of these emotions. While this works well a lot of the time, some technology can be confused by colloquialisms like “bad” or “wicked” that can also be complimentary in the right context.
- Fine-grained analysis: Here, sentences are broken into their constituent parts and analyzed in more detail. For example, in the sentence, “The wipers on my car snapped off after three years,” fine-grain analysis determines the object (“the car”), the feature of the object (“the wipers”), what went wrong (they “snapped off”) and when (“after three years”). It can determine comparatives like “x is better than y” and it can assess sentiment on a given subject ranging from “very positive” to “very negative.” Fine-grained sentiment analysis is used most frequently to gauge opinions on social media, particularly in cases of crisis management.
- Aspect-based analysis: Like fine-grained analysis, this method looks for positive or negative sentiment based on input. An example of this would be a person writing to a chatbot, “The wipers on my car snapped off after three years.” The chatbot would recognize that the customer was in need of help and then transfer the conversation to a human operator for assistance. [Learn more about responding to live chats.]
- Intent analysis: This type determines whether a statement is a question, show of appreciation, complaint, suggestion, opinion, marketing collateral or news. A good example of intent analysis is how Gmail sorts incoming messages as “Social,” “Promotions,” “Updates,” and “Forums,” although Google uses other techniques in addition to intent analysis to achieve this.
How can sentiment analysis improve sales?
Businesses can use the results of sentiment analysis to shape their sales and marketing plans, evaluate social media posts, improve crisis management and brand strength, and translate digital PR into tangible actions. In fact, understanding your clients’ emotions and expectations can be the key to keeping customers.
Sales and marketing
Businesses can use sentiment analysis to see how well their marketing campaigns are going on social media and third-party websites. With brand-new product launches, they can scan online comments to see if any customers are having issues. Companies can also get a sense of how well their target audience has received their new product. Based on the results of the analysis, they can adjust their sales and marketing plans to feed into or address consumer sentiment.
Tip: You can also monitor competitors with sentiment analysis. These findings would be very useful in any competitor analysis exercise.
Social media research
Traditional social media monitoring often focuses on measuring the number of likes, comments and shares a post gets. While these numbers might indicate buzz around a company, they don’t give emotional insights into consumers’ likes, dislikes and expectations.
In contrast, you can use sentiment analysis to “understand whether consumers feel ‘positive,’ ‘negative’ or ‘neutral’ about a certain brand, product or topic,” said Maxime-Samuel Nie-Rouquette, account manager at Tempo Software and former client success manager at Semeon Analytics, a data analytics company that specializes in sentiment analysis.
Sentiment analysis offers companies the opportunity to find more meaning in social media data, said Sean MacPhedran, senior director of innovation at marketing agency SCS. “The most straightforward use for sentiment analysis tools for marketers is the measurement of trends in general sentiment on social media – for example, tracking Macy’s mentions and looking at the words around it for emotion and modifiers. Emotional words are fairly intuitive for us to grasp. ‘Crappy’ or ‘hate’ are bad. ‘Awesome’ and ‘great’ are good.”
MacPhedran recommends diving deeper to determine any nuances in the sentiments expressed. “For example, is there a specific location associated with clusters of negative sentiment? Is there a specific issue that is associated? ‘Returns,’ for example, might indicate people are generally unhappy with a returns policy.”
Key takeaway: According to SuperOffice, only 4% of unhappy customers complain directly to a company. If you use sentiment analysis software to review social media posts, you can identify the most common area of complaints about your products, services, or follow-up that you normally wouldn’t hear directly.
Crisis management and brand health
Crisis management is how companies attempt to seize the narrative and minimize damage following an unexpected emergency. In a crisis, it’s crucial businesses use sentiment analysis to find out how their brand’s supporters and detractors are reacting to the situation. They can also conduct analyses at regular intervals after the crisis passes to determine whether consumers have moved on from the incident.
For example, in 2019, Gillette experienced a PR disaster with its “The Best Men Can Be” video campaign, which addressed toxic masculinity, sexual harassment, and bullying. The video got 1.5 million dislikes on YouTube and the company saw its YouGov BrandIndex buzz score drop by more than five points, plunging it into a negative rating. But the bad buzz eventually died down, and a few months later, sentiment analysis of the follow-up campaign “#MyBestSelf,” featuring a transgender man being taught to shave for the first time by his father, indicated very positive consumer reactions.
In this case, Gillette recognized consumer sentiment to its maligned “The Best Men Can Be” campaign and was able to restrengthen the company’s brand health by adjusting its marketing content.
The goal of digital PR is to create a constant buzz about a particular brand and its products or services. You can measure the volume of content and consumer sentiment toward your brand and the stories people are talking about with sentiment analysis.
“By listening to conversations being held online, a company can understand consumer emotions and give them a connection that goes well beyond whether a product simply sells well or not,” said Nie-Rouquette, who offered examples for the retail sector.
“Retailers can monitor their customers’ reactions and feedback to push content for ‘virality’ or exercise a damage control strategy during crisis management. Retailers such as Walmart, Target, and Costco use sentiment analysis to understand what their customers care about and leverage that information to reposition their products, create new content, or even provide new products and/or services.”
What’s the future of sentiment analysis?
MacPhedran said the next generation of sentiment analysis is very exciting.
“Microservice APIs are able to measure emotion in written content, but also voice and facial expressions. For the sake of the example, assume that we have a CRM system that knows users’ social handles and has an image of the customer usable, with customer permission, for personalization based on facial recognition.”
With that knowledge, your business could better gauge that individual customer’s sentiment and target conversion strategies accordingly. [Learn more about facial recognition advertising.]
You may need to invest in this analysis technology now or risk being outcompeted in the future simply because one company didn’t have key consumer data and another did. A business’s insights, and therefore its success, will be limited by how much data it has.
“Because the backbone of sentiment analysis utilizes big data, using datasets that are comprised of thousands upon thousands of data points, retailers need to have enough data available (including customer conversations and reviews) to gain actionable insights,” Nie-Rouquette said. “So in some cases where data is scarce, sentiment analysis might not provide good insights because of the lack of statistical validity.” [Related article: Big Data vs. CRM: How Can They Help Small Business?]
That’s a fixable issue, and one that companies should address if they want to receive the maximum benefits of sentiment analysis.
“With the availability of data on various online sources, companies (and especially retailers) can leverage sentiment analysis to gather insights that would not be possible using traditional marketing methodologies,” Nie-Rouquette said.
Can small businesses use sentiment analysis now?
There are a wide range of sentiment analysis tools available for small businesses. Virtually all sentiment analysis tools can scan social media networks looking for mentions of your brand and your competitors. You get information back on the volume of content and whether that content was positive, negative or neutral.
You can also plug sentiment analysis apps into your email server and live chat systems, giving the apps instructions on what to do depending on how they interpret the message and the sentiment behind it.
Key takeaway: Many sentiment analysis tools integrate with CRM software to provide deeper insights into customer behavior based on their interactions with your business. See our picks for the best CRM systems.
What is the value of sentiment analysis?
Sentiment analysis can be invaluable to a small business. For a company to succeed, it must be aware of how the marketplace is receiving its products and services. Sentiment analysis can tell a business how customers are feeling about the brand and its offerings. With that knowledge, companies can develop sales strategies that take into account consumer sentiment.
Brian O’Connell contributed to the writing and reporting in this article. Source interviews were conducted for a previous version of this article.