5 Top Trends in Sentiment Analysis

Sentiment analysis is the practice of giving text a positive, negative, or neutral stance. It can use natural language processing (NLP) and machine learning (ML) technologies within the artificial intelligence (AI) sector to analyze and understand how customers are feeling.

AI is helping companies expand the adoption, effectiveness, and scale of sentiment analysis to adjust how they respond to customer opinion.

For instance, the NLP market alone is projected to grow from $20 billion in 2021 to over $127 billion in 2028.

See below for some of the top trends in the sentiment analysis market:

1. Helping human resources

Human resources teams can benefit from developments in sentiment analysis. Creating a good employee experience is important for retaining and engaging employees. Employee burnout is common and knowing how employees are feeling can help keep productivity up within a company.

“HR teams can conduct sentiment analysis and deploy data-driven organization initiatives that focus on employee morale and things today’s workforce considers a priority, such as diversity and sustainability,” said Sameer Maskey, CEO, Fusemachines.

“HR teams also have the ability to leverage AI and data to understand the training needs across each department and create internal reskilling and upskilling opportunities.”

Michael Cohen, CPO at Achievers, says at CMSWire that it is critical for HR and other leadership to listen to their employees and respond.

“Artificial intelligence is one of the ways we can connect an entire employee population and understand what they need,” Cohen says.

Sentiment analysis can help HR improve a working environment, raise employee satisfaction, motivate employees to do their best work.

Read more: Top Natural Language Processing (NLP) Providers

2. Future of brand monitoring

Sentiment analysis can help companies understand how customers feel about a brand: positive, negative, or neutral.

Brand monitoring, including sentiment analysis, is one of the most important ways to keep customers engaged and interested. Branding can help a company improve its recognition, trust, and loyalty among customers as well as the effects of advertising, Forbes says.

“In addition to social media, brand discussion occurs on blogs, news websites, forums, and product evaluations,” said Gavin Johnson, managing director, EV Cable Shop. “Additionally, while it’s acceptable to monitor brand mentions (in terms of volume), it’s much more crucial to examine how they are referencing you.”

Companies that dig into the sentiment of customer comments can gain actionable insights into real-time and trend behaviors.

“Sentiment analysis can help you comprehend the subtleties of consumer opinions and provide useful context for quantitative data,: Johnson said. “You may track changes in brand opinion over time and identify any abrupt ones. To determine the effect of a PR crisis on your brand and analyze the effectiveness of your response, you can also monitor public opinion.”

Read more: 5 Ways Brands Underutilize Data Analytics

3. Sales improvements

Sentiment analysis can help sales teams move beyond vanity metrics, such as clicks, improve sales approaches, and use data to drive selling, according to Outreach.

Customer engagement is essential in sales. Understanding what a consumer wants and doesn’t want can be efficient to changes within sale tactics.

“To engage prospects and make deals, effective salespeople each rely on their own beliefs, intuition, and experiences,” said Jake Cowans, founder, CompanyScouts. “Relying on these characteristics leaves a lot to chance and intuition. AI sentiment analysis can help to fix this and allow the salesperson to simplify their prospecting conversations by eliminating any uncertainty.”

Cowans also says the ability to know what a consumer is saying and feeling can help salespeople adjust their exact tone and language.

“Furthermore, SA tools can assist in locating keywords, competition mentions, pricing references, and a lot more details that might make the difference between a salesperson closing a purchase or not,” Cowans says.

4. Development of artificial emotions

Sentiment analysis and AI could be the answer to mental health treatment, according to TDWI With the ability to read emotions and learn responses, it is believed to be possible.

Some think that it might be dangerous to use AI in the mental health field. However, this trend is popping up more as a serious consideration.

Sentiment analysis has the potential to “pick up on nuanced language and tone that often gets lost in written communication,” said Adam Sypniewski, CTO, Inkhouse.

Sentiment analysis has the potential to be a tool in mental health care in a time where access to mental health care professionals is limited.

In terms of developing and implementing sentiment analysis for mental health care, Dr. Ronny Shalev, founder and CEO of Dyad Medical, believes, “The difficulties here are not only in terms of how much data we use to train the system, but how we approach cultural differences. … There will be differences in the way people express their emotions.”

“It is, however, achievable and will contribute a lot to the way humans will interact with an AI system, since emotions, even if artificial, gives us the sense of relatability.”

5. Customer experience improvements

Consumers are the most important part of a business. With unhappy customers, a company can receive a bad reputation. Sentiment analysis can help with monitoring customer service, and experience.

For instance, using AI technology to analyze customer feedback and customer service exchanges, a company can adjust their service to improve customer satisfaction and loyalty.

“Now, with sentiment monitoring, AI analysis can automatically alert and bridge-in managers when needed as well as provide real-time analytics that streamline customer assistance,” said Ray Nelson, SVP of technical sales and services, ScanSource. “There are also companies who are using AI to analyze the call recordings to help coach call center agents after the call has been completed for future improvement.”

With the “advancement of sentiment analysis in AI, customer service automation can support customer retention, while also saving time and money.”

Sentiment analysis is “applicable to any customer-facing industry and is most widely used for marketing and sales purposes,” said Pavel Tantsiura, CEO, The App Solutions.

Sentiment analysis is making it easier for companies to pick up on customer reactions and emotions and reactions, giving them the option to learn and create a better experience for customers.

Read more: The Voice Recognition Market