WHO BENEFITS FROM SENTIMENT ANALYSIS
Tags: Machine Learning, Sentiment Analysis, Text Mining, Naturallanguageprocessing, Artificial Intelligence

If the raw data retrieved from digital platforms are not analysed and transformed into structured data, further analysis is not possible. Industries require meaningful insights that can help them make data-driven decisions, create operational efficiencies, and value improvement.

Sentiment Analysis (SA) can be referred to as the process of determining the underlying sentiments behind a series of words. It is used to gain a deeper understanding of consumer opinions. Powered by AI and ML techniques, this tool combines Natural Language Processing (NLP) to determine whether a piece of written text is positive, negative, or neutral.

A sentiment analysis system uses advanced NLP techniques to assign weighted sentiment scores to themes, topics, entities, and categories within a sentence or phrase and accordingly classifies written text.

Any area of business can benefit from using sentiment analysis. Across industries like Finance, Retail, Hospitality, Education and Healthcare, applications of this tool are becoming pivotal. Sentiment analysis applications can be found across all sectors such as:

Analysis of competitor market

Optimising marketing strategies

Evaluating ROI on advertising campaigns

Increasing product performance

Improving customer service

Sales and lead generation

Crisis management

Given below are a few examples of industries that benefit from sentiment analysis:

Sentiment Analysis in the Education Industry

Sentiment analysis has become a significant tool in education research, as research papers present copious amounts of scholarly data. Sentiment Analysis of the faculties and students involved in research work gives an evaluation of sentiments within the team members and helps understand the research work pace.

The exponential volume of data generated within the education sector can be either structured or unstructured. Structured data includes enrolment data, attendance, grades, progression data, while unstructured data consists of student opinions expressed on social media through web blogs, discussion forums, and social networking sites.

According to studies by the University of New Hampshire, 96% of students use Facebook, 84% use YouTube, 20% use blogs and 14% use Twitter. Sentiment Analysis of social media data can help institutions build curriculums and improve student retention rates. It can provide the required and efficient methodology for collecting, storing, and processing large datasets belonging to different varieties of data types and samples.

Analysis of education data can contribute to the holistic development of the education sector. Online sentiment analysis tools have further enabled institutions to resolve various challenges, particularly data management and analysis. Owing to the accuracy and speed of such tools, administrations can now save time, reduce expenditure and increase efficiency.

2. Sentiment Analysis in the E-commerce and Retail Industry

In the retail industry, sentiment analysis tools are gaining immense popularity because customers increasingly express their views and opinions on online platforms about products. Many retail companies are turning to text analytics to curate, gather and analyse feedback that helps identify friction points while using an e-commerce website or dealing with customer support.

Let us consider a few real-world examples of product reviews,

have been using this cooktop for one year but now i have observed that some plastic part of it from back side has melted down and disshaped bcz of heat. I feel disappointed and already afraid of using it. I want my refund.

Love the sound quality, but moreover the services offered by this company are pretty amazing!

Average phone, camera quality is worst, screen resolution is not good, battery drains quickly, cost is too much

Sentiment Analysis considers the meaning of words used in such reviews and the specific context of what kind of sentiment was expressed by the customer. When businesses categorise unstructured data into positive, negative, or neutral, they have the opportunity to find out customer feedback and sentiments in real-time.

Based on these insights, they can take appropriate action to develop their services and provide optimum customer satisfaction. Furthermore, online sentiment analysis tools offer simplification of text analytics by enabling fast and efficient analysis. Businesses can use this data to immediately enhance their product quality, product performance, customer service, advertising campaigns, sales revenue and lead generation.

3. Sentiment Analysis in the Marketing Industry

Sentiment analysis is highly beneficial for the marketing industry. With this tool, marketers gain a better understanding of consumer opinions about a particular service or product. They can analyse data on a massive scale and optimise their marketing campaigns based on the obtained data, which can dramatically improve return on investment (ROI).

Marketers can analyse what features of a product their customers like or dislike. They can examine social media platforms and news data to identify trending topics, conversations, resonating content, and more. Accordingly, they can craft engaging brand messages to multiply the reach and influence businesses. The most effective way to plan marketing and advertising campaigns is by “listening” to the target audience.

Sentiment analysis adds an extra dimension to marketing efforts. As an effective tool for social media listening, marketers and advertisers can leverage the power of sentiment analysis to help drive effective business decisions, strategies, and objectives. Whether a business is looking to plot long-term trends or simply understand how a piece of content could have more impact, this tool can significantly simplify and contribute towards growth.

4. Sentiment Analysis in the Healthcare Industry

Hospitals and medical administrators are responsible for storing and processing extensive volumes of unstructured data in the form of patient reviews, survey reports and patient feedback records. Over eighty per cent of this data is available in text, and it is challenging to keep track, making further analysis nearly impossible.

On the other hand, advancements in technology in the healthcare industry have enabled key decision-makers to revamp their approach to offer better and faster treatment. Modern health-tracking wearable tech and mobile apps have opened new possibilities for the acquiring and processing of data.

Sentiment analysis can help analyse, interpret, and classify complex healthcare text data to understand the sentiments and opinions of their patients. They can evaluate their institutions’ public opinion across online platforms. Using this tool, health officials can understand the needs of patients and improve their experience by giving adequate treatment facilities and necessary care.

Such insights can also be combined with patient data analytics to help derive significant data for further analysis. This can bridge the existing communication gap between medical administrators and patients. Sentiment analysis tools can genuinely transform the face of treatment facilities in the healthcare sector.

5. Sentiment Analysis in the Airline Industry

The airline or aviation industry is a highly competitive market where customer satisfaction is of utmost importance. Flights create significant amounts of data in multiple formats, such as maintenance logs and air-traffic reports. If this data is not examined on time, it can cause landing issues, flight delays, and high fuel consumption.

Analysing customer feedback data and sentiments from multiple channels can help airline administrators gauge their brand’s market reputation. Sentiment analysis can be used to evaluate sentiments and monitor changes over time. They can help in continuously improving customer experience and competitive positioning ​​by actively monitoring internal collections like call centres and the web, combined with social networking sites like Twitter and Facebook. Sentiment analysis can be used to evaluate sentiments and monitor changes over time.

Dissatisfied or frustrated customers are likely to share their bad experiences on social media, which can be detrimental to an airline’s brand image. With sentiment analysis tools, airlines can improve customer perception by providing a customised service at the appropriate time based on insights. This would enable them to create and sustain a positive impact on the brand.

Sentiment Analysis further enables emotion detection, which identifies human emotion from any form of written text. It provides insights into the underlying reasons for the sentiment output, whether happy, sad, anger, confusion, and curiosity.

While sentiment analysis seeks to obtain a polarity from the text to gauge if a sentiment expressed is positive, negative, or neutral, emotion analysis is the next step in the analysis process.