Who Uses Sentiment Analysis & Why?


Who Uses Sentiment Analysis & Why?

Emotions and sentiments play a vital role in business. What your customers think of your brand leads to their final decisions.

Sentiment analysis helps determine how people feel about your brand. If they have a positive view, they're more likely to buy from you. If they feel negative, you'll have some work to do.

In this post, we'll discuss what sentiment analysis, who uses it, and its importance in business is.

What Is Sentiment Analysis?

First, let's discuss what sentiment analysis is. It's the process of analysing the emotions and sentiments behind a piece of writing. Sentiment analysis is helpful in social media monitoring and reviews analysis, where brands need to extract public opinion out of a vast amount of data.

Sentiment analysis leverages machine learning and natural language processing techniques to assign sentiment scores to pieces of writing. Intent-based, fine-grained, emotion detection and aspect-based are some common types of sentiment analysis.

Now, you may have a question, "how to perform sentiment analysis." The answer to this could be quite complex. Sentiment analysis involves deploying ML and deep learning algorithms to analyze and filter enormous amounts of information. But nowadays, automated tools are available that help you conduct sentiment analysis with ease.

Industries That Use Sentiment Analysis

There's no industry that can't or shouldn't use sentiment analysis. With social media becoming the primary channel for brand and product talks, all companies should study semantics.

But some industries are truly unleashing the potential of sentiment analysis. These include:

  1. Automotive Industry

    Being one of the largest economic sectors, the automotive industry is vying, which makes analysing customer sentiments a necessity for brands. Automotive companies use social media data to extract customer opinion. This opinion can then be leveraged to streamline marketing and advertising efforts.

    Recently, IEEE Xplore conducted a Twitter sentiment analysis of the automotive industry, which included several car brands. The results were shocking, with Audi and Mercedes having the highest positive and highest negative sentiment, respectively.

  2. Insurance Industry

    The insurance industry has struggled with slow and outdated processes for a long time. Sentiment analysis enables insurance providers to automate recurring processes, thereby reducing the load on insurance agents. It also helps customers file claims without going through lengthy, cumbersome, tedious processes.

  3. Banking and Finance

    The banking and finance industry has witnessed massive digitization over the past couple of years. The rise of cryptocurrency, along with automation of financial operations and the use of technologies like AI and IoT, has increased the reliance on technology. Sentiment analysis helps banking and finance institutions streamline the on-boarding of new customers. It enables banks to optimize market analysis and customer service. It further helps them channelize complicated transactional datasets.

    Some other applications of sentiment analysis in the banking and finance industry include customer expenditure pattern analysis and strengthening of investment strategies.

  4. E-commerce

    The focus of the E-commerce industry has shifted from products and profits to customer experience. E-commerce industries across the globe are using sentiment analysis in multiple ways to recognize their customers' behaviour.

    AI-powered chatbots are a typical example of AI-powered sentiment analysis in the E-commerce industry. Chatbots are computer programs that provide a human-like interactive experience to customers. They analyze the semantics to determine the sentiment behind the customers' queries.

    Apart from chatbots, social media discussion rooms and NLP technologies are some other applications of sentiment analysis in E-commerce.

Why Use Sentiment Analysis?

Sentiment analysis can help you understand what your customers think about your brand. People love to provide feedback, but collecting all the reviews across different channels and analyzing them can be a hurdle. Here's where sentiment analysis comes to your rescue.

The following are some reasons to use sentiment analysis.

  • Data-Driven Marketing Strategy:

    By understanding sentiments around your brand, you can identify the drivers behind your customers' purchasing decisions. You can then optimize your marketing strategy to leverage these drivers.

  • Understand Your Customers:

    A large portion of businesses don't succeed because they fail to understand their customers. With sentiment analysis, you can determine exactly what your customers want.

  • Brand Perception:

    Sentiment analysis helps you understand what your customers think about your brand. If your brand perception is bad, you'll have a hard time selling.

  • Enhanced Customer Service:

    Customer support and service is becoming the cornerstone of running a successful business. With sentiment analysis, you can better understand the problems your customers are facing and deliver tailored solutions.

Conclusion

Back in the day, sentiment analysis was a complicated topic best suited for AI experts. Now with an increasing focus on customer experience and service, sentiment analysis has become a critical aspect of all business development strategies.

In a nutshell, sentiment analysis enables you to understand what people think and feel about your brand. You can derive these insights and utilize them to make informed business decisions.

Author's Bio:
Efrat Vulfsons is the Co-Founder of PR Soprano and a data-driven marketing enthusiast, parallel to her soprano opera singing career. Efrat holds a B.F.A from the Jerusalem Music Academy in Opera Performance.